Comprehensive monitoring method and system for health state of high-voltage motor

Abstract

The invention relates to the technical field of motor state monitoring, in particular to a comprehensive monitoring method and system for the health state of a high-voltage motor, and the method comprises the steps: carrying out the online monitoring and real-time analysis of the insulation state and operation parameters of the high-voltage motor, enabling the system to carry out the data collection, obtaining the data, such as current, voltage, temperature, etc. The data are processed and converted into evaluation information; the system performs fault diagnosis through the early warning module, identifies potential fault hidden dangers and provides early warning; in addition, the system further comprehensively analyzes data, implements early warning and maintenance measures, can timely discover and eliminate health hidden dangers of the motor, effectively prolongs the service life of equipment, reduces economic losses caused by sudden faults, and improves the reliability and safety of motor operation. Meanwhile, due to the introduction of an early warning and maintenance mechanism, the maintenance and repair cost of the equipment is further reduced, and more intelligent and stable equipment management is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of motor condition monitoring, and particularly to a comprehensive monitoring method and system for the health status of high-voltage motors. Background Art

[0002] With the gradual improvement of modern industrial and equipment manufacturing levels, the number of motors used in industrial production systems has been increasing, and the single-machine capacity has also been rising continuously. Large high-voltage motors are used more and more widely and play an increasingly important role. Their working reliability is of great significance for ensuring the safe, efficient, high-quality, and low-consumption operation of the production and manufacturing process. After long-term operation after commissioning, various types of high-voltage motors are affected by environmental temperature, variable electric fields, mechanical vibrations, and external factors, etc. A series of physical changes (morphology, medium softening or dissolution, volatilization of plasticizing materials) and chemical changes (cracking of high-molecular organic substances, medium electrolysis, ionization, etc.) will occur in the characteristics of their internal insulation materials, resulting in a decline in their insulation performance, aging, deterioration, and even breakdown of the insulation structure. The insulation of the coils has shown varying degrees of aging and is extremely prone to local failures. Motor failures not only damage the motor itself but also affect the entire production system and even endanger personal safety, causing huge economic losses and adverse negative impacts. For high-voltage motors in hydropower stations, most are used in the underground powerhouse drainage system. Once a high-voltage motor fails and cannot operate normally, it will bring major risks.

[0003] Conducting on-line condition monitoring, fault diagnosis, and disaster warning for important large high-voltage motors in production can effectively reduce the failure rate of high-voltage motors, reduce economic losses caused by sudden accidents, reduce maintenance costs, and reduce the threat of disasters to the safety of personnel and equipment. It also creates conditions for realizing condition-based maintenance, and can provide empirical data for motor designers and manufacturers and important information for improving the performance and reliability of high-voltage motors. According to statistics, about 50% of motor damage accidents are caused by insulation damage of the motor stator windings, and the aging of the stator bar insulation of high-voltage motors is the main cause of stator bar insulation failures. Abnormal insulation resistance, too high stator temperature, and severe partial discharge are important manifestations of insulation aging. On-line monitoring the resistance value of the insulation resistance of the stator windings of high-voltage motors, the temperature change, and the characteristics of partial discharge signals, judging the degree of stator insulation aging, diagnosing and warning potential fault hazards, helps to improve the service life of large high-voltage motors, prevent sudden accidents from occurring, and reduce the threat of faults to the safety of personnel and equipment, and promotes the gradual transformation of high-voltage electrical equipment from the current preventive maintenance stage to the predictive maintenance stage. Therefore, studying high-voltage motor on-line monitoring systems has very important practical significance. Summary of the Invention

[0004] In view of the problems existing in the above-mentioned prior art, the present invention is proposed.

[0005] Therefore, the technical problem to be solved by the present invention is to establish a comprehensive monitoring and early warning system for the health status of high-voltage motors by online monitoring and real-time analysis of the insulation status and operating parameters of high-voltage motors. The system aims to timely identify potential fault hazards, provide technical support for early warning of faults, thereby effectively extending the service life of equipment, reducing losses caused by sudden faults, and improving the reliability and safety of motor operation. At the same time, the system can also reduce maintenance and repair costs and achieve state-based and intelligent management of high-voltage motors.

[0006] To solve the above technical problem, the present invention provides the following technical solution, a comprehensive monitoring method for the health status of high-voltage motors, including: collecting data to obtain a first type of data; analyzing and processing the collected first type of data to convert it into a first type of evaluation information; through an early warning system, performing fault diagnosis; comprehensively analyzing the data to perform early warning and maintenance.

[0007] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the data collection includes real-time collection of key parameters during the operation of high-voltage motors through a first type of tool to obtain a first type of data for analysis and processing.

[0008] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the analysis and processing includes systematically processing the collected first type of data, and through the analysis and processing process, converting the first type of data into a first type of evaluation information.

[0009] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the fault diagnosis includes real-time detection of the operating status of high-voltage motors through an early warning system based on a first type of evaluation information.

[0010] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the early warning and maintenance includes, after real-time analysis of motor data, identifying fault risks through an early warning system, sending out alarm prompts in advance, and providing maintenance plans.

[0011] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the first type of data includes voltage, current, temperature, and vibration signals.

[0012] As a preferred solution of the comprehensive monitoring method for the health status of high-voltage motors according to the present invention, wherein: the analysis and processing of the collected first type of data includes statistical analysis, feature extraction, and trend judgment of the first type of data.

[0013] Another object of the present invention is to provide a comprehensive monitoring system for the health status of high-voltage motors, aiming to timely detect potential health hazards of motors through real-time monitoring of key parameters such as on-line insulation resistance, leakage current, unbalanced current, real-time power, temperature and vibration of the motors, realize on-line evaluation and fault warning, so as to reduce sudden accidents and improve the safety and reliability of equipment operation.

[0014] To solve the above technical problems, the present invention provides the following technical solutions: A comprehensive monitoring system for the health status of high-voltage motors, including: a data acquisition module, a data processing module, a fault diagnosis module and a warning and maintenance module;

[0015] The data acquisition module performs data acquisition to obtain a type of data;

[0016] The data processing module analyzes and processes the acquired type of data and converts it into a type of evaluation information;

[0017] The fault diagnosis module performs fault diagnosis through a warning system;

[0018] The warning and maintenance module comprehensively analyzes the data and performs warning and maintenance.

[0019] A computer device includes a memory and a processor. The memory stores a computer program. The processor, when executing the computer program, realizes the steps of the above-mentioned comprehensive monitoring method for the health status of high-voltage motors.

[0020] A computer-readable storage medium stores a computer program thereon. The computer program, when executed by a processor, realizes the steps of the above-mentioned comprehensive monitoring method for the health status of high-voltage motors.

[0021] The beneficial effects of the present invention: By on-line monitoring and real-time analysis of the insulation state and operating parameters of high-voltage motors, potential fault hazards can be timely identified, and reliable technical support can be provided for early warning of faults. This effectively extends the service life of the equipment, reduces the losses caused by sudden faults, improves the reliability and safety of motor operation, and at the same time reduces the maintenance and repair costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1Flow chart of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention.

[0024] Figure 2 Flow chart of the early warning algorithm for the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention.

[0025] Figure 3 Real-time trend chart of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention.

[0026] Figure 4 Normal motor speed chart of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention.

[0027] Figure 5 Short-circuit motor speed chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15.

[0028] Figure 6 Short-circuit motor speed chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.35.

[0029] Figure 7 Motor three-phase current comparison chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15.

[0030] Figure 8 Motor three-phase current comparison chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.35.

[0031] Figure 9 Motor torque comparison chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15.

[0032] Figure 10 Motor torque comparison chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.35.

[0033] Figure 11 Motor speed chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15 and the short-circuit resistance is 50 ohms.

[0034] Figure 12 Motor three-phase current chart when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15 and the short-circuit resistance is 50 ohms.

[0035] Figure 13The motor torque diagram when the short-circuit ratio of the comprehensive monitoring method for the health status of a high-voltage motor provided by an embodiment of the present invention is 0.15 and the short-circuit resistance is 50 ohms. Detailed implementation manners

[0036] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the detailed implementation manners of the present invention with reference to the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0037] Example 1, referring to Figure 1 , which is an embodiment of the present invention. This embodiment provides a comprehensive monitoring method for the health status of a high-voltage motor, including:

[0038] S1: Perform data acquisition to obtain a type of data.

[0039] It should be noted that as Figure 1 shown in S1 of

[0040] , data acquisition includes collecting key parameters during the operation of the high-voltage motor in real time through a type of tool to obtain a type of data for analysis and processing.

[0041] Furthermore, the type of data collected covers voltage, current, temperature, and vibration signals, which are collected by dedicated sensors (such as high-frequency current sensors, temperature sensors, and vibration sensors); to ensure the comprehensiveness and accuracy of the collection, the monitoring points of different parameters are distributed in multiple parts of the motor, and the key data of each item is summarized in real time through a data collector and a communication network.

[0042] In the embodiments of the present application, one type of data includes voltage, current, temperature, and vibration signals. These data are important parameters for evaluating the operating state of high-voltage motors. The voltage signal reflects the stability of the motor's input voltage and the voltage changes during operation. The current signal can provide basic data on the motor's load information and operating state, such as the current response during motor startup, shutdown, and load changes. The temperature signal monitors the heat distribution inside the motor and the temperature of key components. In particular, excessively high temperatures in the coils and windings may indicate insulation aging or abnormal heat dissipation, providing important basis for the motor's temperature management. In addition, the vibration signal is mainly used for mechanical performance monitoring. By identifying abnormalities in vibration patterns and frequency components, mechanical faults such as bearing wear, misalignment, and shaft imbalance can be detected early to ensure the smooth operation of the motor.

[0043] In an alternative embodiment, one type of data can also be obtained in other ways. For example, by monitoring the leakage current of the motor in real time to identify the degradation of insulation materials. Leakage current data can reveal early signs of insulation failure, which is particularly important for long-term operating high-voltage motors. High-voltage motors are susceptible to multiple influences of electrical, thermal, and mechanical stresses during operation, leading to gradual aging of insulation materials and ultimately possible insulation failure. By monitoring the leakage current in real time, a warning can be issued before the insulation aging reaches a dangerous level, reminding the operation and maintenance personnel to take preventive measures such as reducing the load or shutting down for timely maintenance. Especially in harsh environments such as humidity and high temperature, leakage current monitoring is more significant for the safe operation of the motor because environmental factors can accelerate the degradation process of insulation materials. Obtaining and analyzing leakage current data in real time can effectively prevent short circuits or equipment damage caused by insulation faults, thereby reducing economic losses caused by sudden failures and improving the reliability and service life of the equipment. Such monitoring methods also provide important basis for the predictive maintenance of the motor, helping motor management personnel optimize the maintenance plan and extend the service life of the equipment.

[0044] In an alternative embodiment, a type of data can also be implemented in other ways. For example, it can be implemented through the acoustic characteristic signals of the motor, that is, by installing an acoustic sensor to collect the sound data of the motor during operation; the acoustic signals contain rich mechanical information, such as the wear of bearings, the meshing state of gears, the balance of the rotating shaft, etc. Through the spectral analysis of the acoustic signals, specific frequencies and sound patterns can be extracted, and these characteristics can reflect the health status of the internal components of the motor; if abnormal noises occur, such as sharp metal friction sounds or low-frequency vibration sounds, this usually indicates the initial signs of mechanical failures such as bearing wear, rotating shaft imbalance, or gear misalignment; by analyzing the acoustic characteristics, these abnormal conditions can be detected at an early stage, effectively preventing potential mechanical failures from deteriorating further, and reducing the risk of downtime and maintenance costs caused by the expansion of failures; by combining the comprehensive analysis of vibration data and acoustic signals, the accuracy of fault diagnosis can also be improved, enabling the early warning system to more sensitively identify minor abnormalities in the mechanical structure, thereby optimizing the maintenance strategy and operating reliability of the motor; acoustic monitoring is not only an important means of mechanical diagnosis, but also a key supplement in multi-source information fusion, providing more in-depth data support for the comprehensive health monitoring of high-voltage motors.

[0045] In the embodiment of the present application, a type of tool is used to complete data acquisition through methods such as sensor collectors and data communication for real-time monitoring of the operating state of high-voltage motors. The specific tools include high-frequency voltage sensors and high-frequency current sensors, which are responsible for collecting the electrical parameters of the motor, while vibration sensors are used to detect the operating state of mechanical components, and temperature sensors monitor the temperature of key components; among them, the measurement range of the vibration sensor is 0 to 50 mm / s, which can detect the vibration displacement and speed during the operation of the motor, providing a basis for judging the state of bearings and mechanical components; the measurement range of the temperature sensor is from -40°C to +80°C, which can accurately detect the temperature distribution inside the motor, especially the winding temperature; in addition, the intelligent perception terminal, as the core device for data acquisition, can realize multi-channel data access and processing, and communicate with the data processing host through RS485 and Ethernet interfaces to ensure the accuracy and real-time nature of data acquisition. The acquisition device adopts a 1U chassis structure, supports 24-channel analog input, and is equipped with a high-performance PC104 industrial control board and an ISA bus acquisition module.

[0046] In an alternative embodiment, a type of tool can also be implemented in other ways, such as through edge computing devices. Edge computing devices can collect, preliminarily analyze, and store data at the on-site location near the high-voltage motor, and handle simple fault diagnosis and data filtering functions on the edge device. This can not only effectively reduce the pressure of data transmission but also complete preliminary anomaly detection and early warning locally to achieve rapid response. For example, when the current or temperature of the motor fluctuates beyond the normal range, the edge computing device can immediately issue an alarm without waiting for the data to be transmitted to the central server for processing, which can significantly reduce the response time and prevent the fault from deteriorating further. In addition, the edge computing device can screen and compress data through intelligent algorithms and only transmit key data to the central server, thereby reducing bandwidth consumption and storage costs. Important data such as fault trends and high-frequency vibration signals can be transmitted to the central server in real time, while unimportant daily operation data can be processed locally or uploaded periodically to further improve the overall efficiency of the system. By performing calculations and processing at the edge, redundant protection of data can also be achieved. When the network is interrupted, the edge device can still continue to monitor and store data to ensure the stability and reliability of the system, and ultimately achieve low-latency fault early warning and flexible fault handling strategies.

[0047] In an alternative embodiment, a type of tool can also be implemented in other ways, such as by using drones or robots for assisted inspection and data collection. For large high-voltage motors or widely distributed equipment systems, drones or mobile robots can be used for regular inspections to collect data such as vibration, temperature, and noise into the on-site server. This inspection method is particularly suitable for collecting data in areas where the motor is installed at high altitude, difficult to access, or has safety hazards, which can improve the safety and convenience of inspections and supplement the data acquisition method of fixed sensors at the same time. Drones can carry a variety of sensor modules and can flexibly approach different parts of the equipment in the air for precise detection, while mobile robots can move flexibly on the ground and touch more parts for comprehensive detection. Drones and robots can also be remotely controlled to transmit data to the central monitoring system in real time via wireless communication, facilitating real-time analysis and fault diagnosis by maintenance personnel. In addition, these devices can autonomously plan inspection paths to cover the key areas of the entire equipment, avoid missed inspections that may occur in manual inspections, and additionally monitor the surface state of the equipment through various sensing technologies such as images and infrared, effectively improving the reliability of equipment operation and the accuracy of fault early warning.

[0048] Embodiment 2, referring to Figures 2 - 3 , is an embodiment of the present invention. This embodiment provides a comprehensive monitoring method for the health status of high-voltage motors, including:

[0049] S2: Analyze and process the collected first - type data and convert it into first - type evaluation information.

[0050] It should be noted that the analysis and processing include systematically processing the collected first - type data, and through the analysis and processing process, converting the first - type data into first - type evaluation information.

[0051] Furthermore, analyzing and processing the collected first - type data includes performing statistical analysis, feature extraction, and trend judgment on the first - type data; the system uses pre - processing methods such as data cleaning, filtering, and integration to effectively remove the noise of the collected data, thereby obtaining a more accurate data basis; in the "real - time waveform analysis" function, curves of signals such as voltage, current, and vibration collected can be displayed, and processing such as filtering and band - stop filtering is supported to extract key feature states.

[0052] Even further, the system can calculate and generate eigenvalue of multiple key parameters based on the collected data, including indicators such as vibration amplitude, current peak value, temperature average value, etc.; various analysis tools such as power spectrum, phase spectrum, and trend graph are also integrated in the data - processing function of the system, which can help identify the fault precursors of high - voltage motors; in addition, the system also has an automatic working - condition recognition function, which can select appropriate data - processing and storage strategies according to different operating states (such as startup, shutdown, steady - state operation); for the data in steady - state operation, the system records it by means of regular sampling, while for dynamic working conditions such as startup and shutdown, the system performs high - density continuous storage to ensure data integrity; through this scenario - based data - management method, users can more clearly analyze the performance of the motor under different working conditions; during the analysis process, the system uses an algorithm based on machine learning to predict the future device state; for example, through the support vector machine regression (SVR) model, key parameters are predicted based on historical data, and an early warning is triggered when the predicted value deviates from the normal range, as Figure 2 shows the process of the early - warning algorithm, from data cleaning to model training, and then to each step of parameter prediction, ensuring the accuracy and timeliness of data analysis.

[0053] S3: Conduct fault diagnosis through the early - warning system.

[0054] It should be noted that fault diagnosis includes, based on the first - type evaluation information, real - time detection of the operating state of the high - voltage motor through the early - warning system.

[0055] Furthermore, the early warning system is not only responsible for monitoring the changes in key parameters during daily operation, but also has the functions of real-time analysis and rapid identification of the initial fault signals. By collecting and processing various data such as vibration, temperature, voltage and current, the system fuses multi-source data to make early diagnosis and warning of potential faults of high-voltage motors. Based on technologies such as adaptive threshold setting and outlier analysis, the early warning system compares historical data with real-time data, discovers trend changes and triggers the alarm mechanism, so as to identify abnormal operating states and prevent the further deterioration of faults. The module design of the early warning system includes a real-time monitoring module, a fault identification module, an alarm output module, a data recording module and a historical data analysis module, and displays the fault warning status and recommended maintenance measures through a human-machine interaction interface.

[0056] Furthermore, in the implementation process of the early warning system, the system adopts a variety of fault diagnosis models. Specifically, for problems such as motor insulation deterioration, coil deformation, and inter-turn short circuit, the system applies fault identification technologies based on multi-variable data models and deep learning algorithms, and fuses historical data and real-time data for trend prediction and anomaly detection. As Figure 2 shown in , the four main steps of this early warning algorithm include data cleaning, training sample data, verification and optimization, and parameter prediction. Through these steps, the changes in the device state are captured in real time to achieve accurate fault prediction and alarm mechanism. In the fault diagnosis stage, the early warning system also adopts an algorithm that combines fuzzy theory and D-S evidence theory to solve the uncertainty problem in the diagnosis process. This method synthesizes the monitoring data of different sensors, uses multi-source information fusion technology, and through logical reasoning and evidence synthesis, accurately identifies potential faults. This method enables the system to provide reliable fault diagnosis results under the conditions of incomplete information or noise interference, and provides a scientific basis for the further maintenance of the device. In addition, the system also has the function of trend state identification, which identifies and analyzes the situation where the fault may develop into a more serious problem, and monitors the trend changes of the device operation state through analog signals. For example, when the vibration value or temperature of the motor exceeds the normal threshold, or its change trend does not conform to the historical data, the system will trigger an over-limit alarm and notify the maintenance personnel to take preventive measures. This process of trend analysis can effectively identify early fault signs and ensure that the motor operates in the best state.

[0057] Specifically, the algorithm for the "normal threshold" can refer to the over-limit alarm strategy for analog quantity monitoring. When the monitored analog quantity exceeds the high limit or the low limit and exceeds the set duration, an alarm is triggered. For example, users can set the high limit and the low limit to define the "normal threshold". When the variable exceeds the high limit and lasts for a certain time, a high limit alarm is output, and vice versa, a low limit alarm is triggered when it is lower than the low limit. This way of setting the threshold ensures that the operating state of the monitored variable is within a reasonable range and can be used for trend warning.

[0058] S4: Comprehensively analyze the data for early warning and maintenance.

[0059] It should be noted that the early warning and maintenance include, after real-time analysis of the motor data, identifying the fault risks through the early warning system, sending out warning prompts in advance, and providing maintenance plans.

[0060] Furthermore, the system processes the collected data through a variety of analysis algorithms, such as trend analysis, spectrum analysis, and anomaly detection, etc., to extract key characteristic values to help identify potential fault risks. For example, Figure 3 The real-time trend analysis graph shown in can, through the display of the real-time trend graph, identify abnormal change trends of the motor operation parameters, helping users judge the health status of the motor; among them, time axis: the horizontal axis represents time, and the time axis shows how the data changes over time; vertical axis: the vertical axis represents the measured physical quantities, such as voltage, current, rotational speed, temperature, etc. Each physical quantity has its own unit, such as voltage (volt), current (ampere), rotational speed (revolutions per minute), etc.; curve or line: each curve or line represents a specific parameter or variable; data points and real-time update: the trend graph usually shows a series of data points, and each data point represents the data collected at a specific time; in the real-time trend graph, the data points are continuously updated over time, thus showing the real-time status and performance changes of the motor.

[0061] Even further, the system has a historical data backtracking function, which can compare the current data with the historical data to identify abnormal changes; for example, when the temperature of the motor rises rapidly within a short period of time and exceeds the historical average value, the system will immediately trigger an early warning.

[0062] The above is a schematic solution of a comprehensive monitoring method for the health status of a high-voltage motor in this embodiment. It should be noted that the technical solution of the system of the comprehensive monitoring method for the health status of the high-voltage motor belongs to the same concept as the technical solution of the above comprehensive monitoring method for the health status of the high-voltage motor. For the details not described in detail in the technical solution of the comprehensive monitoring system for the health status of the high-voltage motor in this embodiment, reference can be made to the description of the technical solution of the above comprehensive monitoring method for the health status of the high-voltage motor.

[0063] Example 3, referring to Figures 4 - 13 , an embodiment of the present invention provides a comprehensive monitoring method for the health status of a high-voltage motor. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0064] As Figure 4It can be seen that the output rotational speed conforms to the operating law of the normal motor speed: when the motor starts, the rotational speed gradually rises to a stable value in a nearly linear relationship after a short-term fluctuation, and then remains unchanged. The rotational speed formula of the motor is:

[0065]

[0066] In the formula, n represents the motor rotational speed, f represents the motor power supply frequency, and P represents the number of pole pairs of the motor. The data of this motor are: the power supply frequency is 50Hz, and the number of pole pairs is 1. The calculation results are in agreement with the simulation results.

[0067] From Figures 5 - 6 it can be seen that although the rotational speed of the short-circuited motor also conforms to the law of oscillating upward at startup and tending to a constant value at stability, the rotational speed of the short-circuited motor fluctuates throughout the process. This is because the short circuit generates negative-sequence current, resulting in unbalanced three-phase currents, which causes braking torque and makes the rotational speed output by the motor fluctuate accordingly. And when the short-circuit ratio increases, although the final stable value remains almost unchanged, the fluctuation of the rotational speed also becomes larger.

[0068] From Figures 7 - 8 it can be seen that when the short-circuit ratio is set to 0.15, the phase current of the short-circuited phase (phase A) of the short-circuited motor is significantly increased compared with that of the normal motor. This is because the short circuit generates short-circuit current. When the short-circuit ratio is increased to 0.35, the difference between the phase current of phase A of the short-circuited motor and that of phase A of the normal motor will also increase accordingly.

[0069] From Figures 9 - 10 it can be seen that due to the occurrence of inter-turn short circuit, the torque of the faulty motor is in a fluctuating state both before and after reaching equilibrium. This is because the short circuit generates negative-sequence current, causing three-phase imbalance, and thus generating braking torque. And as the short-circuit ratio (or the number of short-circuited turns) increases, the degree of this three-phase imbalance will also deepen.

[0070] If the short-circuit ratio is kept at 0.15 unchanged and the magnitude of the short-circuit resistance is adjusted, the results are as Figures 11 - 13 shown.

[0071] Since the value of the short-circuit resistance is generally very small, and even in most studies it is approximately considered that the value of the short-circuit resistance is 0, changing the value of the short-circuit resistance within the normal range (following the law that the short-circuit resistance value is very small) will not have a great impact on the results.

[0072] In summary, this model can accurately output simulation results that conform to the predicted values according to the mathematical model when simulating normal and faulty motors, and has a certain feasibility and reference value.

[0073] Embodiment 4 is an embodiment of the present invention, which provides a comprehensive monitoring system for the health status of high-voltage motors, including: a data acquisition module, a data processing module, a fault diagnosis module, and a warning and maintenance module;

[0074] The data acquisition module performs data acquisition to obtain a type of data;

[0075] The data processing module analyzes and processes the acquired type of data and converts it into a type of evaluation information;

[0076] The fault diagnosis module performs fault diagnosis through a warning system;

[0077] The warning and maintenance module comprehensively analyzes the data for warning and maintenance.

[0078] This embodiment also provides a computing device applicable to the comprehensive monitoring method for the health status of high-voltage motors, including:

[0079] A memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the comprehensive monitoring method for the health status of high-voltage motors as proposed in the above embodiment.

[0080] This embodiment also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, it implements the comprehensive monitoring method for the health status of high-voltage motors as proposed in the above embodiment.

[0081] The storage medium proposed in this embodiment and the comprehensive monitoring method for the health status of high-voltage motors proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0082] If the above functions are implemented in the form of software function units and sold or used as independent products, they 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 a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0083] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered a definitional sequence list of executable instructions for implementing logical functions, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. As used in this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device or in connection with these instruction execution systems, apparatus, or devices.

[0084] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0085] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A comprehensive monitoring method for the health status of a high-voltage motor, characterized in that: include: Conduct data collection to obtain a category of data; Analyze and process a type of collected data and convert it into a type of evaluation information; Conduct fault diagnosis through early warning system; Comprehensively analyze data to conduct early warning and maintenance.

2. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 1, characterized in that: The data acquisition includes collecting key parameters of the high-voltage motor in real time during operation through a type of tool to obtain a type of data for analysis and processing.

3. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 2, characterized in that: The analysis and processing includes systematically processing a type of collected data, and converting a type of data into a type of evaluation information through the analysis and processing process.

4. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 3, characterized in that: The fault diagnosis includes real-time detection of the operating state of the high-voltage motor through an early warning system based on a type of evaluation information.

5. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 4, characterized in that: The early warning and maintenance include identifying the risk of failure through the early warning system after real-time analysis of the motor data, issuing an early warning prompt, and providing a maintenance plan.

6. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 5, characterized in that: The data includes voltage, current, temperature and vibration signals.

7. The method for comprehensive monitoring of the health status of a high-voltage motor according to claim 6, characterized in that: The analyzing and processing of the collected data includes statistical analysis, feature extraction and trend judgment on the data.

8. A system for comprehensive monitoring of the health status of a high-voltage motor based on any one of claims 1 to 7, characterized in that: include: Data acquisition module, data processing module, fault diagnosis module and early warning maintenance module; The data collection module collects data to obtain a type of data; The data processing module analyzes and processes a type of collected data and converts it into a type of evaluation information; The fault diagnosis module performs fault diagnosis through the early warning system; The early warning and maintenance module comprehensively analyzes data and performs early warning and maintenance.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for comprehensive monitoring of the health status of a high-voltage motor according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for comprehensive monitoring of the health status of a high-voltage motor according to any one of claims 1 to 7 are implemented.

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