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

Abstract

The invention relates to the technical field of troubleshooting, in particular to a troubleshooting method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining a plurality of controller variable families through analyzing a controller project file corresponding to a control program of fault equipment; monitoring actual operation data corresponding to root node variables of the plurality of controller variable families, identifying abnormal data in the actual operation data corresponding to the root node variables, and determining root node variables corresponding to the abnormal data; for the root node variable with the abnormal data, acquiring actual operation data corresponding to the intermediate node variable and the leaf node variable having a logic association relationship with the root node variable, and identifying the abnormal data in the actual operation data; the leaf node variable corresponding to the abnormal data and the equipment corresponding to the leaf node variable are determined, and the equipment is a fault source, so that the equipment fault source can be quickly and accurately checked by effectively utilizing the controller data, and shutdown and production halt of a production line are avoided.

Description

Technical Field

[0001] The present disclosure relates to the technical field of fault troubleshooting, and particularly to a fault troubleshooting method, device, electronic device, storage medium, and program product. Background Art

[0002] In industrial production sites, there are usually various manufacturing devices for performing various different process operations on products, such as various rolling beds, stamping presses, numerical control machine tools, conveyor belts, robotic arms, sensors, etc. However, affected by harsh environments such as high temperature, low temperature, humidity, dryness, high vibration, high electromagnetic interference, and pollutants in the industrial site, various devices will inevitably have equipment failures due to reasons such as loose parts, electrical failures, poor contact, or position deviation, such as failures like stopping rotation and position deviation, thus affecting the normal production of the production line.

[0003] To avoid the occurrence of equipment failures, usually, it is necessary to rely on on-site workers for workshop inspections, or rely on the experience and skills of on-site workers to detect faulty equipment. However, the method of manual inspection is lagging in monitoring equipment failures, cannot quickly and accurately determine the location of equipment failures, and is even less able to achieve early prediction of equipment failures. For some large production workshops, the workshop area is often very large, and the equipment is complex, and the electrical connections and wiring are complex. Even after determining the faulty section and location, it is impossible to specifically determine the specific fault location of large equipment, and multiple experts and technicians need to rush to the scene for consultation, consuming a large amount of time and human resources. The timeliness of fault resolution cannot be guaranteed, and at the same time, it will cause the production line to stop production, bringing huge economic losses to the enterprise.

[0004] Fault troubleshooting through the data of the PLC controller corresponding to the faulty equipment is an implementation method to achieve rapid troubleshooting of equipment failures. However, the amount of data actually generated by the PLC controller corresponding to the faulty equipment is extremely large. If all the controller data is monitored and troubleshot, very high-performance hardware configurations and data acquisition and transmission technologies are required, resulting in the inability to effectively rely on the PLC controller data for equipment fault troubleshooting.

[0005] Therefore, how to effectively utilize the controller data to quickly and accurately troubleshoot the root cause of equipment failures, ensure the timely resolution of equipment failures, and avoid production line shutdowns is a technical problem that urgently needs to be solved. Summary of the Invention

[0006] To solve the above technical problems, the present disclosure provides a fault troubleshooting method, device, electronic device, storage medium, and program product.

[0007] The first aspect of the embodiments of the present disclosure provides a fault troubleshooting method, including: Parse the controller engineering file corresponding to the control program of the faulty device to obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables logically associated with the root node variables, and leaf node variables. The root node variables are controller variables without a parent node, the intermediate node variables are controller variables with both a parent node and a child node, and the leaf node variables are controller variables without a child node; Monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation 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 the actual operation data corresponding to the intermediate node variables and leaf node variables logically associated with the root node variables, and identify the abnormal data in the actual operation data; Determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables. The device is the root cause of the failure of the faulty device.

[0008] A second aspect of the embodiments of the present disclosure provides a fault troubleshooting device, including: A controller variable family acquisition module, configured to parse the controller engineering file corresponding to the control program of the faulty device to obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables logically associated with the root node variables, and leaf node variables. The root node variables are controller variables without a parent node, the intermediate node variables are controller variables with both a parent node and a child node, and the leaf node variables are controller variables without a child node; A root node variable monitoring module, configured to monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data; An abnormal data identification module, configured to, for the root node variables with abnormal data, obtain the actual operation data corresponding to the intermediate node variables and leaf node variables logically associated with the root node variables, and identify the abnormal data in the actual operation data; A fault root cause location module, configured to determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables. The device is the root cause of the failure of the faulty device.

[0009] A third aspect of the embodiments of the present disclosure provides an electronic device, including: A processor; A memory; and A computer program; Wherein, the computer program is stored in the memory and is configured to be executed by the processor to implement the fault troubleshooting method provided in the first aspect above.

[0010] In the fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided. The storage medium stores a computer program, and when the computer program is executed by a processor, the processor is enabled to implement the fault troubleshooting method provided in the first aspect above.

[0011] In the fifth aspect of the embodiments of the present disclosure, a computer-readable program product is provided. The program product includes a computer program or instruction, and when the computer program or instruction is executed by a processor, the processor is enabled to implement the fault troubleshooting method provided in the first aspect above.

[0012] The technical solutions provided by the embodiments of the present disclosure have the following advantages compared with the prior art: The fault troubleshooting method, device, electronic device, storage medium, and program product provided by the embodiments of the present disclosure parse the controller engineering file corresponding to the control program of the faulty device to obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables logically associated with the root node variables, and leaf node variables. The root node variables are controller variables without a parent node, the intermediate node variables are controller variables with both a parent node and a child node, and the leaf node variables are controller variables without a child node. Monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation 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 the actual operation data corresponding to the intermediate node variables and leaf node variables logically associated with the root node variables, and identify the abnormal data in the actual operation data. Determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables. The devices corresponding to the leaf node variables are the root causes of the faults of the faulty devices. Thus, it is possible to effectively utilize the controller data to quickly and accurately troubleshoot the root causes of device faults, ensure the timely resolution of device faults, and avoid production line shutdowns. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present disclosure and used together with the specification to explain the principles of the present disclosure.

[0014] 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 for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 is a flowchart of a fault troubleshooting method provided by an embodiment of the present disclosure; Figure 2 is a flowchart of another fault troubleshooting method provided by an embodiment of the present disclosure; Figure 3 It is a schematic diagram of a family of controller variables provided by an embodiment of the present disclosure; Figure 4 It is a schematic diagram of a node unit in the step-by-step troubleshooting of a family of controller variables provided by an embodiment of the present disclosure; Figure 5 It is a schematic structural diagram of a fault troubleshooting device provided by an embodiment of the present disclosure; Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. Detailed implementation manners

[0016] In order to be able to more clearly understand the above objects, features and advantages of the present disclosure, the solutions of the present disclosure will be further described below. It should be noted that, without conflict, the embodiments of the present disclosure and the features in the embodiments may be combined with each other.

[0017] Many specific details are set forth in the following description in order to fully understand the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only a part of the embodiments of the present disclosure, rather than all of the embodiments.

[0018] It should be understood that the various steps recorded in the method embodiments of the present disclosure may be executed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.

[0019] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0020] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise clearly stated in the context, it should be understood as "one or more".

[0021] Fault troubleshooting by using the data of the PLC controller corresponding to the faulty device is a way to quickly troubleshoot device faults. However, the amount of data generated by the PLC controller corresponding to the faulty device is extremely large. If all the controller data is synchronously monitored and troubleshot, very high-performance hardware configurations and data acquisition and transmission technologies are required, resulting in the inability to effectively rely on the PLC controller data to troubleshoot the root cause of device faults. To address this problem, the embodiments of the present disclosure provide a fault troubleshooting method, which will be introduced below in combination with specific embodiments.

[0022] Figure 1 FIG. is a flowchart of a fault troubleshooting method provided by an embodiment of the present disclosure. This method can be executed by a fault troubleshooting device, which can be implemented in a software and / or hardware manner. The fault troubleshooting device can be configured in an electronic device, such as a server or a terminal.

[0023] As Figure 1 shown, the fault troubleshooting method provided in this embodiment includes the following steps.

[0024] S110. Analyze the controller engineering file corresponding to the control program of the faulty device to obtain multiple controller variable families. The controller variable family includes a root node variable, intermediate node variables having a logical association with the root node variable, and leaf node variables. 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, and the leaf node variable is a controller variable without a child node.

[0025] In the embodiments of the present disclosure, the faulty device is a device in an industrial production site that is controlled by a controller and has a fault, including but not limited to automation devices such as sensors, cameras, motors, frequency converters, robots, transmission devices, roller beds, and numerically controlled machine tools in the industrial site. These devices are normally controlled by a controller and execute in an orderly manner according to a predetermined program.

[0026] The controller is any controller capable of controlling a device, including but not limited to: Programmable Logic Controller (PLC), Distributed Control System (DCS), and robot-specific controllers, etc. Different types of controllers have different control methods and application scenarios. The controller is a physical controller that runs a control program, and this control program controls various types of devices in the field through digital or analog input and output data.

[0027] The controller project file corresponding to the control program of the controller refers to the file created and used during the controller development process, which contains all the information required to implement a specific automation control task. For example, configuration files such as those used to describe the hardware configuration, communication configuration, and parameter configuration of the controller, as well as program files used to describe the control logic of the controller, etc.

[0028] By parsing the controller project file, the controller variable table and the corresponding program text can be obtained, and then all controller variable families related to the control program can be obtained. A controller variable family refers to a set of variables with the root node variable at the top, including the root node variable, all intermediate node variables and leaf node variables that have a logical association relationship with the root node variable from top to bottom. The control program can be disassembled into multiple different controller variable families based on different root node variables.

[0029] Generally, the root node variables do not overlap or are the same. There may be overlapping or identical situations for intermediate node variables and leaf node variables, resulting in overlapping or intersections among different controller variable families.

[0030] Among them, the controller variable table records all controller variables involved in the control program. A controller variable refers to an element in the controller program used to store and operate actual running data, and the controller program operates instructions through controller variables. Controller variables include 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 control logic dependency relationships between controller variables involved in the control program. In the program text, the program location corresponding to the controller variable can be located by using the variable name or variable address of the controller variable as the query condition.

[0031] Optionally, the program corresponding to the controller variable is presented in multiple language forms, including but not limited to Sequential Function Chart (SFC), Function Block Diagram (FBD), Ladder Diagram (LD), Instruction List (IL), and Structured Text (ST).

[0032] Among them, a node refers to an element of the abstract syntax tree corresponding to the controller program in the project 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.

[0033] Node types can include root nodes, leaf nodes, and intermediate nodes. Among them, a root node refers to a node without a parent node. The root node is generally the topmost node, and it may contain multiple intermediate nodes and leaf nodes below it. A leaf node refers to a node without child nodes, and it is generally the bottommost node. An intermediate node refers to a node other than the root node and the leaf node.

[0034] A parent node refers to the node one level above a certain node along the tree structure, which is called the parent node of that node; a child node refers to the node one level below a certain node along the tree structure, which is called the child node of that node.

[0035] Each node usually contains corresponding variable information. Here, the variable information refers to the variable name, variable type, variable address, location information of the DB block or program block where the variable is located, etc. of at least one controller variable contained in the node.

[0036] 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 child nodes, 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 child nodes.

[0037] Optionally, the root node is the starting node, and the root node variable is a variable without a parent node upward. The root node variable is generally a global variable, and the variable types include but are not limited to: Q variable, DB variable, M variable, T variable, C variable. The intermediate node variable is a variable with both a parent node and child nodes, and the types of intermediate node variables include but are not limited to: M variable, DB variable, C variable, T variable, etc. The leaf node variable is a variable without descendant nodes, and the types of leaf node variables include but are not limited to: I variable, DB variable, M variable, T variable, C variable.

[0038] Optionally, the controller variables having a logical association relationship with the root node variable include the leaf node variable and the intermediate node variable. 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. Here, the association relationship 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 to determine the association relationship of the variables contained in each node.

[0039] Thus, by parsing the controller project 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 independently extractable and troubleshootable controller variable families. Compared with simultaneously troubleshooting all controller data, it can effectively reduce the amount of data for troubleshooting and reduce the requirements for the performance of the hardware device for troubleshooting.

[0040] S120. Monitor the actual running data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual running data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data.

[0041] In an embodiment of the present disclosure, the actual operation data corresponding to the root node variables of multiple controller variable families is obtained, and the obtaining methods include, but are not limited to, active collection or listening collection.

[0042] Optionally, the actual operation data refers to the data actually generated by the control program of the controller in the industrial field, including the actually generated real-time operation data and / or historical actual operation data.

[0043] Optionally, after the actual operation data corresponding to the root node variables is collected and before the abnormal data is identified, these actual operation data are stored. The storage method is not specifically limited.

[0044] Optionally, there are various ways to identify abnormal data in the actual operation data. Here, the abnormal data refers to the actual operation data that is incorrect or does not conform to the normal rules. The normal data refers to the actual operation data that is correct or conforms to the normal rules.

[0045] For the control program of the PLC controller, the corresponding controller data volume exceeds tens of millions, and the ordinary PLC control program has at least hundreds of thousands of controller variable families, and each controller variable family includes at least thousands or tens of thousands of controller variables. If all the data of all controller variable families are monitored simultaneously, the data volume is huge, and due to the bottleneck of the existing data collection technology, it is impossible to achieve the simultaneous monitoring of all controller variable families.

[0046] If only the root node variables of each controller variable family are monitored, the data volume for troubleshooting is greatly reduced, and by identifying the root node variables with abnormal actual operation data, the controller variable families corresponding to the root node variables with normal actual operation data can be directly excluded, further reducing the data volume for troubleshooting, and realizing quickly troubleshooting and determining the root cause of equipment failures with only a small amount of data.

[0047] S130. For the root node variables with abnormal data, obtain the actual operation data corresponding to the intermediate node variables and leaf node variables that have a logical association relationship with the root node variables, and identify the abnormal data in the actual operation data.

[0048] In an embodiment of the present disclosure, after the root node variables with abnormal data are obtained, the controller variable family headed by the root node variables can be determined, and then all the intermediate node variables and leaf node variables that have a logical association relationship with the root node variables in the controller variable family are obtained, and the corresponding actual operation data is obtained. Here, the actual operation data refers to the data actually generated by the control program of the controller in the industrial field, including the actually generated real-time operation data and / or historical actual operation data.

[0049] Optionally, after collecting the actual operation data corresponding to the intermediate node variables and leaf node variables and before identifying abnormal data, store these actual operation data. The storage method is not specifically limited.

[0050] S140. Determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and this device is the root cause of the failure of the faulty device.

[0051] 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 can be determined. The devices here include the devices controlled by the controller in the industrial field, including but not limited to one or more of devices such as sensors, switches, indicator lights, motors, or frequency converters. These devices are usually the root causes of the formation of faults in faulty devices.

[0052] Exemplarily, the leaf node variables include but are not limited to: I variables, DB variables, M variables, T variables, C variables.

[0053] Since the root node variables and leaf node variables in the controller variable family can be directly corresponding to the devices connected to the controller, while the intermediate node variables belong to the variables corresponding to the intermediate calculation process data and do not directly correspond to the devices connected to the controller, only by checking the leaf node variables can the root cause of the failure of the faulty device be finally determined, and then the device failure can be solved from the root cause.

[0054] In the embodiments of the present disclosure, by parsing the controller project file corresponding to the control program of the faulty device, multiple controller variable families are obtained. The controller variable family includes root node variables, intermediate node variables and leaf node variables that have a logical association relationship with the root node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables with both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes; monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation 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 the actual operation data corresponding to the intermediate node variables and leaf node variables that have a logical association relationship with the root node variables, and identify the abnormal data in the actual operation data; determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and this device is the root cause of the failure of the faulty device. Thus, the controller data can be effectively utilized to quickly and accurately check the root cause of the device failure, ensure the timely solution of the device failure, and avoid the production line from stopping production.

[0055] Based on the above embodiments, Figure 2 is a flowchart of another fault troubleshooting method provided by the embodiments of the present disclosure. As Figure 2 shown, it specifically includes the following steps: S210. Analyze the controller engineering file corresponding to the control program of the parsing device to obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables logically associated with the root node variables, and leaf node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables with both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes.

[0056] It should be noted that the specific implementation manner of S210 is similar to the above implementation manner and will not be elaborated here.

[0057] S220. Monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data: Simulate the operation process of the control program of the faulty device to obtain simulated operation data; Compare the actual operation data corresponding to the root node variables of multiple controller variable families with the simulated operation data. When the actual operation data is inconsistent with the simulated operation data, identify the inconsistent actual operation data as abnormal data.

[0058] In the embodiments of the present disclosure, the operation process of the control program corresponding to the faulty device is simulated to obtain simulated operation data; The actual operation data corresponding to the root node variables of multiple controller variable families is compared with the simulated operation data. When the actual operation data is inconsistent with the simulated operation data, the inconsistent actual operation data is identified as abnormal data.

[0059] Optionally, by simulating the operation process of the control program corresponding to the faulty device, simulated operation data can be obtained. Specifically, a simulated control program can be set, which has the same or similar operation logic as the control program corresponding to the faulty device, so as to realize the operation of the control program corresponding to the faulty device and thus obtain the simulated operation data.

[0060] Optionally, the simulated control program is a program that can simulate the operation of the control program of the controller in the industrial field. The simulated control program can run on a hardware redundant controller (such as a redundant PLC device, a redundant DCS device, etc.), and can also run on a data acquisition module integrated in the hardware controller. It can also run on any electronic device capable of running the simulated control program. The simulated control program can be a soft PLC, which is not limited here.

[0061] Optionally, the simulated control program can calculate and obtain the simulated operation data of the intermediate node variables and / or leaf node variables logically associated with the root node variable by running the same or similar program as the target control program.

[0062] Optionally, by comparing the actual operating data of intermediate node variables and / or leaf node variables that have a logical association with the root node variable with the simulated operating data, when the actual operating data of the same controller variable is inconsistent with the simulated operating data, the actual operating data at the time of inconsistency is identified as abnormal data.

[0063] S230. For the root node variable with abnormal data, obtaining the actual operating data corresponding to the intermediate node variables and leaf node variables that have a logical association with the root node variable, and identifying the abnormal data in the actual operating data further includes: for the root node variable with abnormal data, hierarchically checking the controller variable family corresponding to the root node variable, using the node unit corresponding to at least one controller variable at the current level as the object to be checked, where the node unit includes the controller variable at the current level and the controller variables at the next level with the controller variable at the current level as the parent node, and the controller variable includes any one or more of the root node variable, intermediate node variable, and leaf node variable; when the actual operating data of the controller variable at the next level in the node unit is abnormal data, using the node unit corresponding to the controller variable at the next level with abnormal data as the object to be checked.

[0064] In the embodiments of the present disclosure, for the root node variable with abnormal data, all 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 all controller variables in a controller variable family, if the actual operating data of all controller variables in the controller variable family is obtained simultaneously, the data volume is relatively large, and most of the data is data that does not need to be checked.

[0065] By hierarchically checking the controller variable family corresponding to the root node variable with abnormal data, each time using the node unit corresponding to at least one controller variable at the current level as the object to be checked, instead of checking the actual operating data of all controller variables in the controller variable family simultaneously, the data volume to be checked is greatly reduced. At the same time, the next check only needs to check the node unit corresponding to the controller variable with abnormal data, without checking all controller variables at the next level, which also greatly reduces the data volume to be checked to a certain extent, thereby improving the efficiency of fault checking, facilitating obtaining the fault checking result and solving the fault at the fastest speed, and avoiding long-term shutdown and production stoppage of the production line.

[0066] Specifically, the controller variable family takes the root node variable as the head and includes, from top to bottom, the root node variable, all intermediate node variables and leaf node variables that have a logical association with the root node variable. 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 variable includes any one or more of the root node variable, intermediate node variable, and leaf node variable.

[0067] Specifically, in the controller variable family, the controller variables included in the nodes of the first level are root node variables; the controller variables included in the nodes of the second level are multiple first-level intermediate node variables and / or multiple first-level leaf node variables, where the first-level intermediate node variables and / or the first-level leaf node variables have the root node variables as their parent nodes; the controller variables included in the nodes of the third level are multiple second-level intermediate node variables and / or multiple second-level leaf node variables, where different second-level intermediate node variables and / or second-level leaf node variables have different first-level intermediate node variables as their parent nodes; and so on, until the nodes of the last level (such as the N + 1 level), and the controller variables included in the nodes of this level are N-level leaf node variables.

[0068] Figure 3 Illustrates the node level relationship of the controller variable family. As Figure 3 shown, in a certain controller variable family, the controller variable included in the node of the first level is a root node variable a1; the controller variables included in the nodes of the second level are two first-level intermediate node variables a2, a4 and a first-level leaf node variable a3, where the first-level intermediate node variables a2, a4 and the first-level leaf node variable a3 have the root node variable a1 as their parent nodes; the controller variables included in the nodes of the third level are four second-level intermediate node variables a5, a6, a8, a9 and two second-level leaf node variables a7, a10, where different second-level intermediate node variables and second-level leaf node variables have different first-level intermediate node variables as their parent nodes, such as the second-level intermediate node variables a5, a6 and the second-level leaf node variable a7 have the first-level intermediate node variable a2 as their parent nodes, and the second-level intermediate node variables a8, a9 and the second-level leaf node variable a10 have the first-level intermediate node variable a4 as their parent nodes; the controller variables included in the nodes of the fourth level are six third-level leaf node variables a11, a12, a13, a14, a15, a16.

[0069] When conducting a step-by-step investigation of the controller variable family corresponding to the root node variable with abnormal data, the node units corresponding to at least one controller variable at the current level are taken as the investigation objects. The node units here include the controller variables at the current level and the controller variables at the next level that have the controller variables at the current level as their parent nodes. And when the actual operation data of the controller variables at the next level in the node unit is abnormal data, the node units corresponding to the controller variables at the next level with abnormal data are taken as the investigation objects.

[0070] Figure 4 Illustrates the node units in the process of step-by-step investigation of the controller variable family, where the content in the dotted box are different node units. As Figure 4As shown, for the root node variable a1 with abnormal actual operation 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. This node unit includes the current controller variable a1 at the first level and the controller variables a2, a3, and a4 at the second level with the current controller variable a1 at the first level as the parent node. In this node unit, the controller variable a1 is the root node variable, and the controller variables a2, a3, and a4 are intermediate node variables. If the actual operation data of a2 among the controller variables a2, a3, and a4 at the second level in this node unit is abnormal data, while the actual operation data of a3 and a4 is normal data, then the node unit corresponding to the controller variable a2 at the second level with abnormal data is taken as the object to be checked. At this time, there is no need to exclude the node units corresponding to a3 and a4 and all the controller variables below (such as a8, a9, a10, a14, a15, and a16), thus greatly narrowing the scope of the next check, which is beneficial to reducing the amount of data for fault checking and quickly obtaining the fault checking result.

[0071] In the further check level by level downward, taking the node unit corresponding to the controller variable a2 with abnormal data as the object to be checked, then this node unit includes the current controller variable a2 at the second level and the controller variables a5, a6, and a7 at the third level with the current controller variable a2 at the second level as the parent node. In this node unit, the controller variable a2 is a first-level intermediate node variable, the controller variables a5 and a6 are second-level intermediate node variables, and the controller variable a7 is a second-level leaf node variable. If the actual operation data of a5 among the controller variables a5, a6, and a7 at the third level in this node unit is abnormal data, while the actual operation data of a6 and a7 is normal data, then the node unit corresponding to the controller variable a5 at the third level with abnormal data is taken as the object to be checked, that is, the node unit composed of the controller variables a5, a11, and a12 is taken as the object to be checked, and there is no need to check the controller variable a13. At this time, since the controller variables a11 and a12 are leaf node variables and they directly correspond to the relevant equipment in the industrial field, the equipment corresponding to the controller variable a11 and / or a12 with abnormal actual operation data is the root cause of the fault.

[0072] For example, when an industrial production line stops or shuts down, by retrieving the control programs of all the devices corresponding to the production line, obtaining the controller engineering files corresponding to the control programs, and then obtaining multiple controller variable families, it is only necessary to monitor the root node variables of the controller variable families, identify the root node variables with abnormal actual operation data, and further troubleshoot the controller variable families corresponding to these abnormal root node variables, thereby excluding a large number of controller variable families with no abnormal root node variables, greatly narrowing the scope of troubleshooting; further, to improve the troubleshooting efficiency, the node unit is used as the troubleshooting unit to gradually troubleshoot these controller variable families, and the scope of troubleshooting is continuously narrowed through gradual troubleshooting, excluding the controller variables with no abnormal data, and finally determining the devices corresponding to the leaf node variables that cause the root cause of the failure. The root cause of the failure here may be that one or more sensors malfunction, or one or more frequency converters are damaged, or one or several switches are damaged.

[0073] Optionally, for multiple root node variables with abnormal data, when there are the same intermediate node variables and leaf node variables among the multiple root node variables, the troubleshooting results of the abnormal data of the same intermediate node variables and leaf node variables are reused. Specifically, when some intermediate node variables and leaf node variables of multiple controller variable families overlap or are the same, it is only necessary to perform a single troubleshooting of the abnormal data for the overlapping or identical intermediate node variables and leaf node variables, without the need for multiple troubleshootings, realizing the reuse of the troubleshooting results of the abnormal data, and further improving the efficiency of fault troubleshooting.

[0074] In fact, the shutdown or production suspension of the production line means huge economic losses of up to millions or tens of millions for the factory. It is crucial for the factory to determine the root cause of the failure and solve the problem at the fastest speed to make the production line operate normally. If multiple root node variables have abnormal data at the same time, troubleshooting the controller variable families corresponding to these root node variables simultaneously will increase the amount of data for fault troubleshooting. At this time, if these controller variable families can be queued and processed based on the priority, the efficiency of fault troubleshooting can be further improved.

[0075] Optionally, for multiple root node variables with abnormal data, based on the preset controller variable tags, the priority of troubleshooting the abnormal data of the multiple root node variables is determined. The controller variable tags include the variable information of the controller variables, and the variable information includes any one or more of the variable name, variable address, variable type, device name corresponding to the variable, device address corresponding to the variable, physical function of the device corresponding to the variable, use of the device corresponding to the variable, variable importance priority, and device failure probability.

[0076] Exemplarily, the controller variable tags include variable information such as preset variable importance priorities and variable failure probabilities. For controller variables with high importance priorities or high equipment failure probabilities, fault troubleshooting is preferentially performed on the controller variable families corresponding to these controller variables, so as to more quickly determine the root cause of the equipment failure. For example, the importance priority of the motor is higher than that of the switch. In this case, the controller variable family corresponding to the root node variable of the motor should be preferentially troubleshot.

[0077] S240. Determine the leaf node variable corresponding to the abnormal data and the equipment corresponding to the leaf node variable. The equipment corresponding to the leaf node variable is the root cause of the failure of the faulty equipment.

[0078] 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 equipment corresponding to the leaf node variable can be determined. The equipment here includes the equipment controlled by the controller in the industrial field, including but not limited to one or more of sensors, switches, indicator lights, motors, or frequency converters, etc. These equipment are usually the root cause of the formation of the faulty equipment.

[0079] Exemplarily, the leaf node variables include but are not limited to: I variables, DB variables, M variables, T variables, C variables.

[0080] In the embodiments of the present disclosure, by taking the node unit as the troubleshooting unit to gradually troubleshoot the controller variable family, not only only a small number of controller variables within the node unit range need to be troubleshot each time, and the actual operation data corresponding to the small number of controller variables can be quickly obtained and it can be determined whether there is abnormal data; moreover, as the abnormal data is gradually troubleshot, the controller variables with normal data can be gradually excluded, so that the troubleshooting scope of the fault troubleshooting gradually shrinks. Compared with synchronously troubleshooting all the controller variables of the entire controller variable family, only a small amount of data is required to quickly and accurately determine the root cause of the equipment failure, so as to more quickly determine the root cause of the failure and solve the failure in time, greatly shortening the production line downtime.

[0081] On the basis of the above embodiments, to facilitate the user to more intuitively master the location of the root cause of the failure, after determining the leaf node variable corresponding to the abnormal data and the equipment corresponding to the leaf node variable, the equipment information of the equipment corresponding to the leaf node variable is displayed. The equipment information includes any one or more of the equipment name, equipment location, equipment model, equipment operation data, equipment physical function, and equipment use.

[0082] Optionally, based on the preset controller variable tags, taking the variable name of the leaf node variable as the query entry, the relevant information of the variable corresponding to the root cause of the equipment failure is obtained, 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 further repair.

[0083] Optionally, to facilitate the user's more intuitive understanding of the root cause of the fault, the relevant information about the root cause of the fault can be displayed in various ways, including but not limited to text display, sound prompt, graphical display, and combined display of any of the above methods.

[0084] Optionally, the root cause of the fault is displayed graphically, including but not limited to highlighting the device-related information corresponding to the root cause of the fault in a 3D mechanical drawing. The fault location is displayed graphically on the user interface of the user terminal, making the display of the fault location more intuitive and clear. Specifically, it can display the overall layout diagram of the factory, or the layout diagram of a certain production line, or the layout of a certain device, or a partial enlarged view of a certain component, etc. Here, the fault location refers to the physical location of the device corresponding to the fault data.

[0085] Exemplarily, 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 partial enlarged view of the device component can display the assembly relationship and position of the component according to a certain scale. When it is detected that there is fault data in the PLC data corresponding to a certain device, the component position of the device can be located. The factory layout diagram, device layout diagram, or partial enlarged view of the faulty component containing the device can be displayed in a highlighted manner.

[0086] Optionally, the highlighting methods include but are not limited to: enlarged display, color differentiation, graphical selection, text reminder, language playback, etc. For example, use a red border for the device with a fault and a black border for others.

[0087] Optionally, the displayed content includes but is not limited to: specific device name, corresponding graphics, specific position in the corresponding graphics, specific numerical values, associated abnormal data before and after, time corresponding to the data, fault duration, etc.

[0088] Optionally, in addition to displaying the location of the root cause of the fault graphically, the information related to the fault data and the 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's fault and the fault history data.

[0089] 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 and perform maintenance or improve relevant process flows in advance.

[0090] Optionally, it also includes sending warning / alarm information to the user. After viewing the fault data, the user can process the warning / alarm information, such as confirming or canceling the warning / alarm information.

[0091] Figure 5 This is a schematic structural 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 embodiment of the fault troubleshooting method, such as Figure 5 As shown, 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 cause location module 54.

[0092] Among them, the controller variable family acquisition module 51 can be used to parse the controller engineering file corresponding to the control program of the faulty device, and obtain multiple controller variable families. The controller variable family includes a root node variable, intermediate node variables and leaf node variables that have 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 that has both a parent node and a child node, and the leaf node variable is a controller variable without a child node.

[0093] The root node variable monitoring module 52 can be used to monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify abnormal data in the actual operation data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data.

[0094] The abnormal data identification module 53 can be used to obtain the actual operation data corresponding to the intermediate node variables and leaf node variables that have a logical association relationship with the root node variable for the root node variable with abnormal data, and identify the abnormal data in the actual operation data.

[0095] The fault root cause location module 54 can be used to determine the leaf node variable corresponding to the abnormal data and the device corresponding to the leaf node variable, and this device is the fault root cause of the faulty device.

[0096] In the embodiments of the present disclosure, multiple controller variable families can be obtained by parsing the controller engineering file corresponding to the control program of the faulty device. The controller variable family includes a root node variable, intermediate node variables logically associated with the root node variable, and leaf node variables. 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. Monitor the actual operation data corresponding to the root node variables of multiple controller variable families, identify the abnormal data in the actual operation 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 the actual operation data corresponding to the intermediate node variables and leaf node variables logically associated with the root node variables, and identify the abnormal data in the actual operation data. Determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables. The devices corresponding to the leaf node variables are the root causes of the faults of the faulty devices. Thus, the controller data can be effectively utilized to quickly and accurately identify the root causes of device faults, ensure the timely resolution of device faults, and avoid production line shutdowns and production halts.

[0097] In some embodiments of the present disclosure, the root node variable monitoring module 52 further includes a simulated operation data acquisition sub-module and a comparison sub-module. Among them, the simulated operation data acquisition sub-module is used to simulate the operation process of the control program corresponding to the faulty device to obtain simulated operation data; the comparison sub-module is used to compare the actual operation data corresponding to the root node variable with the simulated operation data, and when the actual operation data is inconsistent with the simulated operation data, identify the inconsistent actual operation data as abnormal data.

[0098] In some embodiments of the present disclosure, the abnormal data identification module 53 further includes a node unit step-by-step troubleshooting sub-module, which is used to step by step troubleshoot the controller variable family corresponding to the root node variable with abnormal data, and take the node units corresponding to at least one controller variable at the current level as the troubleshooting objects. The node unit includes the controller variables at the current level and the controller variables at the next level with the controller variables at the current level as the parent nodes. The controller variables include any one or more of the root node variables, intermediate node variables, and leaf node variables. When the actual operation data of the controller variables at the next level in the node unit is abnormal data, take the node unit corresponding to the controller variables at the next level with abnormal data as the troubleshooting object.

[0099] In some embodiments of the present disclosure, the abnormal data identification module 53 further includes an abnormal data troubleshooting result reuse sub-module, which is used for multiple root node variables with abnormal data. When there are the same intermediate node variables and leaf node variables among the multiple root node variables, reuse the abnormal data troubleshooting results of the same intermediate node variables and leaf node variables.

[0100] In some embodiments of the present disclosure, the abnormal data recognition module 53 further includes a root node variable priority determination sub-module and a controller variable label sub-module. Among them, the root node variable priority determination sub-module is used to determine the priority of abnormal data troubleshooting for multiple root node variables based on preset controller variable labels; the controller variable label sub-module is used to preset the variable information of the controller variables, and the variable information includes any one or more of variable name, variable address, variable type, device name corresponding to the variable, device address corresponding to the variable, physical function of the device corresponding to the variable, purpose of the device corresponding to the variable, variable importance priority, and device failure probability.

[0101] In some embodiments of the present disclosure, the fault troubleshooting device further includes a display module, which can be used to display the device information of the device corresponding to the leaf node variable, and the device information includes any one or more of device name, device location, device model, device operation data, device physical function, and device purpose.

[0102] Figure 5 The fault troubleshooting device of the embodiment can be used to execute the technical solutions of the above method embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0103] Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. The electronic device provided by the embodiment of the present disclosure can execute the processing flow provided by the fault troubleshooting method embodiment. As Figure 6 shown, the electronic device 6 includes: 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 embodiment of the present disclosure Figures 1 to 4 The provided fault troubleshooting method.

[0104] In addition, an embodiment of the present disclosure further provides a computer-readable storage medium, which can store a computer program. When the computer program is executed by a processor, the processor is enabled to implement the embodiment of the present disclosure Figures 1 to 4 The provided fault troubleshooting method.

[0105] The above storage medium can, for example, include a memory of a computer program, and the above computer program can be executed by the processor of the fault troubleshooting device to complete the embodiment of the present disclosure Figures 1 to 4 The provided fault troubleshooting method. Optionally, the storage medium can be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium can be ROM, random access memory (Random Access Memory, RAM), compact disc read-only memory (Compact Disc ROM, CD-ROM), magnetic tape, floppy disk, and optical data storage configuration devices, etc.

[0106] In addition, an embodiment of the present disclosure further provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the above-mentioned fault troubleshooting method is implemented.

[0107] The above are only specific embodiments of the present disclosure, enabling those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be obvious to those skilled in the art. 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 rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A fault troubleshooting method, characterized in that, Including: Analyze the controller engineering file corresponding to the control program of the faulty device, and obtain multiple controller variable families. The controller variable families include root node variables, intermediate node variables logically associated with the root node variables, and leaf node variables. The root node variables are controller variables without parent nodes, the intermediate node variables are controller variables with both parent nodes and child nodes, and the leaf node variables are controller variables without child nodes; Monitor the actual operation data corresponding to the root node variables of the multiple controller variable families, identify the abnormal data in the actual operation 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 the actual operation data corresponding to the intermediate node variables and the leaf node variables logically associated with the root node variables, and identify the abnormal data in the actual operation data; Determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables. The devices are the root causes of the faults of the faulty device.

2. The method according to claim 1, characterized in that, The monitoring of the actual operation data corresponding to the root node variables of the multiple controller variable families, identifying the abnormal data in the actual operation data corresponding to the root node variables, and determining the root node variables corresponding to the abnormal data further includes: Simulate the operation process of the control program of the faulty device to obtain simulated operation data; Compare the actual operation data corresponding to the root node variables of the multiple controller variable families with the simulated operation data. When the actual operation data is inconsistent with the simulated operation data, identify the inconsistent actual operation data as abnormal data.

3. The method according to claim 1, characterized in that, The obtaining of the actual operation data corresponding to the intermediate node variables and the leaf node variables logically associated with the root node variables for the root node variables with abnormal data, and identifying the abnormal data in the actual operation data further includes: For the root node variables with abnormal data, hierarchically check the controller variable families corresponding to the root node variables. Take the node units corresponding to at least one controller variable at the current level as the objects to be checked. The node units include the controller variables at the current level and the controller variables at the next level with the controller variables at the current level as the parent nodes. The controller variables include any one or more of the root node variables, intermediate node variables, and leaf node variables; When the actual operation data of the controller variables at the next level in the node unit is abnormal data, take the node unit corresponding to the controller variables at the next level with abnormal data as the object to be checked.

4. The method according to claim 1, wherein For the controller variable families corresponding to multiple root node variables with abnormal data, when there are the same intermediate node variables and leaf node variables in multiple controller variable families, reuse the abnormal data troubleshooting results of the same intermediate node variables and leaf node variables.

5. The method according to claim 1, wherein For multiple root node variables with abnormal data, based on a preset controller variable tag, determine the priority of troubleshooting abnormal data for the multiple root node variables. The controller variable tag includes variable information of the controller variable, and the variable information includes any one or more of variable name, variable address, variable type, device name corresponding to the variable, device address corresponding to the variable, physical function of the device corresponding to the variable, use of the device corresponding to the variable, variable importance priority, and device failure probability.

6. The method according to claim 1, characterized in that After determining the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables, where the devices are the root causes of the failures of the faulty devices, the method further includes: Display device information of the devices corresponding to the leaf node variables, where the device information includes any one or more of device name, device location, device model, device operation data, device physical function, and device use.

7. A fault troubleshooting device, characterized in that, Includes: A controller variable family acquisition module, configured to parse a controller engineering file corresponding to a control program of a faulty device, and acquire multiple controller variable families. The controller variable families include root node variables, intermediate node variables having a logical association relationship with the root node variables, and leaf node variables. The root node variables are controller variables without a parent node, the intermediate node variables are controller variables having both a parent node and a child node, and the leaf node variables are controller variables without a child node; A root node variable monitoring module, configured to monitor actual operation data corresponding to the root node variables of the multiple controller variable families, identify abnormal data in the actual operation data corresponding to the root node variables, and determine the root node variables corresponding to the abnormal data; An abnormal data identification module, configured to, for the root node variables with abnormal data, acquire actual operation data corresponding to the intermediate node variables and the leaf node variables having a logical association relationship with the root node variables, and identify abnormal data in the actual operation data; A fault root cause location module, configured to determine the leaf node variables corresponding to the abnormal data and the devices corresponding to the leaf node variables, where the devices are the root causes of the failures of the faulty devices.

8. An electronic device, characterized in that, Includes: A processor; A memory; And A computer program; Wherein, the computer program is stored in the memory and is configured to be executed by the processor to implement the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement the method according to any one of claims 1-6 above.

10. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instruction is executed by a processor, the method according to any one of claims 1-6 is implemented.

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