Industrial robot fault analysis system based on internetTechnical Field
The invention relates to the technical field of robots, in particular to an industrial robot fault analysis system based on the Internet.
Background
Under the background of rapid development of the Internet, more and more intelligent devices replace manpower to complete various complex operations, a robot is one of typical intelligent devices, particularly in an application scene of intelligent storage, the robot is required to transport and process tasks in the storage, and backlog can be effectively avoided only when the robot runs efficiently and safely.
The fault of the robot is unavoidable in a long-time running state, so that the analysis of the fault of the industrial robot becomes important in time and accurately, the existing fault analysis scheme for the industrial robot is inaccurate, a lot of misleading information exists, the experience requirement on technicians is quite high, and the maintenance speed of the industrial robot is low.
Disclosure of Invention
The invention aims to provide an industrial robot fault analysis system based on the Internet, wherein a controller diagnosis module is used for monitoring data in the operation process of an industrial robot and sending the data of the industrial robot to a diagnosis processor, the diagnosis processor is used for receiving the data of the industrial robot sent by the controller diagnosis module and matching an adaptive fault case in the diagnosis processor according to the data of the industrial robot, and when the fault case matched with the data of the industrial robot is stored in the diagnosis processor, the fault case matched with the data of the industrial robot is used as a target case, and diagnosis information of the target case is sent to a terminal device, so that a technician can conveniently process the fault of the industrial robot.
The aim of the invention can be achieved by the following technical scheme:
An internet-based industrial robot fault analysis system comprising a controller diagnostic module for a robot;
The controller diagnosis module comprises a dynamic monitoring unit for the industrial robot;
The dynamic detection unit calculates operation data of the industrial robot to obtain a fault point and a fault parameter of the industrial robot, and obtains the dumping time of the industrial robot based on the fault parameter, wherein the dumping time is the fault clearing time in the operation process of the industrial robot;
The fault parameters are sent to a diagnosis processor, and the diagnosis processor performs diagnosis analysis;
and sending the fault clearing time to the terminal equipment, so that a technician can complete fault diagnosis within the fault clearing time.
As a further scheme of the invention, the dynamic monitoring unit comprises four pressure sensors, two height sensors, a first acceleration sensor and a second acceleration sensor, wherein the four pressure sensors are respectively arranged on the bottom surfaces of four machine feet of the industrial robot, a first speed sensor is arranged on the left front foot of the industrial robot, a second speed sensor is arranged on the left rear foot of the industrial robot, two height sensors are arranged, one height sensor is arranged between the two front machine feet of the industrial robot, and the other height sensor is arranged between the two rear machine feet of the industrial robot.
As a further scheme of the invention, the dynamic monitoring unit specifically detects the operation data of the industrial robot as follows:
The method comprises the steps that firstly, pressure information of an industrial robot is monitored in real time through a pressure sensor, pressure information values obtained by the same walking cycle of four machines of the industrial robot are obtained, the maximum value and/or the minimum value in the group of data are deleted, the average pressure value of the rest data in the group of data is obtained through calculation, and the average pressure value is marked as Fi, i=1, and the number of the rest data is n;
Comparing the average pressure value in the running process of the industrial robot in the step one with a preset pressure value uploaded by terminal equipment, and calculating a difference value to obtain a pressure difference Pi, and judging that the industrial robot moves normally when Pi < Ki, ki is a preset pressure threshold value in the same period of time;
If Pi is more than or equal to Ki, judging the running state of the industrial robot;
When judging the running state of the industrial robot, acquiring a first speed of the left front foot of the industrial robot in real time through a first speed sensor, marking the first speed as Vi1, acquiring a second speed of the left rear foot of the industrial robot in real time through a second speed sensor, marking the second speed as Vi2, and comparing the difference between the first speed Vi1 and the second speed Vi 2;
if Vi1-Vi2 is not equal to 0, judging that the industrial robot has a fault and has a tilting risk;
Step four, when judging that the industrial robot fails, acquiring a front end height value in real time through a height sensor between two front machine feet of the industrial robot and marking the front end height value as Hi1, and acquiring a rear end height value in real time through a height sensor between two rear machine feet of the industrial robot and marking the rear end height value as Hi2 in the same walking period;
calculating the difference value between the front end height value H11 and the rear end height value H12 in the same walking period of the industrial robot, namely Z1= -H11-H12|;
taking the difference between the front end height value H21 and the rear end height value H22 in the adjacent walking period, namely Z2= |H221-H2|;
Comparing the difference between Z1 and Z2, and calculating according to a formula Ch= -Z1-Z2|toobtain a height difference Ch in the walking process of two adjacent industrial robots;
Step six, setting the difference value between the critical height of the industrial robot toppling in the walking process and the height of the industrial robot in the normal state as D, and according to the formulaAnd calculating the dumping time of the industrial robot.
In the fourth step, the difference value between the front end height value Hi1 and the rear end height value Hi2 is compared;
if Hi1-Hi2>0, the rear robot foot of the industrial robot fails;
If Hi1-Hi2<0, the front robot foot of the industrial robot fails.
As a further scheme of the invention, the controller diagnosis module further comprises a data acquisition unit for acquiring the operation parameters of the industrial robot based on the diagnosis result of the industrial robot.
As a further scheme of the invention, the operation parameters of the industrial robot comprise the electricity storage capacity of the industrial robot, the total operation period of the industrial robot and the failure times of the industrial robot;
the data acquisition unit processes the data as follows:
s1, acquiring the storage capacity of the industrial robot, and marking the storage capacity of the industrial robot as Xi;
s2, acquiring the total operation period of the industrial robot, and marking the total operation period of the industrial robot as Ni;
S3, acquiring the failure times of the industrial robot, and marking the failure times of the industrial robot as Mi;
s4, acquiring an industrial robot running environment parameter Ji=beta× (xi×d1+Ni×d2+Mi×d3) ×e1.1564 through a formula, wherein d1, d2 and d3 are preset proportionality coefficients, and d1> d2> d3 and e are natural constants;
S5, comparing the operation environment parameter Ji of the industrial robot with the normal operation reference threshold value of the industrial robot;
if the operation environment parameter of the industrial robot is smaller than the normal operation reference threshold value of the industrial robot, the operation state of the industrial robot is not ideal, abnormal information is produced, and the abnormal information is fed back to the terminal equipment;
if the industrial robot operating environment parameter is higher than the industrial robot operating normal reference threshold, the industrial robot operating state is normal.
The diagnosis processor stores the fault case library of the industrial robot, receives the diagnosis data of the diagnosis equipment on the industrial robot, matches the fault case in the diagnosis processor according to the diagnosis data, generates early warning information for the fault case and feeds back the early warning information to the terminal equipment for fault analysis.
The invention has the beneficial effects that the dynamic data of the industrial robot in the running process is monitored in real time through the controller diagnosis module, the pressure value of the industrial robot in the running process is processed in advance, the advancing state of the industrial robot is studied and judged, the difference value processing is synchronously carried out on the front foot speed and the rear foot speed of the industrial robot in the running process, the fault point of the industrial robot is obtained, and the dumping time of the industrial robot is calculated through the processing of the difference value in the adjacent running period of the industrial robot, so that maintenance personnel can carry out fault elimination on the industrial robot before the industrial robot is dumped.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic structural view of the principle of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
Referring to fig. 1, the invention is an industrial robot fault analysis system based on internet, a controller diagnosis module, a diagnosis processor and a terminal device;
the controller diagnosis module is used for monitoring data in the running process of the industrial robot and sending the data of the industrial robot to the diagnosis processor;
The diagnosis processor is used for receiving the data of the industrial robot sent by the controller diagnosis module, matching the matched fault case in the diagnosis processor according to the data of the industrial robot, and when the fault case matched with the data of the industrial robot is stored in the diagnosis processor, taking the fault case matched with the data of the industrial robot as a target case, and sending the diagnosis information of the target case to the terminal equipment;
the terminal device is used for fault diagnosis of the industrial robot through analysis of the diagnosis information.
The controller diagnosis module comprises a dynamic monitoring unit for the industrial robot, wherein the dynamic monitoring unit is used for monitoring dynamic data of the industrial robot in real time in the running process;
The dynamic monitoring unit comprises four pressure sensors, height sensors, a first acceleration sensor and a second acceleration sensor, wherein the four pressure sensors are respectively arranged on the bottom surfaces of four machine feet of the industrial robot, a first speed sensor is arranged on the left front foot of the industrial robot, a second speed sensor is arranged on the left rear foot of the industrial robot, the two height sensors are arranged, one height sensor is arranged between the two front machine feet of the industrial robot, the other height sensor is arranged between the two rear machine feet of the industrial robot, and the dynamic monitoring unit specifically detects operation data of the industrial robot as follows:
The method comprises the steps that firstly, pressure information of an industrial robot is monitored in real time through a pressure sensor, pressure information values obtained by the same walking cycle of four machines of the industrial robot are obtained, the maximum value and/or the minimum value in the group of data are deleted, the average pressure value of the rest data in the group of data is obtained through calculation, and the average pressure value is marked as Fi, i=1, and the number of the rest data is n;
Comparing the average pressure value in the running process of the industrial robot in the step one with a preset pressure value uploaded by terminal equipment, and calculating a difference value to obtain a pressure difference Pi, and judging that the industrial robot moves normally when Pi < Ki, ki is a preset pressure threshold value in the same period of time;
If Pi is more than or equal to Ki, judging the running state of the industrial robot;
When judging the running state of the industrial robot, acquiring a first speed of the left front foot of the industrial robot in real time through a first speed sensor, marking the first speed as Vi1, acquiring a second speed of the left rear foot of the industrial robot in real time through a second speed sensor, marking the second speed as Vi2, and comparing the difference between the first speed Vi1 and the second speed Vi 2;
if Vi1-Vi2 is not equal to 0, judging that the industrial robot has a fault and has a tilting risk;
When judging that the industrial robot fails, acquiring a front end height value in real time through a height sensor between two front machine feet of the industrial robot and marking the front end height value as Hi1, acquiring a rear end height value in real time through a height sensor between two rear machine feet of the industrial robot and marking the rear end height value as Hi2 in the same walking period, and comparing the difference value between the front end height value Hi1 and the rear end height value Hi 2;
if Hi1-Hi2>0, the rear robot foot of the industrial robot fails;
If Hi1-Hi2<0, the front robot foot of the industrial robot fails;
calculating the difference value between the front end height value H11 and the rear end height value H12 in the same walking period of the industrial robot, namely Z1= -H11-H12|;
taking the difference between the front end height value H21 and the rear end height value H22 in the adjacent walking period, namely Z2= |H221-H2|;
Comparing the difference between Z1 and Z2, and calculating according to a formula Ch= -Z1-Z2|toobtain a height difference Ch in the walking process of two adjacent industrial robots;
Step six, setting the difference value between the critical height of the industrial robot toppling in the walking process and the height of the industrial robot in the normal state as D, and according to the formulaAnd calculating the dumping time of the industrial robot.
The controller diagnosis module further comprises a data acquisition unit for acquiring operation parameters of the industrial robot based on the diagnosis result of the industrial robot, wherein the data acquisition unit specifically comprises the storage capacity of the industrial robot, the total operation period of the industrial robot and the failure times of the industrial robot;
the data acquisition unit processes the data as follows:
s1, acquiring the storage capacity of the industrial robot, and marking the storage capacity of the industrial robot as Xi;
s2, acquiring the total operation period of the industrial robot, and marking the total operation period of the industrial robot as Ni;
S3, acquiring the failure times of the industrial robot, and marking the failure times of the industrial robot as Mi;
s4, acquiring an industrial robot running environment parameter Ji=beta× (xi×d1+Ni×d2+Mi×d3) ×e1.1564 through a formula, wherein d1, d2 and d3 are preset proportionality coefficients, and d1> d2> d3 and e are natural constants;
S5, comparing the operation environment parameter Ji of the industrial robot with the normal operation reference threshold value of the industrial robot;
if the operation environment parameter of the industrial robot is smaller than the normal operation reference threshold value of the industrial robot, the operation state of the industrial robot is not ideal, abnormal information is produced, and the abnormal information is fed back to the terminal equipment;
if the industrial robot operating environment parameter is higher than the industrial robot operating normal reference threshold, the industrial robot operating state is normal.
The diagnosis processor stores an industrial robot fault case library, wherein the fault case library comprises all public fault cases based on the Internet;
The diagnosis processor receives diagnosis data of the diagnosis equipment on the industrial robot, matches corresponding fault cases in the diagnosis processor according to the diagnosis data, and feeds back early warning information generated by the fault cases to the terminal equipment when the matching is consistent, so that a user can conveniently analyze faults;
the fault case early warning information comprises a date of fault case disclosure, a retrievable website, a diagnosis record and the like.
When the fault case library of the diagnosis processor cannot be matched with the diagnosis data of the industrial robot, the early warning information is also produced, the early warning information is sent to the terminal equipment, and the fault diagnosis data of the industrial robot is stored in the fault case library.
The terminal equipment receives the early warning information transmitted by the diagnosis processor and carries out fault processing on the industrial robot in the time range before dumping.
The invention monitors dynamic data of the industrial robot in real time in the running process through the controller diagnosis module, pre-learns the pressure value of the industrial robot in the running process, researches and judges the running state of the industrial robot, synchronously processes the difference value of the front foot speed and the rear foot speed of the industrial robot in the running process to obtain a fault point of the industrial robot, and calculates the dumping time of the industrial robot by processing the difference value of the adjacent running periods of the industrial robot so as to ensure that maintenance personnel perform fault elimination on the industrial robot before the industrial robot dumps;
The second key point of the invention is that the fault case library is stored in the diagnosis processor based on the Internet, the controller diagnosis module is used for matching the fault diagnosis data of the industrial robot with the fault case library, and the adaptive fault case is preferably obtained, so that a technician can quickly find out and process the fault point of the robot based on the fault case, and the fault processing efficiency of the industrial robot is improved.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.