Disclosure of Invention
The invention provides a motor driving intelligent regulation and control method and a motor driving intelligent regulation and control system, which are used for solving the technical defects of the traditional motor driving intelligent regulation and control method, including limited self-adaptability, accuracy and multi-modal performance. Furthermore, past approaches often lack real-time data analysis and big data support, making advanced fault detection and health management difficult. Lack of remote monitoring and control capability, and integrated energy efficiency optimization:
The invention provides a motor drive intelligent regulation and control method, which comprises the following steps:
s1: analyzing a motor driving intelligent regulation and control system, and determining the system requirement of the motor driving intelligent regulation and control system, wherein the system requirement comprises control precision, a speed range, a torque requirement and performance indexes;
S2: according to the requirements of a motor driving intelligent regulation and control system, a motor and a sensor are selected, the motor data are measured through the sensor, feedback information of the measured data is obtained, and the motor is controlled to move through the feedback information and a motor driving control algorithm; the motor data comprises the position, the speed and the current state of the motor;
S3: a real-time control system is established through the sensor data and the motor drive control algorithm, the motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result;
s4: the method comprises the steps of establishing a safety monitoring control system, wherein the safety monitoring control system comprises a user interface module and a fault detection module, and the user interface module is used for monitoring and adjusting the running state of a motor by an operator; the fault detection module finds and diagnoses the system fault and performs performance tuning.
Further, the sensor comprises a position sensor, a speed sensor, a torque sensor, a current sensor, a temperature sensor, a vibration sensor, a pressure sensor, a gas and liquid flow sensor;
the position sensor is used for measuring the position of the motor rotor and comprises an encoder, a grating encoder and a Hall effect sensor, and is responsible for providing feedback information about the position of the motor and the accurate position of the motor;
the speed sensor is used for measuring the speed of the motor rotor;
The torque sensor is used for measuring the torque output by the motor and the torque on the load, and the real-time control system monitors the load condition through the torque sensor;
the current sensor is used for measuring the current consumption of the motor and detecting overload, faults and abnormal conditions;
the temperature sensor is used for measuring the temperature of the motor and the motor driver, monitoring the temperature and controlling the temperature;
the vibration sensor is used for detecting the vibration of the motor;
the pressure sensor is used for measuring hydraulic pressure;
the gas and liquid flow sensors are used for monitoring the flow of liquid and gas;
And carrying out closed-loop control and intelligent regulation by measuring data through the sensor and real-time information of the states of the motor and the motor driving intelligent regulation system.
Further, the control algorithm employs a proportional-integral-derivative controller and adjusts the output of the motor via a PID controller that is used to provide the desired motion, position and speed of the motor.
The calculation formula of the PID controller is as follows:
PID output = kp×e (t) +ki×jjjjje (t) dt ] +kd×de (t)/dt;
Wherein the PID output is an output signal of the PID controller; kp is the proportional gain, controlling the effect of the proportional term; ki is the integral gain, controlling the effect of the integral term; kd is the differential gain, controlling the effect of the differential term; e (t) is an error signal representing the difference between the desired value and the actual value, and is the difference between the set value and the actual value; where [ e (t) dt ] is the integral of the error signal e (t), representing the accumulation of error over time; de (t)/dt is the derivative of the error signal e (t), representing the rate of change of the error over time; the PID controller adjusts the output of the motor-driven intelligent regulation and control system through the combination of the proportional term, the integral term and the differential term, eliminates errors and realizes accurate control.
Further, a real-time control system is established through the sensor data and the motor drive control algorithm, the motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result; comprising the following steps:
S31: establishing a multi-mode control strategy according to performance requirements of different working modes of the motor, and determining control parameters and targets of the modes;
S32: when the motor runs, monitoring the state and the environmental condition of the motor in real time, and determining the current working mode through the sensor data;
s33: developing a mode switching logic, wherein the mode switching logic determines working mode switching time according to real-time monitoring data based on the real-time monitoring data;
s34: when the motor is switched to different working modes, the PID controller is adjusted;
S35: implementing the control algorithm and logic, monitoring the motor performance in real time, and adjusting the control parameters according to the needs; and proceeds to the next step of input.
S36: in practical application, the multi-mode control system is tested and verified, and the performance of various working modes is fed back in real time to meet the running requirement of the motor;
S37: the multi-modal control system is continually optimized to improve control strategy and performance based on actual operation and feedback data.
Further, the multi-mode control strategy comprises different working modes of the motor, wherein the working modes correspond to specific running states and performance requirements of the motor;
The working modes comprise a high-speed mode, a high-torque mode, an energy-saving mode and a static mode;
the multi-mode control strategy is used for determining the working mode requirements, wherein the working mode requirements comprise the motor speed, torque, position accuracy and response time;
The multi-mode control strategy adopts intelligent mode switching logic to switch working modes based on real-time monitoring threshold, performance index, load condition and environmental condition data;
The multi-mode control strategy adjusts gain parameters of the PID controller when the working mode is switched;
the multi-mode control strategy monitors the actual speed, torque and position of the motor in real time, adjusts the control parameters according to the needs, and implements a fault detection mechanism to detect the system faults of the motor.
Further, the next step of input is obtained through system parameters and control parameters, and the formula is obtained; comprising the following steps:
Wherein X (b) is the next input, g is a system parameter, K is a control quantity gain of the system, P (b) is the output of the system, and P' (b+1) is a set reference value;
The current system parameter g is estimated according to the previous step information of the motor, and the system parameter g is obtained according to the following formula:
Wherein P (b) is the output of the system, X (b-1) is the output of the last step controller, namely the input value of the motor, and P (b-1) is the input value of the last step controller, namely the output value of the motor.
Further, the fault monitoring step of the fault monitoring module includes:
A1: detecting motor winding faults, sensor faults and power supply problems of the motor and the motor driving intelligent regulation and control system by self-diagnosis and analysis of the sensor data;
a2: classifying and identifying the detected problems, and determining which type of faults and anomalies the problems belong to;
a3: based on the self-diagnosis result and the sensor data, calculating health indexes of the motor and the motor driving intelligent regulation and control system; and calculating the motor health index by the following formula:
Wherein Eindex represents the motor health index scoring value, F represents the motor load weighting value, a' represents the motor health factor weighting value, Cγ,Nγ and Jγ respectively represent the motor winding, the sensor and the power supply use stability factor,Representing a normal operation time factor, wherein T 'is the longest operation time of the motor in an evaluation period, T' is the normal operation reference time of the motor, and Yc is the abnormal stop times of the motor;
A4: establishing a safety monitoring control system, recording and tracking the health condition of the motor according to the health index of the motor, storing historical data, generating an alarm and a report by the safety monitoring control system, monitoring the performance of the motor in real time, and providing a user interface for an operator to monitor and adjust the running state of the motor;
a5: corresponding safety measures are adopted according to the self-diagnosis and the health index, wherein the safety measures comprise emergency shutdown, switching to a standby system, load reduction, notifying an operator and maintenance, and automatically adjusting control parameters and modes;
a6: corresponding operations are performed based on the health of the motor, including periodic maintenance, replacement of components, and performance of repairs.
Further, the performing a corresponding operation based on the health condition of the motor includes:
A61: determining a health index of the motor according to the sensor data, the history record and the health model; analyzing the health index and the sensor data, and detecting fault types, positions and severity problems and abnormal conditions in the motor and the motor drive intelligent regulation system;
a62: the health state of the motor is monitored in real time, and compared with a preset health index threshold value and a preset standard, abnormality and problem are found, and an alarm is triggered; the integrated alarm system sends information through an email, a short message and a visual interface, and timely informs operators and maintenance personnel to take measures to deal with the problem;
A63: generating a maintenance plan including maintenance recommendations, spare part replacement recommendations, and maintenance schedule maintenance based on the health indicators and fault diagnosis results;
a64: tracking changes in the motor performance and predicting future problems using the historical data and trend analysis tools;
a65: the changing demands are accommodated by updating the health model, improving the fault diagnosis algorithm, and optimizing the alarm strategy.
Further, the fault detection module stores the sensor data by establishing a big data storage system on a cloud server; the storage step comprises the following steps:
B1: determining the total storage space of a cloud server, dividing the storage space according to the requirement index of a sensor, and determining the size and the capacity of each storage partition according to the size of data volume and the access frequency; the demand index comprises the total amount of sensor data, the generation frequency and the storage period;
B2: dividing the storage space of the cloud server according to different sensor data types, importance and access frequency; selecting a storage technology and cloud services according to the divided storage space, wherein the storage technology and the cloud services comprise object storage, file storage and database storage;
B3: compressing and optimizing sensor data through a compression algorithm and a data de-duplication algorithm, and backing up the compressed and optimized data and designing a redundancy strategy;
b4: and monitoring the performance and capacity use condition of the storage system, and timely adjusting the storage space division and expansion plan.
The invention provides a motor driving intelligent regulation and control system, which comprises:
the demand analysis module: analyzing a motor driving intelligent regulation and control system, and determining the system requirement of the motor driving intelligent regulation and control system, wherein the system requirement comprises control precision, a speed range, a torque requirement and performance indexes;
and a drive control module: according to the requirements of a motor driving intelligent regulation and control system, a motor and a sensor are selected, the motor data are measured through the sensor, feedback information of the measured data is obtained, and the motor is controlled to move through the feedback information and a motor driving control algorithm; the motor data comprises the position, the speed and the current state of the motor;
And the real-time control module is used for: a real-time control system is established through the sensor data and the motor drive control algorithm, the motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result;
And a safety monitoring module: the method comprises the steps of establishing a safety monitoring control system, wherein the safety monitoring control system comprises a user interface module and a fault detection module, and the user interface module is used for monitoring and adjusting the running state of a motor by an operator; the fault detection module finds and diagnoses the system fault and performs performance tuning.
The invention has the beneficial effects that:
(1) The invention adopts an advanced self-adaptive control strategy, and can automatically adjust control parameters according to real-time data and working mode requirements, thereby realizing higher performance and efficiency;
(2) The invention introduces a multi-mode control strategy, so that the motor can be automatically switched under different working modes, thereby meeting diversified application requirements and providing greater flexibility and versatility;
(3) The invention utilizes big data analysis technology, can monitor the motor state in real time, and early identify problems and abnormal conditions, thereby taking measures in advance and reducing downtime and maintenance cost;
(4) The cloud computing system is combined with a cloud computing technology, has strong computing and storage capacity, supports remote monitoring, data storage and remote decision making, and improves the operability and accessibility of the system;
(5) The invention can detect the problems in the motor system in advance through the self-diagnosis and health management system, generate a maintenance plan and provide maintenance advice, thereby improving the maintainability and reliability of the system;
(6) The invention provides an intuitive user interface, allows an operator to easily check and adjust the working mode and monitor performance, and performs necessary operations, thereby improving the operability of the system.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, and the described embodiments are merely some, rather than all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
In one embodiment of the present invention, as shown in fig. 1, a motor driving intelligent regulation method, the method includes:
s1: analyzing a motor driving intelligent regulation and control system, and determining the system requirement of the motor driving intelligent regulation and control system, wherein the system requirement comprises control precision, a speed range, a torque requirement and performance indexes;
S2: according to the requirements of a motor driving intelligent regulation and control system, a motor and a sensor are selected, the motor data are measured through the sensor, feedback information of the measured data is obtained, and the motor is controlled to move through the feedback information and a motor driving control algorithm; the motor data comprises the position, the speed and the current state of the motor;
S3: a real-time control system is established through the sensor data and the motor drive control algorithm, the motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result;
s4: the method comprises the steps of establishing a safety monitoring control system, wherein the safety monitoring control system comprises a user interface module and a fault detection module, and the user interface module is used for monitoring and adjusting the running state of a motor by an operator; the fault detection module is used for finding and diagnosing system faults and performing performance tuning.
The working principle of the technical scheme is as follows: by analyzing the motor-driven intelligent regulation and control system, the requirements of the system are determined, including control accuracy, speed range, torque requirement and other performance indexes. These requirements will be the basis for the subsequent selection of motors and sensors; suitable motors and sensors are selected according to system requirements. The sensors are used to measure motor data and provide feedback information including position, speed, current status, etc. The motor motion is controlled through the data measured by the sensor and a motor driving control algorithm; based on the sensor data and the motor drive control algorithm, a real-time control system is established. The system can monitor motor data in real time and obtain real-time monitoring results. According to the real-time monitoring result, parameters of a motor driving control algorithm are adjusted to optimize the performance of the system; to ensure the safety of the system, a safety monitoring control system is established. The system includes a user interface module and a fault detection module. The user interface module is used for an operator to monitor the running state of the motor and correspondingly adjust the running state. The fault detection module is used for detecting and diagnosing system faults and performing performance tuning so as to ensure the reliability and stability of the system.
The technical scheme has the effects that: through the analysis of the motor drive intelligent regulation and control system demand and the adjustment of parameters, the accurate control of the motor motion can be realized. The control precision of the system can be improved, and the requirements of different application scenes are met; by establishing a real-time control system and real-time monitoring of sensor data, the position, speed, current state and other information of the motor can be timely obtained. The method is beneficial to knowing the running state of the motor in real time, finding problems in time and adjusting, and improving the stability and reliability of the system; the safety monitoring control system is established to ensure the safety of the system. The user interface module may provide operator monitoring and adjustment capabilities for the motor operating conditions, increasing the flexibility and ease of use of the system. The fault detection module can timely detect and diagnose system faults and perform performance tuning, so that the influence of the system faults on production and equipment is reduced; through optimization and parameter adjustment of the motor driving intelligent regulation and control system, performance indexes of the system, such as control precision, speed range, torque requirement and the like, can be improved. This helps to improve production efficiency and product quality, meeting the user's requirements for system performance.
One embodiment of the invention, the sensor comprises a position sensor, a speed sensor, a torque sensor, a current sensor, a temperature sensor, a vibration sensor, a pressure sensor, a gas and liquid flow sensor;
the position sensor is used for measuring the position of the motor rotor and comprises an encoder, a grating encoder and a Hall effect sensor, and is responsible for providing feedback information about the position of the motor and the accurate position of the motor;
the speed sensor is used for measuring the speed of the motor rotor;
the torque sensor is used for measuring the torque output by the motor and the torque on the load, and the real-time control system monitors the load condition through the torque sensor; adjusting the system when needed;
the current sensor is used for measuring the current consumption of the motor and detecting overload, faults and abnormal conditions; the safety and stability of the system are ensured;
The temperature sensor is used for measuring the temperature of the motor and the motor driver, monitoring the temperature and controlling the temperature; to prevent overheating of the motor;
the vibration sensor is used for detecting the vibration of the motor;
the pressure sensor is used for measuring hydraulic pressure;
the gas and liquid flow sensors are used for monitoring the flow of gas and liquid;
And carrying out closed-loop control and intelligent regulation by measuring data through the sensor and real-time information of the states of the motor and the motor driving intelligent regulation system.
The working principle of the technical scheme is as follows: the position sensor is used for measuring the position of the motor rotor, and an encoder, a grating encoder, a Hall effect sensor or the like can be used. The position sensor is responsible for providing feedback information about the position of the motor so that the control system knows the position of the motor accurately; the speed sensor is used for measuring the rotating speed of the motor rotor, and can be calculated by measuring the change of the position of the motor rotor in the time interval. The speed sensor provides real-time feedback of the speed of the motor rotor, which is helpful for the control system to accurately control the movement of the motor; the torque sensor is used for measuring the torque output by the motor and the torque on the load so as to monitor the load condition in real time and adjust the system when required. The control system can detect the load change of the motor in real time through the torque sensor, so that the stability and performance of the system under different load conditions are ensured; the current sensor is used for measuring the current consumption of the motor, can detect overload, faults and abnormal conditions, and ensures the safety and stability of the system. The control system can monitor the current change of the motor in real time through the current sensor, and adjust and protect the motor according to the requirement; the temperature sensor is used for measuring the temperature of the motor and the motor driver and monitoring and controlling the temperature so as to prevent the motor from overheating. The temperature sensor is used for monitoring the temperatures of the motor and the driver in real time by the control system, and corresponding measures such as load reduction or cooling effect improvement are adopted to protect the motor and the system; the vibration sensor is used for detecting the vibration condition of the motor and can help monitor the running state and the fault condition of the motor. The control system can monitor the change of motor vibration in real time through the vibration sensor, discover abnormal conditions in time and take corresponding measures; the pressure sensor is used for measuring the pressure condition of the hydraulic system and can be used for monitoring the working state and the performance of the hydraulic system. The control system can monitor the pressure change of the hydraulic system in real time through the pressure sensor, and adjust and control the pressure change according to the requirement; gas and liquid flow sensors are used to monitor the flow of liquids and gases and can be used to control and regulate the flow of liquids and gases. The flow sensor is used for monitoring the flow change of liquid and gas in real time by the control system, and the flow change can be regulated and controlled according to the requirement.
The technical scheme has the effects that: through the cooperation of the position sensor and the speed sensor, the position and the speed of the motor can be accurately controlled, so that the requirements of different application scenes on the motor movement are met; the torque sensor can monitor the torque output by the motor and the torque on the load in real time, so that the control system can know the load condition, and the adjustment and the protection can be carried out when needed; the current sensor can monitor the current consumption of the motor, timely detect overload, faults and abnormal conditions, and take corresponding measures to ensure the safety and stability of the system; the temperature sensor can monitor the temperature of the motor and the temperature of the driver and control the motor and the driver in real time, so that the motor is prevented from overheating, and the motor and the system are prevented from being damaged; the vibration sensor can detect the vibration condition of the motor, timely find abnormal conditions such as bearing faults or unbalance, and take maintenance measures in advance to avoid serious damage and shutdown; through the monitoring of the pressure sensor and the gas and liquid flow sensors, the control system can know the working state and the flow condition of the hydraulic system in real time, so that the optimization adjustment is carried out, and the system performance is improved.
In one embodiment of the invention, the control algorithm employs a proportional-integral-derivative controller and adjusts the output of the motor via a PID controller that is used to provide the desired motion, position and speed of the motor.
The calculation formula of the PID controller is as follows:
PID output = kp×e (t) +ki×jjjjje (t) dt ] +kd×de (t)/dt;
Wherein the PID output is an output signal of the PID controller; kp is the proportional gain, controlling the effect of the proportional term; ki is the integral gain, controlling the effect of the integral term; kd is the differential gain, controlling the effect of the differential term; e (t) is an error signal representing the difference between the desired value and the actual value, and is the difference between the set value and the actual value; where [ e (t) dt ] is the integral of the error signal e (t), representing the accumulation of error over time; de (t)/dt is the derivative of the error signal e (t), representing the rate of change of the error over time; the PID controller adjusts the output of the motor-driven intelligent regulation and control system through the combination of the proportional term, the integral term and the differential term, eliminates errors and realizes accurate control.
The working principle of the technical scheme is as follows: the control algorithm employs a proportional-integral-derivative controller and adjusts the output of the motor via a PID controller that is used to provide the desired motion, position and speed of the motor. In the motor driving application, a proportional term of the PID controller is used for reducing the error between the current position and the set position of the motor, an integral term is used for eliminating static error, and a differential term is used for suppressing oscillation and improving the stability of the motor; the PID controller adjusts control input through proportional, integral and differential terms to control the running speed of the motor; and the PID controller controls the motor output torque to finally realize the load requirement of the motor.
The technical scheme has the effects that: the PID controller can realize accurate control of the motor through combination adjustment of proportional, integral and differential terms, so that the motor can meet the expected position, speed and load requirements; the PID controller can rapidly adjust the output torque of the motor according to the magnitude and the change rate of the error signal, so that rapid response to the motor is realized, and the dynamic performance of the system is improved; the PID controller has self-adaptability, can dynamically adjust control parameters according to actual conditions, adapts to different working environments and load changes, and improves the stability and reliability of the system; the PID controller can adapt to different control demands by changing proportional, integral and differential gains, has certain robustness to the conditions of system parameter change, noise interference and the like, and improves the anti-interference capability of the system; the PID controller can adjust the output torque of the motor according to the system requirement, so that the motor is kept in an optimal state in the working process, the energy consumption is reduced, and the energy utilization efficiency is improved. The motor can be accurately, stably and rapidly controlled through the formula, the load requirements under different working conditions can be met, meanwhile, the PID controller can be adjusted through the proportional gain Kp according to the magnitude and the direction of the error signal e (t), so that the motor can accurately reach the expected position and keep stable; through the adjustment of the integral term and the differential term, the PID controller can accurately control the speed and the acceleration of the motor, so that the motor can quickly respond to external instructions or changes, and the response speed of the system is improved; the PID controller can adjust through integral gain Ki according to the accumulation condition of errors along with time, so that the accurate control of the motor load capacity is realized, and the load demands under different working conditions are met; through the adjustment of the differential terms, the PID controller can inhibit the oscillation phenomenon of the motor system, and the stability and the control precision of the system are improved; the PID controller can dynamically adjust the proportional, integral and differential gains according to actual conditions, adapt to the change of system parameters, and improve the robustness and adaptability of the system.
According to one embodiment of the invention, a real-time control system is established through sensor data and a motor drive control algorithm, motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result; comprising the following steps:
S31: establishing a multi-mode control strategy according to performance requirements of different working modes of the motor, and determining control parameters and targets of the modes;
S32: when the motor runs, monitoring the state and the environmental condition of the motor in real time, and determining the current working mode through the sensor data;
s33: developing a mode switching logic, wherein the mode switching logic determines working mode switching time according to real-time monitoring data based on the real-time monitoring data;
S34: when the motor is switched to different working modes, the PID controller is adjusted; the performance requirement of the working mode is met;
s35: implementing the control algorithm and logic, monitoring the motor performance in real time, and adjusting the control parameters according to the needs; and calculating the next step of input; the next step of input is obtained through system parameters and control parameters, and the obtaining formula is as follows:
Wherein X (b) is the next input, g is a system parameter, K is a control quantity gain of the system, P (b) is the output of the system, and P' (b+1) is a set reference value;
The current system parameter g is estimated according to the previous step information of the motor, and the system parameter g is obtained according to the following formula:
Wherein P (b) is the output of the system, X (b-1) is the output of the last step controller, namely the input value of the motor, and P (b-1) is the input value of the last step controller, namely the output value of the motor.
S36: in practical application, the multi-mode control system is tested and verified, and the performance of various working modes is fed back in real time to meet the running requirement of the motor;
S37: the multi-modal control system is continually optimized to improve control strategy and performance based on actual operation and feedback data.
The working principle of the technical scheme is as follows: according to the performance requirements of different working modes of the motor, corresponding control strategies are designed and established, wherein the control strategies comprise control parameters and targets. Each operating mode has its specific requirements and operating conditions; the state data of the motor, including position, speed, current, temperature, etc., are collected in real time through the sensor, and environmental conditions, such as temperature, humidity, etc., can also be monitored. These data will be used to determine the current mode of operation and adjust the control parameters; based on the real-time monitored data, mode switching logic is developed to determine the switching time of the operating mode. When the monitoring data reach a certain threshold value or a triggering condition, the system switches the working modes according to preset logic; when the motor is switched to different working modes, the parameters of the PID controller are adjusted according to the performance requirements of the modes so as to meet the control requirements in the modes. Different modes of operation may require different control parameters to achieve optimal performance; and in the running process of the motor, adjusting the control parameters according to the data monitored in real time. For example, according to the change of the motor load or the change of the environmental condition, the parameters of the PID controller are adjusted in real time so as to maintain good control performance; in practical application, the multi-mode control system is tested and verified, and whether the motor operation requirement is met is judged by feeding back the performances of various working modes in real time. Optimizing and improving according to the test result and the feedback data; based on actual operation and feedback data, the multi-modal control system is continually optimized, including improving control strategies and performance. Through optimization, stability, efficiency and reliability of the motor system are improved.
The technical scheme has the effects that: by establishing a multi-mode control strategy, control parameters and targets can be adjusted according to performance requirements of different working modes, so that the running performance of the motor is optimized; the state and the environmental condition of the motor are monitored in real time, and real-time adjustment is carried out according to the monitored data, so that the motor can respond to the change in time, the stable operation of the motor is kept, and the control precision and accuracy are improved; by developing the mode switching logic, the switching time of the working mode can be determined according to the data monitored in real time, smooth transition and switching are realized, and unstable or adverse effects caused by abrupt switching are avoided; according to different working modes, parameters of the PID controller are adjusted, so that the PID controller has optimal response and stability under different working conditions, and the control performance of the motor is improved; the motor performance can be dynamically optimized by monitoring the motor performance in real time and adjusting the control parameters according to the needs so as to adapt to different working loads and environmental conditions; the performance and reliability of the system can be evaluated by testing and verifying the actual application of the multi-mode control system, and the system can be improved and optimized according to the result, so that the system can meet the running requirement of a motor; according to actual operation and feedback data, the control strategy and performance of the multi-mode control system are continuously optimized, the efficiency, stability and reliability of the motor are improved, and better control effect and energy-saving effect are achieved. The formula can realize real-time monitoring and control parameter adjustment of the motor system, optimize the system performance and improve the running efficiency and stability of the motor system. Meanwhile, by calculating the next step of input and estimating system parameters, more accurate control and better system response can be realized, and the performance and control quality of the motor system are further improved. Meanwhile, the above formula is implemented by a control algorithm and logic, so that the performance of the motor can be monitored in real time. The motor system is beneficial to quickly finding potential problems or abnormal conditions and adopting corresponding adjustment measures to ensure the stability and reliability of the motor system; according to the motor performance condition monitored in real time, the control parameters can be adjusted according to the requirements. The response speed, stability and accuracy of the motor system can be improved by optimizing the control parameters, so that the motor system can better meet the actual requirements; based on the system parameters and the control parameters, the input values for the next step can be calculated. The method is favorable for predicting the running state and the behavior of the system, provides reference basis for the subsequent control and operation, and realizes the accurate control of the motor system; based on the previous step information of the current motor, the system parameter g can be estimated. By the parameter, the dynamic characteristic and the change trend of the system can be known more accurately, so that finer adjustment is made in the control process.
In one embodiment of the present invention, the multi-mode control strategy includes different operation modes of the motor, the operation modes corresponding to specific operation states and performance requirements of the motor;
The working modes comprise a high-speed mode, a high-torque mode, an energy-saving mode and a static mode;
the multi-mode control strategy is used for determining the working mode requirements, wherein the working mode requirements comprise the motor speed, torque, position accuracy and response time;
The multi-mode control strategy adopts intelligent mode switching logic to switch working modes based on real-time monitoring threshold, performance index, load condition and environmental condition data;
The multi-mode control strategy adjusts gain parameters of the PID controller when the working mode is switched;
the multi-mode control strategy monitors the actual speed, torque and position of the motor in real time, adjusts the control parameters according to the needs, and implements a fault detection mechanism to detect the system faults of the motor.
The working principle of the technical scheme is as follows: different working modes are determined according to the running state and the performance requirement of the motor. For example, the high-speed mode is suitable for a case where a rapid rotation speed is required, the high-torque mode is suitable for a case where a large torque output is required, the energy-saving mode is suitable for a case where a reduction in energy consumption is required, and the stationary mode is suitable for a case where a stationary position is required to be maintained; and switching the working mode by adopting intelligent mode switching logic through the data of the threshold value, the performance index, the load condition and the environmental condition which are monitored in real time. Comparing the monitoring data with preset switching conditions to determine whether to switch to a corresponding working mode; in the process of switching the working modes, the gain parameters of the PID controller are adjusted to ensure the control performance in each working mode. According to the requirements and characteristics of different working modes, the parameters of the PID controller are adjusted, so that the PID controller can better respond and stably control the motor; the actual speed, torque and position of the motor are monitored in real time, and control parameters are adjusted according to requirements. According to the data monitored in real time, dynamically adjusting control parameters to adapt to different working loads and environmental conditions, and optimizing the motor performance; and implementing a fault detection mechanism to monitor the system faults of the motor. If a fault is detected, switching to a standby mode in time, and taking emergency measures to ensure safe operation of the motor; and testing and verifying the actual application of the multi-mode control system, and collecting actual operation and feedback data. And according to the data analysis result, the control strategy and performance are continuously optimized to adapt to the continuously changing application requirements and environmental conditions.
The technical scheme has the effects that: the multi-mode control strategy can meet specific running states and performance requirements according to different working modes of the motor, so that the motor can flexibly adapt to different working scenes and task requirements; by adopting intelligent mode switching logic, according to the data and the threshold value monitored in real time, the working mode and the control parameter are adjusted, so that the efficiency, the precision and the response time of the motor can be improved, and the overall performance is improved; the energy consumption cost of the motor can be reduced through the application of the energy-saving mode and the energy consumption optimization, the national energy-saving and emission-reduction policy requirements are met, and the energy-saving and emission-reduction motor is environment-friendly; the multi-mode control strategy implements a fault detection mechanism, timely detects system faults of the motor, switches standby modes and takes emergency measures to ensure safe operation of the motor and prolong the service life; through testing and verification in practical application, the multi-mode control system is continuously optimized, the control strategy and performance are improved, the application requirements and environmental conditions which are continuously changed are adapted, and the reliability and stability of the whole system are improved.
In one embodiment of the present invention, the fault monitoring step of the fault monitoring module includes:
A1: detecting motor winding faults, sensor faults and power supply problems of the motor and the motor driving intelligent regulation and control system by self-diagnosis and analysis of the sensor data;
a2: classifying and identifying the detected problems, and determining which type of faults and anomalies the problems belong to;
a3: based on the self-diagnosis result and the sensor data, calculating health indexes of the motor and the motor driving intelligent regulation and control system; and calculating the motor health index by the following formula:
Wherein Eindex represents the motor health index scoring value, F represents the motor load weighting value, a' represents the motor health factor weighting value, Cγ,Nγ and Jγ respectively represent the motor winding, the sensor and the power supply use stability factor,And representing a normal running time factor, wherein T 'is the longest running time of the motor in an evaluation period, T' is the normal running reference time of the motor, and Yc is the abnormal stop frequency of the motor.
A4: establishing a safety monitoring control system, recording and tracking the health condition of the motor according to the health index of the motor, storing historical data, generating an alarm and a report by the safety monitoring control system, monitoring the performance of the motor in real time, and providing a user interface for an operator to monitor and adjust the running state of the motor;
a5: corresponding safety measures are adopted according to the self-diagnosis and the health index, wherein the safety measures comprise emergency shutdown, switching to a standby system, load reduction, notifying an operator and maintenance, and automatically adjusting control parameters and modes;
a6: corresponding operations are performed based on the health of the motor, including periodic maintenance, replacement of components, and performance of repairs.
The working principle of the technical scheme is as follows: the sensor is used for collecting data of the motor, including relevant data such as the working state, temperature, vibration and current of the motor; the sensor data are analyzed through self-diagnosis, and the problems of motor winding faults, sensor faults, power supply problems and the like of a motor and a motor driving intelligent regulation and control system are detected; classifying and identifying the detected problems, and determining which type of faults and anomalies the problems belong to; based on the self-diagnosis result and the sensor data, calculating health indexes of the motor and the motor driving intelligent regulation and control system so as to evaluate the running condition of the motor; establishing a safety monitoring control system to record and track the health condition of the motor, storing historical data, generating alarms and reports, monitoring the performance of the motor in real time, and providing a user interface for an operator to monitor and adjust the running state of the motor; corresponding safety measures are adopted according to the self-diagnosis and health indexes, including emergency shutdown, switching to a standby system, load reduction, notifying an operator and maintenance, and control parameters and modes are automatically adjusted; corresponding operations are performed based on the health of the motor, including periodic maintenance, replacement of components, and performance of repairs.
The technical scheme has the effects that: the motor winding faults, the sensor faults and the power supply problems can be accurately detected through self-diagnosis analysis and comprehensive application of the sensor data, and the fault detection accuracy is improved; by classifying and identifying the detected problems, the fault type can be rapidly determined, and guidance is provided for subsequent processing and maintenance; based on the self-diagnosis result and the sensor data, calculating health indexes of the motor and the motor driving system, evaluating the health condition of the motor, and providing comprehensive and reliable health index data; establishing a safety monitoring control system, recording and tracking the health condition of the motor in real time, generating an alarm and a report, finding out abnormal conditions in time and reminding an operator to take corresponding measures; corresponding safety measures are adopted according to the self-diagnosis and health indexes, including emergency shutdown, switching to a standby system, load reduction and the like, so that the safe operation of the motor and the system is ensured; corresponding operations are executed based on the health condition of the motor, including periodic maintenance, component replacement and maintenance execution, so that maintenance plans can be reasonably planned and optimized, and the service life of the motor can be prolonged. Through the formula, the motor fault can be automatically diagnosed, the motor health index can be calculated, a scientific evaluation system and effective maintenance support can be provided for motor operation, and meanwhile, the safety and stability of the motor can be improved. Meanwhile, the health index of the motor and the motor driving intelligent regulation and control system can be obtained in real time through calculation based on the self-diagnosis result and the sensor data. The motor system operation state and the health condition can be accurately grasped, and a reference basis is provided for subsequent predictive maintenance; the health index adopts a scoring value calculation method, and comprehensively considers a plurality of factors such as a load weight value of the motor, a weight value of each health factor, a use stability factor, a normal running time factor, abnormal stop times and the like. Through the comprehensive consideration of the factors, the health condition of the motor system can be more accurately estimated, and a scientific and reasonable estimation system is formed; by adopting the technical scheme, the health condition of the motor can be accurately evaluated, and unnecessary cost and workload caused by inaccurate evaluation or excessive maintenance are avoided. Meanwhile, the failure rate of the motor can be reduced, and the stability and safety of the motor are improved; through accurate evaluation motor health condition, can realize more scientific and accurate maintenance planning, provide effective instruction and reference for maintenance work. This helps to reduce maintenance costs and improve maintenance efficiency.
According to one embodiment of the invention, the performing of the corresponding operation based on the health condition of the motor comprises:
A61: determining a health index of the motor according to the sensor data, the history record and the health model; analyzing the health index and the sensor data, and detecting fault types, positions and severity problems and abnormal conditions in the motor and the motor drive intelligent regulation system;
a62: the health state of the motor is monitored in real time, and compared with a preset health index threshold value and a preset standard, abnormality and problem are found, and an alarm is triggered; the integrated alarm system sends information through an email, a short message and a visual interface, and timely informs operators and maintenance personnel to take measures to deal with the problem;
A63: generating a maintenance plan including maintenance recommendations, spare part replacement recommendations, and maintenance schedule maintenance based on the health indicators and fault diagnosis results;
a64: tracking changes in the motor performance and predicting future problems using the historical data and trend analysis tools;
a65: the changing demands are accommodated by updating the health model, improving the fault diagnosis algorithm, and optimizing the alarm strategy.
The working principle of the technical scheme is as follows: various parameter data including temperature, vibration, current and the like are acquired in real time when the motor operates through a sensor arranged on the motor. The sensors transmit data to a monitoring system for processing; the monitoring system calculates health indexes of the motor by using sensor data, a history record and a pre-established health model. Different health index thresholds and references can be set according to different motor types and application scenes; the monitoring system analyzes the health index and the sensor data, and detects the fault type, position and severity degree problems of the motor and the intelligent driving control system. By comparing the actual data with a preset health index threshold, the system can identify anomalies and problems and trigger an alarm; once the monitoring system detects an abnormal condition in the motor, it will trigger an alarm mechanism. The integrated alarm system can inform operators and maintenance personnel in time in a mode of e-mail, short message, visual interface and the like so that the operators and maintenance personnel can take corresponding measures to cope with the problems; based on the health indicator and the fault diagnosis result, the monitoring system generates a maintenance plan including a repair recommendation, a replacement recommendation, and a maintenance schedule. These plans can help maintenance personnel to perform reasonable maintenance and repair work, improving the reliability and service life of the motor; through the use of historical data and trend analysis tools, the monitoring system can track changes in motor performance and predict future problems that may occur. This helps to formulate more accurate maintenance plans and optimize operation and maintenance strategies; according to actual conditions and demand changes, the monitoring system can be continuously optimized. This includes updating the health model, improving the fault diagnosis algorithm, and optimizing the alarm strategy to accommodate changing demands.
The technical scheme has the effects that: through the health condition of real-time supervision motor to compare with preset health index threshold value, once discovery is unusual and problem, can in time trigger the alarm. This helps to quickly discover potential failures and problems and take appropriate action to avoid further damage and downtime; based on the sensor data, the history and the health model, the system can analyze the fault type, the position and the severity problems and abnormal conditions in the motor and the motor drive intelligent regulation and control system. The method is beneficial to accurately diagnosing faults, provides guidance for maintenance personnel, and can quickly locate and repair problems; by generating a maintenance plan, including repair recommendations, replacement recommendations, and maintenance schedules, the system can assist maintenance personnel in performing efficient maintenance work. Meanwhile, by analyzing historical data and trend prediction, the system can predict the possible problems of the motor in advance, and a maintenance plan is formulated in a targeted manner, so that the reliability and the service life of the motor are improved to the greatest extent; through the integrated alarm system, the system can timely inform operators and maintenance personnel through e-mails, short messages, visual interfaces and the like. The motor control system is beneficial to enabling the motor to know the health state and abnormal condition of the motor in time, and taking corresponding measures to improve the operation efficiency and safety of the equipment; the scheme supports continuous optimization and updating of health models, fault diagnosis algorithms, and alarm strategies. This can make the system continuously adapt to changing demands and new technological developments, improving the accuracy and effect of monitoring and management.
According to one embodiment of the invention, the fault detection module stores the sensor data by establishing a big data storage system on a cloud server; the storage step comprises the following steps:
B1: determining the total storage space of a cloud server, dividing the storage space according to the requirement index of a sensor, and determining the size and the capacity of each storage partition according to the size of data volume and the access frequency; the demand index comprises the total amount of sensor data, the generation frequency and the storage period;
b2: dividing the storage space of the cloud server according to different sensor data types, importance and access frequency; for example, the data can be partitioned according to the characteristics of the data, such as the time, the equipment, the sensor type and the like, so that the data are stored independently of each other, and the management and the retrieval are convenient. Selecting a storage technology and cloud services according to the divided storage space, wherein the storage technology and the cloud services comprise object storage, file storage and database storage;
B3: compressing and optimizing sensor data through a compression algorithm and a data de-duplication algorithm, and backing up the compressed and optimized data and designing a redundancy strategy; for example; data backup may be selected across available areas, across data centers, etc. to address the risk of hardware failure and data loss.
B4: and monitoring the performance and capacity use condition of the storage system, and timely adjusting the storage space division and expansion plan.
The working principle of the technical scheme is as follows: the size and capacity of each storage partition is determined according to the total storage space of the cloud server and the demand indicators of the sensor data, such as the data amount, the generation frequency and the storage period. This may be divided according to different factors, such as time, device and sensor type, etc., in order to manage and retrieve data; according to the divided storage space, a proper storage technology and cloud service are selected. Common storage techniques include object storage, file storage, and database storage. Selecting proper storage technology and cloud service according to the data type, importance, access frequency and other factors; and compressing and optimizing the sensor data to reduce the occupation of the storage space and improve the data transmission efficiency. Compression algorithms and data deduplication algorithms may be used to achieve compression and optimization of data. The optimized data also needs to design backup and redundancy strategies to cope with the risks of hardware faults and data loss; appropriate backup strategies are selected, such as data backup across available areas, across data centers, etc., to ensure redundant storage and reliability of the data. This can improve the usability of the data and prevent data loss and corruption; and monitoring the performance and capacity use condition of the storage system, and timely adjusting the storage space division and expansion plan according to the requirement.
The technical scheme has the effects that: by rationally dividing the storage space and selecting an appropriate storage technique, efficient storage of sensor data can be achieved. Different types of data can be stored independently, so that management and retrieval are convenient, and the access speed and response performance of the data are improved; and the sensor data is compressed and optimized through a compression algorithm and a data deduplication algorithm, so that the occupation of storage space is reduced. This helps to save costs and reduce maintenance burden on the storage system; by designing backup and redundancy strategies, reliable storage of sensor data is achieved. Data backup in modes of cross-available area, cross-data center and the like can improve the usability of the data and prevent the data from being lost and damaged; the storage space division and the expansion plan adjustment are timely carried out by monitoring the performance and the capacity use condition of the storage system. This helps to maintain efficient operation of the storage system and accommodates the ever-increasing amount and demand of sensor data.
In one embodiment of the present invention, as shown in fig. 2, a motor-driven intelligent regulation system, the system includes:
the demand analysis module: analyzing a motor driving intelligent regulation and control system, and determining the system requirement of the motor driving intelligent regulation and control system, wherein the system requirement comprises control precision, a speed range, a torque requirement and performance indexes;
and a drive control module: according to the requirements of a motor driving intelligent regulation and control system, a motor and a sensor are selected, the motor data are measured through the sensor, feedback information of the measured data is obtained, and the motor is controlled to move through the feedback information and a motor driving control algorithm; the motor data comprises the position, the speed and the current state of the motor;
And the real-time control module is used for: a real-time control system is established through the sensor data and the motor drive control algorithm, the motor data is monitored in real time, a real-time monitoring result is obtained, and parameters of the motor drive control algorithm are adjusted based on the real-time monitoring result;
And a safety monitoring module: the method comprises the steps of establishing a safety monitoring control system, wherein the safety monitoring control system comprises a user interface module and a fault detection module, and the user interface module is used for monitoring and adjusting the running state of a motor by an operator; the fault detection module finds and diagnoses the system fault and performs performance tuning.
The working principle of the technical scheme is as follows: by analyzing the motor-driven intelligent regulation and control system, the requirements of the system are determined, including control accuracy, speed range, torque requirement and other performance indexes. These requirements will be the basis for the subsequent selection of motors and sensors; suitable motors and sensors are selected according to system requirements. The sensors are used to measure motor data and provide feedback information including position, speed, current status, etc. The motor motion is controlled through the data measured by the sensor and a motor driving control algorithm; based on the sensor data and the motor drive control algorithm, a real-time control system is established. The system can monitor motor data in real time and obtain real-time monitoring results. According to the real-time monitoring result, parameters of a motor driving control algorithm are adjusted to optimize the performance of the system; to ensure the safety of the system, a safety monitoring control system is established. The system includes a user interface module and a fault detection module. The user interface module is used for an operator to monitor the running state of the motor and correspondingly adjust the running state. The fault detection module is used for detecting and diagnosing system faults and performing performance tuning so as to ensure the reliability and stability of the system.
The technical scheme has the effects that: through the analysis of the motor drive intelligent regulation and control system demand and the adjustment of parameters, the accurate control of the motor motion can be realized. The control precision of the system can be improved, and the requirements of different application scenes are met; by establishing a real-time control system and real-time monitoring of sensor data, the position, speed, current state and other information of the motor can be timely obtained. The method is beneficial to knowing the running state of the motor in real time, finding problems in time and adjusting, and improving the stability and reliability of the system; the safety monitoring control system is established to ensure the safety of the system. The user interface module may provide operator monitoring and adjustment capabilities for the motor operating conditions, increasing the flexibility and ease of use of the system. The fault detection module can timely detect and diagnose system faults and perform performance tuning, so that the influence of the system faults on production and equipment is reduced; through optimization and parameter adjustment of the motor driving intelligent regulation and control system, performance indexes of the system, such as control precision, speed range, torque requirement and the like, can be improved. This helps to improve production efficiency and product quality, meeting the user's requirements for system performance.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.