Motor fault detection method and device, electronic equipment and processor

Abstract

The invention discloses a fault detection method and device of a motor, electronic equipment and a processor. The method comprises the steps that electrical waveform information of a motor to be detected is acquired, and the electrical waveform information is used for representing the electrical operation state of the motor; recording the electrical waveform information to obtain recording information, the recording information being triggered by the electrical waveform information in the presence of a target fluctuation event and being used for obtaining the change degree of the electrical operation state before and after the occurrence of the target fluctuation event; converting the electrical waveform information and the wave recording information to obtain the waveform information of the motor group; the motor group waveform information is detected, a detection result is obtained, and the detection result is used for representing whether the motor breaks down or not under the target fluctuation event. The technical problem that fault detection of the motor cannot be effectively carried out is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of online monitoring of high-voltage motors, and in particular to a method, device, electronic equipment and processor for detecting faults of motors. Background Art

[0002] At present, as an important part of the power system, the safe and reliable operation of high-voltage motors is the key to ensure the stable operation of the power system. However, during operation, high-voltage motors are often affected by multiple factors such as electromagnetic, mechanical, and environmental factors, and are prone to multiple faults such as overheating, overcurrent, inverter failure, and three-phase imbalance, which can lead to motor damage or power system failure, causing serious economic losses and safety hazards. Therefore, online monitoring and fault diagnosis of high-voltage motors has become one of the important tasks of power system operation management.

[0003] In the related technologies, the high-voltage motor monitoring system mainly performs fault diagnosis through regular inspections, power outage inspections, offline detection and other methods, but these methods have the disadvantages of low monitoring frequency, poor diagnostic accuracy, and inability to monitor in real time. Therefore, there is a need for an online monitoring system for high-voltage motors based on advanced technologies such as the Internet of Things, big data, and artificial intelligence to improve the accuracy and real-time performance of fault diagnosis, extend the service life of high-voltage motors, and ensure the safe and stable operation of the power system. Therefore, there is still a technical problem that the fault detection of motors cannot be effectively performed.

[0004] Currently, no effective solution has been proposed for the above technical problems. Summary of the invention

[0005] Embodiments of the present invention provide a method, device, electronic device and processor for detecting faults of a motor, so as to at least solve the technical problem that fault detection of a motor cannot be effectively performed.

[0006] According to one aspect of an embodiment of the present invention, a method for detecting a fault of a motor is provided. The method may include: obtaining electrical waveform information of a motor to be detected, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; recording the electrical waveform information to obtain recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change in the electrical operating state before and after the target fluctuation event occurs; converting the electrical waveform information and the recorded information to obtain motor group waveform information; detecting the motor group waveform information to obtain a detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event.

[0007] Optionally, the operating status detection method of a high-voltage motor is applied to an operating status detection system of a high-voltage motor, wherein the operating status detection system includes a motor comprehensive protection and waveform acquisition terminal and a recording and conversion unit, wherein electrical waveform information of the high-voltage motor to be detected is obtained, including: controlling the motor comprehensive protection and waveform acquisition terminal to monitor the electrical operating status of the high-voltage motor, obtaining electrical information, and converting the electrical information into electrical waveform information; the method also includes: controlling the motor comprehensive protection and waveform acquisition terminal to transmit the electrical waveform information to the recording and conversion unit.

[0008] Optionally, the electrical waveform information is recorded to obtain the recorded information, including: in response to the recording and conversion unit receiving the electrical waveform information, controlling the recording and conversion unit to detect the electrical waveform information to obtain a target fluctuation event; controlling the recording and conversion unit to record the waveforms before and after the target fluctuation event occurs to obtain the recorded information.

[0009] Optionally, the operating status detection system also includes a motor status and defect diagnosis management machine, wherein the electrical waveform information and the recorded wave information are converted to obtain the waveform information of the motor group, including: in response to the fact that there are multiple high-voltage motors to be detected, the electrical waveform information and the recorded wave information are time-aligned to obtain the electrical waveform information and the recorded wave information under the same time reference; the electrical waveform information and the recorded wave information under the same time reference from multiple high-voltage motors are integrated to obtain the motor group waveform information; the method also includes: controlling the recorded wave and conversion unit to transmit the motor group waveform information to the motor status and defect diagnosis management machine.

[0010] Optionally, the waveform information of the motor group is detected to obtain a detection result, including: in response to the motor state and defect diagnosis management machine receiving the motor group waveform information, controlling the motor state and defect diagnosis management machine to perform Fourier transform on the motor group waveform information to obtain a spectrum diagram; detecting the spectrum diagram to obtain a detection result; the method also includes: in response to the detection result being a failure of the high-voltage motor under the target fluctuation event, determining the fault type of the fault, wherein the fault type is used to indicate the severity of the fault.

[0011] Optionally, the operating status detection system also includes a main station system, wherein the method further includes: controlling the motor status and defect diagnosis management machine to transmit the fault type and detection result to the main station system.

[0012] Optionally, the method further includes: in response to the master station system receiving the fault type and the detection result, generating a detection report corresponding to the fault type and the detection result, and visually displaying the detection report.

[0013] According to another aspect of the embodiment of the present invention, a motor fault detection device is also provided. The device may include: an acquisition unit, used to acquire electrical waveform information of a motor to be detected, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; a recording unit, used to record the electrical waveform information to obtain recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs; a conversion unit, used to convert the electrical waveform information and the recorded information to obtain motor group waveform information; a detection unit, used to detect the motor group waveform information to obtain a detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event.

[0014] According to another aspect of the embodiments of the present invention, a computer-readable storage medium is also provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method of the embodiments of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a processor is provided, which is used to run a program, wherein the method of the embodiment of the present invention is executed when the program is run.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is further provided. The computer program product includes a computer program, and when the computer program is executed by a processor, the method of the embodiment of the present application is implemented.

[0017] In an embodiment of the present invention, the electrical waveform information of the motor to be detected is obtained, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; the electrical waveform information is recorded to obtain the recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs; the electrical waveform information and the recorded information are converted to obtain the motor group waveform information; the motor group waveform information is detected to obtain the detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event. In this embodiment, through real-time monitoring, intelligent recording, data integration and deep detection, comprehensive, accurate and timely detection of motor faults is achieved, which can not only improve the efficiency and accuracy of fault diagnosis, but also optimize the operation and management of the power system through data analysis, provide a scientific basis for the decision-making of the enterprise, and have significant technical effects and application value. Thereby, the technical effect of effectively detecting the fault of the motor is achieved, and the technical problem of not being able to effectively detect the fault of the motor is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a method for detecting a fault of a motor according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a motor fault detection device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present invention, an embodiment of a method for detecting faults in an electric motor is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flow chart of a motor fault detection method according to an embodiment of the present invention, such as Figure 1 As shown, the method may include the following steps:

[0025] Step S102, obtaining electrical waveform information of the motor to be detected.

[0026] In the technical solution provided in the above step S102 of the present invention, the electrical waveform information is used to indicate the electrical operation state of the motor, and may be motor waveform information. The motor may be a high-voltage motor.

[0027] In this embodiment, if it is necessary to detect a fault of a motor to be detected, the electrical waveform information of the motor can be obtained.

[0028] Optionally, obtaining electrical waveform information of the motor to be tested is a key link in the high-voltage motor online monitoring system.

[0029] Optionally, during the operation of the high-voltage motor, its electrical parameters such as voltage, current, frequency, etc. will change over time to form continuous waveform data. These electrical parameters are collected in real time, and the continuous analog signal is converted into a digital signal to form digital waveform information (electrical waveform information).

[0030] Optionally, the electrical waveform information is not only the instantaneous values ​​of voltage and current, but more importantly the shape and characteristics of the waveform. Waveform anomalies, such as the appearance of peaks, waveform distortion, frequency offset, etc., may indicate that there is a problem with the electrical operation of the motor. For example, the appearance of specific frequency components (harmonics) in the current waveform may indicate an imbalance or electrical connection problem inside the motor; distortion of the voltage waveform may indicate poor power quality or motor overload.

[0031] Optionally, the acquired electrical waveform information is the basis for subsequent fault detection and analysis. The waveform information is recorded and preliminarily processed, such as denoising, filtering, etc., and then the processed waveform information is converted into motor group waveform information, which is further transmitted to the motor status and defect diagnosis management machine for in-depth fault diagnosis. By analyzing and comparing the electrical waveform information, signs of motor failure, such as overload, short circuit, insulation failure, harmonic problems, etc., can be found. The acquisition process of electrical waveform information is continuous and real-time, which can ensure the response speed of the monitoring system and the timeliness of fault detection. For high-voltage motors, any minor electrical anomalies may quickly develop into major faults, so real-time electrical waveform information acquisition and rapid fault detection are the key to ensuring motor operation safety and production continuity.

[0032] In summary, the above process is the data input link in the high-voltage motor online monitoring system. By collecting the electrical waveform information of the motor in real time and continuously, it provides a comprehensive and accurate data basis for subsequent fault detection and status diagnosis. The acquisition and transmission process of electrical waveform information needs to ensure the integrity and real-time nature of the data to ensure the effectiveness and response speed of the monitoring system.

[0033] Step S104, recording the electrical waveform information to obtain recorded waveform information.

[0034] In the technical solution provided in the above step S104 of the present invention, the waveform recording information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs, which can also be called waveform recording data. The target fluctuation event can be an event of violent signal fluctuation, such as an event of violent signal fluctuation caused by a motor failure or abnormality.

[0035] In this embodiment, after obtaining the electrical waveform information of the motor to be detected, the electrical waveform information can be recorded to obtain recorded information. The above steps are key steps for fault detection and status analysis in the high-voltage motor online monitoring system.

[0036] Optionally, the wave recording does not continuously record all electrical waveform information, but has an intelligent trigger mechanism. This mechanism starts the wave recording based on specific conditions or events. For example, when the monitored electrical waveform fluctuates abnormally or suddenly changes, the target fluctuation event is triggered, and the system automatically starts the wave recording function to record the electrical waveform information before and after the event. Such abnormal fluctuations may be caused by factors such as internal faults of the motor, external interference, and power grid fluctuations, such as overload, short circuit, voltage mutation, etc.

[0037] Optionally, the waveform information is essentially a subset of the electrical waveform information, which pays special attention to the changes in electrical parameters before and after the target fluctuation event occurs. The waveform information will include electrical waveform data for a period of time before the target fluctuation event occurs, at the moment of the event, and for a period of time after the event occurs. These data record the details of the changes in the electrical state of the motor, which is crucial for analyzing the cause of the fault, determining the type of fault, and assessing the severity of the fault.

[0038] Optionally, the acquisition of recorded information is of great value for fault diagnosis and preventive maintenance. When the target fluctuation event occurs, the recorded information can capture the electrical state at the moment of the fault. By analyzing this information, the type of fault can be determined, such as whether it is overload, short circuit, grid voltage mutation, etc. In addition, the recorded information can also help engineers analyze the process of the fault, determine the time point of the fault, and the scope of the fault, so as to take corresponding maintenance measures to prevent further deterioration of the fault. The recorded information will be further processed to convert the electrical waveform information into motor group waveform information, that is, pre-processing such as data formatting and label addition will be performed to make it more suitable for subsequent analysis and diagnosis. The processed information will be uploaded to the motor status and defect diagnosis management machine for more in-depth analysis and fault diagnosis.

[0039] In summary, when an abnormality is detected in the electrical state of the motor, the key electrical waveform data is recorded through the waveform recording function to provide detailed and accurate information for subsequent fault analysis and diagnosis. The acquisition of waveform information is based on the intelligent analysis of electrical waveform information and the event triggering mechanism. It can capture the instantaneous state of the fault, which plays an important role in the timely detection and handling of faults.

[0040] Step S106, converting the electrical waveform information and the recorded waveform information to obtain the motor group waveform information.

[0041] In the technical solution of step S106 of the present invention, after recording and broadcasting the electrical waveform information to obtain the recorded waveform information, the electrical waveform information and the recorded waveform information can be converted to obtain the motor group waveform information. The above process is a key step in data processing and integration in the high-voltage motor online monitoring system.

[0042] Optionally, the waveform recording and conversion unit integrates the received electrical waveform information (i.e., waveform data during normal operation) and the waveform recording information (i.e., waveform data before and after the target fluctuation event occurs). The purpose of the integration is to associate the data of a single motor with the data of other motors or power grids to form waveform information of the motor group, so as to obtain more comprehensive and systematic power system status information.

[0043] For example, the conversion process may involve changes in data formats, data scalarization, data preprocessing (such as filtering, denoising, smoothing, etc.), and data structuring. Electrical waveform information usually exists in the form of a time series, which may contain voltage and current values ​​of multiple sampling points, and the converted motor group waveform information may be more structured, which is convenient for subsequent analysis and processing. For example, through conversion, the electrical waveform information and the recorded information can be sorted in chronological order, and the data of different motors can be associated to form a unified data format, which is convenient for the master station system to perform data analysis.

[0044] Optionally, during the conversion process, the electrical waveform information and the recorded information may be temporally correlated to analyze the impact of the target fluctuation event on the motor group. For example, by comparing the electrical waveform information and the recorded information, it can be determined whether the target fluctuation event has affected other motors, as well as the extent and scope of the impact. This correlation analysis can help determine whether the motor failure is an independent event or a manifestation of an overall problem in the power system. During the conversion process, the data may also need to be standardized or normalized to eliminate data differences between different motors or different acquisition devices to ensure the accuracy and consistency of subsequent analysis. Based on the converted motor group waveform information, more advanced analysis and fault diagnosis are performed.

[0045] Step S108, detecting the waveform information of the motor group to obtain the detection result.

[0046] In the technical solution provided in the above step S108 of the present invention, the detection result is used to indicate whether the motor fails under the target fluctuation event, and may also be referred to as a diagnosis result or diagnosis result data.

[0047] In this embodiment, after converting the electrical waveform information and the recorded waveform information to obtain the motor group waveform information, the motor group waveform information can be detected to obtain the detection result. Detecting the motor group waveform information to obtain the detection result is the core analysis and diagnosis step in the entire high-voltage motor online monitoring system.

[0048] Optionally, the motor status and defect diagnosis management machine receives the converted motor group waveform information and uses a preset fault detection algorithm or model to perform in-depth analysis on the waveform information. This analysis may include harmonic analysis, spectrum analysis, trend analysis, correlation analysis, etc., aiming to find patterns, trends and anomalies from the waveform data. These analysis results will be used to determine whether the motor has a fault, as well as the type and location of the fault.

[0049] Optionally, based on the analysis results, the system can perform fault detection to identify whether the electrical parameters of the motor are abnormal under the target fluctuation event, such as sudden changes in voltage or current, the presence of harmonics, unstable frequency, etc., which may indicate that the motor is faulty. If a fault is detected, the system will further diagnose and determine the specific type of fault, such as overload, short circuit, insulation fault, mechanical imbalance, bearing fault, etc., as well as the severity of the fault.

[0050] Optionally, the diagnosis result will include information such as whether the motor is faulty, the specific type of fault, the severity of the fault and the possible fault location. This information is presented in the form of test results, which can be a text report, a data file or a graphical fault diagnosis result.

[0051] Optionally, the motor status and defect diagnosis management machine uploads the generated test results to the main station system, which visualizes the test results, generates daily reports, monthly reports and diagnostic reports, and provides them to maintenance personnel or decision makers. These reports can display the current motor operation status, historical fault records, fault prediction trends, etc., to help operation and maintenance personnel take timely actions to prevent the expansion of faults, and also provide data support for the company's equipment maintenance and production scheduling. By continuously analyzing the waveform information of the motor group, the above method can also be used for predictive maintenance, that is, potential problems can be identified through subtle changes in the waveform before the fault occurs, and measures can be taken in advance to avoid major faults, reduce unplanned downtime, and improve production efficiency. The test results can not only be used for fault detection and diagnosis, but also for optimizing the operation of the system, such as adjusting the load distribution of the power system, optimizing the operating parameters of the motor, etc., to reduce the risk of possible future failures.

[0052] In the embodiment of the present application, detailed detection results are generated through in-depth analysis and detection of the waveform information of the motor group, which are used to determine the fault state of the motor under the target fluctuation event. The above method not only relies on advanced data processing and analysis technology, but also combines theoretical knowledge and experience of motor operation, which is the core of realizing online monitoring and fault diagnosis of motors. The accuracy and timeliness of the detection results are of great significance to improving the operating efficiency of the power system, reducing maintenance costs and ensuring production safety.

[0053] In the above steps S102 to S108 of the present application, the electrical waveform information of the motor to be detected is obtained, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; the electrical waveform information is recorded to obtain the recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs; the electrical waveform information and the recorded information are converted to obtain the motor group waveform information; the motor group waveform information is detected to obtain the detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event. In this embodiment, through real-time monitoring, intelligent recording, data integration and deep detection, comprehensive, accurate and timely detection of motor faults is achieved, which can not only improve the efficiency and accuracy of fault diagnosis, but also optimize the operation and management of the power system through data analysis, provide a scientific basis for the decision-making of the enterprise, and have significant technical effects and application value. Thus, the technical effect of effectively detecting the fault of the motor is achieved, and the technical problem of not being able to effectively detect the fault of the motor is solved.

[0054] The above method of this embodiment is further introduced below.

[0055] As an optional implementation mode, the motor operation status detection method is applied to the motor operation status detection system, wherein the operation status detection system includes a motor comprehensive protection and waveform acquisition terminal and a recording and conversion unit, wherein step S102, obtaining the electrical waveform information of the motor to be detected, includes: controlling the motor comprehensive protection and waveform acquisition terminal, monitoring the electrical operation status of the motor, obtaining electrical information, and converting the electrical information into electrical waveform information; the method also includes: controlling the motor comprehensive protection and waveform acquisition terminal, transmitting the electrical waveform information to the recording and conversion unit.

[0056] In this embodiment, in the process of obtaining the electrical waveform information of the motor to be detected, the motor comprehensive protection and waveform acquisition terminal in the motor operation state detection system can be controlled to detect the electrical operation state of the motor, obtain electrical information, and convert the electrical information into electrical waveform information. The motor comprehensive protection and waveform acquisition terminal can also be controlled to transmit the electrical waveform information to the recording and conversion unit. Among them, the motor operation state detection method is applied to the motor operation state detection system. The operation state detection system includes a motor comprehensive protection and waveform acquisition terminal and a recording and conversion unit.

[0057] Optionally, the electrical operating state of the motor is monitored by controlling the motor comprehensive protection and waveform acquisition terminal. In the above method, the motor comprehensive protection and waveform acquisition terminal continuously monitors the electrical parameters of the motor, such as voltage, current, frequency, power, etc., through built-in sensors and data acquisition modules. These electrical parameters are recorded in numerical form to form preliminary electrical information. Subsequently, the electrical information is converted into electrical waveform information, that is, the changing trend of the electrical parameters is presented in the form of a time series, which is convenient for subsequent analysis and processing of the waveform. The conversion process of waveform information may involve data preprocessing, such as filtering, denoising, smoothing, etc., to eliminate interference and improve data quality.

[0058] Optionally, after the electrical waveform information is generated, the motor comprehensive protection and waveform acquisition terminal is controlled to transmit this information to the recording and conversion unit. Data transmission is usually completed through a high-speed RS485 interface to ensure the real-time and accuracy of data transmission. In the recording and conversion unit, the electrical waveform information will be further processed, including but not limited to data format conversion, anomaly detection, data storage, etc., to prepare for subsequent recording and status analysis.

[0059] Optionally, the motor comprehensive protection and waveform acquisition terminal is controlled to collect and transmit electrical information, which reflects the intelligent control and automation capabilities in the system design. Through the preset control strategy or algorithm, the system can automatically start data acquisition without manual intervention, ensuring the continuity and timeliness of data acquisition. In addition, the automatic transmission of data reduces the delay of data processing and improves the response speed of the system.

[0060] In the embodiment of the present application, the cooperation mechanism between different components in the motor operation status detection system. The motor comprehensive protection and waveform acquisition terminal is the front end of data acquisition, and the recording and conversion unit is the intermediate link of data processing. The data transmission and processing flow design between the two ensures the overall operation efficiency and data accuracy of the system. This system integration method enables each component to give full play to its function and jointly complete the comprehensive detection of the motor operation status.

[0061] In summary, by controlling the motor comprehensive protection and waveform acquisition terminal to collect and convert electrical information, as well as transmit electrical waveform information, a high-quality, real-time data foundation is provided for motor operation status detection. This process reflects the automation, intelligence and integration characteristics of the system, and provides key support for subsequent fault detection and diagnosis, data conversion and system optimization. Through this precise data acquisition and transmission mechanism, the system can more accurately monitor the electrical status of the motor, promptly detect potential fault risks, and improve the operating safety and efficiency of the motor.

[0062] As an optional implementation method, step S104, recording the electrical waveform information to obtain the recorded information, includes: in response to the recording and conversion unit receiving the electrical waveform information, controlling the recording and conversion unit to detect the electrical waveform information to obtain the target fluctuation event; controlling the recording and conversion unit to record the waveforms before and after the target fluctuation event occurs to obtain the recorded information.

[0063] In this embodiment, after recording the electrical waveform information to obtain the recorded information, the recording and conversion unit can be controlled to detect the electrical waveform information to obtain the target fluctuation event. The recording and conversion unit is controlled to record the waveform before and after the target fluctuation event occurs to obtain the recorded information.

[0064] Optionally, after receiving the electrical waveform information transmitted from the motor comprehensive protection and waveform acquisition terminal, the recording and conversion unit first performs real-time event detection. This process may include the real-time operation of an algorithm to identify abnormal fluctuations or mutations in the electrical waveform information, which may be caused by internal faults in the motor, external grid disturbances, or improper operation. The detection of target fluctuation events is usually based on threshold comparison, pattern matching, or data mining algorithms. For example, if the monitored current suddenly increases by more than a preset threshold, or the voltage drops abnormally, it may be regarded as a target fluctuation event, triggering subsequent recording operations.

[0065] Optionally, once the target fluctuation event is detected, the recording and conversion unit will immediately start the recording function to record the electrical waveform information before and after the event. The recording operation usually starts at the moment the event is detected and lasts for a certain period of time to capture the complete event process and subsequent recovery status. The recording data includes the normal operating waveform before the event (usually a few seconds to a few minutes), the abnormal waveform when the event occurs, and the recovery waveform after the event, which provides rich information for subsequent fault analysis.

[0066] Optionally, the recording and conversion unit may adopt an intelligent recording strategy when performing the recording operation, that is, dynamically adjust the duration, frequency and range of the recording according to the type and severity of the target fluctuation event. For example, for a slight voltage fluctuation, only a few seconds of data may be recorded; while for a serious short circuit fault, it may be necessary to record the waveform for a longer time to capture the entire process of the fault. Automatically detecting the target fluctuation event and starting the recording reflects the intelligent and automated characteristics of the system. This automation capability ensures that when an event occurs, the system can respond immediately and capture key data, avoiding delays and omissions in manual intervention, and improving the timeliness and accuracy of fault detection.

[0067] In the embodiment of the present invention, the event detection and waveform recording of the recording and conversion unit realizes the instant response to the motor operating status and the accurate recording of key data. This process not only relies on advanced data analysis and automation technology, but also reflects the intelligent control and optimization strategy in system design, which is a key step to ensure that the high-voltage motor online monitoring system can detect and diagnose faults in a timely and accurate manner. Through the application of intelligent recording strategies, the system can process data more efficiently and provide strong support for fault analysis and preventive maintenance.

[0068] As an optional implementation method, the operating status detection system also includes a motor status and defect diagnosis management machine, wherein step S106, converts the electrical waveform information and the recorded wave information to obtain the motor group waveform information, including: in response to the fact that there are multiple motors to be detected, time-aligning the electrical waveform information and the recorded wave information to obtain the electrical waveform information and the recorded wave information under the same time reference; integrating the electrical waveform information and the recorded wave information under the same time reference from multiple motors to obtain the motor group waveform information; the method also includes: controlling the recorded wave and conversion unit to transmit the motor group waveform information to the motor status and defect diagnosis management machine.

[0069] In this embodiment, in the process of converting the electrical waveform information and the recording information to obtain the motor group waveform information, if there are multiple motors to be detected, the electrical waveform information and the recording information can be time-aligned to obtain the electrical waveform information and the recording information under the same time reference, and then the motor waveform information can be integrated. The recording and conversion unit can be controlled to transmit the motor group waveform information to the motor state and defect diagnosis management machine. Among them, the operation state detection system also includes a motor state and defect diagnosis management machine.

[0070] Optionally, when there are multiple motors to monitor, the electrical waveform information and recording information generated by each motor may have different timestamps due to differences in sensor startup time, data transmission delays, or inconsistent system clocks. The purpose of time alignment processing is to adjust the data from different motors to the same time base to ensure that the comparison and analysis of the data is accurate in time. This is usually achieved by methods such as timestamp correction, data interpolation or extrapolation to eliminate time deviations.

[0071] Optionally, after time alignment, the electrical waveform information and recorded waveform information from multiple motors are integrated into motor group waveform information. This integration process may include data aggregation, classification, labeling, etc. to form a unified data view for subsequent analysis and diagnosis. The motor group waveform information not only contains the operating status of a single motor, but also reflects the mutual influence between the motor groups and the overall status of the power system through comparison and analysis.

[0072] Optionally, the integrated motor group waveform information is controlled and transmitted to the motor status and defect diagnosis management machine. This transmission process is usually completed through a high-speed, stable network connection (such as an Ethernet connection with an RJ45 interface) to ensure the real-time and integrity of the data. As the center of data management and analysis, the motor status and defect diagnosis management machine further stores, analyzes and manages the received data and generates reports that can be used for fault diagnosis and status evaluation.

[0073] Optionally, the motor status and defect diagnosis management machine can perform system-level analysis and diagnosis using the motor group waveform information. It can identify abnormal or fault modes of the system by comparing the responses of different motors under target fluctuation events. For example, if all motors show similar current fluctuations when the grid voltage suddenly drops, it may indicate that this is a systemic grid problem rather than a single motor failure. This system-level analysis helps to locate the problem more accurately and optimize the system maintenance strategy. By analyzing the waveform information of the motor group, the motor status and defect diagnosis management machine can identify specific fault modes, such as overload, short circuit, harmonic interference, etc., which may be difficult to detect in a single motor, but are more obvious in the motor group. Fault pattern recognition is an algorithm based on deep learning, machine learning or expert system, which can automatically analyze waveform data, extract features, and perform pattern matching. By integrating and analyzing the waveform information of the motor group, the motor status and defect diagnosis management machine can provide insights into the entire power system, including load distribution, power quality, equipment efficiency, etc. This insight helps to optimize the performance of the system by adjusting operating parameters such as frequency, voltage, load distribution, etc. to reduce the risk of failure and improve production efficiency. Using the waveform information of the motor group, the system can also perform predictive maintenance, that is, by analyzing the trends and patterns of the waveform data before a failure occurs, it can predict possible failures and take preventive measures in advance. This maintenance method can significantly reduce unplanned downtime, reduce maintenance costs, and improve equipment reliability and availability.

[0074] In the embodiment of the present invention, through time alignment processing, waveform information integration and data transmission to the motor status and defect diagnosis management machine, a comprehensive, system-level fault detection and status assessment capability is provided for the high-voltage motor online monitoring system. This process not only relies on data processing and analysis technology, but also reflects the intelligent and automated characteristics in system design, which plays an important role in improving the operational safety and efficiency of the power system.

[0075] As an optional implementation method, step S108, detects the waveform information of the motor group to obtain a detection result, including: in response to the motor status and defect diagnosis management machine receiving the motor group waveform information, controlling the motor status and defect diagnosis management machine to perform Fourier transform on the motor group waveform information to obtain a spectrum diagram; detecting the spectrum diagram to obtain a detection result; the method also includes: in response to the detection result being a motor failure under a target fluctuation event, determining the fault type of the fault, wherein the fault type is used to indicate the severity of the fault.

[0076] In this embodiment, in the process of detecting the waveform information of the motor group and obtaining the detection result, the motor state and defect diagnosis management machine can be controlled to perform Fourier transformation on the waveform information of the motor group to obtain a spectrum diagram; and the spectrum diagram can be detected to obtain the detection result. When the detection result is that the motor fails under the target fluctuation event, the fault type can be determined, wherein the fault type can be used to indicate the severity of the fault.

[0077] Optionally, after the motor status and defect diagnosis management machine receives the waveform information of the motor group, it first uses Fourier transform to process the waveform data and convert it into a spectrum diagram. Fourier transform is a mathematical tool that converts time domain signals into frequency domain signals. It can decompose complex waveform signals into superpositions of different frequency components, thereby revealing the frequency characteristics of the signal. In motor monitoring, Fourier transform can help identify abnormal frequency components in the operating state of the motor, such as harmonics, vibration frequencies, etc. These frequency components are often associated with specific fault types. After obtaining the spectrum diagram, the motor status and defect diagnosis management machine will perform spectrum diagram analysis, which is the core step of fault detection.

[0078] For example, look for abnormally increased frequency components in the spectrum graph. These components may indicate mechanical or electrical problems inside the motor, such as bearing failure, rotor imbalance, winding short circuit, etc. Compare the amplitudes of different frequency components. Abnormally increased frequency components usually indicate the severity of the fault. For example, for a bearing fault, a significant increase in the amplitude of a specific frequency component may mean increased bearing wear. Observe the changing trend of the frequency components over time. The continuously increasing frequency components may indicate a worsening trend of the fault, and maintenance measures need to be taken in advance.

[0079] Optionally, the specific type of fault can be determined by analyzing the spectrum diagram, which is a key step in fault diagnosis. Fault types may include mechanical faults (such as bearing wear, rotor imbalance), electrical faults (such as overload, short circuit, insulation aging), systemic faults (such as power grid fluctuations, uneven load), etc. Determining the fault type helps to further assess the severity of the fault and guide maintenance personnel to adopt appropriate maintenance strategies. Once the fault type is determined, the system can evaluate the severity of the fault based on the amplitude of the fault frequency component, the change trend, and the comparison results with other motors. For example, if the amplitude of the bearing fault frequency component is significantly higher than the normal range and continues to increase over time, it may indicate that the bearing is seriously damaged and needs to be replaced immediately; if the amplitude of the electrical fault frequency component is small and the change trend is stable, it may mean that the fault is in the early stage and can be controlled by adjusting the operating parameters.

[0080] Optionally, the detection results, including the fault type and severity, will be uploaded to the main station system for generating detailed fault reports and maintenance recommendations. This data support is crucial for decision makers, who can formulate reasonable maintenance plans and adjust production strategies based on the information in the report to reduce the risk of failure and improve equipment reliability and production efficiency. Since the waveform information of the motor group is analyzed, the motor status and defect diagnosis management machine can also perform system-level fault diagnosis and identify fault modes that may affect the operation of the entire system. For example, if multiple motors show similar abnormal frequency components in the spectrum diagram, it may mean that there are general problems in the power system, which need to be investigated and optimized at the system level.

[0081] In the embodiment of the present invention, through Fourier transformation, spectrum analysis and fault type determination, in-depth detection and intelligent diagnosis of the operating status of the motor group are achieved. This process not only relies on data processing and analysis technology, but also reflects the intelligent and automated characteristics in system design, which is of great significance for improving the operational safety of the power system, reducing unplanned downtime and optimizing maintenance strategies. Through system-level fault diagnosis, potential systemic problems can also be identified and handled in advance, further improving the stability of the power system and the operating efficiency of the motor.

[0082] As an optional embodiment, the operating status detection system also includes a main station system, wherein the method further includes: controlling the motor status and defect diagnosis management machine to transmit the fault type and detection result to the main station system.

[0083] In this embodiment, the operating status detection system may further include a master station system, and the motor status and defect management machine may be controlled to transmit the fault type and detection result to the master station system.

[0084] Optionally, the operation status detection system is further expanded to include a master station system to achieve higher-level data management, generation and visualization of fault diagnosis reports, and system-level decision support. Controlling the motor status and defect diagnosis management machine to transmit the fault type and detection results to the master station system is a key step in achieving this function.

[0085] Optionally, after the motor status and defect diagnosis management machine completes the in-depth analysis of the motor group waveform information, it transmits the identified fault type and the corresponding test results to the master station system through the network. This transmission process requires high accuracy and real-time performance of the data to ensure that the master station system can receive the latest fault information in a timely manner. After receiving the data, the master station system performs integrated processing, which may include the unification of data format, data storage, data backup, etc., to ensure the integrity and availability of the data.

[0086] As an optional implementation manner, the method further includes: in response to the master station system receiving the fault type and the detection result, generating a detection report corresponding to the fault type and the detection result, and visually displaying the detection report.

[0087] In this embodiment, when the master station system receives the fault type and the detection result, it can generate a corresponding detection report and perform a visual display, wherein the detection report can also be called a fault diagnosis report.

[0088] Optionally, the master station system generates a detailed fault diagnosis report using the received fault type and detection results. The report includes not only the specific information of the fault, such as fault type, fault severity, fault occurrence time, etc., but also the possible cause of the fault, recommended maintenance strategy, historical fault records, and trend analysis. The generation of this report is based on data analysis and visualization technology, which can transform complex technical information into an intuitive and easy-to-understand form, making it easier for non-professional operators to understand and operate.

[0089] Optionally, the master station system provides a visual human-computer interaction interface to display the fault type and detection results in the form of charts, curves or maps. Through the real-time updated display interface, the operator can intuitively see the operating status of each motor in the system and the distribution of faults. This visual display not only improves the transparency of information, but also enhances the operator's real-time perception of the system's operating status, which helps to respond quickly and reduce the impact of faults.

[0090] Optionally, the master station system provides data support and decision suggestions to maintenance personnel and decision makers based on the fault type and detection results. For example, if a motor frequently has bearing failures, the system may recommend preventive replacement of the bearings; if multiple motors show abnormalities at a specific frequency, the system may prompt to check the grid quality or load distribution. This decision support can optimize maintenance plans, reduce maintenance costs, and improve production efficiency.

[0091] Optionally, the master station system can store and manage historical fault data. By comparing and analyzing historical data, the fault patterns and trends can be identified, which is important for predicting possible future faults and optimizing the operating parameters of the equipment. Historical data analysis can also help the system learn and optimize fault detection algorithms, improving the accuracy and efficiency of fault diagnosis.

[0092] Optionally, the master station system can evaluate the overall performance of the power system by comprehensively analyzing the fault type, detection results, and the operating status of the motor group, and put forward optimization suggestions, such as adjusting power supply, optimizing load distribution, improving power quality, etc. This system-level optimization can improve the operating efficiency of the power system, reduce energy waste, and improve the operating safety of the motor.

[0093] Optionally, the master station system usually has remote monitoring and control capabilities, which means that maintenance personnel or decision makers can access the system's real-time data and fault reports from a remote location to handle faults and adjust the system. This remote capability improves maintenance flexibility, reduces maintenance costs, and enhances the system's ability to respond to emergencies.

[0094] In summary, transmitting fault types and detection results to the master station system not only realizes advanced data management and comprehensive fault diagnosis, but also provides a key data foundation for system optimization and decision support. Through the data integration, report generation, visualization and decision support functions of the master station system, the operation status detection system can more effectively monitor and manage the operation status of the motor group, improve the stability and production efficiency of the power system, and reduce maintenance costs.

[0095] In an embodiment of the present invention, the electrical waveform information of the motor to be detected is obtained, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; the electrical waveform information is recorded to obtain the recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs; the electrical waveform information and the recorded information are converted to obtain the motor group waveform information; the motor group waveform information is detected to obtain the detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event. In this embodiment, through real-time monitoring, intelligent recording, data integration and deep detection, comprehensive, accurate and timely detection of motor faults is achieved, which can not only improve the efficiency and accuracy of fault diagnosis, but also optimize the operation and management of the power system through data analysis, provide a scientific basis for the decision-making of the enterprise, and have significant technical effects and application value. Thereby, the technical effect of effectively detecting the fault of the motor is achieved, and the technical problem of not being able to effectively detect the fault of the motor is solved.

[0096] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0097] At present, the high-voltage motor monitoring system can mainly include an offline monitoring system, an online monitoring system, a motor protection device and a motor diagnostic system. Specifically, the offline monitoring system is mainly used to check the operating status of the motor regularly or periodically. It needs to be performed when the motor is stopped, so it cannot provide real-time operating data of the motor, nor can it detect and handle motor faults in time. The online monitoring system can collect the operating data of the motor in real time, but it mainly focuses on the monitoring of the electrical parameters of the motor (such as voltage, current, frequency, etc.), and has weak monitoring capabilities for the mechanical state of the motor (such as bearings, rotors, etc.). The motor protection device is mainly used to prevent motor overload, short circuit, overheating and other faults, but its state monitoring and fault diagnosis capabilities of the motor are weak. The motor diagnostic system is mainly used for the diagnosis and prediction of motor faults, but it needs to rely on professional diagnostic personnel and complex diagnostic equipment, and cannot achieve online and automatic monitoring and diagnosis of motors.

[0098] High-voltage motors are widely used in the industrial field, and their operating status directly affects the production efficiency of enterprises. Therefore, real-time online monitoring of high-voltage motors is of great practical significance. However, the above-mentioned monitoring systems can often only provide a single protection or measurement and control function, which cannot meet the needs of comprehensive monitoring of motors. Some need to be performed when the motor is shut down, and cannot provide real-time operating data, and cannot detect and handle motor faults in time. The present invention can collect and process the operating data of the motor in real time through an online monitoring system, and detect and handle motor faults in time. The motor monitoring system in the above-mentioned related technologies mainly focuses on the monitoring of the electrical parameters of the motor, and has weak monitoring capabilities for the mechanical state of the motor. It is necessary to rely on professional diagnostic personnel and complex diagnostic equipment, and it is impossible to achieve online, automatic monitoring and diagnosis of the motor.

[0099] Therefore, the above method still has the technical problem of being unable to effectively perform fault detection of the motor.

[0100] Compared with the related art, the embodiment of the present invention proposes an online monitoring system for high-voltage motors, which integrates functions such as motor comprehensive protection, waveform acquisition, waveform recording conversion, state diagnosis and data visualization, and can monitor and diagnose the operating status of the motor in real time and accurately, improve the operating efficiency and safety of the motor, and meet the needs of industrial production. The present invention can comprehensively monitor and diagnose the electrical and mechanical states of the motor through the motor state and defect diagnosis management machine. Through the integrated system design, online and automated monitoring and diagnosis of the motor can be achieved. Thereby achieving the technical effect of effectively performing motor fault detection, and solving the technical problem of being unable to effectively perform motor fault detection.

[0101] The embodiments of the present invention are further described below.

[0102] In an embodiment of the present invention, a high-voltage motor online monitoring system is provided, which consists of a motor comprehensive protection and waveform acquisition terminal, a waveform recording and conversion unit, a motor status and defect diagnosis management machine and a master station system.

[0103] Optionally, the motor comprehensive protection and waveform acquisition terminal provides complete protection and measurement and control functions, provides high-frequency and high-precision acquisition of motor electrical information, and transmits it to the recording and conversion unit via high-speed RS485.

[0104] Optionally, the recording and conversion unit receives and records the motor waveform information from the motor comprehensive protection and waveform acquisition terminal, converts the motor waveform information and the recorded data into motor group waveform information, and sends it to the motor status and defect diagnosis management machine via RJ45.

[0105] Optionally, the motor status and defect diagnosis management machine receives the motor group waveform information sent from the recording and conversion unit, diagnoses the motor's mechanical and electrical defects, and uploads the monitoring and diagnosis result information to the main station system.

[0106] Perform fast Fourier transform on the collected current data to obtain the current spectrum. Analyze the specific frequency components in the current spectrum to diagnose the fault type of the motor. The severity of the fault can usually be evaluated by the amplitude of the characteristic frequency components.

[0107] Optionally, the master station system receives and visually displays the monitoring and diagnosis result data sent from the motor diagnosis and defect diagnosis management machine, generates daily, monthly and diagnostic reports to provide data support for motor diagnosis and maintenance, realizes visual human-computer interaction, and supports historical events, historical curve queries, etc.

[0108] In an embodiment of the present invention, through the above-mentioned settings, the present invention can monitor the operating status of the high-voltage motor in real time and accurately, promptly discover and diagnose the mechanical and electrical defects of the motor, improve the operating efficiency and safety of the motor, and meet the needs of modern industrial production.

[0109] In this embodiment, the monitoring system can comprehensively monitor and diagnose the electrical and mechanical status of the motor, thereby improving the accuracy of fault diagnosis. The above-mentioned monitoring system can realize online, automated monitoring and diagnosis of the motor, reduce the reliance on professional diagnostic personnel and complex diagnostic equipment, and reduce operating costs. The master station system can realize the visualization display and human-computer interaction of the motor monitoring data, improve the convenience and efficiency of operation, and enable the operator to understand the operating status and possible faults of the motor more intuitively and quickly. Through real-time, comprehensive, and automatic monitoring and diagnosis, the present invention can timely detect and handle motor faults, significantly improving the operational safety of the motor. Through real-time monitoring and diagnosis of the motor status, the present invention can help operation and maintenance personnel locate problems more accurately, improve maintenance efficiency, and reduce downtime.

[0110] Optionally, the motor status and defect diagnosis management machine includes status evaluation and fault diagnosis algorithms or programs that can accurately evaluate the operating status of the motor and diagnose possible faults. The design and implementation of the overall system, including the configuration and connection methods of each component, to achieve real-time, comprehensive, automated, and visual online monitoring and diagnosis of the motor.

[0111] In an embodiment of the present invention, the electrical waveform information of the motor to be detected is obtained, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; the electrical waveform information is recorded to obtain the recorded information, wherein the recorded information is triggered by the electrical waveform information in the presence of a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs; the electrical waveform information and the recorded information are converted to obtain the motor group waveform information; the motor group waveform information is detected to obtain the detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event. In this embodiment, through real-time monitoring, intelligent recording, data integration and deep detection, comprehensive, accurate and timely detection of motor faults is achieved, which can not only improve the efficiency and accuracy of fault diagnosis, but also optimize the operation and management of the power system through data analysis, provide a scientific basis for the decision-making of the enterprise, and have significant technical effects and application value. Thereby, the technical effect of effectively detecting the fault of the motor is achieved, and the technical problem of not being able to effectively detect the fault of the motor is solved.

[0112] According to an embodiment of the present invention, a motor fault detection device is also provided. It should be noted that the motor fault detection device can be used to execute the motor fault detection method in the above embodiment.

[0113] Figure 2 Schematic diagram of a motor fault detection device according to an embodiment of the present invention. Figure 2 As shown, the motor fault detection device 200 may include: an acquisition unit 202 , a wave recording unit 204 , a conversion unit 206 and a detection unit 208 .

[0114] The acquisition unit 202 is used to acquire electrical waveform information of the motor to be detected, wherein the electrical waveform information is used to represent the electrical operating state of the motor.

[0115] The recording unit 204 is used to record the electrical waveform information to obtain recorded information, wherein the recorded information is triggered by the electrical waveform information when there is a target fluctuation event, and is used to obtain the degree of change of the electrical operating state before and after the target fluctuation event occurs.

[0116] The conversion unit 206 is used to convert the electrical waveform information and the recorded waveform information to obtain the motor group waveform information.

[0117] The detection unit 208 is used to detect the waveform information of the motor group to obtain a detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event.

[0118] In the embodiment of the present invention, the electrical waveform information of the motor to be detected is obtained by the acquisition unit 202, wherein the electrical waveform information is used to represent the electrical operation state of the motor; the electrical waveform information is recorded by the recording unit 204 to obtain the recorded waveform information; the electrical waveform information and the recorded waveform information are converted by the conversion unit 206 to obtain the motor group waveform information; the motor group waveform information is detected by the detection unit 208 to obtain the detection result. Thus, the technical effect of effectively performing motor fault detection is achieved, and the technical problem of being unable to effectively perform motor fault detection is solved.

[0119] According to an embodiment of the present invention, a computer-readable storage medium is further provided. The storage medium includes a stored program, wherein the program executes the motor fault detection method in the above embodiment.

[0120] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the motor fault detection method in the above embodiment is executed when the program is run.

[0121] The embodiment of the present application further provides a computer program product. Optionally, in the present embodiment, the computer program product may include a computer program, and when the computer program is executed by a processor, the motor fault detection method of the embodiment of the present application is implemented.

[0122] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0125] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (RandomAccess Memory, referred to as RAM), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0127] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting a fault of an electric motor, characterized in that: include: Acquiring electrical waveform information of the motor to be detected, wherein the electrical waveform information is used to indicate the electrical operating state of the motor; Recording the electrical waveform information to obtain recorded information, wherein the recorded information is triggered by the electrical waveform information when a target fluctuation event occurs, and is used to obtain a degree of change in the electrical operating state before and after the target fluctuation event occurs; Converting the electrical waveform information and the recorded waveform information to obtain the motor group waveform information; The waveform information of the motor group is detected to obtain a detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event.

2. The method according to claim 1, characterized in that The motor operation state detection method is applied to the motor operation state detection system, wherein the motor operation state detection system includes a motor comprehensive protection and waveform acquisition terminal and a wave recording and conversion unit, wherein obtaining electrical waveform information of the motor to be detected includes: Controlling the motor comprehensive protection and waveform acquisition terminal to monitor the electrical operation state of the motor, obtain electrical information, and convert the electrical information into the electrical waveform information; The method further includes: controlling the motor comprehensive protection and waveform acquisition terminal to transmit the electrical waveform information to the recording and conversion unit.

3. The method according to claim 2, characterized in that Recording the electrical waveform information to obtain recorded waveform information includes: In response to the wave recording and conversion unit receiving the electrical waveform information, controlling the wave recording and conversion unit to detect the electrical waveform information to obtain the target fluctuation event; The recording and conversion unit is controlled to record the waveforms before and after the target fluctuation event occurs to obtain the recording information.

4. The method according to claim 2, characterized in that: The operation status detection system also includes a motor status and defect diagnosis management machine, wherein the electrical waveform information and the recorded waveform information are converted to obtain the motor group waveform information, including: In response to the number of motors to be detected being multiple, time alignment processing is performed on the electrical waveform information and the recorded waveform information to obtain the electrical waveform information and the recorded waveform information under the same time reference; Integrate the electrical waveform information and the recorded waveform information from the plurality of motors at the same time reference to obtain the motor group waveform information; The method also includes: controlling the waveform recording and conversion unit to transmit the waveform information of the motor group to the motor status and defect diagnosis management machine.

5. The method according to claim 4, characterized in that The waveform information of the motor group is detected to obtain the detection result, including: In response to the motor state and defect diagnosis management machine receiving the motor group waveform information, controlling the motor state and defect diagnosis management machine to perform Fourier transformation on the motor group waveform information to obtain a frequency spectrum diagram; Detecting the spectrum diagram to obtain the detection result; The method further includes: in response to the detection result that the fault occurs in the motor under the target fluctuation event, determining a fault type of the fault, wherein the fault type is used to indicate the severity of the fault.

6. The method according to claim 5, characterized in that The operation status detection system further includes a master station system, wherein the method further includes: The motor status and defect diagnosis management machine is controlled to transmit the fault type and the detection result to the main station system.

7. The method according to claim 6, characterized in that The method further comprises: In response to the master station system receiving the fault type and the detection result, a detection report corresponding to the fault type and the detection result is generated, and the detection report is visually displayed.

8. A motor fault detection device, characterized in that: include: An acquisition unit, used for acquiring electrical waveform information of the motor to be detected, wherein the electrical waveform information is used for indicating the electrical operating state of the motor; A wave recording unit, used for recording the electrical waveform information to obtain wave recording information, wherein the wave recording information is triggered by the electrical waveform information when a target fluctuation event exists, and is used for obtaining the degree of change of the electrical operating state before and after the target fluctuation event occurs; A conversion unit, used for converting the electrical waveform information and the recorded waveform information to obtain the motor group waveform information; The detection unit is used to detect the waveform information of the motor group to obtain a detection result, wherein the detection result is used to indicate whether the motor fails under the target fluctuation event.

9. An electronic device, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the motor fault detection method according to any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein the program, when run by the processor, executes the motor fault detection method according to any one of claims 1 to 7.

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