Servo motor fault judgment method and device, electronic equipment and storage medium
By performing principal component analysis and edge sensitivity analysis on the host computer, the problem of high cost in servo motor fault diagnosis for small and medium-sized enterprises is solved, and efficient and low-cost fault judgment is achieved.
Patent Information
- Application Number
- CN202511660300.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-13
- Publication Date
- 2026-02-13
AI Technical Summary
Small and medium-sized enterprises lack high-quality data and costly algorithms when diagnosing servo motor faults, resulting in high costs for online fault diagnosis and difficulty in achieving effective fault judgment.
By performing principal component analysis on the host computer, the target operating parameters of the servo motor are determined, and sensitivity analysis and fault diagnosis are performed on the embedded system board on the edge side, using lightweight algorithms to reduce costs.
It enables efficient fault diagnosis at the device edge, significantly reducing fault diagnosis costs and is suitable for small and medium-sized enterprises.
Smart Images
Figure CN121522450A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of motor fault diagnosis, and in particular to a servo motor fault judgment method and device, an electronic device and a storage medium. BACKGROUND
[0002] In recent years, full servo motor systems have been widely used in the field of industrial automation. With the improvement of production efficiency, the reliability of servo motors in the running process is also concerned. In the prior art, when performing online fault diagnosis of a servo motor, a large amount of high-frequency data needs to be analyzed, and small and medium-sized enterprises do not have the conditions to provide high-quality data. Secondly, the algorithm is too complex, and can only rely on high-quality chips or large servers, resulting in increased costs, which exceeds the cost that small and medium-sized enterprises can afford. SUMMARY
[0003] The present application provides a servo motor fault judgment method, device, electronic device and storage medium, which is suitable for application on the edge side of the device and can significantly reduce the cost of fault diagnosis.
[0004] According to an aspect of the present application, a servo motor fault judgment method is provided, which comprises:
[0005] Obtaining historical running data of a servo motor, performing principal component analysis on running parameters in the historical running data, and determining target running parameters of the servo motor; wherein the principal component analysis is performed by a host computer;
[0006] Performing sensitivity analysis on the target running parameters according to the historical running data for the running reliability of the servo motor, and determining a sensitive interval of the target running parameters;
[0007] Obtaining real-time running data of the servo motor, and judging whether the servo motor has a fault according to the real-time running data and the sensitive interval; wherein the sensitivity analysis and fault judgment are performed by an embedded system board applied to the edge side of the servo motor.
[0008] According to another aspect of the present application, a servo motor fault judgment device is provided, which comprises:
[0009] A parameter determination module for obtaining historical running data of a servo motor, performing principal component analysis on running parameters in the historical running data, and determining target running parameters of the servo motor; wherein the principal component analysis is performed by a host computer;
[0010] The interval determination module is used to perform sensitivity analysis on the target operating parameters for the reliability of the servo motor operation based on the historical operating data, and to determine the sensitive interval of the target operating parameters;
[0011] The fault diagnosis module is used to acquire the real-time operating data of the servo motor and determine whether the servo motor has a fault based on the real-time operating data and the sensitive range; wherein, the sensitivity analysis and fault diagnosis are performed by an embedded system board applied to the edge side of the servo motor.
[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:
[0013] At least one processor; and
[0014] A memory communicatively connected to the at least one processor; wherein,
[0015] The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the servo motor fault diagnosis method according to any embodiment of the present invention.
[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the servo motor fault diagnosis method according to any embodiment of the present invention.
[0017] The technical solution of this invention involves acquiring historical operating data of a servo motor, performing principal component analysis on the operating parameters in the historical operating data to determine the target operating parameters of the servo motor; wherein the principal component analysis is performed by a host computer; performing sensitivity analysis on the target operating parameters for the reliability of the servo motor based on the historical operating data to determine the sensitive range of the target operating parameters; acquiring real-time operating data of the servo motor, and judging whether the servo motor has a fault based on the real-time operating data and the sensitive range; wherein the sensitivity analysis and fault judgment are performed by an embedded system board applied to the edge side of the servo motor. This technical solution, after determining the target operating parameters by performing principal component analysis on the operating parameters in the historical operating data through a host computer, can achieve sensitivity analysis of the target operating parameters and fault diagnosis of the servo motor through an embedded system board applied to the edge side of the servo motor and a lightweight algorithm. It is suitable for application at the edge side of equipment and can significantly reduce fault diagnosis costs.
[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart of a servo motor fault diagnosis method provided in Embodiment 1 of the present invention;
[0021] Figure 2 This is a schematic diagram of the workflow of an embedded system board according to Embodiment 1 of the present invention;
[0022] Figure 3 This is a flowchart of a servo motor fault diagnosis method provided in Embodiment 2 of the present invention;
[0023] Figure 4 This is a schematic diagram of a process for determining target operating parameters according to Embodiment 2 of the present invention;
[0024] Figure 5 This is a schematic diagram of a process for determining a sensitive region according to Embodiment 2 of the present invention.
[0025] Figure 6 This is a schematic diagram of a servo motor fault diagnosis device according to Embodiment 3 of the present invention;
[0026] Figure 7 This is a schematic diagram of the structure of an electronic device that implements the servo motor fault judgment method of the present invention. Detailed Implementation
[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0029] Example 1
[0030] Figure 1 This is a flowchart illustrating a servo motor fault diagnosis method according to Embodiment 1 of the present invention. This embodiment is applicable to diagnosing potential faults in servo motors. The method can be executed by a servo motor fault diagnosis device, which can be implemented in hardware and / or software. Figure 1 As shown, the method includes:
[0031] S110. Obtain historical operating data of the servo motor, perform principal component analysis on the operating parameters in the historical operating data, and determine the target operating parameters of the servo motor; wherein, the principal component analysis is performed through the host computer.
[0032] Servo motors are core components in automated control systems that enable high-precision position, speed, and torque control. They can convert electrical signals into precise mechanical motion through a closed-loop feedback mechanism and are widely used in industrial robots, CNC machine tools, aerospace, medical equipment, and other fields.
[0033] Principal component analysis (PCA) is an unsupervised learning method widely used for data dimensionality reduction, feature extraction, and visualization. Its core idea is to project the original high-dimensional data into a low-dimensional space through linear transformation, while preserving the main variation information in the data, thereby simplifying the data structure and revealing potential patterns. In this embodiment of the invention, PCA is performed via a host computer, which can be a computer or other computing device.
[0034] In this embodiment of the invention, low-volume, low-frequency operating data can be used as historical operating data to analyze the reliability of the servo motor. When acquiring historical operating data, a preset sampling frequency and preset data volume can be used, such as a sampling frequency of once per second and a data volume of 1000 records, to read stored operating data from the servo motor's driver or controller as historical operating data. Subsequently, to streamline the algorithm and meet its deployment requirements on embedded system boards with lower chip costs, the principal component analysis portion of the algorithm can be performed on a host computer. That is, the host computer performs principal component analysis on the operating parameters in the historical operating data to determine the key characteristic operating parameters affecting the servo motor's operation, which are then used as target operating parameters.
[0035] S120. Based on historical operating data, perform sensitivity analysis on the target operating parameters for the reliability of servo motor operation, and determine the sensitive range of the target operating parameters.
[0036] Sensitivity analysis is a systematic method used to assess the sensitivity of the output of a model, system, or decision to changes in input parameters or assumptions. Its core objective is to identify which factors have the greatest impact on the outcome, thereby providing decision-makers with a basis for risk assessment, resource allocation, and uncertainty management. In this embodiment of the invention, sensitivity analysis is performed using an embedded system board applied to the edge side of a servo motor. The embedded system board includes a main control chip, an OLED screen, a communication chip, DIP switches, and a power supply chip.
[0037] In this embodiment of the invention, after determining the target operating parameters, these parameters can be encoded and transmitted to the embedded system board via a DIP switch. Simultaneously, historical operating data can be transmitted to the embedded system board through its communication module. Then, the main control chip in the embedded system board can perform a range analysis method to conduct a sensitivity analysis of the target operating parameters on the reliability of the servo motor based on the historical operating data. This determines the range within which the target operating parameters have the greatest impact on the reliability of the servo motor, and this range is designated as the sensitive range for the target operating parameters. It should be noted that the main control chip of the embedded system board only needs a clock frequency of 100MHz or higher.
[0038] S130. Acquire real-time operating data of the servo motor and determine whether there is a fault in the servo motor based on the real-time operating data and the sensitive range; wherein, the sensitivity analysis and fault judgment are performed by an embedded system board applied to the edge side of the servo motor.
[0039] In this embodiment of the invention, real-time operating data of the servo motor can be acquired through an embedded system board applied to the edge side of the servo motor. The main control chip within the embedded system board then determines whether the servo motor is faulty based on the real-time operating data and sensitive ranges. By using a low-frequency main control chip in the embedded system board and a lightweight algorithm, fault detection of the servo motor can be achieved, making it suitable for application at the device edge and significantly reducing fault diagnosis costs.
[0040] Optionally, the step of determining whether the servo motor has a fault based on the real-time operating data and the sensitive interval includes: determining the real-time data corresponding to the target operating parameter in the real-time operating data, and determining whether the real-time data falls within the sensitive interval corresponding to the target operating parameter; if the real-time data corresponding to the target operating parameter falls within the sensitive interval corresponding to the target operating parameter, it is determined that the servo motor has a fault.
[0041] In this embodiment of the invention, the real-time data corresponding to the target operating parameter in the real-time operating data can be determined first, and it can be judged whether the real-time data falls within the sensitive interval corresponding to the target operating parameter. It is understood that there can be multiple target operating parameters, and correspondingly, there can also be multiple sensitive intervals. When determining whether a servo motor is faulty, as long as the real-time data corresponding to any one target operating parameter falls within the sensitive interval corresponding to that target operating parameter, it is determined that the servo motor is faulty.
[0042] Optionally, after determining that the servo motor has a fault, the method further includes: determining the target operating parameters that the real-time data falls within the sensitive range as fault operating parameters; issuing an alarm based on the fault operating parameters; and visually displaying the fault operating parameters on the screen of the embedded system board.
[0043] In this embodiment of the invention, after determining that a servo motor has a fault, the target operating parameters that fall within the sensitive range of real-time data can be identified, i.e., the target operating parameters that affect the reliability of servo motor operation, as the fault operating parameters. At this time, an alarm can be triggered based on the fault operating parameters, and the fault operating parameters can be visualized on the OLED screen of the embedded system board. For example, Figure 2 A schematic diagram of the workflow of an embedded system board is shown.
[0044] The technical solution of this invention involves acquiring historical operating data of a servo motor, performing principal component analysis on the operating parameters in the historical operating data, and determining the target operating parameters of the servo motor. The principal component analysis is performed via a host computer. Based on the historical operating data, a sensitivity analysis is conducted on the target operating parameters to assess the reliability of the servo motor operation, determining the sensitive range of the target operating parameters. Real-time operating data of the servo motor is acquired, and the presence of a fault in the servo motor is determined based on the real-time operating data and the sensitive range. The sensitivity analysis and fault diagnosis are performed using an embedded system board applied to the edge of the servo motor. This technical solution, after determining the target operating parameters through principal component analysis of the operating parameters in the historical operating data via a host computer, utilizes an embedded system board applied to the edge of the servo motor and a lightweight algorithm to achieve sensitivity analysis of the target operating parameters and fault diagnosis of the servo motor. This method is suitable for application at the edge of equipment and can significantly reduce fault diagnosis costs.
[0045] Example 2
[0046] Figure 3 This is a flowchart of a servo motor fault diagnosis method provided in Embodiment 2 of the present invention. The embodiments of the present invention are optimized based on the above embodiments. Solutions not described in detail in the embodiments of the present invention are described in the above embodiments. Figure 3 As shown, the method includes:
[0047] S210. Obtain historical operating data of the servo motor, perform principal component analysis on the operating parameters in the historical operating data, and determine the target operating parameters of the servo motor.
[0048] Optionally, the step of performing principal component analysis on the operating parameters in the historical operating data to determine the target operating parameters of the servo motor includes: constructing a data matrix based on the operating parameters in the historical operating data, standardizing the data matrix; calculating the covariance matrix of the standardized data matrix, and determining the target operating parameters of the servo motor based on the covariance matrix.
[0049] In this embodiment of the invention, a data matrix can be constructed based on the operating parameters in the historical operating data, and the data matrix can be standardized.
[0050] For example, the operating parameters in the historical operating data may include phase A current, phase B current, phase C current, phase A voltage, phase B voltage, phase C voltage, active power, reactive power, and power factor. In this case, a 9x9 data matrix A can be constructed. Optionally, data matrix A can be represented as: Next, data matrix A can be standardized to obtain matrix B. Optionally, the standardization process is as follows:
[0051] ;
[0052] ;
[0053] ;
[0054] in, Refers to data matrix No. The average of the column, Refers to data matrix No. The standard deviation of the column, Refers to data matrix No. Line number The value of the column, This refers to the matrix obtained after standardization. No. Line number The values of the columns. Then, the standardized matrix can be calculated. covariance matrix And based on the covariance matrix Determine the target operating parameters for the servo motor.
[0055] Optionally, determining the target operating parameters of the servo motor based on the covariance matrix includes: determining the eigenvalue corresponding to each operating parameter based on the covariance matrix, and calculating the contribution rate of each operating parameter based on the eigenvalue; arranging the operating parameters in descending order according to the size of the eigenvalue, and calculating the cumulative contribution rate corresponding to each operating parameter starting from the first operating parameter; wherein, the cumulative contribution rate corresponding to the operating parameter is the sum of the contribution rates of all operating parameters from the first operating parameter to that operating parameter; when the cumulative contribution rate exceeds a preset threshold, taking all operating parameters corresponding to the contribution rates participating in the calculation of the cumulative contribution rate as the target operating parameters.
[0056] For example, it can be done first based on the covariance matrix Determine the characteristic value corresponding to each running parameter Then based on the eigenvalues Calculate the contribution rate of each operating parameter. Optionally, the formula for calculating the contribution rate of an operating parameter based on its eigenvalue is as follows:
[0057] ;
[0058] in, For the first The contribution rate of each operating parameter For the first The characteristic values of each running parameter This represents the number of running parameters. Next, the running parameters can be sorted in descending order of their eigenvalues, and the cumulative contribution rate for each running parameter can be calculated starting from the first parameter. The cumulative contribution rate for each running parameter is the sum of the contribution rates of all running parameters from the first parameter to that parameter, which can be expressed as:
[0059] ;
[0060] in, It refers to the first The cumulative contribution rate corresponding to each operating parameter, in If the percentage exceeds a preset threshold, such as 80%, the operating parameters corresponding to all contribution rates involved in the cumulative contribution rate calculation can be used as the target operating parameters. For example, Figure 4 A schematic diagram of the process for determining target operating parameters is shown.
[0061] S220. For each target operating parameter, determine the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval corresponding to the target operating parameter based on historical operating data.
[0062] In this embodiment of the invention, each operating parameter has a corresponding code. After the target operating parameter is determined, it can be uploaded to the embedded system board via a DIP switch according to the code corresponding to the target operating parameter. For example, the code corresponding to phase A voltage is 000000000001, the code corresponding to phase B voltage is 000000000010, the code corresponding to phase C voltage is 000000000100, the code corresponding to phase A current is 000000001000, the code corresponding to phase B current is 000000010000, the code corresponding to phase C current is 000000100000, the code corresponding to active power is 000001000000, the code corresponding to reactive power is 000010000000, and the code corresponding to power factor is 000100000000. Then, for each target operating parameter, the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval can be determined based on historical operating data.
[0063] Optionally, determining the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval corresponding to the target operating parameter based on the historical operating data includes: determining the maximum value, the minimum value, and the median value of the target operating parameter in the historical operating data; generating the first sensitivity analysis interval based on a first preset value and the maximum value, generating the second sensitivity analysis interval based on a second preset value and the minimum value, and generating the third sensitivity analysis interval based on a third preset value and the median value.
[0064] In this embodiment of the invention, the maximum, minimum, and median values of the target operating parameter in historical operating data can be determined first. Then, appropriate values can be selected around the maximum, minimum, and median values to form intervals for sensitivity analysis. Specifically, a first sensitivity analysis interval is generated based on a first preset value and the maximum value; a second sensitivity analysis interval is generated based on a second preset value and the minimum value; and a third sensitivity analysis interval is generated based on a third preset value and the median value. It should be noted that in this embodiment of the invention, the first, second, and third preset values can be the same or different, and can be set by those skilled in the art according to actual circumstances. This embodiment of the invention does not limit the specific settings in this regard.
[0065] S230. Calculate the derivatives of the reliability index in the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval, respectively; wherein, the reliability index is used to measure the operational reliability of the servo motor.
[0066] Among them, the reliability index is used to measure the operational reliability of the servo motor, and can include the servo motor's power loss, efficiency, current imbalance, safety factor, reliability, failure rate, maximum case temperature, etc.
[0067] In this embodiment of the invention, for each target operating parameter, the derivative of the reliability index in the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval can be calculated respectively, that is, the rate of change of the reliability index in each sensitivity analysis interval, so as to identify the sensitivity analysis interval where the parameter change has the greatest impact on reliability.
[0068] S240. The sensitivity analysis interval corresponding to the derivative with the largest value is taken as the sensitivity interval of the target operating parameter.
[0069] In this embodiment of the invention, the sensitivity analysis interval corresponding to the derivative with the largest value can be determined. This means that the rate of change of the reliability index is the largest within this sensitivity analysis interval, i.e., the parameter change has the greatest impact on reliability within this sensitivity analysis interval. In this case, this sensitivity analysis interval can be used as the sensitivity interval of the target operating parameter. For example, Figure 5A schematic diagram of the process for determining a sensitive interval is shown.
[0070] S250: Obtain real-time operating data of the servo motor, and determine whether there is a fault in the servo motor based on the real-time operating data and the sensitive range.
[0071] The technical solution of this invention involves acquiring historical operating data of a servo motor, performing principal component analysis on the operating parameters in the historical operating data to determine the target operating parameters of the servo motor, and for each target operating parameter, determining a first sensitivity analysis interval, a second sensitivity analysis interval, and a third sensitivity analysis interval corresponding to the target operating parameter based on the historical operating data. The derivatives of the reliability index on the first, second, and third sensitivity analysis intervals are calculated respectively; wherein, the reliability index is used to measure the operational reliability of the servo motor; the sensitivity analysis interval corresponding to the largest derivative value is taken as the sensitivity interval of the target operating parameter; real-time operating data of the servo motor is acquired, and the presence of a fault in the servo motor is determined based on the real-time operating data and the sensitivity interval. This technical solution, after determining the target operating parameters by performing principal component analysis on the operating parameters in the historical operating data through a host computer, can achieve sensitivity analysis of the target operating parameters and fault diagnosis of the servo motor through an embedded system board applied to the edge side of the servo motor and a lightweight algorithm. It is suitable for application at the edge of equipment and can significantly reduce the cost of fault diagnosis.
[0072] Example 3
[0073] Figure 6 This is a schematic diagram of a servo motor fault diagnosis device provided in Embodiment 3 of the present invention. Figure 6 As shown, the device includes:
[0074] The parameter determination module 310 is used to acquire historical operating data of the servo motor, perform principal component analysis on the operating parameters in the historical operating data, and determine the target operating parameters of the servo motor; wherein, the principal component analysis is performed by a host computer.
[0075] The interval determination module 320 is used to perform a sensitivity analysis on the target operating parameters for the reliability of the servo motor operation based on the historical operating data, and to determine the sensitive interval of the target operating parameters;
[0076] The fault judgment module 330 is used to acquire the real-time operating data of the servo motor and judge whether the servo motor has a fault based on the real-time operating data and the sensitive range; wherein, the sensitivity analysis and fault judgment are performed by an embedded system board applied to the edge side of the servo motor.
[0077] Optionally, the parameter determination module 310 includes:
[0078] A data matrix construction unit is used to construct a data matrix based on the operating parameters in the historical operating data and to perform standardization processing on the data matrix.
[0079] The target operating parameter determination unit is used to calculate the covariance matrix of the standardized data matrix and determine the target operating parameters of the servo motor based on the covariance matrix.
[0080] Optionally, the target operating parameter determination unit is specifically used for:
[0081] The eigenvalues corresponding to each operating parameter are determined based on the covariance matrix, and the contribution rate of each operating parameter is calculated based on the eigenvalues.
[0082] The operating parameters are arranged in descending order of their feature values, and the cumulative contribution rate of each operating parameter is calculated starting from the first operating parameter; wherein, the cumulative contribution rate of an operating parameter is the sum of the contribution rates of all operating parameters from the first operating parameter to that operating parameter;
[0083] When the cumulative contribution rate exceeds a preset threshold, the operating parameters corresponding to all contribution rates involved in the calculation of the cumulative contribution rate are used as the target operating parameters.
[0084] Optionally, the interval determination module 320 includes:
[0085] The analysis interval determination unit is used to determine, based on the historical operation data, the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval corresponding to each target operation parameter.
[0086] The indicator derivative calculation unit is used to calculate the derivative of the reliability index in the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval, respectively; wherein, the reliability index is used to measure the operational reliability of the servo motor;
[0087] The sensitive interval determination unit is used to determine the sensitivity analysis interval corresponding to the derivative with the largest value as the sensitive interval of the target operating parameter.
[0088] Optionally, the analysis interval determination unit is specifically used for:
[0089] Determine the maximum, minimum, and median values of the target operating parameter in the historical operating data;
[0090] A first sensitivity analysis interval is generated based on a first preset value and the maximum value; a second sensitivity analysis interval is generated based on a second preset value and the minimum value; and a third sensitivity analysis interval is generated based on a third preset value and the median value.
[0091] Optionally, the fault diagnosis module 330 includes:
[0092] The fault determination unit is used to determine the real-time data corresponding to the target operating parameter in the real-time operating data, and to determine whether the real-time data falls within the sensitive range corresponding to the target operating parameter.
[0093] The fault determination unit is used to determine that the servo motor has a fault if the real-time data corresponding to the target operating parameter falls within the sensitive range corresponding to the target operating parameter.
[0094] Optionally, the fault diagnosis module 330 further includes:
[0095] The fault parameter determination unit is used to determine the target operating parameters that the real-time data falls within the sensitive range, and use them as fault operating parameters.
[0096] The fault parameter visualization unit is used to generate an alarm based on the fault operating parameters and to visualize the fault operating parameters on the screen of the embedded system board.
[0097] The servo motor fault diagnosis device provided in this embodiment of the invention can execute the servo motor fault diagnosis method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.
[0098] Example 4
[0099] Figure 7 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.
[0100] like Figure 7As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0101] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0102] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as servo motor fault diagnosis methods.
[0103] In some embodiments, the servo motor fault diagnosis method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the servo motor fault diagnosis method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the servo motor fault diagnosis method by any other suitable means (e.g., by means of firmware).
[0104] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0105] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0106] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0107] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0108] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.
[0109] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.
[0110] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.
[0111] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.
Claims
1. A method for diagnosing servo motor faults, characterized in that, The method includes: Historical operating data of the servo motor is acquired, and principal component analysis is performed on the operating parameters in the historical operating data to determine the target operating parameters of the servo motor; wherein, the principal component analysis is performed through a host computer. Based on the historical operating data, a sensitivity analysis of the target operating parameters is performed on the servo motor's operating reliability to determine the sensitive range of the target operating parameters; The system acquires real-time operating data of the servo motor and determines whether the servo motor has a fault based on the real-time operating data and the sensitive range; wherein the sensitivity analysis and fault determination are performed by an embedded system board applied to the edge side of the servo motor.
2. The method according to claim 1, characterized in that, The step of performing principal component analysis on the operating parameters in the historical operating data to determine the target operating parameters of the servo motor includes: A data matrix is constructed based on the operating parameters in the historical operating data, and the data matrix is then standardized. Calculate the covariance matrix of the standardized data matrix, and determine the target operating parameters of the servo motor based on the covariance matrix.
3. The method according to claim 2, characterized in that, Determining the target operating parameters of the servo motor based on the covariance matrix includes: The eigenvalues corresponding to each operating parameter are determined based on the covariance matrix, and the contribution rate of each operating parameter is calculated based on the eigenvalues. The operating parameters are arranged in descending order of their feature values, and the cumulative contribution rate of each operating parameter is calculated starting from the first operating parameter; wherein, the cumulative contribution rate of an operating parameter is the sum of the contribution rates of all operating parameters from the first operating parameter to that operating parameter; When the cumulative contribution rate exceeds a preset threshold, the operating parameters corresponding to all contribution rates involved in the calculation of the cumulative contribution rate are used as the target operating parameters.
4. The method according to claim 1, characterized in that, The step of performing a sensitivity analysis on the target operating parameters based on the historical operating data for the reliability of the servo motor operation, and determining the sensitive range of the target operating parameters, includes: For each target operating parameter, a first sensitivity analysis interval, a second sensitivity analysis interval, and a third sensitivity analysis interval are determined based on the historical operating data. The derivatives of the reliability index are calculated in the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval, respectively; wherein, the reliability index is used to measure the operational reliability of the servo motor; The sensitivity analysis interval corresponding to the derivative with the largest value is taken as the sensitivity interval of the target operating parameter.
5. The method according to claim 4, characterized in that, The step of determining the first sensitivity analysis interval, the second sensitivity analysis interval, and the third sensitivity analysis interval corresponding to the target operating parameter based on the historical operating data includes: Determine the maximum, minimum, and median values of the target operating parameter in the historical operating data; A first sensitivity analysis interval is generated based on a first preset value and the maximum value; a second sensitivity analysis interval is generated based on a second preset value and the minimum value; and a third sensitivity analysis interval is generated based on a third preset value and the median value.
6. The method according to claim 1, characterized in that, The step of determining whether the servo motor has a fault based on the real-time operating data and the sensitive range includes: Determine the real-time data corresponding to the target operating parameter in the real-time operating data, and determine whether the real-time data falls within the sensitive interval corresponding to the target operating parameter; If the real-time data corresponding to the target operating parameter falls within the sensitive range corresponding to the target operating parameter, it is determined that the servo motor has a fault.
7. The method according to claim 6, characterized in that, After determining that the servo motor has a fault, the method further includes: The target operating parameters that fall within the sensitive range of the real-time data are determined as fault operating parameters; An alarm is triggered based on the fault operating parameters, and the fault operating parameters are displayed visually on the screen of the embedded system board.
8. A servo motor fault diagnosis device, characterized in that, The device includes: The parameter determination module is used to acquire historical operating data of the servo motor, perform principal component analysis on the operating parameters in the historical operating data, and determine the target operating parameters of the servo motor; wherein, the principal component analysis is performed by a host computer. The interval determination module is used to perform sensitivity analysis on the target operating parameters for the reliability of the servo motor operation based on the historical operating data, and to determine the sensitive interval of the target operating parameters; The fault diagnosis module is used to acquire the real-time operating data of the servo motor and determine whether the servo motor has a fault based on the real-time operating data and the sensitive range; wherein, the sensitivity analysis and fault diagnosis are performed by an embedded system board applied to the edge side of the servo motor.
9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the servo motor fault diagnosis method according to any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the servo motor fault diagnosis method according to any one of claims 1-7.