Troubleshooting method and device, electronic equipment, storage medium and program product

Abstract

The present disclosure relates to the technical field of troubleshooting, and particularly relates to a troubleshooting method and device, electronic equipment, storage medium and program product, wherein by analyzing a controller engineering file corresponding to a control program of a fault device, a plurality of controller variable families are obtained; actual running data corresponding to root node variables of the plurality of controller variable families are monitored, abnormal data in the actual running data corresponding to the root node variables is identified, and the root node variables corresponding to the abnormal data are determined; for the root node variables with abnormal data, actual running data corresponding to intermediate node variables and leaf node variables having a logical correlation with the root node variables are obtained, and abnormal data in the actual running data is identified; leaf node variables corresponding to the abnormal data are determined, and the device corresponding to the leaf node variables is determined, the device being a fault root source, thereby the controller data can be effectively utilized to quickly and accurately troubleshoot the fault root source of the device, and production line downtime is avoided.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of troubleshooting, and in particular, to a troubleshooting method and device, an electronic device, a storage medium, and a program product. BACKGROUND

[0002] In an industrial production site, there are usually various manufacturing equipment for performing various process operations on products, such as various rolling beds, punching beds, numerical control machine tools, conveyors, mechanical arms, sensors, and the like. However, due to the influence of harsh environments such as high temperature, low temperature, humidity, dryness, high vibration, high electromagnetic interference, and pollutants in the industrial site, various equipment will inevitably fail due to reasons such as part loosening, electrical failure, poor contact, or position deviation, such as stop rotating, position deviation, and the like, thereby affecting the normal production of the production line.

[0003] In order to avoid the occurrence of equipment failure, it is usually necessary to rely on on-site personnel to conduct workshop inspection, or rely on the experience and technology of on-site personnel to find the equipment with failure. However, the manual inspection method is lagging behind in monitoring equipment failure, and cannot quickly and accurately determine the equipment failure position, let alone achieve early prediction of equipment failure. For some large production workshops, the workshop area is usually very large, and the equipment is complex, the electrical connection and wiring are complex, even if the fault section and position are determined, the specific fault position of the large equipment cannot be determined, and a large number of experts and technical personnel need to rush to the scene for consultation, which consumes a lot of time and human resources, and the timeliness of solving the fault cannot be guaranteed, and at the same time, it will cause the production line to stop production, causing huge economic losses to the enterprise.

[0004] The troubleshooting of the PLC controller data corresponding to the faulty equipment is an implementation way to realize the rapid troubleshooting of equipment failure. However, the actual data amount generated by the PLC controller corresponding to the faulty equipment is very large, and if all the controller data is monitored and troubleshooted, a very high-performance hardware configuration and data acquisition and transmission technology are required, which leads to the fact that the PLC controller data cannot be effectively relied on for equipment troubleshooting.

[0005] Therefore, how to effectively use the controller data to quickly and accurately troubleshoot the root cause of equipment failure, ensure that the equipment failure is solved in time, and avoid the shutdown of the production line is a technical problem to be solved. SUMMARY

[0006] In order to solve the above technical problems, the present disclosure provides a troubleshooting method and device, an electronic device, a storage medium, and a program product.

[0007] A first aspect of an embodiment of the present disclosure provides a troubleshooting method, comprising:

[0008] The control program corresponding to the controller engineering file of the fault device is parsed, and a plurality of controller variable families are obtained. The controller variable family includes a root node variable, an intermediate node variable having a logical correlation relationship with the root node variable, and a leaf node variable. The root node variable is a controller variable without a parent node. The intermediate node variable is a controller variable having both a parent node and a child node. The leaf node variable is a controller variable without a child node.

[0009] The actual running data corresponding to the root node variable of the plurality of controller variable families is monitored, and abnormal data in the actual running data corresponding to the root node variable is identified. The root node variable corresponding to the abnormal data is determined.

[0010] For the root node variable with abnormal data, the actual running data corresponding to the intermediate node variable and the leaf node variable having a logical correlation relationship with the root node variable is obtained, and abnormal data in the actual running data is identified.

[0011] The leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable are determined. The device is the fault root of the fault device.

[0012] A second aspect of an embodiment of the present disclosure provides a troubleshooting device, comprising:

[0013] A controller variable family acquisition module is configured to parse the control program corresponding to the controller engineering file of the fault device, and obtain a plurality of controller variable families. The controller variable family includes a root node variable, an intermediate node variable having a logical correlation relationship with the root node variable, and a leaf node variable. The root node variable is a controller variable without a parent node. The intermediate node variable is a controller variable having both a parent node and a child node. The leaf node variable is a controller variable without a child node.

[0014] A root node variable monitoring module is configured to monitor the actual running data corresponding to the root node variable of the plurality of controller variable families, identify abnormal data in the actual running data corresponding to the root node variable, and determine the root node variable corresponding to the abnormal data.

[0015] An abnormal data identification module is configured to, for the root node variable with abnormal data, obtain the actual running data corresponding to the intermediate node variable and the leaf node variable having a logical correlation relationship with the root node variable, and identify abnormal data in the actual running data.

[0016] A fault root positioning module is configured to determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable. The device is the fault root of the fault device.

[0017] A third aspect of an embodiment of the present disclosure provides an electronic device, comprising:

[0018] A processor;

[0019] a memory; and

[0020] a computer program;

[0021] The computer program is stored in the memory and is configured to be executed by the processor to implement the troubleshooting method provided in the first aspect.

[0022] The fourth aspect of the embodiments of the present disclosure provides a computer readable storage medium, the storage medium stores a computer program, when the computer program is executed by the processor, the processor implements the troubleshooting method provided in the first aspect.

[0023] The fifth aspect of the embodiments of the present disclosure provides a computer readable program product, the program product includes a computer program or instructions, when the computer program or instructions are executed by the processor, the processor implements the troubleshooting method provided in the first aspect.

[0024] The technical solutions provided by the embodiments of the present disclosure have the following advantages compared with the prior art:

[0025] The troubleshooting method, device, electronic equipment, storage medium and program product provided by the embodiments of the present disclosure, by analyzing the controller engineering file corresponding to the control program of the fault device, obtaining a plurality of controller variable families, the controller variable family includes a root node variable, an intermediate node variable and a leaf node variable having a logical association relationship with the root node variable, the root node variable is a controller variable without a parent node, the intermediate node variable is a controller variable with a parent node and a child node, and the leaf node variable is a controller variable without a child node; monitoring the actual running data corresponding to the root node variable of the plurality of controller variable families, identifying the abnormal data in the actual running data corresponding to the root node variable, and determining the root node variable corresponding to the abnormal data; for the root node variable with abnormal data, obtaining the actual running data corresponding to the intermediate node variable and the leaf node variable having a logical association relationship with the root node variable, identifying the abnormal data in the actual running data; determining the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and the device corresponding to the leaf node variable is the fault root of the fault device, so that the controller data can be effectively utilized to quickly and accurately troubleshoot the device fault root, ensure that the device fault is solved in time, and avoid line downtime. BRIEF DESCRIPTION OF DRAWINGS

[0026] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure.

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required by the embodiments or prior art description. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative effort.

[0028] Figure 1 is a flowchart of a troubleshooting method provided by an embodiment of the present disclosure;

[0029] Figure 2 is a flowchart of another troubleshooting method provided by an embodiment of the present disclosure;

[0030] Figure 3 is a schematic diagram of a controller variable family provided by an embodiment of the present disclosure;

[0031] Figure 4 is a schematic diagram of a node unit in step-by-step troubleshooting of a controller variable family provided by an embodiment of the present disclosure;

[0032] Figure 5 is a structural schematic diagram of a troubleshooting device provided by an embodiment of the present disclosure;

[0033] Figure 6 is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0034] In order to more clearly illustrate the above-mentioned purposes, features and advantages of the present disclosure, the solutions of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0035] In the following description, many specific details are set forth in order to fully understand the present disclosure, but the present disclosure can also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some of the embodiments of the present disclosure, not all the embodiments.

[0036] It should be understood that each step recorded in the method embodiments of the present disclosure can be executed in different order and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the steps shown. The scope of the present disclosure is not limited in this respect.

[0037] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0038] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0039] Using data from the PLC controller corresponding to the faulty equipment for troubleshooting is one way to quickly diagnose equipment faults. However, the amount of data generated by the PLC controller corresponding to the faulty equipment is enormous. Simultaneous monitoring and troubleshooting of all controller data requires very high-performance hardware and data acquisition and transmission technology, making it impossible to effectively rely on PLC controller data for root cause diagnosis of equipment faults. To address this problem, this disclosure provides a troubleshooting method, which is described below with reference to specific embodiments.

[0040] Figure 1 This is a flowchart of a troubleshooting method provided in an embodiment of the present disclosure. The method can be executed by a troubleshooting device, which can be implemented in software and / or hardware and can be configured in an electronic device, such as a server or terminal.

[0041] like Figure 1 As shown, the troubleshooting method provided in this embodiment includes the following steps.

[0042] S110. Parse the controller project file corresponding to the control program of the faulty equipment to obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables and leaf node variables that have a logical relationship with the root node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables that have both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes.

[0043] In the embodiments of the present disclosure, the faulty device is a device in an industrial production site controlled by a controller and having a fault, including but not limited to sensors, cameras, motors, frequency converters, robots, transmission devices, roller beds, numerical control machine tools and other automated devices in an industrial site, which are controlled by the controller under normal circumstances and orderly executed according to a predetermined program.

[0044] The controller is any controller capable of being used for device control, including but not limited to programmable logic controllers (PLC), distributed control systems (DCS) and robot-specific controllers. Different types of controllers have different control methods and application scenarios. The controller is a physical controller, which runs a control program that controls various types of devices in the field through digital or analog input and output data.

[0045] The controller engineering file corresponding to the control program of the controller refers to the file created and used in the development process of the controller, which contains all the information required to implement a specific automation control task, such as configuration files for describing the hardware configuration, communication configuration, parameter configuration, etc. of the controller, and program files for describing the control logic of the controller, etc.

[0046] By parsing the controller engineering file, the controller variable table and the corresponding program text can be obtained, and then all the controller variable families related to the control program can be obtained. The controller variable family refers to the root node variable as the first, including the root node variable, all intermediate node variables and leaf node variables having a logical association relationship with the root node variable from top to bottom. The control program can be divided into multiple different controller variable families based on different root node variables.

[0047] Generally, the root node variables do not overlap or are the same, and the intermediate node variables and the leaf node variables may overlap or be the same, resulting in overlapping or intersection of different controller variable families.

[0048] The controller variable table records all the controller variables involved in the control program. The controller variable refers to an element in the controller program for storing and operating actual running data, and the controller program operates instructions through the controller variable. The controller variable includes one or more of variable name, data type and variable address. The program text records the program instruction information corresponding to the control program, including but not limited to the controller variables involved in the control program and the control logic dependency relationship between the controller variables. In the program text, the variable name or variable address of the controller variable is used as a query condition to locate the program position corresponding to the controller variable.

[0049] Optionally, the program corresponding to the controller variable is presented in multiple languages, including but not limited to sequential function chart (SFC), function block diagram (FBD), ladder diagram (LD), instruction list (IL) and structured text (ST).

[0050] Wherein, the node refers to an element of an abstract syntax tree of the controller program in the engineering file, and each element in the tree is called a node. These elements can be basic components of the controller program (such as variables, constants, operators), or more complex structures (such as expressions, statements, functions or modules). The hierarchical relationship between nodes reflects the logical relationship of the program code.

[0051] The node type can include root node, leaf node and intermediate node. The root node refers to a node without a parent node. The root node is generally the topmost node, which can contain multiple intermediate nodes and leaf nodes. The leaf node refers to a node without a child node, which is generally the bottommost node. The intermediate node refers to a node other than the root node and the leaf node.

[0052] The parent node refers to a node one level up along the tree structure, which is called the parent node of the node; the child node refers to a node one level down along the tree structure, which is called the child node of the node.

[0053] Each node usually contains corresponding variable information. The variable information here refers to the variable name, variable type, variable address, location information of the DB block or program block of at least one controller variable contained in the node.

[0054] Optionally, the root node contains root node variables, the leaf node contains leaf node variables, and the intermediate node contains intermediate node variables. The leaf node variable is a controller variable without a child node, the root node variable is a controller variable without a parent node, and the intermediate node variable is a controller variable with both a parent node and a child node.

[0055] Optionally, the root node is the starting node, and the root node variable is a variable without a parent node. The root node variable is generally a global variable, and the variable type includes but is not limited to Q variable, DB variable, M variable, T variable and C variable. The intermediate node variable is a variable with both a parent node and a child node, and the type of the intermediate node variable includes but is not limited to M variable, DB variable, C variable and T variable. The leaf node variable is a variable without a child node, and the type of the leaf node variable includes but is not limited to I variable, DB variable, M variable, T variable and C variable.

[0056] Optionally, the controller variables having a logical association relationship with the root node variable include leaf node variables and intermediate node variables. Whether it is a leaf node variable or an intermediate node variable, it is a variable having an association relationship with the root node variable. The association relationship here refers to the dependency relationship between the variables contained in each node. By analyzing the logical relationship of the control program code, the hierarchical relationship between the nodes can be obtained, and then the dependency relationship between the variables contained in each node can be obtained, and the association relationship of the variables contained in each node can be determined.

[0057] Therefore, by parsing the controller engineering file corresponding to the control program of the device, the control program is divided into multiple independent controller variable families, so that a large amount of controller data for troubleshooting can be divided into data corresponding to multiple independent controller variable families that can be independently extracted and troubleshooted. Compared with simultaneous synchronous troubleshooting of all controller data, the amount of data for troubleshooting can be effectively reduced, and the demand for hardware device performance for troubleshooting can be reduced.

[0058] S120, monitoring actual running data corresponding to the root node variable of the plurality of controller variable families, identifying abnormal data in the actual running data corresponding to the root node variable, and determining the root node variable corresponding to the abnormal data.

[0059] In the embodiments of the present disclosure, the actual running data corresponding to the root node variable of the plurality of controller variable families is obtained, wherein the obtaining manner includes but is not limited to active collection or listening mode collection.

[0060] Optionally, the actual running data refers to the data generated by the actual running of the control program of the controller in the industrial field, including real-time generated actual running data and / or historical actual running data.

[0061] Optionally, after collecting the actual running data corresponding to the root node variable, the actual running data is stored before identifying the abnormal data. The storage manner is not limited.

[0062] Optionally, there can be multiple ways to identify abnormal data in the actual running data. The abnormal data here refers to incorrect or abnormal actual running data. The normal data refers to correct or normal actual running data.

[0063] Since the control program of the PLC controller has a controller data amount exceeding ten million, and the ordinary PLC control program has at least hundreds of thousands of controller variable families, each controller variable family includes at least thousands or tens of thousands of controller variables. If all the data of all the controller variable families is monitored at the same time, the data amount is huge, and is subject to the bottleneck of existing data collection technology, so that simultaneous monitoring of all the controller variable families cannot be realized.

[0064] If only the root node variables of each controller variable family are monitored, the amount of data for troubleshooting is greatly reduced, and by identifying the root node variables whose actual operation data are abnormal data, the controller variable family corresponding to the root node variables whose actual operation data are normal data can be directly excluded, further reducing the amount of data for troubleshooting, and realizing that the root cause of equipment failure can be quickly determined by using only a small amount of data.

[0065] In S130, for the root node variable with abnormal data, actual operation data corresponding to the intermediate node variables and the leaf node variables having a logical correlation relationship with the root node variable are obtained, and abnormal data in the actual operation data is identified.

[0066] In the embodiments of the present disclosure, after the root node variable with abnormal data is obtained, the controller variable family with the root node variable as the first can be determined, and then all the intermediate node variables and the leaf node variables having a logical correlation relationship with the root node variable in the controller variable family are obtained, and the actual operation data corresponding thereto is obtained. The actual operation data here refers to the data generated by the actual operation of the control program of the controller in the industrial field, including real-time generated actual operation data and / or historical actual operation data.

[0067] Optionally, after the actual operation data corresponding to the intermediate node variables and the leaf node variables is obtained, the actual operation data is stored before the abnormal data is identified. The storage manner is not limited.

[0068] In S140, the leaf node variable corresponding to the abnormal data and the equipment corresponding to the leaf node variable are determined, and the equipment is the root cause of the fault equipment.

[0069] In the embodiments of the present disclosure, the leaf node variable corresponding to the abnormal data can be determined by the identified abnormal data, and thus the equipment corresponding to the leaf node variable is determined. The equipment here includes the equipment controlled by the controller in the industrial field, including but not limited to one or more of the sensor, the switch, the indicator light, the motor or the frequency converter and the like. These equipments are usually the root cause of the formation of the fault equipment.

[0070] For example, the leaf node variable includes but is not limited to the I variable, the DB variable, the M variable, the T variable and the C variable.

[0071] Since the root node variables and the leaf node variables in the controller variable family can be directly corresponding to the equipment connected with the controller, and the intermediate node variables belong to the variables corresponding to the intermediate calculation process data and do not directly correspond to the equipment connected with the controller, only the leaf node variable can be finally determined to determine the root cause of the fault equipment, and thus the root cause of the equipment failure is solved.

[0072] The embodiment of the present disclosure can obtain a plurality of controller variable families by analyzing a controller engineering file corresponding to a control program of a faulty device, the controller variable families including root node variables, intermediate node variables having a logical correlation relationship with the root node variables, and leaf node variables, the root node variables being controller variables without parent nodes, the intermediate node variables being controller variables having both parent nodes and child nodes, and the leaf node variables being controller variables without child nodes; monitor actual running data corresponding to the root node variables of the plurality of controller variable families, identify abnormal data in the actual running data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data; for the root node variables with abnormal data, obtain actual running data corresponding to the intermediate node variables and the leaf node variables having a logical correlation relationship with the root node variables, and identify abnormal data in the actual running data; determine the leaf node variables corresponding to the abnormal data and the device corresponding to the leaf node variables, which is the root cause of the faulty device. Thus, the controller data can be effectively utilized to quickly and accurately troubleshoot the root cause of the device fault, ensure that the device fault is solved in a timely manner, and avoid line downtime.

[0073] On the basis of the above-mentioned embodiments, Figure 2 is a flowchart of another troubleshooting method provided by the embodiment of the present disclosure, as shown in Figure 2 , specifically comprising the following steps:

[0074] S210, analyze a controller engineering file corresponding to a control program of a device to obtain a plurality of controller variable families, the controller variable families including root node variables, intermediate node variables having a logical correlation relationship with the root node variables, and leaf node variables, the root node variables being controller variables without parent nodes, the intermediate node variables being controller variables having both parent nodes and child nodes, and the leaf node variables being controller variables without child nodes.

[0075] It should be noted that the specific implementation of S210 is similar to the above-mentioned embodiments, which will not be repeated here.

[0076] S220, monitor actual running data corresponding to the root node variables of the plurality of controller variable families, identify abnormal data in the actual running data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data: simulate the running process of the control program of the faulty device to obtain simulation running data; compare the actual running data corresponding to the root node variables of the plurality of controller variable families with the simulation running data, and when the actual running data and the simulation running data are inconsistent, identify the inconsistent actual running data as abnormal data.

[0077] In the embodiments of the present disclosure, the simulation running data is obtained by simulating the running process of the control program corresponding to the faulty equipment; the actual running data corresponding to the root node variables of the multiple controller variable families is compared with the simulation running data, and when the actual running data is inconsistent with the simulation running data, the inconsistent actual running data is identified as abnormal data.

[0078] Optionally, the simulation running data is obtained by simulating the running process of the control program corresponding to the faulty equipment. Specifically, a simulation control program can be set, which has the same or similar operation logic as the control program corresponding to the faulty equipment, to simulate the running of the control program corresponding to the faulty equipment, thereby obtaining the simulation running data.

[0079] Optionally, the simulation control program is a program capable of simulating the running of the control program of the controller in the industrial field. The simulation control program can run on a hardware redundant controller (such as a redundant PLC device, a redundant DCS device, etc.), can also run on a data acquisition module integrated in the hardware controller, and can also run on any electronic device capable of running the simulation control program. The simulation control program can be a soft PLC, which is not limited here.

[0080] Optionally, the simulation control program can calculate the simulation running data of the intermediate node variables and / or leaf node variables having a logical association relationship with the root node variable by running the same or similar program as the target control program.

[0081] Optionally, the actual running data of the intermediate node variables and / or leaf node variables having a logical association relationship with the root node variable is compared with the simulation running data, and when the actual running data of the same controller variable is inconsistent with the simulation running data, the actual running data when inconsistent is identified as abnormal data.

[0082] S230, for the root node variable with abnormal data, obtaining actual running data corresponding to the intermediate node variables and the leaf node variables having a logical association relationship with the root node variable, and identifying abnormal data in the actual running data, further comprising: for the root node variable with abnormal data, sequentially investigating the controller variable family corresponding to the root node variable, taking at least one node unit of the controller variable of the current level as the investigation object, the node unit including the controller variable of the current level and the controller variable of the next level taking the controller variable of the current level as the parent node, the controller variable including any one or more of the root node variable, the intermediate node variable and the leaf node variable; when the actual running data of the controller variable of the next level in the node unit is abnormal data, taking the node unit corresponding to the controller variable of the next level with abnormal data as the investigation object.

[0083] In the embodiments of the present disclosure, for the root node variable with abnormal data, all the intermediate node variables and leaf node variables of the corresponding controller variable family can be obtained through the root node variable. Since there are at least thousands of controller variables in one controller variable family, if the actual running data of all the controller variables in the controller variable family are obtained at the same time, the data volume is relatively large, and most of the data is unnecessary to be checked.

[0084] By checking the controller variable family corresponding to the root node variable with abnormal data step by step, at least one node unit corresponding to the controller variable at the current level is taken as the checking object each time, and the actual running data of all the controller variables in the controller variable family do not need to be checked at the same time, so that the data volume for checking is greatly reduced. At the same time, the node unit corresponding to the controller variable with abnormal data needs to be checked next time, and all the controller variables at the next level do not need to be checked, which also greatly reduces the data volume for checking to a certain extent, thereby improving the efficiency of fault checking, facilitating obtaining the fault checking result at the fastest speed and solving the fault, and avoiding long-time shutdown of the production line.

[0085] Specifically, the controller variable family includes, from top to bottom, the root node variable, all the intermediate node variables and leaf node variables having a logical correlation relationship with the root node variable, taking the root node variable as the first. The controller variable family has multiple levels of nodes from top to bottom, and the nodes at different levels include different types of controller variables. The controller variables include any one or more of the root node variable, the intermediate node variable, and the leaf node variable.

[0086] Specifically, in the controller variable family, the nodes at the first level include the root node variable; the nodes at the second level include a plurality of first-level intermediate node variables and / or a plurality of first-level leaf node variables, wherein the first-level intermediate node variables and / or the first-level leaf node variables take the root node variable as the parent node; the nodes at the third level include a plurality of second-level intermediate node variables and / or a plurality of second-level leaf node variables, wherein different second-level intermediate node variables and / or second-level leaf node variables take different first-level intermediate node variables as the parent node; and so on, until the nodes at the last level (such as N+1 level), which include N-level leaf node variables.

[0087] Figure 3 The node level relationship of the controller variable family is shown. As shown in FIG. 1, the controller variable family includes the root node variable, the first-level intermediate node variable, the first-level leaf node variable, the second-level intermediate node variable, and the second-level leaf node variable. Figure 3As shown, in a certain controller variable family, the first level of nodes includes one root node variable a1; the second level of nodes includes two first level intermediate node variables a2, a4 and one first level leaf node variable a3, wherein the first level intermediate node variables a2, a4 and the first level leaf node variable a3 take the root node variable a1 as the parent node; the third level of nodes includes four second level intermediate node variables a5, a6, a8, a9 and two second level leaf node variables a7, a10, wherein different second level intermediate node variables and second level leaf node variables take different first level intermediate node variables as the parent node, such as the second level intermediate node variables a5, a6 and the second level leaf node variable a7 take the first level intermediate node variable a2 as the parent node, and the second level intermediate node variables a8, a9 and the second level leaf node variable a10 take the first level intermediate node variable a4 as the parent node; the fourth level of nodes includes six third level leaf node variables a11, a12, a13, a14, a15, a16.

[0088] When the controller variable family corresponding to the root node variable with abnormal data is checked level by level, at least one node unit corresponding to the controller variable at the current level is taken as the checking object. The node unit here includes the controller variable at the current level and the controller variable at the next level taking the controller variable at the current level as the parent node. And when the actual running data of the controller variable at the next level in the node unit is abnormal data, the node unit corresponding to the controller variable at the next level with abnormal data is taken as the checking object.

[0089] Figure 4 The node unit in the controller variable family checking process is shown, wherein the contents in the dashed box are different node units. As shown in the figure, Figure 4 As shown, for the root node variable a1 with abnormal actual running data, the corresponding controller variable family is checked level by level. First, the node unit corresponding to the controller variable a1 at the first level is checked, which includes the current controller variable a1 at the first level and the controller variables a2, a3, a4 at the second level taking the controller variable a1 at the current first level as the parent node. The controller variable a1 in the node unit is the root node variable, and the controller variables a2, a3, a4 are intermediate node variables. If the actual running data of a2 among the controller variables a2, a3, a4 at the second level in the node unit is abnormal data, while the actual running data of a3, a4 is normal data, the node unit corresponding to the controller variable a2 at the second level with abnormal data is taken as the checking object. At this time, there is no need to exclude the node units corresponding to a3, a4 and all the controller variables (such as a8, a9, a10, a14, a15, a16) downward, thereby greatly reducing the checking range of the next step, which is conducive to reducing the data amount of fault checking, so as to quickly obtain the fault checking result.

[0090] In further step-by-step troubleshooting, the node unit corresponding to the controller variable a2 with abnormal data is taken as the troubleshooting object, and the node unit includes the current second-level controller variable a2 and the third-level controller variables a5, a6, a7 with the current second-level controller variable a2 as the parent node. The controller variable a2 in the node unit is a first intermediate node variable, the controller variables a5, a6 are second intermediate node variables, and the controller variable a7 is a second leaf node variable. If the actual running data of the controller variable a5 in the third-level controller variables a5, a6, a7 in the node unit is abnormal data, and the actual running data of a6 and a7 is normal data, the node unit corresponding to the third-level controller variable a5 with abnormal data is taken as the troubleshooting object, that is, the node unit composed of the controller variables a5, a11, a12 is taken as the troubleshooting object, and the controller variable a13 does not need to be troubleshooted. At this time, since the controller variables a11 and a12 are leaf node variables, they directly correspond to the related equipment in the industrial field, and the equipment corresponding to the controller variables a11 and / or a12 with abnormal actual running data is the fault root source.

[0091] For example, a certain industrial production line is shut down or stopped, the control programs of all the equipment corresponding to the production line are called to obtain the controller engineering files corresponding to the control programs, and then a plurality of controller variable families are obtained. Only the root node variables of the controller variable families need to be monitored, the root node variables with abnormal actual running data are identified, the controller variable families corresponding to these abnormal root node variables are further troubleshooted, and a large number of controller variable families without abnormal root node variables are excluded, greatly reducing the troubleshooting range. Further, to improve the troubleshooting efficiency, the controller variable families are step-by-step troubleshooted by taking the node unit as the troubleshooting unit, the troubleshooting range is continuously reduced by step-by-step troubleshooting, the controller variables without abnormal data are excluded, and finally the equipment corresponding to the leaf node variable causing the fault root source is determined. The fault root source here may be one or more malfunctioning sensors, one or more damaged frequency converters, or one or more damaged switches.

[0092] Optionally, for a plurality of root node variables with abnormal data, when a plurality of root node variables have the same intermediate node variables and leaf node variables, the abnormal data troubleshooting results of the same intermediate node variables and leaf node variables are reused. Specifically, when part of the intermediate node variables and leaf node variables of a plurality of controller variable families overlap or are the same, only one abnormal data troubleshooting needs to be performed on the overlapping or same part of the intermediate node variables and leaf node variables, and multiple troubleshootings are not needed, the reuse of the abnormal data troubleshooting results is realized, and the troubleshooting efficiency is further improved.

[0093] In fact, the production line shutdown means a huge economic loss of up to millions of ten million for the factory. It is crucial for the factory to determine the root cause of the fault and solve the fault as soon as possible to make the production line run normally. If multiple root node variables have abnormal data at the same time, and the controller variable family corresponding to these root node variables is checked at the same time, the data volume of fault checking will be increased. At this time, if the controller variable family can be queued based on priority, the efficiency of fault checking can be further improved.

[0094] Optionally, for multiple root node variables with abnormal data, based on a preset controller variable label, a priority of abnormal data checking of the multiple root node variables is determined. The controller variable label includes variable information of the controller variable, and the variable information includes any one or more of a variable name, a variable address, a variable type, a variable corresponding device name, a variable corresponding device address, a physical function of a variable corresponding device, a use of the variable corresponding device, a variable importance priority, and a device failure probability.

[0095] For example, the controller variable label includes preset variable information such as variable importance priority and variable failure probability. For the controller variable with high importance priority or the controller variable with high device failure probability, the controller variable family corresponding to the controller variable is preferentially checked, so that the root cause of the device failure can be determined more quickly. For example, the importance priority of the motor is higher than that of the switch. At this time, the controller variable family corresponding to the root node variable corresponding to the motor should be preferentially checked.

[0096] In S240, a leaf node variable corresponding to the abnormal data and a device corresponding to the leaf node variable are determined. The device corresponding to the leaf node variable is a root cause of the failure of the failure device.

[0097] In the embodiments of the present disclosure, the leaf node variable corresponding to the abnormal data can be determined through the identified abnormal data, and thus the device corresponding to the leaf node variable is determined. The device herein includes a device controlled by the controller in the industrial field, including but not limited to one or more of a sensor, a switch, an indicator light, a motor, or a frequency converter, and the like. These devices are usually the root cause of the failure of the failure device.

[0098] For example, the leaf node variable includes but is not limited to an I variable, a DB variable, an M variable, a T variable, and a C variable.

[0099] The embodiments of the present disclosure perform step-by-step troubleshooting on the controller variable family by taking the node unit as the troubleshooting unit. Each time, only a few controller variables in the node unit range need to be checked, the actual running data corresponding to the few controller variables is quickly obtained, and it is determined whether there is abnormal data. With step-by-step troubleshooting of abnormal data, controller variables with normal data can be excluded step by step, so that the troubleshooting range of fault troubleshooting is gradually reduced. Compared with synchronous troubleshooting of all controller variables of the entire controller variable family, only a small amount of data is needed to quickly and accurately determine the equipment failure root cause, so that the failure root cause can be determined faster and the failure can be solved in time, greatly shortening the production line downtime.

[0100] On the basis of the above-mentioned embodiments, in order to enable the user to more intuitively master the location of the failure root cause, determine the leaf node variable corresponding to the abnormal data and the equipment corresponding to the leaf node variable, and display the equipment information of the equipment corresponding to the leaf node variable, the equipment information includes any one or more of the equipment name, the equipment location, the equipment model, the equipment running data, the equipment physical function, and the equipment purpose.

[0101] Optionally, based on the preset controller variable label, the variable name of the leaf node variable is taken as a query entrance to obtain the related information of the variable corresponding to the root cause of the equipment failure, and then the specific on-site equipment information corresponding to the variable is determined, and the specific on-site equipment is the equipment that needs to be further maintained.

[0102] Optionally, in order to enable the user to more intuitively master the failure root cause, the related information of the failure root cause can be displayed in various ways, including but not limited to text display, sound prompt, graphical display, and combined display of any one of the above-mentioned ways.

[0103] Optionally, the failure root cause is displayed in a graphical manner, including but not limited to highlighting the related information of the equipment corresponding to the failure root cause in a three-dimensional mechanical diagram. The user interface on the user terminal displays the failure location in a graphical manner, so that the failure location display is more intuitive and clear. Specifically, the overall layout diagram of the factory, the layout diagram of a production line, the layout of a device, or a local enlarged diagram of a component, etc. can be displayed. Here, the failure location refers to the physical location of the equipment corresponding to the failure data.

[0104] For example, the layout diagram of the factory can display various production lines and devices in the factory according to a certain scale and relative position relationship, and different devices are identified by different elements. The local enlarged diagram of the device component can display the component assembly relationship and position according to a certain scale. When it is detected that the PLC data corresponding to a device has failure data, the component position of the device can be located. The factory layout diagram, the device layout diagram, or the local enlarged diagram of the failure component, etc. containing the device can be displayed in a highlighted manner.

[0105] Optionally, the highlighted manner includes but is not limited to: magnified display, color distinction, graphic frame selection, text reminder, language broadcast, etc. For example, red frame is used for the device with fault, and black frame is used for others.

[0106] Optionally, the displayed content includes but is not limited to: specific device name, corresponding graphic, specific position in the corresponding graphic, specific numerical value, associated abnormal data before and after, data corresponding time, fault duration, etc.

[0107] Optionally, in addition to displaying the position of the fault root in a graphic manner, information related to the fault data and analysis results can also be displayed, including but not limited to: specific fault data, fault occurrence time, fault level, and the frequency of the device fault and fault history data.

[0108] Optionally, it also includes storing the fault information as training data for the fault prediction artificial intelligence algorithm model, for subsequent big data analysis to predict possible device faults, advance maintenance or improve related process flow.

[0109] Optionally, it also includes sending a warning / alarm information to the user. The user can handle the warning / alarm information after viewing the fault data, such as confirming or canceling the warning / alarm information.

[0110] Figure 5 is a structural schematic diagram of a fault troubleshooting device provided by an embodiment of the present disclosure. The fault troubleshooting device provided by the embodiment of the present disclosure can execute the processing flow provided by the fault troubleshooting method embodiment, as shown in Figure 5 The fault troubleshooting device 50 includes a controller variable family acquisition module 51, a root node variable monitoring module 52, an abnormal data identification module 53, and a fault root positioning module 54.

[0111] The controller variable family acquisition module 51 can be configured to parse a controller engineering file corresponding to a control program of a fault device, and acquire a plurality of controller variable families. The controller variable family includes a root node variable, an intermediate node variable having a logical association relationship with the root node variable, and a leaf node variable. The root node variable is a controller variable without a parent node. The intermediate node variable is a controller variable with both a parent node and a child node. The leaf node variable is a controller variable without a child node.

[0112] The root node variable monitoring module 52 can be configured to monitor actual running data corresponding to the root node variable of the plurality of controller variable families, identify abnormal data in the actual running data corresponding to the root node variable, and determine the root node variable corresponding to the abnormal data.

[0113] The abnormal data identification module 53 can be configured to, for the root node variable with abnormal data, acquire actual running data corresponding to the intermediate node variable and the leaf node variable having a logical correlation relationship with the root node variable, and identify abnormal data in the actual running data.

[0114] The fault root location module 54 can be configured to determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and the device is the fault root of the fault device.

[0115] In the embodiments of the present disclosure, the controller engineering file corresponding to the control program of the fault device can be parsed to obtain a plurality of controller variable families, the controller variable family includes a root node variable, an intermediate node variable and a leaf node variable having a logical correlation relationship with the root node variable, the root node variable is a controller variable without a parent node, the intermediate node variable is a controller variable with both a parent node and a child node, and the leaf node variable is a controller variable without a child node; the actual running data corresponding to the root node variable of the plurality of controller variable families is monitored, abnormal data in the actual running data corresponding to the root node variable is identified, and the root node variable corresponding to the abnormal data is determined; for the root node variable with abnormal data, the actual running data corresponding to the intermediate node variable and the leaf node variable having a logical correlation relationship with the root node variable is acquired, and abnormal data in the actual running data is identified; the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable are determined, and the device corresponding to the leaf node variable is the fault root of the fault device, thereby effectively utilizing the controller data to quickly and accurately troubleshoot the device fault root, ensuring timely solution of the device fault, and avoiding line downtime.

[0116] In some embodiments of the present disclosure, the root node variable monitoring module 52 further includes a simulation running data acquisition submodule and a comparison submodule. The simulation running data acquisition submodule is configured to simulate the running process of the control program corresponding to the fault device to obtain simulation running data; and the comparison submodule is configured to compare the actual running data corresponding to the root node variable with the simulation running data, and identify inconsistent actual running data as abnormal data when the actual running data is inconsistent with the simulation running data.

[0117] In some embodiments of the present disclosure, the abnormal data identification module 53 further comprises a node unit step-by-step troubleshooting submodule, configured to, for a root node variable with abnormal data, step-by-step troubleshoot the controller variable family corresponding to the root node variable, taking the node unit corresponding to at least one controller variable at the current level as the troubleshooting object, the node unit including the controller variable at the current level and the controller variable at the next level with the controller variable at the current level as the parent node, the controller variable including any one or more of the root node variable, the intermediate node variable and the leaf node variable; and when the actual running data of the controller variable at the next level in the node unit is abnormal data, taking the node unit corresponding to the controller variable at the next level with abnormal data as the troubleshooting object.

[0118] In some embodiments of the present disclosure, the abnormal data identification module 53 further comprises an abnormal data troubleshooting result multiplexing submodule, configured to, for a plurality of root node variables with abnormal data, when the plurality of root node variables have the same intermediate node variable and leaf node variable, multiplex the abnormal data troubleshooting result of the same intermediate node variable and leaf node variable.

[0119] In some embodiments of the present disclosure, the abnormal data identification module 53 further comprises a root node variable priority determination submodule and a controller variable label submodule. The root node variable priority determination submodule is configured to determine the priority of abnormal data troubleshooting of a plurality of root node variables based on a preset controller variable label. The controller variable label submodule is configured to preset variable information of a controller variable, the variable information including any one or more of a variable name, a variable address, a variable type, a variable corresponding device name, a variable corresponding device address, a physical function of a variable corresponding device, a purpose of a variable corresponding device, a variable importance priority, and a device failure probability.

[0120] In some embodiments of the present disclosure, the troubleshooting device further comprises a display module, which can be configured to display device information of a leaf node variable corresponding device, the device information including any one or more of a device name, a device location, a device model, device running data, a device physical function, and a device purpose.

[0121] Figure 5 The troubleshooting device of the embodiments can be used to execute the technical solutions of the above-mentioned method embodiments, and has similar implementation principles and technical effects, which will not be repeated here.

[0122] Figure 6 A structural schematic diagram of an electronic device is provided for the embodiments of the present disclosure. The electronic device provided by the embodiments of the present disclosure can execute the processing flow provided by the troubleshooting method embodiments, as shown in Figure 6As shown, the electronic device 6 comprises a processor 61, a memory 62, and a computer program 63; wherein the computer program is stored in the memory 62, and is configured to read the computer program 63 from the memory 62 and execute the computer program 63 to implement the embodiments of the present disclosure Figures 1 to 4 The troubleshooting method is provided.

[0123] In addition, the embodiments of the present disclosure further provide a computer readable storage medium, which can store a computer program, and when the computer program is executed by a processor, the processor implements the embodiments of the present disclosure Figures 1 to 4 The troubleshooting method is provided.

[0124] The storage medium described above can for example include a memory of a computer program, which can be executed by a processor of a troubleshooting device to complete the embodiments of the present disclosure Figures 1 to 4 The troubleshooting method is provided. Optionally, the storage medium can be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium can be a ROM, a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage configuration device, etc.

[0125] In addition, the embodiments of the present disclosure further provide a computer program product, which comprises a computer program or instructions, and when the computer program or instructions are executed by a processor, the troubleshooting method as above is implemented.

[0126] The above is only a specific embodiment of the present disclosure, which enables those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A troubleshooting method, characterized in that, include: The controller project file corresponding to the control program of the faulty equipment is parsed to obtain multiple independent controller variable families. The controller variable families include root node variables, intermediate node variables and leaf node variables that have a logical relationship with the root node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables that have both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes. The faulty equipment is equipment in the industrial production site that is controlled by the controller and has a fault. Monitor the actual operating data corresponding to the root node variables of the multiple independent controller variable families, identify abnormal data in the actual operating data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data; For the root node variable containing abnormal data, obtain the actual running data corresponding to the intermediate node variable and the leaf node variable that have a logical relationship with the root node variable, and identify the abnormal data in the actual running data; The leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable are determined. The device is the root cause of the fault of the faulty device, and the device corresponding to the leaf node variable is a device controlled by a controller in the industrial field. The step of monitoring the actual operating data corresponding to the root node variables of the multiple independent controller variable families, identifying abnormal data in the actual operating data corresponding to the root node variables, and determining the root node variables corresponding to the abnormal data further includes: Simulate the operation of the control program of the faulty device to obtain simulated operation data; Compare the actual running data corresponding to the root node variable of the multiple controller variable families with the simulated running data. When the actual running data is inconsistent with the simulated running data, identify the inconsistent actual running data as abnormal data. The process of simulating the operation of the control program of the faulty device to obtain simulated operation data includes: setting a simulated control program that has the same or similar operational logic as the control program corresponding to the faulty device, so as to simulate the operation of the control program corresponding to the faulty device, thereby obtaining the simulated operation data.

2. The method according to claim 1, characterized in that, The step of obtaining the actual running data corresponding to the intermediate node variables and leaf node variables that have a logical relationship with the root node variables, and identifying abnormal data in the actual running data, further includes: For the root node variable with abnormal data, the controller variable family corresponding to the root node variable is checked level by level. The node unit corresponding to at least one controller variable at the current level is the object of the check. The node unit includes the controller variable at the current level and the controller variable at the next level with the controller variable at the current level as the parent node. The controller variable includes any one or more of the root node variable, intermediate node variable and leaf node variable. When the actual running data of the controller variable at the next level in the node unit is abnormal, the node unit corresponding to the controller variable at the next level where the abnormal data exists is the object of investigation.

3. The method according to claim 1, characterized in that, For multiple root node variables corresponding to controller variable families with abnormal data, when multiple controller variable families have the same intermediate node variables and leaf node variables, the abnormal data investigation results of the same intermediate node variables and leaf node variables are reused.

4. The method according to claim 1, characterized in that, For multiple root node variables with abnormal data, the priority of abnormal data investigation for multiple root node variables is determined based on preset controller variable labels. The controller variable labels include variable information of the controller variable, which includes any one or more of the following: variable name, variable address, variable type, variable corresponding device name, variable corresponding device address, physical function of the device corresponding to the variable, purpose of the device corresponding to the variable, variable importance priority, and device failure probability.

5. The method according to claim 1, characterized in that, After determining the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and that the device is the root cause of the fault in the faulty device, the method further includes: Displays the device information corresponding to the leaf node variable, which includes any one or more of the following: device name, device location, device model, device operating data, device physical function, and device purpose.

6. A fault diagnosis device, characterized in that, include: The controller variable family acquisition module is used to parse the controller project file corresponding to the control program of the faulty equipment and acquire multiple independent controller variable families. The controller variable families include root node variables, intermediate node variables and leaf node variables that have a logical relationship with the root node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables that have both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes. The faulty equipment is equipment in the industrial production site that is controlled by the controller and has a fault. The root node variable monitoring module is used to monitor the actual operating data corresponding to the root node variables of the multiple independent controller variable families, identify abnormal data in the actual operating data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data. The step of monitoring the actual operating data corresponding to the root node variables of the multiple independent controller variable families, identifying abnormal data in the actual operating data corresponding to the root node variables, and determining the root node variables corresponding to the abnormal data further includes: Simulate the operation of the control program of the faulty device to obtain simulated operation data; Compare the actual running data corresponding to the root node variable of the multiple controller variable families with the simulated running data. When the actual running data is inconsistent with the simulated running data, identify the inconsistent actual running data as abnormal data. The process of simulating the operation of the control program of the faulty device to obtain simulated operation data includes: setting a simulated control program that has the same or similar operational logic as the control program corresponding to the faulty device, so as to simulate the operation of the control program corresponding to the faulty device, thereby obtaining the simulated operation data; An abnormal data identification module is used to obtain the actual running data corresponding to the intermediate node variables and the leaf node variables that have a logical relationship with the root node variables, and to identify the abnormal data in the actual running data for the root node variables that contain abnormal data. The fault root cause location module is used to determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable. The device is the root cause of the fault of the faulty device, and the device corresponding to the leaf node variable includes devices controlled by the controller in the industrial field.

7. An electronic device, characterized in that, include: processor; Memory; And computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, causes the processor to implement the method described in any one of claims 1-5.

9. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method as described in any one of claims 1-5.

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