Mechanical Arm Fault Warning and Analysis Method, Device and Terminal Equipment

Abstract

This application is applicable to the field of manipulator technology, and provides a manipulator fault warning and analysis method, device and terminal device. The method includes: obtaining the motion data of each component of the manipulator; constructing a monitoring model, which includes a real-time monitoring model of the manipulator and a business data monitoring model; constructing a digital twin model of the manipulator based on the motion data and the real-time monitoring model of the manipulator, and the digital twin model of the manipulator is a three-dimensional model; determining the manipulator fault warning and fault analysis based on the business data monitoring model and the digital twin model of the manipulator. This application can achieve fault warning for the manipulator and conduct fault analysis on the problems that occur.

Description

Technical Field

[0001] This application belongs to the technical field of manipulators, and particularly relates to a method, device, and terminal device for fault early warning and analysis of manipulators. Background Art

[0002] With the increase in labor costs and the shortage of talent reserves, factories are more inclined to use robots and manipulators to replace automated assembly line operations performed by humans.

[0003] However, currently, for the assembly line using manipulators, only whether the manipulator fails is monitored, and there is no corresponding fault early warning system. In the actual production process, if the manipulator fails, it often directly affects the entire automated assembly line, greatly reducing production efficiency.

[0004] Therefore, there is an urgent need for a method for fault early warning and analysis of manipulators to eliminate potential fault hazards in advance and analyze the occurring faults. Summary of the Invention

[0005] To overcome the problems existing in the related art, the embodiments of this application provide a method, device, and terminal device for fault early warning and analysis of manipulators, which can achieve fault early warning for manipulators and perform fault analysis on the occurring problems.

[0006] This application is implemented through the following technical solutions:

[0007] In a first aspect, the embodiments of this application provide a method for fault early warning and analysis of manipulators, including:

[0008] Obtain the motion data of each component of the manipulator; construct a monitoring model, where the monitoring model includes a real-time monitoring model of the manipulator and a business data monitoring model; construct a digital twin model of the manipulator based on the motion data and the real-time monitoring model of the manipulator, and the digital twin model of the manipulator is a three-dimensional model; determine the fault early warning and fault analysis of the manipulator based on the business data monitoring model and the digital twin model of the manipulator.

[0009] In a possible implementation manner of the first aspect, the motion data of each component of the manipulator includes: the motion trajectories, motion frequencies of each component of the manipulator in the normal motion state, and the force parameters of each component of the manipulator.

[0010] In a possible implementation manner of the first aspect, the motion data of each component of the manipulator further includes: the historical motion data of each component of the manipulator, the allowable number of motions of each component of the manipulator, and the maintenance information of each component of the manipulator.

[0011] In a possible implementation of the first aspect, the business data monitoring model includes: quality indicators, performance data, and delivery data. The quality indicators include the qualified indicators of each dimension in the products delivered by the manipulator, the qualified rate of the delivered products, and the required qualified rate for the delivered products; the performance data includes the data of the products delivered by the manipulator in a preset historical period; the delivery data includes the time and quantity of the products that the manipulator needs to deliver within a predetermined time.

[0012] In a possible implementation of the first aspect, based on the business data monitoring model and the manipulator digital twin model, the manipulator fault warning is determined, including: drawing a first data curve based on the motion data of each component of the manipulator; drawing a second data curve based on the performance data and the delivery data, and the second data curve is the motion curve required by each component of the manipulator for delivering products; comparing the first data curve and the second data curve to predict the time when any component of the manipulator fails.

[0013] In a possible implementation of the first aspect, based on the business data monitoring model and the manipulator digital twin model, the manipulator fault analysis is determined, including:

[0014] Determining whether the qualified rate of the products delivered by the manipulator meets the standard based on the quality indicators. If the qualified rate of the products delivered by the manipulator does not reach the quality indicators, then drawing a third data curve based on the manipulator real-time monitoring model, and the third data curve is determined based on the motion data of each component of the manipulator delivering unqualified products; drawing a fourth data curve based on the motion data of each component of the manipulator, and the fourth data curve is determined based on the motion data of each component of the manipulator in the normal motion state; comparing the third data curve and the fourth data curve to analyze and determine the fault location of the manipulator.

[0015] In a possible implementation of the first aspect, the manipulator fault warning and analysis method further includes: notifying the maintenance personnel to perform maintenance and fault repair on the manipulator based on the fault warning and the fault analysis.

[0016] The beneficial effects of the embodiments of the present application compared with the prior art are:

[0017] In the method disclosed in the embodiments of the present application, first, a monitoring model including a real-time monitoring model of the manipulator and a monitoring model of business data is constructed. Then, a digital twin model of the manipulator is constructed based on the motion data of each component of the manipulator and the real-time monitoring model of the manipulator. Finally, by combining the business data monitoring model and the digital twin model of the manipulator, fault early warning and fault analysis of the manipulator can be carried out. The technical solution of the present application establishes a digital twin model according to the motion data and real-time scenario of the manipulator, and combines business data to give early warning of possible faults of the manipulator, so as to eliminate potential fault hazards in advance, ensure the normal operation of the manipulator, and when the manipulator fails, accurately locate the fault position by analyzing the digital twin model to assist maintenance personnel in quickly repairing the fault.

[0018] In a second aspect, an embodiment of the present application provides a manipulator fault early warning and analysis device, including:

[0019] A data acquisition module for acquiring the motion data of each component of the manipulator. A monitoring model construction module for constructing a monitoring model, which includes a real-time monitoring model of the manipulator and a business data monitoring model. A digital twin construction module for constructing a digital twin model of the manipulator based on the motion data and the real-time monitoring model of the manipulator, and the digital twin model of the manipulator is a three-dimensional model. A fault determination module for determining manipulator fault early warning and fault analysis based on the business data monitoring model and the digital twin model of the manipulator.

[0020] In a third aspect, an embodiment of the present application provides a terminal device, including a memory and a processor. A computer program that can run on the processor is stored in the memory, and when the processor executes the computer program, it implements the manipulator fault early warning and analysis method according to any one of the first aspects.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements the manipulator fault early warning and analysis method according to any one of the first aspects.

[0022] In a fifth aspect, an embodiment of the present application provides a computer program product, which when running on a terminal device, causes the terminal device to execute the manipulator fault early warning and analysis method according to any one of the first aspects.

[0023] It can be understood that the beneficial effects of the above second aspect to the fifth aspect can refer to the relevant descriptions in the first aspect above, and will not be repeated here.

[0024] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this specification. Description of the Drawings

[0025] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0026] Figure 1 It is a schematic flowchart of a method for warning and analyzing manipulator failures provided by an embodiment of the present application;

[0027] Figure 2 It is a schematic flowchart of determining a manipulator failure warning provided by an embodiment of the present application;

[0028] Figure 3 It is a schematic flowchart of determining a manipulator failure analysis provided by an embodiment of the present application;

[0029] Figure 4 It is a schematic structural diagram of a manipulator failure warning and analysis device provided by an embodiment of the present application;

[0030] Figure 5 It is a schematic structural diagram of a terminal device provided by an embodiment of the present application. Detailed implementation manners

[0031] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are proposed to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0032] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0033] It should also be understood that the term " / and" as used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0034] As used in the specification of this application and the appended claims, the term "if" may be construed contextually as "when", or "once", or "in response to determining", or "in response to detecting". Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be construed contextually to mean "once determined", or "in response to determining", or "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]".

[0035] In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are used only for differential description and should not be construed as indicating or implying relative importance.

[0036] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0037] To make the objectives, technical solutions, and advantages of this application more clear and definite, the following provides a detailed description of this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described below are only used to explain this application and are not used to limit this application.

[0038] Figure 1 is a schematic flowchart of a method for early warning and analysis of manipulator failures provided by an embodiment of this application. Referring to Figure 1 this method can be executed through steps 101 to 104, which are described in detail as follows:

[0039] In step 101, motion data of each component of the manipulator is acquired.

[0040] The manipulator is assembled from multiple components. When the manipulator is operating, each component will move orderly according to a preset program.

[0041] In some embodiments, the motion data of each component of the manipulator acquired may at least include: motion data of the motion trajectories of each component of the manipulator in the moving state, motion data of the motion frequencies of each component of the manipulator, and motion data of the force parameters of each component of the manipulator.

[0042] In some embodiments, the motion data of each component of the manipulator obtained may further include historical data, such as the motion data of all historical motion trajectories of each component of the manipulator, the motion data of all historical motion frequencies, and the motion data of all historical force parameters.

[0043] In some embodiments, the motion data of each component of the manipulator obtained may further include the maintenance information of each component of the manipulator, and the maintenance information may include historical maintenance information, expected maintenance information, etc.

[0044] In some embodiments, the motion data of each component of the manipulator obtained may further include the allowable number of motions of each component of the manipulator.

[0045] The motion parameters of each component of the manipulator of multiple time periods and multiple types obtained in step 101 provide a data basis for subsequent construction of the digital twin model of the manipulator.

[0046] In step 102, a monitoring model is constructed, and the monitoring model includes a real-time monitoring model of the manipulator and a business data monitoring model.

[0047] In some embodiments, a real-time monitoring model of the manipulator is constructed to monitor the motion trajectory, motion frequency, and force parameters of each component of the manipulator in real time and record the monitored data.

[0048] In some embodiments, a business data monitoring model is constructed to monitor the business information of the products to be delivered by the manipulator. These business information may include quality indicators, performance data, and delivery data.

[0049] Exemplarily, the quality indicators may include the data of each dimension in the products delivered by the manipulator, the yield rate of the delivered products, and the required yield rate for the delivered products.

[0050] Exemplarily, the performance data may include the data of the products delivered by the manipulator within a preset historical period. The preset historical period may be the period from the current moment of each component of the manipulator to the last maintenance, and the data of the delivered products may be the quantity and type of the products that the manipulator has delivered. Different quantities and types of products will correspond to different motion data of each component in the manipulator.

[0051] Exemplarily, the delivery data may include the time and quantity of the products that the manipulator needs to deliver within a predetermined time. The motion data required for each component in the manipulator can be statistically analyzed according to the delivery data.

[0052] In step 102, a real-time monitoring model of the manipulator and a business data monitoring model are constructed, which can not only obtain the real-time motion data of each component of the manipulator, but also statistically analyze the motion data required for each component of the manipulator according to business requirements.

[0053] In step 103, a digital twin model of the manipulator is constructed based on the motion data and the real-time monitoring model of the manipulator.

[0054] In some embodiments, taking the motion data of each component of the manipulator as the basic data, through various sensors on the manipulator, combined with the real-time monitoring model of the manipulator, a digital twin model of the manipulator is constructed.

[0055] In some embodiments, the digital twin model of the manipulator is a three-dimensional model, and various motion parameters of each component of the manipulator can be displayed in real time according to the sensor data collected by the real-time monitoring model of the manipulator.

[0056] In step 104, based on the business data monitoring model and the digital twin model of the manipulator, manipulator fault warning and fault analysis are determined.

[0057] In some embodiments, based on the business data monitoring model and the digital twin model of the manipulator, manipulator fault warning can be determined. Determining the manipulator fault warning can be executed through steps 1041 to 1043, as shown in Figure 2 , and the details are as follows:

[0058] In step 1041, a first data curve is drawn based on the motion data of each component of the manipulator.

[0059] Exemplarily, the first data curve can be determined based on the historical motion data of each component of the manipulator, that is, determined according to the motion data of all historical motion trajectories of each component of the manipulator, the motion data of all historical motion frequencies, and the motion data of the historical force parameters.

[0060] In step 1042, a second data curve is drawn based on the performance data and the delivery data.

[0061] Exemplarily, the second data curve can be the data curve of the motion required for each component of the manipulator to deliver different quantities and types of products.

[0062] In step 1043, the first data curve and the second data curve are compared to predict the time when any component of each component of the manipulator fails.

[0063] Exemplarily, by comparing the first data curve and the second data curve, the threshold of the remaining number of movements of each component of the manipulator can be analyzed. When the threshold of the number of movements is exceeded, the manipulator may fail and affect the production efficiency. Therefore, by comparing the first data curve and the second data curve, the time when any component of each component of the manipulator fails can be predicted.

[0064] In some embodiments, based on the business data monitoring model and the digital twin model of the manipulator, the manipulator fault analysis can be determined. The determination of the manipulator fault analysis can be performed through steps 1044 to 1046, as follows with reference to Figure 3 , which is described in detail as follows:

[0065] In step 1044, a third data curve is drawn based on the real-time monitoring model of the manipulator.

[0066] Exemplarily, based on the quality index, it can be determined whether the qualified rate of the products delivered by the manipulator meets the standard. If unqualified products appear or the qualified rate does not reach the quality index, a third data curve is drawn based on the real-time monitoring model of the manipulator.

[0067] Optionally, the third data curve can be determined based on the motion data of the unqualified products delivered by the manipulator, that is, the real-time motion data of the manipulator in the real-time monitoring model of the manipulator is retrieved, and the motion data of each component of the manipulator can be drawn.

[0068] In step 1045, a fourth data curve is drawn based on the motion data of each component of the manipulator.

[0069] Exemplarily, the fourth data curve can be determined based on the motion data of each component of the manipulator in the normal motion state, that is, the motion curve of delivering qualified products when each component of the manipulator is in the normal motion state is drawn.

[0070] In step 1046, the third data curve and the fourth data curve are compared to analyze and determine the fault location of the manipulator.

[0071] Exemplarily, by comparing the third data curve and the fourth data curve, any component of the manipulator that does not conform to the normal motion can be analyzed, so as to achieve the purpose of locating the fault location of the manipulator.

[0072] In some embodiments, based on Figure 1 the embodiments shown above, the above-mentioned manipulator fault warning and analysis method may further include: based on the fault warning and fault analysis, notifying the maintenance personnel to perform maintenance and fault repair on the manipulator.

[0073] Exemplarily, the digital twin model of the manipulator issues a fault warning to notify the manipulator maintenance personnel, and the maintenance personnel can determine the components of the manipulator that need maintenance through the fault warning.

[0074] Exemplarily, the digital twin model of the manipulator issues a fault analysis warning to notify the manipulator maintenance personnel, and the maintenance personnel can determine the fault location of the manipulator through the fault analysis warning and quickly eliminate the fault.

[0075] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution, and the order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0076] Corresponding to the robot arm fault warning and analysis method described in the above embodiments, Figure 4 The structural block diagram of the robot arm fault warning and analysis device provided by the embodiments of the present application is shown. For the convenience of description, only the parts related to the embodiments of the present application are shown.

[0077] See Figure 4 , the robot arm fault warning and analysis device in the embodiments of the present application may include: a data acquisition module 201, a monitoring model construction module 202, a digital twin construction module 203, and a fault determination module 204.

[0078] The data acquisition module 201 is used to acquire the motion data of each component of the robot arm.

[0079] Optionally, the motion data of each component of the robot arm includes: the motion trajectory, motion frequency of each component of the robot arm under normal motion conditions, and the force parameters of each component of the robot arm.

[0080] Optionally, the motion data of each component of the robot arm further includes: the historical motion data of each component of the robot arm, the allowable number of motions of each component of the robot arm, and the maintenance information of each component of the robot arm.

[0081] The monitoring model construction module 202 is used to construct a monitoring model, and the monitoring model includes a robot arm real-time monitoring model and a service data monitoring model.

[0082] Among them, the service data monitoring model includes: quality indicators, performance data, and delivery data.

[0083] Optionally, the quality indicators include the qualified indicators of each dimension in the products delivered by the robot arm, the qualified rate of the delivered products, and the required qualified rate for the delivered products.

[0084] Optionally, the performance data includes the data of the products delivered by the robot arm in a preset historical period.

[0085] Optionally, the delivery data includes the time and quantity of the products that the robot arm needs to deliver within a predetermined time.

[0086] The digital twin construction module 203 is used to construct a robot arm digital twin model based on the motion data and the robot arm real-time monitoring model, where the robot arm digital twin model is a three-dimensional model.

[0087] The fault determination module 204 is used to determine the robot arm fault warning and fault analysis based on the service data monitoring model and the robot arm digital twin model.

[0088] Optionally, based on the business data monitoring model and the digital twin model of the manipulator, determining the manipulator fault warning may include: drawing a first data curve based on the motion data of each component of the manipulator; drawing a second data curve based on the performance data and the delivery data, where the second data curve is the data curve of the motion required by each component of the manipulator for delivering products; comparing the first data curve and the second data curve to predict the time when any component of the manipulator fails.

[0089] Optionally, based on the business data monitoring model and the digital twin model of the manipulator, determining the manipulator fault analysis includes: determining whether the qualified rate of the products delivered by the manipulator meets the standard based on the quality index. If the products delivered by the manipulator are unqualified or the qualified rate of the delivered products does not reach the quality index, then draw a third data curve based on the manipulator real-time monitoring model, where the third data curve is determined based on the motion data of the manipulator delivering unqualified products; draw a fourth data curve based on the motion data of each component of the manipulator, where the fourth data curve is determined based on the motion data of each component of the manipulator in the normal motion state; compare the third data curve and the fourth data curve to analyze and determine the fault location of the manipulator.

[0090] It should be noted that for the information interaction, execution process, etc. between the above-mentioned devices / units, since they are based on the same concept as the method embodiments of the present application, their specific functions and the technical effects brought can be specifically referred to the method embodiment part, and will not be elaborated here.

[0091] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example for illustration. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments and will not be elaborated here.

[0092] The embodiment of the present application also provides a terminal device. See Figure 5, the terminal device 300 may include: at least one processor 310 and a memory 320. The memory 320 stores a computer program 321 that can run on the at least one processor 310. When the processor 310 executes the computer program 321, the steps in any of the above method embodiments are implemented, such as Figure 1 the steps 101 to 104 in the illustrated embodiment. Alternatively, when the processor 310 executes the computer program 321, the functions of each module / unit in the above device embodiments are implemented, such as Figure 4 the functions of the illustrated modules 201 to 204.

[0093] Exemplarily, the computer program 321 may be divided into one or more modules / units. One or more modules / units are stored in the memory 320 and executed by the processor 310 to complete this application. The one or more modules / units may be a series of computer program segments capable of performing specific functions, and these program segments are used to describe the execution process of the computer program in the terminal device 300.

[0094] Those skilled in the art can understand that Figure 5 this is only an example of the terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0095] The processor 310 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0096] The memory 320 may be an internal storage unit of the terminal device or an external storage device of the terminal device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. The memory 320 is used to store the computer program and other programs and data required by the terminal device. The memory 320 may also be used to temporarily store data that has been output or is to be output.

[0097] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the buses in the drawings of this application are not limited to only one bus or one type of bus.

[0098] The method for warning and analyzing manipulator faults provided in the embodiments of this application can be applied to terminal devices such as computers, wearable devices, vehicle-mounted devices, tablet computers, laptop computers, netbooks, personal digital assistants (PDAs), augmented reality (AR) / virtual reality (VR) devices, mobile phones, etc. The embodiments of this application do not impose any restrictions on the specific types of terminal devices.

[0099] The embodiments of this application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps in each of the above embodiments of the method for warning and analyzing manipulator faults can be implemented.

[0100] The embodiments of this application provide a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal is enabled to execute the steps in each of the above embodiments of the method for warning and analyzing manipulator faults.

[0101] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device capable of carrying the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0102] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0103] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0104] In the embodiments provided in this application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0105] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for early warning and analysis of manipulator faults, characterized in that, Including: Obtain the motion data of each component of the manipulator; The motion data of each component of the manipulator includes: the motion trajectory, motion frequency, force parameters of each component of the manipulator, historical motion data of each component of the manipulator, the allowable number of motions of each component of the manipulator, and the maintenance information of each component of the manipulator; Construct a monitoring model, which includes a real-time monitoring model of the manipulator and a business data monitoring model; Based on the motion data and the real-time monitoring model of the manipulator, construct a digital twin model of the manipulator, and the digital twin model of the manipulator is a three-dimensional model; Based on the business data monitoring model and the digital twin model of the manipulator, determine the fault warning and fault analysis of the manipulator; The business data monitoring model is used to monitor the business information of the products that the manipulator needs to deliver; the business information includes quality indicators, performance data, and delivery data; The quality indicators include the qualified indicators of each dimension in the products delivered by the manipulator, the qualified rate of the delivered products, and the required qualified rate for the delivered products; The performance data includes the data of the products delivered by the manipulator in a preset historical period; The delivery data includes the time and quantity of the products that the manipulator needs to deliver within a predetermined time; The determining of the fault warning of the manipulator based on the business data monitoring model and the digital twin model of the manipulator includes: Draw a first data curve based on the motion data of each component of the manipulator; Draw a second data curve based on the performance data and the delivery data, and the second data curve is the data curve of the motion required for each component of the manipulator for delivering products; Compare the first data curve and the second data curve to predict the time when any component of the manipulator fails; The determining of the fault analysis of the manipulator based on the business data monitoring model and the digital twin model of the manipulator includes: Judge whether the qualified rate of the products delivered by the manipulator meets the standard based on the quality indicators. If the products delivered by the manipulator are unqualified or the qualified rate of the delivered products does not reach the quality indicators, then draw a third data curve based on the real-time monitoring model of the manipulator, and the third data curve is determined based on the motion data of the manipulator delivering unqualified products; Draw a fourth data curve based on the motion data of each component of the manipulator, and the fourth data curve is determined based on the motion data of each component of the manipulator in the normal motion state; Compare the third data curve and the fourth data curve to analyze and determine the fault location of the manipulator.

2. The method for early warning and analysis of manipulator faults according to claim 1, characterized in that, This method further includes: based on the fault warning and the fault analysis, notify the maintenance personnel to perform maintenance and fault repair on the manipulator.

3. A device for early warning and analysis of manipulator faults, characterized in that, Including: A data acquisition module for obtaining the motion data of each component of the manipulator; The motion data of each component of the manipulator includes: the motion trajectory, motion frequency, force parameters of each component of the manipulator, historical motion data of each component of the manipulator, the allowable number of motions of each component of the manipulator, and the maintenance information of each component of the manipulator; The monitoring model construction module is used to construct a monitoring model, and the monitoring model includes a real-time monitoring model of the manipulator and a business data monitoring model; the business data monitoring model is used to monitor the business information of the products to be delivered by the manipulator; the business information includes quality indicators, performance data, and delivery data; the quality indicators include the qualified indicators of each dimension in the products delivered by the manipulator, the qualified rate of the delivered products, and the required qualified rate for the delivered products; the performance data includes the data of the products delivered by the manipulator in a preset historical period; the delivery data includes the time and quantity of the products to be delivered by the manipulator within a predetermined time. The digital twin construction module is used to construct a manipulator digital twin model based on the motion data and the real-time monitoring model of the manipulator, and the manipulator digital twin model is a three-dimensional model. The fault determination module is used to determine the manipulator fault warning and fault analysis based on the business data monitoring model and the manipulator digital twin model. Specifically, the fault determination module is used for: Drawing a first data curve based on the motion data of each component of the manipulator; Drawing a second data curve based on the performance data and the delivery data, and the second data curve is the data curve of the motion required by each component of the manipulator for the delivered products; Comparing the first data curve and the second data curve to predict the time when any component of the manipulator fails; Judging whether the qualified rate of the products delivered by the manipulator meets the standard based on the quality indicators. If the products delivered by the manipulator are unqualified or the qualified rate of the delivered products does not reach the quality indicators, a third data curve is drawn based on the real-time monitoring model of the manipulator, and the third data curve is determined based on the motion data of the manipulator delivering unqualified products; Drawing a fourth data curve based on the motion data of each component of the manipulator, and the fourth data curve is determined based on the motion data of each component of the manipulator in a normal motion state; Comparing the third data curve and the fourth data curve to analyze and determine the fault location of the manipulator.

4. A terminal device, including a memory and a processor, and a computer program that can run on the processor is stored in the memory, characterized in that, When the processor executes the computer program, the method described in any one of claims 1 to 2 is implemented.

5. A computer-readable storage medium, and a computer program is stored in the computer-readable storage medium, characterized in that,When the computer program is executed by the processor, the method described in any one of claims 1 to 2 is implemented.

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