Disclosure of Invention
The embodiment of the invention provides a bus module disconnection control method, device, equipment and storage medium aiming at the defects, which are used for solving the problems existing in the prior art.
In order to solve the above technical problems, an embodiment of the present invention provides a bus module disconnection control method, where the method includes:
the upper computer terminal is controlled to send a state inquiry command at regular time so as to monitor the running states of the bus module master station and the bus module slave station in real time;
If the abnormal operation of the bus module master station and the bus module slave station is monitored, a fault prediction mechanism is triggered;
acquiring the current working phase and load conditions of the bus module master station and the bus module slave station;
according to the current working phase and the load condition of the bus module master station and the bus module slave station, dynamically adjusting the prediction parameters of a fault prediction model;
applying the adjusted prediction parameters to the fault prediction model;
the upper computer terminal is controlled to conduct fault prediction on the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station;
and controlling the upper computer terminal to take measures in advance according to the fault prediction result so as to prevent the bus module master station and the bus module slave station from actually disconnecting.
Preferably, the dynamically adjusting the prediction parameters of the fault prediction model according to the current working phases and the load conditions of the bus module master station and the bus module slave station includes:
confirming that the current working phases of the bus module master station and the bus module slave station are a starting phase, a stable operation phase or a heavy load phase;
Confirming that the current load conditions of the bus module master station and the bus module slave station are light load, standard load or heavy load;
according to a preset prediction parameter adjustment rule, the adjustment direction of the prediction parameters under different working phases and load conditions is defined;
And actually adjusting the prediction parameters according to the adjustment directions of the prediction parameters.
Preferably, before the control upper computer terminal actively sends a state query command at regular time so as to monitor the running states of the bus module master station and the bus module slave station in real time, the bus module disconnection control method further comprises the following steps:
The bus module slave station is controlled to automatically apply for a communication address after accessing a communication bus, and monitor communication data of the communication bus;
If the communication address received by the bus module slave station is the same as the self address, address conflict reporting processing is carried out;
If the bus module slave station does not receive conflict signals of other module nodes, the bus module slave station address application is judged to be successful, and the normal communication state is entered.
Preferably, the controlling the host computer terminal performs fault prediction on the bus module master station and the bus module slave station according to the fault prediction model, so as to predict a disconnection condition of the bus module master station and the bus module slave station includes:
collecting historical operation data of the bus module master station and the bus module slave station;
Training historical operation data of the bus module master station and the bus module slave station according to a machine learning algorithm, and establishing the fault prediction model;
And inputting real-time monitoring data of the bus module master station and the bus module slave station into the fault prediction model, and outputting the fault prediction result.
Preferably, the method for controlling the disconnection of the bus module further comprises the following steps:
feeding back the fault prediction result and the actual disconnection condition to the upper computer terminal;
And controlling the upper computer terminal to optimize the fault prediction model according to the fault prediction result and the actual disconnection condition.
Preferably, the determining the adjustment direction of the prediction parameters under different working phases and load conditions according to a preset adjustment rule of the prediction parameters includes:
Judging whether the prediction parameters need to be adjusted according to different working stages and load conditions;
if necessary, according to a preset prediction parameter adjustment rule, the adjustment directions of the prediction parameters under different working phases and load conditions are defined.
Preferably, the determining the adjustment direction of the prediction parameters under different working phases and load conditions according to a preset adjustment rule of the prediction parameters further includes:
And if not, applying the current prediction parameters to the fault prediction model.
In order to solve the above technical problems, an embodiment of the present invention provides a bus module disconnection control device, including:
The monitoring module is used for controlling the upper computer terminal to send a state inquiry command at fixed time so as to monitor the running states of the bus module master station and the bus module slave station in real time;
the triggering module is used for triggering a fault prediction mechanism if abnormal operation of the bus module master station and the bus module slave station is monitored;
the information confirmation module is used for acquiring the current working phase and load condition of the bus module master station and the bus module slave station;
The dynamic adjustment module is used for dynamically adjusting the prediction parameters of the fault prediction model according to the current working phase and the load condition of the bus module master station and the bus module slave station;
an optimization module for applying the adjusted prediction parameters to the fault prediction model so as to optimize the fault prediction model;
The fault prediction module is used for controlling the upper computer terminal to perform fault prediction on the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station;
and the prevention module is used for controlling the upper computer terminal to take measures in advance according to the prediction result so as to prevent the bus module master station and the bus module slave station from actually disconnecting.
To solve the above technical problems, an embodiment of the present invention provides a bus module drop control device, including at least one processor, at least one memory, and computer program instructions stored in the memory, where the computer program instructions implement a method according to the first aspect of the above embodiment when executed by the processor.
To solve the above technical problem, an embodiment of the present invention provides a storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method as in the first aspect of the above embodiments.
In summary, the embodiment of the invention provides a method, a device, equipment and a storage medium for controlling a bus module to be disconnected. The method comprises the steps of controlling an upper computer terminal to send a state inquiry command at fixed time so as to monitor the running states of a bus module master station and a bus module slave station in real time, triggering a fault prediction mechanism if abnormal running of the bus module master station and the bus module slave station is monitored, acquiring the current working stage and load condition of the bus module master station and the bus module slave station, dynamically adjusting prediction parameters of a fault prediction model according to the current working stage and load condition of the bus module master station and the bus module slave station, applying the adjusted prediction parameters to the fault prediction model so as to optimize the fault prediction model, controlling the upper computer terminal to conduct fault prediction on the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station, and controlling the upper computer terminal to take measures in advance according to prediction results so as to prevent the actual disconnection of the bus module master station and the bus module slave station. Therefore, the invention can effectively realize the anti-drop control of the bus module and improve the working stability of the bus module.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely configured to illustrate the invention and are not configured to limit the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the invention by showing examples of the invention.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that comprises an element.
Referring to fig. 1, fig. 1 is a schematic diagram of a bus module disconnection control method according to the present application, the method includes the following steps:
S1, controlling an upper computer terminal to send a state query instruction at fixed time so as to monitor the running states of a bus module master station and a bus module slave station in real time.
Specifically, in the present embodiment, the bus module includes a bus module master station and a bus module slave station. The bus module master station acts as a control center in the network and is responsible for managing network communications and operations and exchanging data with the various bus module slaves. The bus module slave station is used as an execution unit to respond to the instruction of the master station and complete the appointed task. A one-to-many control relationship is formed between the bus module master station and the bus module slave station.
Specifically, in this embodiment, the communication data transmission is performed between the master station of the bus module, the slave stations of each bus module, and the upper computer terminal through communication technologies such as CAN protocol, modbus protocol, CANopen protocol, profinet protocol, etherCAT protocol, etc., and the communication mode among the master station of the bus module, the slave stations of each bus module, and the upper computer terminal is not limited herein.
Specifically, in this embodiment, the upper computer terminal is configured as a master control center of the system, and is configured to periodically send a status query instruction. The sending period of the state query command is set according to the actual network environment and the system requirement, and is not particularly limited herein. It can be understood that, through the state inquiry instruction, the host computer terminal can monitor the running state of the bus module master station and the bus module slave station in real time, so as to ensure that the state of the bus module can be effectively monitored and network resources can not be excessively occupied.
S2, if abnormal operation of the bus module master station and the bus module slave station is monitored, a fault prediction mechanism is triggered.
Specifically, in this embodiment, after the state query instruction is issued, the upper computer terminal receives response signals from the bus module master station and the bus module slave station. On the one hand, the upper computer terminal judges whether the bus module master station and the bus module slave station normally operate or not through the response signal, and if the response is not received within the preset time, the bus module is indicated to have the disconnection risk. On the other hand, the upper computer terminal performs data analysis on the response signal after receiving the corresponding signal to acquire the operation data of the bus module master station and the bus module slave station, and if the bus module master station and the bus module slave station are abnormal in operation, a fault prediction mechanism is triggered.
Specifically, in this embodiment, the judging parameters of the abnormal operation of the master station and the slave station of the bus module include a communication state, and whether the communication is abnormal is judged by monitoring parameters such as whether a communication signal exists, signal strength, communication delay and the like, and also include electrical parameters such as current, voltage, power and the like, if the parameters exceed a normal working range, the abnormal operation of the device may be indicated, in addition, the judging parameters further include temperature, and abnormal increase of the temperature of the device may indicate overload or failure of the device and the like, which is not limited in this description.
S3, acquiring the current working phase and load conditions of the master station of the bus module and the slave station of the bus module.
Specifically, in this embodiment, after the failure prediction mechanism is triggered, the upper computer terminal further sends a status query instruction to obtain more detailed status information such as the current working phases and load conditions of the bus module master station and the bus module slave station.
It is worth noting that the bus module master and the bus module slave have different operating characteristics at different operating phases. For example, the current and temperature are different for the start-up phase and the steady operation phase. In addition, the load of the bus module master and the bus module slave directly affects the workload and wear. For example, high loads may result in an increased risk of equipment failure. Thus, the working phase and load conditions are key factors affecting the operating state of the device. When the application predicts faults, besides considering abnormal operation parameters of the modules, the working phases and the load conditions of the master station and the slave station of the bus module are used as characteristic inputs, so that the fault prediction model is more suitable for the current operation environment, and the accuracy of prediction is improved.
It is worth to say that, the application triggers the failure prediction mechanism again when monitoring the abnormal state of the master station of the bus module and the slave station of the bus module, and carries out the failure prediction after triggering the failure prediction mechanism, thereby achieving effective balance in network communication efficiency and failure prediction, not only ensuring the network communication rate when the master station of the bus module and the slave station of the bus module normally work, but also realizing failure early warning when the master station of the bus module and the slave station of the bus module are abnormal, and effectively preventing the actual disconnection of the master station of the bus module and the slave station of the bus module.
S4, dynamically adjusting the prediction parameters of the fault prediction model according to the current working stage and load conditions of the master station of the bus module and the slave station of the bus module.
S5, applying the adjusted prediction parameters to the fault prediction model.
Specifically, in this embodiment, the upper computer terminal dynamically adjusts the prediction parameters of the preset fault prediction model according to the difference between the current working phases and the load conditions of the received bus module master station and the bus module slave station, and applies the adjusted prediction parameters to the fault prediction model, so that the fault prediction model can output a more accurate prediction result when performing fault prediction, and the network communication quality of the bus module is improved.
S6, controlling the upper computer terminal to conduct fault prediction on the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station.
And S7, controlling the upper computer terminal to take measures in advance according to the prediction result so as to prevent the bus module master station and the bus module slave station from actually disconnecting.
Specifically, in this embodiment, the host computer terminal predicts the bus module master station and the bus module slave station using the updated failure prediction model. If the prediction result shows that the bus module master station or the bus module slave station has the risk of disconnection, the upper computer terminal takes measures to prevent the bus module master station or the bus module slave station from actually disconnecting.
Specifically, in this embodiment, measures for preventing the bus module master station and the bus module slave station from actually dropping include sending an alarm to an operator, redistributing the network load to relieve the pressure of the high risk module, or starting the spare module or the redundant path to keep the system stable, etc., which are not limited in detail herein.
Therefore, the bus module disconnection control method provided by the application can actively prevent and respond to potential disconnection problems of the bus module master station and the bus module slave station, thereby improving the reliability and stability of the whole network.
In summary, the application provides a bus module disconnection control method, in the scheme, a state inquiry command is sent at regular time by controlling an upper computer terminal so as to monitor the running states of a bus module master station and a bus module slave station in real time, thereby timely finding out abnormality. If abnormal operation of the bus module master station and the bus module slave station is monitored, a fault prediction mechanism is triggered, potential faults are predicted, and the risk of system operation is reduced. The current working stage and load condition of the bus module master station and the bus module slave station are obtained, and accurate data support is provided for fault prediction. According to the current working stage and load condition of the master station and the slave station of the bus module, the prediction parameters of the fault prediction model are dynamically adjusted, and the accuracy of fault prediction is improved. The adjusted prediction parameters are applied to the fault prediction model so as to optimize the fault prediction model, and the fault prediction model can be ensured to reflect the actual running condition of the bus module more accurately. And the control upper computer terminal predicts faults of the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station. And the control upper computer terminal takes measures in advance according to the prediction result to prevent the actual disconnection of the bus module master station and the bus module slave station and ensure the stable operation of the bus module master station and the bus module slave station. Therefore, the application can effectively realize the anti-drop control of the bus module and improve the working stability of the bus module.
Based on the above embodiments:
Referring to fig. 2, fig. 2 is a schematic flow chart of dynamically adjusting prediction parameters of a fault prediction model according to current working phases and load conditions of a master station and a slave station of a bus module.
As a preferred embodiment, dynamically adjusting the prediction parameters of the fault prediction model according to the current working phase and load conditions of the bus module master station and the bus module slave station includes:
S41, confirming that the current working phases of the bus module master station and the bus module slave station are a starting phase, a stable operation phase or a heavy load phase.
Specifically, in this embodiment, by monitoring the operation parameters of the bus module master station and the bus module slave station, it is automatically identified whether the bus module master station and the bus module slave station are in the start-up phase, the steady operation phase, or the heavy load phase.
Further, in this embodiment, if the system is just started, it is determined as a start-up phase, if the system is running stably and has no abnormal fluctuation, it is determined as a steady running phase, and if the system load exceeds a preset threshold, it is determined as a heavy load phase.
Specifically, in the present embodiment, the difference in working phases affects the accuracy and efficiency of the failure prediction model. For example, a startup phase may require more sensitive prediction parameters to capture incipient instability, while a steady operation phase may require more stable prediction parameters to reduce false positives. Therefore, the application confirms that the current working phases of the master station and the slave station of the bus module are conducive to more accurately adjusting the prediction model, thereby improving the accuracy of prediction.
S42, confirming that the current load conditions of the bus module master station and the bus module slave station are light load, standard load or heavy load.
Specifically, in this embodiment, the bus module master station and the bus module slave station are identified as currently being lightly loaded, standard loaded, and heavily loaded by monitoring the load conditions of the bus module master station and the bus module slave station, such as CPU usage, memory usage, and the like.
Further, the bus module master station and the bus module slave station determine light load if the CPU utilization rate of the bus module master station and the bus module slave station is lower than 30%, determine standard load if the CPU utilization rate of the bus module master station and the bus module slave station is between 30% and 70%, and determine heavy load if the CPU utilization rate of the bus module master station and the bus module slave station is higher than 70%. It will be appreciated that the distinction between light load, standard load and heavy load may be set as desired and is not specifically limited herein.
Specifically, in this embodiment, the difference in load conditions affects the probability and type of occurrence of a bus module master and a bus module slave failure. Therefore, the application can effectively predict the potential faults by adjusting the prediction parameters according to the load condition, thereby taking preventive measures.
S43, according to a preset prediction parameter adjustment rule, the adjustment directions of the prediction parameters in different working phases and under the load condition are defined.
Specifically, in this embodiment, the preset adjustment rule is used to guide parameter adjustment of the fault prediction model under different working phases and load conditions, so as to ensure the accuracy of prediction.
S44, actually adjusting the prediction parameters according to the adjustment directions of the prediction parameters.
Specifically, in this embodiment, the preset prediction parameter adjustment rule specifically includes:
in the starting stage, the sensitivity of the predicted parameters is increased if the load is light, in the steady operation stage, the predicted parameters are kept unchanged if the load is standard, and in the heavy load stage, the sensitivity of the predicted parameters is reduced to avoid false alarm no matter what the working stage is.
Referring to fig. 3, fig. 3 is a schematic flow chart before the upper computer terminal is controlled to actively send a state query command at regular time so as to monitor the operation states of the master station and the slave station of the bus module in real time.
As a preferred embodiment, before the host computer terminal is controlled to actively send a state query command at regular time so as to monitor the operation states of the bus module master station and the bus module slave station in real time, the bus module disconnection control method further includes:
and S01, automatically applying for a communication address after the control bus module slave station accesses the communication bus, and monitoring communication data of the communication bus.
In particular, in a bus communication system, each bus module slave is provided with a unique communication address for communicating with a bus module master. When the bus module secondary station is powered on or reset, a specific address application frame is automatically sent to the communication bus, data on the bus is monitored, and the address distributed by the upper computer terminal is ready to be received. It will be appreciated that automatically applying for a communication address ensures that the bus slave module can successfully access the communication network.
And S02, if the communication address received by the bus module slave station is the same as the self address, performing address conflict reporting processing.
Specifically, address collision may cause communication confusion, and multiple bus slave modules may not normally communicate using the same address. In this embodiment, if the bus slave module detects that the address in one address allocation instruction is the same as the address applied by itself when listening to the bus data, it will immediately stop communication, and report an address conflict to the host terminal or the bus module master station, and request to reallocate the address.
S03, if the bus module slave station does not receive conflict signals of other module nodes, judging that the address application of the bus module slave station is successful, and entering a normal communication state.
Specifically, in this embodiment, if the bus module slave station does not receive the collision signal of the other module nodes, it is determined that the bus module slave station obtains the unique communication address, and enters the normal communication state. Therefore, the application ensures that the slave station module can quickly enter the normal working state under the condition of no conflict, and improves the response speed and the stability of the system.
Referring to fig. 4, fig. 4 is a schematic flow chart of a control upper computer terminal according to the present application for performing fault prediction on a bus module master station and a bus module slave station according to a fault prediction model so as to predict a disconnection condition of the bus module master station and the bus module slave station.
As a preferred embodiment, the controlling the host computer terminal to predict the failure of the bus module master station and the bus module slave station according to the failure prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station includes:
s61, collecting historical operation data of the master station and the slave stations of the bus module.
S62, training historical operation data of the bus module master station and the bus module slave station according to a machine learning algorithm, and establishing a fault prediction model.
S63, inputting real-time monitoring data of the bus module master station and the bus module slave station into a fault prediction model, and outputting a fault prediction result.
Specifically, in this embodiment, the fault prediction model is a logical Sigmoid function, and the formula is specifically:
;
wherein y represents the probability of occurrence of faults, y is more than or equal to 0 and less than or equal to 1, and y is used for indicating the probability of occurrence of faults;
representing working phases, load conditions, abnormal operation parameters and the like of a bus module master station and a bus module slave station in the operation process as a set of input features;
wi represents the weight of each input feature, namely a fault prediction parameter, which reflects the importance degree of the input feature to the fault prediction;
b represents the bias term of the fault prediction model for further adjusting the accuracy of the prediction result, and n represents the number of input features.
Specifically, in the present embodiment, the working phase, the load condition, and the abnormal operation parameters of the bus module are converted into the input features of the failure prediction model. Working phase Encoding-Encoding the working phase (start-up, steady running, heavy load) to a digital signature, for example using One-Hot Encoding (One-Hot Encoding). Load situation quantification-the load situations (light load, standard load, heavy load) are quantified as values, and the percentage or grading values of the actual load are directly used. The abnormal operation parameters are standardized or normalized, wherein different abnormal parameters have different dimensions and numerical ranges, and the standardized or normalized process is needed to eliminate the dimension influence, so that the contribution of each feature to the model is equal.
Specifically, in the present embodiment, when designing the input layer of the logical Sigmoid function, features such as the working phase, the load condition, and the abnormal operation parameter of the bus module are taken as the input node (xi). The number of input layer nodes should be equal to the sum of all features, including working phase encoding, load situation quantization values, and possibly other monitoring parameters.
Specifically, in the present embodiment, an adjustment strategy of the prediction parameters is defined according to the working phase and the load condition.
Specifically, in this embodiment, the weight of each input feature, i.e., the prediction parameter, is adjusted by defining a weight adjustment rule in advance according to different working phases, load conditions, and abnormal operation parameters. For example, if the failure prediction model's response to certain features during heavy load phases needs to be enhanced, the weights of those features are increased.
Specifically, in this embodiment, the bias term may be adjusted according to the characteristics of different stages, which is not limited herein.
The method comprises the steps of carrying out model training, and adjusting prediction parameters according to the following steps, wherein in the model running process, working phases and load conditions of a module can be monitored in real time, and parameters can be dynamically adjusted.
Specifically, in the present implementation, the Sigmoid activation function is used to compress the output to between 0 and 1, i.e., translate the output of the fault prediction model into a probability of fault occurrence. Wherein, the fault is coded as 1, and the fault is not coded as 0.
Specifically, in the present implementation, after model training is completed, the output y is converted into an actual failure prediction result using the following method:
the threshold is set by setting a threshold (e.g. 0.5) above which if y is greater then a fault is predicted, otherwise no fault is predicted. For example, in prediction:
model output y was 0.65, indicating a 65% probability of failure.
Threshold decision if the threshold is set to 0.5, the predicted outcome is a fault as 0.65 > 0.5.
Referring to fig. 5, fig. 5 is a schematic flow chart of a control upper computer terminal according to the present application for performing fault prediction on a bus module master station and a bus module slave station according to a fault prediction model so as to predict a disconnection condition of the bus module master station and the bus module slave station.
As a preferred embodiment, the method for controlling the disconnection of a bus module according to the present application further includes:
s64, feeding back a fault prediction result and an actual disconnection condition to the upper computer terminal.
And S65, controlling the upper computer terminal to optimize a fault prediction model according to the fault prediction result and the actual disconnection condition.
Specifically, the application can carry out optimization training on the fault prediction model according to the historical operation data of the bus module master station and the bus module slave station, including the fault prediction result and the actual disconnection condition. For example, assume that during a heavy load phase, the historical data shows that the failure prediction results correspond to actual dropped conditions, the prediction is accurate, and that the correlation of certain features with the failure increases in the historical data. The system will increase the weight of these features so that the fault prediction model is more focused on these features. The system applies these weight adjustments to the fault prediction model and retrains the fault prediction model.
Referring to fig. 6, fig. 6 is a schematic flow chart before defining the adjustment directions of the prediction parameters under different working phases and load conditions according to the preset adjustment rules of the prediction parameters.
As a preferred embodiment, determining the adjustment direction of the prediction parameters in different working phases and under load conditions according to a preset prediction parameter adjustment rule includes:
s431, judging whether the prediction parameters need to be adjusted according to different working phases and load conditions.
S432, if necessary, determining the adjustment directions of the prediction parameters under different working phases and load conditions according to a preset prediction parameter adjustment rule.
As a preferred embodiment, determining the adjustment direction of the prediction parameters in different working phases and under load conditions according to the preset adjustment rule of the prediction parameters further includes:
S433, if not needed, the current prediction parameters are applied to the fault prediction model.
Referring to fig. 7, an embodiment of the present invention provides a bus module drop control device, including:
The monitoring module 1 is used for controlling the upper computer terminal to send a state inquiry command at regular time so as to monitor the running states of the bus module master station and the bus module slave station in real time.
And the triggering module 2 is used for triggering a fault prediction mechanism if abnormal operation of the bus module master station and the bus module slave station is monitored.
And the information confirmation module 3 is used for acquiring the current working phase and load condition of the bus module master station and the bus module slave station.
And the dynamic adjustment module 4 is used for dynamically adjusting the prediction parameters of the fault prediction model according to the current working phase and load conditions of the master station of the bus module and the slave station of the bus module.
And an optimization module 5, configured to apply the adjusted prediction parameters to the failure prediction model.
The fault prediction module 6 is used for controlling the upper computer terminal to perform fault prediction on the bus module master station and the bus module slave station according to the fault prediction model so as to predict the disconnection condition of the bus module master station and the bus module slave station.
And the prevention module 7 is used for controlling the upper computer terminal to take measures in advance according to the prediction result so as to prevent the bus module master station and the bus module slave station from actually disconnecting.
In addition, a method for controlling a bus module drop in accordance with the embodiment of the present invention described in connection with fig. 1 may be implemented by a network bus module drop control device. Fig. 8 is a schematic diagram of a hardware structure of a bus module drop control device according to an embodiment of the present invention.
The bus module drop control device may include a processor 401 and a memory 402 in which computer program instructions are stored.
In particular, the processor 401 may include a Central Processing Unit (CPU), or an Application SPECIFIC INTEGRATED Circuit (ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present invention.
The memory 402 may include mass storage for data or instructions. By way of example, and not limitation, memory 402 may comprise a hard disk drive (HARD DISK DRIVE, HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a universal serial bus (Universal Serial Bus, USB) drive, or a combination of two or more of the foregoing. Memory 402 may include removable or non-removable (or fixed) media, where appropriate. Memory 402 may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory 402 is a non-volatile solid state memory. In a particular embodiment, the memory 402 includes Read Only Memory (ROM). The ROM may be mask programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these, where appropriate.
The processor 401 reads and executes the computer program instructions stored in the memory 402 to implement any of the bus module drop control methods in the above embodiments.
In one example, the bus module drop control device may also include a communication interface 403 and a bus 410. As shown in fig. 8, the processor 401, the memory 402, and the communication interface 403 are connected to each other by a bus 410 and perform communication with each other.
The communication interface 403 is mainly used to implement communication between each module, device, unit and/or apparatus in the embodiment of the present invention.
Bus 410 includes hardware, software, or both, that couple the components of the bus module drop control device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 410 may include one or more buses, where appropriate. Although embodiments of the invention have been described and illustrated with respect to a particular bus, the invention contemplates any suitable bus or interconnect.
In addition, in combination with the method for controlling the disconnection of the bus module in the above embodiment, the embodiment of the invention may be implemented by providing a computer readable storage medium. The computer readable storage medium has stored thereon computer program instructions which when executed by a processor implement any of the bus module drop control methods of the above embodiments.
It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. The present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.
In the foregoing, only the specific embodiments of the present invention are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present invention is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and they should be included in the scope of the present invention.