Electric power equipment motor operation fault diagnosis method and system

Abstract

The invention relates to a power equipment motor operation fault diagnosis method and system, and the method comprises the steps: obtaining the current power generation demand and the power equipment basic data of the current power generation execution power equipment, generating the current power generation demand raw material total amount, and generating the estimated motor working time; generating a motor power sampling detection time period, and generating an estimated working power curve; calculating a motor power difference value with the estimated working power curve according to real-time motor working data; and judging whether the motor power difference value is greater than or equal to a pre-stored standard power difference value, if so, generating a current motor fault warning, and sending the current motor fault warning to a motor maintenance management main body, and the prompting module is used for prompting the motor maintenance management main body to overhaul the currently used motor in the current power generation execution power equipment. According to the invention, fault monitoring and fault diagnosis of equipment using a motor in power equipment are realized.

Description

Technical Field

[0001] The present application relates to the technical field of motor monitoring of electric power equipment, and in particular to a method and system for diagnosing motor operation faults of electric power equipment. Background Art

[0002] Motor refers to an electromagnetic device that realizes the conversion or transmission of electric energy according to the law of electromagnetic induction. It is divided into electric motors and generators. The generator is usually used in power equipment. Power equipment mainly includes two categories: power generation equipment and power supply equipment. The power generation equipment mainly includes power station boilers, steam turbines, gas turbines, water turbines, generators, transformers, etc. The power supply equipment mainly includes transmission lines of various voltage levels, mutual inductors, contactors, etc.

[0003] For power equipment, health assessment during operation is related to whether it can operate normally, so there are already many existing technologies for its fault monitoring. For example, the invention patent with publication number CN118111739A discloses a method and system for diagnosing faults in the fine treatment system of a thermal power generator set. The method includes: obtaining water quality parameters of each mixed bed in the fine treatment system corresponding to the thermal power generator set and water quality parameters of the fine treatment outlet main pipe; diagnosing whether each mixed bed is faulty according to the water quality parameters of each mixed bed in the fine treatment system and preset mixed bed diagnosis rules; diagnosing whether each mixed bed main pipe is faulty according to the water quality parameters of the fine treatment outlet main pipe and preset fine treatment mixed bed main pipe diagnosis rules.

[0004] Although the technical solution in the above patent document can timely and efficiently diagnose faults in the precision processing system, thereby improving the accuracy and efficiency of fault diagnosis, its coverage is limited. For the detection and fault determination of equipment using motors in power equipment, there is still a problem of limited coverage and inability to detect operating faults of motors in power equipment. Summary of the invention

[0005] Based on this, it is necessary to provide a method and system for diagnosing motor operation faults in electric power equipment, which can detect whether a motor in the electric power equipment fails during operation, in order to solve the above technical problems.

[0006] The technical solution of the present invention is as follows:

[0007] A method for diagnosing motor operation faults of electric power equipment, the method comprising:

[0008] Obtain current power generation demand and basic data of power equipment of current power generation executing power equipment, generate the total amount of raw materials of current power generation demand according to the basic data of power equipment and current power generation demand, and generate estimated motor working time according to the total amount of raw materials of current power generation demand; set the motor power sampling detection time period according to the estimated working time, and generate an estimated working power curve according to the estimated working time and the total amount of raw materials of current power generation demand; obtain real-time motor working data of the current power generation executing power equipment within the motor power sampling detection time period, calculate the motor power difference value with the estimated working power curve according to the real-time motor working data; judge whether the motor power difference value is greater than or equal to the pre-stored standard power difference value, if judged as yes, generate a current motor fault warning, send the current motor fault warning to the motor maintenance management subject, and use it to prompt the motor maintenance management subject to repair the currently used motor in the current power generation executing power equipment.

[0009] Optionally, obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generating the total amount of raw materials of the current power generation demand according to the basic data of the power equipment and the current power generation demand, and generating the estimated motor working time according to the total amount of raw materials of the current power generation demand; including:

[0010] Obtain the current power generation demand and the basic data of the power equipment for the current power generation executing power equipment, and obtain the current motor type and the actual service life of the motor currently in use in the current power generation executing power equipment according to the basic data of the power equipment; obtain the standard service life of the motor currently in use according to the current motor type; obtain the number of motor maintenance and abnormal shutdown times of the motor currently in use during the actual service life;

[0011] The current electric equipment wear coefficient is generated based on the actual service life, standard service life, motor maintenance times and abnormal shutdown times according to the following formula:

[0012]

[0013] Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns;

[0014] Obtain standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated; generate the total amount of raw materials for current power generation demand based on the total amount of power generation raw materials to be evaluated and the wear coefficient of the current power equipment; generate an estimated motor working time based on the total amount of raw materials for current power generation demand and the current average power of the current power generation execution power equipment, wherein the current average power is preset.

[0015] Optionally, a motor power sampling detection time period is set according to the estimated working time, and an estimated working power curve is generated according to the estimated working time and the total amount of raw materials required for current power generation; including:

[0016] The overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated based on the estimated working time; the overload working level is generated based on the overload working time difference, and the motor power sampling detection quantity is generated based on the overload working level; the motor power sampling detection time period is set in the time period in which the estimated working time exceeds the preset working duration based on the motor power sampling detection quantity; the estimated working power curve is generated based on the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

[0017] Optionally, obtaining real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, and calculating the motor power difference value between the real-time motor working data and the estimated working power curve; including:

[0018] Acquire the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, split the real-time motor working data according to the sampling time interval, and generate multiple sampled motor working data, wherein the sampling time interval is preset; generate motor sampling power curves according to each of the sampled motor working data, wherein the number of the motor adopted power curves is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve; calculate the actual change slope of each motor adopted power curve and the estimated change slope of the estimated motor power curve, wherein one average change slope corresponds to one motor sampling power curve; determine whether there is an actual change slope greater than or equal to the fault fluctuation slope in each of the actual change slopes, wherein the fault toggle slope is pre-stored; if the judgment is yes, generate a current motor fault warning, and send the current motor fault warning to the motor maintenance management subject; if the judgment is no, calculate the real-time average slope according to each of the actual change slopes, and calculate the estimated average slope according to each of the estimated change slopes;

[0019] The motor power difference value is generated according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula:

[0020]

[0021] Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

[0022] Optionally, a system for diagnosing motor operation faults of electric power equipment is also provided, the system comprising:

[0023] A motor working time generation module is used to obtain the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generate the total amount of raw materials required for the current power generation according to the basic data of the power equipment and the current power generation demand, and generate the estimated motor working time according to the total amount of raw materials required for the current power generation;

[0024] A motor working curve generating module, used for setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation;

[0025] A motor power difference generating module, used for obtaining the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, and calculating the motor power difference value with the estimated working power curve according to the real-time motor working data;

[0026] The motor fault inspection and repair judgment module is used to judge whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is judged to be yes, a current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to inspect the currently used motor in the current power generation execution power equipment.

[0027] Optionally, the motor working time generating module is further used for:

[0028] Obtain the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, obtain the current motor type of the motor currently used in the current power generation executing power equipment and the actual service life of the motor currently used according to the basic data of the power equipment; obtain the standard service life of the motor currently used according to the current motor type; obtain the number of motor maintenance and abnormal shutdown times of the motor currently used in the actual service life; generate the current power equipment wear coefficient according to the actual service life, standard service life, motor maintenance times and abnormal shutdown times based on the following formula:

[0029]

[0030] Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns;

[0031] Obtain standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated; generate the total amount of raw materials for current power generation demand based on the total amount of power generation raw materials to be evaluated and the wear coefficient of the current power equipment; generate an estimated motor working time based on the total amount of raw materials for current power generation demand and the current average power of the current power generation execution power equipment, wherein the current average power is preset.

[0032] Optionally, the motor working curve generating module is further used for:

[0033] The overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated based on the estimated working time; the overload working level is generated based on the overload working time difference, and the motor power sampling detection quantity is generated based on the overload working level; the motor power sampling detection time period is set in the time period in which the estimated working time exceeds the preset working duration based on the motor power sampling detection quantity; the estimated working power curve is generated based on the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

[0034] Optionally, the motor power difference generating module is further used for:

[0035] Acquire the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, split the real-time motor working data according to the sampling time interval, and generate multiple sampled motor working data, wherein the sampling time interval is preset; generate motor sampling power curves according to each of the sampled motor working data, wherein the number of the motor adopted power curves is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve; calculate the actual change slope of each of the motor adopted power curves and the estimated change slope of the estimated motor power curve, wherein , one of the average change slopes corresponds to one motor sampling power curve; judging whether there is an actual change slope greater than or equal to the fault fluctuation slope among the actual change slopes, wherein the fault toggle slope is pre-stored; if the judgment is yes, generating a current motor fault warning, and sending the current motor fault warning to the motor maintenance management body; if the judgment is no, calculating a real-time average slope according to each of the actual change slopes, and calculating an estimated average slope according to each of the estimated change slopes; generating a motor power difference value according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula:

[0036]

[0037] Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

[0038] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method for diagnosing motor operation faults of electric equipment when executing the computer program.

[0039] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for diagnosing motor operation faults of electric power equipment.

[0040] The technical effects achieved by the present invention are as follows:

[0041] The above-mentioned method and system for diagnosing faults in the operation of electric motors of electric equipment successively obtains the current power generation demand and the basic data of the electric equipment of the current power generation executing electric equipment, generates the total amount of raw materials of the current power generation demand according to the basic data of the electric equipment and the current power generation demand, and generates an estimated motor working time according to the total amount of raw materials of the current power generation demand; sets a motor power sampling detection time period according to the estimated working time, and generates an estimated working power curve according to the estimated working time and the total amount of raw materials of the current power generation demand; obtains the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, and calculates the estimated working power curve according to the real-time motor working data Calculate the motor power difference value with the estimated working power curve; determine whether the motor power difference value is greater than or equal to the pre-stored standard power difference value, if it is determined to be yes, generate a current motor fault warning, send the current motor fault warning to the motor maintenance management body, and use it to prompt the motor maintenance management body to repair the currently used motor in the current power generation execution power equipment. First, in order to generate an estimated working time according to the actual power equipment situation, first obtain the current power generation demand and the power equipment basic data of the current power generation execution power equipment, and generate the current power generation demand raw material total amount according to the power equipment basic data and the current power generation demand. , generate an estimated motor working time according to the total amount of raw materials required for the current power generation, and then, in order to accurately evaluate whether the motor may fail, set the motor power sampling detection time period according to the estimated working time, and generate an estimated working power curve according to the estimated working time and the total amount of raw materials required for the current power generation; then, obtain the real-time motor working data of the current power generation execution power equipment within the motor power sampling detection time period, and calculate the motor power difference value with the estimated working power curve according to the real-time motor working data, wherein the motor power difference value is a measure of the difference between the estimated working efficiency of the motor and the actual working efficiency. When the difference is large, it means that the motor has failed, and an early warning is needed. Specifically, it is determined whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is determined to be yes, a current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to repair the currently used motor in the current power generation execution power equipment, so as to determine whether it deviates too much from the estimated normal power curve based on the actual operating data in the power equipment. If it is determined to be yes, it can be accurately determined that it may have a fault, thereby realizing fault monitoring and fault diagnosis of equipment using motors in the power equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a flow chart of a method for diagnosing a motor operation fault of an electric power device in one embodiment;

[0043] Figure 2 The present invention is a structural block diagram of a system for diagnosing motor operation faults of electric power equipment in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] In one embodiment, a terminal is provided, which is used to: obtain current power generation demand and basic data of power equipment of current power generation executing power equipment, generate the total amount of raw materials of current power generation demand according to the basic data of power equipment and current power generation demand, and generate an estimated motor working time according to the total amount of raw materials of current power generation demand; set a motor power sampling detection time period according to the estimated working time, and generate an estimated working power curve according to the estimated working time and the total amount of raw materials of current power generation demand; obtain real-time motor working data of the current power generation executing power equipment within the motor power sampling detection time period, and calculate the motor power difference value with the estimated working power curve according to the real-time motor working data; determine whether the motor power difference value is greater than or equal to a pre-stored standard power difference value, and if so, generate a current motor fault warning, send the current motor fault warning to a motor maintenance management subject, and prompt the motor maintenance management subject to repair the currently used motor in the current power generation executing power equipment.

[0046] The terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices.

[0047] It should be noted that the motor described in the present invention can be a generator or a motor in a generator set. In this application, the motor of a coal mill in a dynamic generator set is used as an example for explanation.

[0048] In one embodiment, Figure 1 As shown, a method for diagnosing motor operation faults of electric equipment is provided, the method comprising:

[0049] Step S100: obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generating the total amount of raw materials for the current power generation demand according to the basic data of the power equipment and the current power generation demand, and generating the estimated motor working time according to the total amount of raw materials for the current power generation demand;

[0050] Step S200: setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation;

[0051] Step S300: acquiring the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, and calculating the motor power difference value between the real-time motor working data and the estimated working power curve;

[0052] Step S400: Determine whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is, generate a current motor fault warning, send the current motor fault warning to the motor maintenance management body, and prompt the motor maintenance management body to inspect the currently used motor in the current power generation execution power equipment.

[0053] In this step, when it is determined that any one of the motor power difference values ​​is greater than or equal to the pre-stored standard power difference value, the determination is yes, and therefore a current motor fault warning needs to be generated.

[0054] In this embodiment, first, in order to generate an estimated working time according to the actual situation of the power equipment, the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment are first obtained, and the current power generation demand total amount of raw materials is generated according to the basic data of the power equipment and the current power generation demand, and the estimated motor working time is generated according to the current power generation demand total amount of raw materials. Then, in order to accurately evaluate whether the motor may fail, the motor power sampling detection time period is set according to the estimated working time, and an estimated working power curve is generated according to the estimated working time and the current power generation demand total amount of raw materials; then, the real-time motor working data of the current power generation executing power equipment within the motor power sampling detection time period is obtained, and the estimated working power curve is calculated according to the real-time motor working data The motor power difference value is a measure of the difference between the estimated working efficiency and the actual working efficiency of the motor. When the deviation is large, it means that the motor has a fault, and an early warning is required. Specifically, it is determined whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is determined to be yes, a current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to repair the currently used motor in the current power generation execution power equipment, so as to determine whether it deviates too much from the estimated normal power curve based on the actual operating data in the power equipment. If it is determined to be yes, it can be accurately determined that it may have a fault, thereby realizing fault monitoring and fault diagnosis of equipment using motors in the power equipment.

[0055] In one embodiment, step S100: obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generating the total amount of raw materials of the current power generation demand according to the basic data of the power equipment and the current power generation demand, and generating the estimated motor working time according to the total amount of raw materials of the current power generation demand; comprising:

[0056] Step S110: obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, and obtaining the current motor type and the actual service life of the motor currently used in the current power generation executing power equipment according to the basic data of the power equipment;

[0057] Step S120: acquiring the standard service life of the currently used motor according to the current motor type;

[0058] Step S130: Obtaining the number of motor maintenance and abnormal shutdown times of the currently used motor in the actual service life;

[0059] Step S140: Generate the current electric equipment wear coefficient according to the actual service life, standard service life, motor maintenance times and abnormal shutdown times based on the following formula:

[0060]

[0061] Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns;

[0062] Step S150: obtaining the standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated;

[0063] Step S160: generating the total amount of raw materials currently required for power generation according to the total amount of power generation raw materials to be evaluated and the current wear coefficient of power equipment;

[0064] Step S170: Generate an estimated motor working time according to the total amount of raw materials currently required for power generation and the current average power of the current power generation executing electrical equipment, wherein the current average power is preset.

[0065] In this embodiment, in order to provide accurate reference data for the subsequent evaluation of whether the motor in the power equipment may fail during operation, it is necessary to first calculate the total amount of power generation raw materials required based on the current power equipment and power generation. First of all, it should be noted that the current power generation demand and the working efficiency of the standard power equipment are in a corresponding relationship. The standard power equipment should be understood as a relatively new power equipment with a wear rate of less than 10% and a service time of less than 1 year, and its production and power generation efficiency is relatively high, that is, the standard power equipment is a pre-marked power equipment. Of course, the above-mentioned 1 year can be set according to actual conditions, such as setting it to 2 years. For standard power equipment, a standard power generation demand corresponds to a standard total amount of power generation raw materials. When the power generation is the current power generation demand, the raw material data can be generated according to the relationship between the standard power generation demand and the standard total amount of power generation raw materials. However, in most cases, the power equipment that actually performs the power task does not meet the requirements of the standard power equipment. Therefore, it is necessary to obtain the basic data of the electric equipment of the current power generation execution equipment to determine the gap between the current power generation execution equipment and the standard power equipment, and calculate the total amount of raw materials required for current power generation according to the gap. The basic data of the electric equipment is the usage data of the current power generation execution equipment in the past. First, the current power generation demand and the basic data of the electric equipment of the current power generation execution equipment are obtained. According to the basic data of the electric equipment, the current motor type of the motor currently used in the current power generation execution equipment and the actual service life of the motor currently used are obtained. Then, according to the current motor type, the standard service life of the motor currently used is obtained; the number of motor maintenance and abnormal shutdown times of the motor currently used in the actual service life are obtained. Finally, the wear degree of the current power generation execution equipment is generated by comprehensively considering the actual service life, standard service life, motor maintenance times and abnormal shutdown times. Specifically, the wear coefficient of the current power equipment is generated, that is, the wear coefficient of the current power equipment is a characterization of the wear degree of the current power generation execution equipment. The larger the wear coefficient of the current power equipment, the greater the wear degree, so the lower the power generation conversion rate.Next, obtain the standard power equipment corresponding to the current power generation demand, and obtain the total amount of standard power generation materials corresponding to the standard power equipment. Specifically, first compare the current power generation demand with each pre-stored standard power generation demand, and obtain the standard power generation demand that is the same as the current power generation demand. The power equipment corresponding to the standard power generation demand is the standard power equipment corresponding to the current power generation demand in step S150. Then, compare the wear coefficient of the current power equipment with the wear coefficient of the pre-stored standard power equipment, and obtain the wear coefficient of the standard power equipment that is the same as the wear coefficient of the current power equipment. The wear coefficient of the standard power equipment is pre-stored, and the wear coefficient of each standard power equipment is also stored. One-to-one corresponding power generation raw material energy consumption increase coefficient, the power generation raw material energy consumption increase coefficient corresponding to the standard power equipment wear coefficient that is the same as the current power equipment wear coefficient is recorded as the current equipment energy consumption increase coefficient, wherein the current equipment energy consumption increase coefficient is used to characterize the proportion of power generation raw materials that need to be consumed to achieve the same power generation as the standard power equipment under the current power equipment wear coefficient; specifically, the current power generation demand raw material total amount is generated according to the to-be-evaluated power generation raw material total amount and the power generation raw material energy consumption increase coefficient, for example, when the to-be-evaluated power generation raw material total amount is 1 ton, the power generation raw material energy consumption increase coefficient is 0.02, then the current power generation demand raw material total amount is 1.02 tons. Furthermore, the estimated motor working time is generated according to the current power generation demand raw material total amount and the current average power of the current power generation execution power equipment.

[0066] In one embodiment, step S200: setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation; comprising:

[0067] Step S210: calculating the overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor according to the estimated working time;

[0068] Step S220: generating an overload working level according to the overload working time difference, and generating a motor power sampling detection quantity according to the overload working level;

[0069] Step S230: setting a motor power sampling detection time period in a time period exceeding the preset working duration in the estimated working time according to the motor power sampling detection quantity;

[0070] Step S240: Generate an estimated working power curve according to the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

[0071] In this embodiment, after obtaining the estimated working time, the overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated to determine whether the normal working time will be exceeded. The preset working duration is the normal working time of the currently used motor. If it exceeds the preset working duration, it is an overload operation. Therefore, the overload working time difference is calculated first to facilitate the subsequent judgment of whether the motor failure is likely to occur in the time period corresponding to the overload working time difference. Then, the overload working time difference is compared with the pre-stored standard overload time difference, and the standard overload time difference that is the same as the overload working time difference is selected and recorded as the target overload time difference. There are multiple standard overload time differences, each of which corresponds to a different standard working level. Then, the standard working level corresponding to the target overload time difference is recorded as the overload working level. Then, the numerical value corresponding to the overload working level is set as the motor power sampling detection quantity, that is, the overload working level is generated according to the overload working time difference, and the motor power sampling detection quantity is generated according to the overload working level. Then, based on the fact that the probability of a failure occurring during overload operation is greater than the probability of a failure occurring during the normal working time period, the method of performing sampling detection during the normal working time period in the prior art is not adopted. This application sets a motor power sampling detection time period in the time period that exceeds the preset working duration in the estimated working time, and sets the number of the motor power sampling detection time periods to the motor power sampling detection quantity. Finally, an estimated working power curve is generated according to the estimated working time, the current average power of the current power generation executing power equipment, and the total amount of raw materials required for the current power generation.

[0072] Specifically, the estimated power curve is generated by a preset power prediction neural network model. The power prediction neural network model matches the currently used motor, that is, one currently used motor corresponds to one power prediction neural network model, and of course, multiple motors may correspond to one power prediction neural network model. The power prediction neural network model first obtains the power data of the currently used motor in the past use process, and uses the obtained power data as a sample, then removes outliers and noise to ensure data quality, and then extracts power-related features, such as working time, average power, real-time power, average current, real-time voltage, real-time raw material demand and other features, and standardizes or normalizes the above data to meet the input requirements of the neural network. A neural network architecture suitable for time series prediction is selected, such as any one of a multilayer perceptron, a recurrent neural network, a long short-term memory network or a gated recurrent unit, which can be set by technical personnel in this field, and then the number of network layers, the number of neurons, the activation function, the loss function and the optimizer are determined, and finally the power prediction neural network model is obtained by training based on the above sample data. Based on the power prediction neural network model, when the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation are obtained, an estimated working power curve can be quickly generated, thereby providing accurate data reference for subsequent motor equipment fault detection and diagnosis.

[0073] In one embodiment, step S300: obtaining the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, and calculating the motor power difference value with the estimated working power curve according to the real-time motor working data; comprising:

[0074] Step S310: acquiring real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, splitting the real-time motor working data according to a sampling time interval, and generating a plurality of sampled motor working data, wherein the sampling time interval is preset;

[0075] Step S320: generating motor sampled power curves respectively according to the sampled motor working data, wherein the number of motor power curves used is multiple, and each motor sampled power curve corresponds to an estimated motor power curve in the estimated working power curve;

[0076] Step S330: calculating the actual change slope of each motor power curve and the estimated change slope of the estimated motor power curve, wherein one average change slope corresponds to one motor sampled power curve;

[0077] Step S340: determining whether there is an actual change slope greater than or equal to the fault fluctuation slope among the actual change slopes, wherein the fault switching slope is pre-stored;

[0078] Step S350: if the judgment is yes, then generate a current motor fault warning, and send the current motor fault warning to the motor maintenance management body;

[0079] Step S360: If the judgment is no, then calculating the real-time average slope according to each of the actual change slopes, and calculating the estimated average slope according to each of the estimated change slopes;

[0080] Step S370: Generate a motor power difference value according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula:

[0081]

[0082] Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

[0083] In this embodiment, the sampling time interval is pre-set, such as 10 seconds. Through the setting of the sampling time interval, the real-time motor working data is evenly divided by the sampling time interval, that is, the real-time motor working data of the current power generation executing power equipment within the motor power sampling detection time period is obtained, the real-time motor working data is split according to the sampling time interval, and after generating multiple sampled motor working data, the number of the sampled motor working data is n, and then, the motor sampling power curve is generated according to each of the sampled motor working data, wherein the number of power curves adopted by the motor is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve. After obtaining the actual motor working data, the motor sampling power curve can be generated, and the power curve segment corresponding to the estimated working power curve of each motor sampling power curve is screened out according to the corresponding time point, which is the estimated motor power curve. Next, in order to accurately determine whether there is a fault, the actual change slope of the power curve adopted by each motor and the estimated change slope of the estimated motor power curve are first calculated, and then, it is determined whether there is an actual change slope greater than or equal to the fault fluctuation slope among the actual change slopes, wherein the fault toggle slope is pre-stored; if it is determined to be yes, it means that a large fluctuation has occurred at this time, and the fluctuation exceeds the normal range, and the internal fault problem of the motor may occur during this time period, so the current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body. If it is determined to be no, the real-time average slope is calculated according to each actual change slope, and the estimated average slope is calculated according to each estimated change slope; and, by comprehensively considering various factors, specifically by generating a motor power difference value according to each actual change slope, each estimated change slope, the real-time average slope and the estimated average slope, the motor power difference value is used to measure whether the power of the motor operation is abnormal, and then determine whether there is a fault problem.

[0084] In one embodiment, the determining whether the motor power difference value is greater than or equal to a pre-stored standard power difference value further includes:

[0085] Step S510: if it is determined that the motor power difference value is less than the pre-stored standard power difference value, then obtaining a pre-stored associated maintenance component, wherein the associated maintenance component is pre-associated with the currently used motor;

[0086] Step S520: obtaining the vibration data of the associated components of the associated maintenance components within the motor power sampling detection time period based on a preset vibration detection sensor;

[0087] Step S530: extracting the normal coordinated vibration frequency in the associated vibration data, and recording the remaining data in the associated vibration data after extracting the normal coordinated vibration frequency as abnormal fluctuation frequency data;

[0088] Step S540: determining whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data;

[0089] Step S550: if the judgment is yes, a motor-related collaborative warning is generated, and the motor-related collaborative warning is sent to the motor maintenance management subject, and is used to prompt the motor maintenance management subject to perform maintenance on the currently used motor and the associated maintenance components in the current power generation execution power equipment;

[0090] Step S560: if the judgment is no, then generate an estimated operating temperature of the associated component according to the estimated motor operating time, obtain the real-time operating temperature of the associated maintenance component, and calculate the operating excess temperature at which the estimated operating temperature of the associated component exceeds the real-time operating temperature;

[0091] Step S570: generating external temperature excitation data according to the working over-value temperature, applying external excitation to the associated maintenance component according to the external temperature excitation data, and acquiring vibration feedback frequency data of the associated maintenance component;

[0092] Step S580: determining whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data;

[0093] Step S590: If the judgment is yes, a motor-related coordination warning is generated, and the motor-related coordination warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to inspect the currently used motor and the associated maintenance components in the current power generation execution power equipment; if the judgment is no, a motor-related coordination normal indication is generated.

[0094] In this embodiment, in order to accurately determine whether the motor has a fault, when it is determined that the motor power difference value is less than the pre-stored standard power difference value, it is not directly determined that there is no fault, but further detects whether the associated components that are easily affected by the motor fault are normal. If the associated components are normal, the motor is also normal. If the associated components are abnormal, the motor may have a problem. Specifically, the pre-stored associated maintenance components are first obtained, wherein the associated maintenance components are pre-associated with the currently used motor. In this embodiment, the associated maintenance component is the base of the coal mill in the thermal power generator set. The motor of the coal mill is connected to the reducer in a transmission manner, and the reducer is installed in the base. Specifically, the reducer is accommodated in the lower part of the base. If the motor fails, the reducer will inevitably be affected. Considering that the reducer is generally an integrated device, considering the high cost, or it is inconvenient to integrate a sensor used for detection separately, and the base is more convenient to install the sensor, the associated maintenance component is pre-set to facilitate the accurate judgment of whether the motor is normal through the associated maintenance component. In this embodiment, the motor refers to the coal mill motor in the coal mill. Of course, different associated maintenance components can be set according to different motors. This application is only an example and not a limitation. Next, based on the preset vibration detection sensor, the associated component vibration data of the associated maintenance component within the motor power sampling detection time period is obtained; the conventional coordinated vibration frequency in the associated vibration data is extracted, and the remaining data in the associated vibration data after the conventional coordinated vibration frequency is extracted is recorded as abnormal fluctuation frequency data; it is determined whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data; wherein the abnormal fluctuation frequency threshold is pre-set, specifically the fluctuation frequency set by technicians in this field in advance through experiments, such as the fluctuation frequency caused by part breakage. Further, if it is determined to be yes, a motor-associated coordinated warning is generated, and the motor-associated coordinated warning is sent to the motor maintenance management subject, and is used to prompt the motor maintenance management subject to perform maintenance on the currently used motor and the associated maintenance component in the current power generation execution power equipment. In order to make a more accurate judgment, if the judgment is no, the estimated operating temperature of the related components is generated based on the estimated motor working time, wherein the generation of the estimated operating temperature is achieved by reference to pre-stored historical data. It should be noted that the estimated operating temperature is generally a temperature range.Furthermore, the real-time operating temperature of the associated maintenance component is obtained, and the operating excess temperature at which the estimated operating temperature of the associated component exceeds the real-time operating temperature is calculated; then, external temperature excitation data is generated according to the operating excess temperature, external excitation is applied to the associated maintenance component according to the external temperature excitation data, and vibration feedback frequency data of the associated maintenance component is obtained; wherein, the external temperature excitation data includes but is not limited to hot water excitation, and the external temperature excitation data is used to simulate the operating temperature under the highest workload, and to achieve advance simulation to prevent subsequent direct problems from causing large losses and reduced work efficiency, and then, determine whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data; if the judgment is yes, a motor-related collaborative warning is generated, and the motor-related collaborative warning is sent to the motor maintenance management subject, and is used to prompt the motor maintenance management subject to perform maintenance on the currently used motor in the current power generation execution power equipment and the associated maintenance component; if the judgment is no, a motor-related collaborative normal indication is generated, thereby achieving accurate motor fault maintenance and diagnosis.

[0095] In one embodiment, Figure 2 As shown, a system for diagnosing motor operation faults of electric power equipment is provided, the system comprising:

[0096] A motor working time generation module is used to obtain the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generate the total amount of raw materials required for the current power generation according to the basic data of the power equipment and the current power generation demand, and generate the estimated motor working time according to the total amount of raw materials required for the current power generation;

[0097] A motor working curve generating module, used for setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation;

[0098] A motor power difference generating module, used for obtaining the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, and calculating the motor power difference value with the estimated working power curve according to the real-time motor working data;

[0099] The motor fault inspection and repair judgment module is used to judge whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is judged to be yes, a current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to inspect the currently used motor in the current power generation execution power equipment.

[0100] In one embodiment, the motor working time generation module is further used for:

[0101] Obtain the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, obtain the current motor type of the motor currently used in the current power generation executing power equipment and the actual service life of the motor currently used according to the basic data of the power equipment; obtain the standard service life of the motor currently used according to the current motor type; obtain the number of motor maintenance and abnormal shutdown times of the motor currently used in the actual service life; generate the current power equipment wear coefficient according to the actual service life, standard service life, motor maintenance times and abnormal shutdown times based on the following formula:

[0102]

[0103] Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns;

[0104] Obtain standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated; generate the total amount of raw materials for current power generation demand based on the total amount of power generation raw materials to be evaluated and the wear coefficient of the current power equipment; generate an estimated motor working time based on the total amount of raw materials for current power generation demand and the current average power of the current power generation execution power equipment, wherein the current average power is preset.

[0105] In one embodiment, the motor working curve generating module is further used for:

[0106] The overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated based on the estimated working time; the overload working level is generated based on the overload working time difference, and the motor power sampling detection quantity is generated based on the overload working level; the motor power sampling detection time period is set in the time period in which the estimated working time exceeds the preset working duration based on the motor power sampling detection quantity; the estimated working power curve is generated based on the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

[0107] In one embodiment, the motor power difference generation module is further used for:

[0108] Acquire the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, split the real-time motor working data according to the sampling time interval, and generate multiple sampled motor working data, wherein the sampling time interval is preset; generate motor sampling power curves according to each of the sampled motor working data, wherein the number of the motor adopted power curves is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve; calculate the actual change slope of each of the motor adopted power curves and the estimated change slope of the estimated motor power curve, wherein , one of the average change slopes corresponds to one motor sampling power curve; judging whether there is an actual change slope greater than or equal to the fault fluctuation slope among the actual change slopes, wherein the fault toggle slope is pre-stored; if the judgment is yes, generating a current motor fault warning, and sending the current motor fault warning to the motor maintenance management body; if the judgment is no, calculating a real-time average slope according to each of the actual change slopes, and calculating an estimated average slope according to each of the estimated change slopes; generating a motor power difference value according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula:

[0109]

[0110] Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

[0111] The motor fault inspection and repair judgment module is also used for: if it is judged that the motor power difference value is less than the pre-stored standard power difference value, then obtaining the pre-stored associated inspection component, wherein the associated inspection component is pre-associated with the currently used motor; obtaining the associated component vibration data of the associated inspection component within the motor power sampling detection time period based on a preset vibration detection sensor; extracting the conventional coordinated vibration frequency in the associated vibration data, and recording the remaining data in the associated vibration data after extracting the conventional coordinated vibration frequency as abnormal fluctuation frequency data; judging whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data; if the judgment is yes, generating a motor-associated coordination warning, and sending the motor-associated coordination warning to the motor maintenance management subject, and used to prompt the motor maintenance management subject to perform an abnormal operation on the currently used motor and the associated motor in the current power generation execution power equipment. The maintenance component is overhauled; if the judgment is no, an estimated operating temperature of the associated component is generated according to the estimated motor working time, the real-time operating temperature of the associated maintenance component is obtained, and the operating excess temperature of the estimated operating temperature of the associated component exceeding the real-time operating temperature is calculated; external temperature excitation data is generated according to the operating excess temperature, external excitation is applied to the associated maintenance component according to the external temperature excitation data, and vibration feedback frequency data of the associated maintenance component is obtained; it is judged whether there is a pre-stored abnormal fluctuation frequency threshold in the abnormal fluctuation frequency data; if the judgment is yes, a motor-related collaborative warning is generated, and the motor-related collaborative warning is sent to the motor maintenance management subject, and is used to prompt the motor maintenance management subject to overhaul the currently used motor in the current power generation execution power equipment and the associated maintenance component; if the judgment is no, a motor-related collaborative normal indication is generated.

[0112] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned method for diagnosing motor operation faults of electric power equipment when executing the computer program.

[0113] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for diagnosing motor operation faults of electric power equipment.

[0114] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0115] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for diagnosing motor operation faults of electric power equipment, characterized in that: The method comprises: Obtain current power generation demand and basic data of power equipment of current power generation executing power equipment, generate the total amount of raw materials of current power generation demand according to the basic data of power equipment and current power generation demand, and generate estimated motor working time according to the total amount of raw materials of current power generation demand; set the motor power sampling detection time period according to the estimated working time, and generate an estimated working power curve according to the estimated working time and the total amount of raw materials of current power generation demand; obtain real-time motor working data of the current power generation executing power equipment within the motor power sampling detection time period, calculate the motor power difference value with the estimated working power curve according to the real-time motor working data; judge whether the motor power difference value is greater than or equal to the pre-stored standard power difference value, if judged as yes, generate a current motor fault warning, send the current motor fault warning to the motor maintenance management subject, and use it to prompt the motor maintenance management subject to repair the currently used motor in the current power generation executing power equipment.

2. The method for diagnosing motor operation faults of electric power equipment according to claim 1, characterized in that: Obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generating the total amount of raw materials of the current power generation demand according to the basic data of the power equipment and the current power generation demand, and generating the estimated motor working time according to the total amount of raw materials of the current power generation demand; including: Obtain the current power generation demand and the basic data of the power equipment for the current power generation executing power equipment, and obtain the current motor type and the actual service life of the motor currently in use in the current power generation executing power equipment according to the basic data of the power equipment; obtain the standard service life of the motor currently in use according to the current motor type; obtain the number of motor maintenance and abnormal shutdown times of the motor currently in use during the actual service life; The current electric equipment wear coefficient is generated based on the actual service life, standard service life, motor maintenance times and abnormal shutdown times according to the following formula: Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns; Obtain standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated; generate the total amount of raw materials for current power generation demand based on the total amount of power generation raw materials to be evaluated and the wear coefficient of the current power equipment; generate an estimated motor working time based on the total amount of raw materials for current power generation demand and the current average power of the current power generation execution power equipment, wherein the current average power is preset.

3. The method for diagnosing motor operation faults of electric power equipment according to claim 1, characterized in that: Setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation; include: The overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated based on the estimated working time; the overload working level is generated based on the overload working time difference, and the motor power sampling detection quantity is generated based on the overload working level; the motor power sampling detection time period is set in the time period in which the estimated working time exceeds the preset working duration based on the motor power sampling detection quantity; the estimated working power curve is generated based on the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

4. The method for diagnosing motor operation faults of electric power equipment according to claim 1, characterized in that: Acquiring the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, and calculating the motor power difference value between the real-time motor working data and the estimated working power curve; including: Acquire the real-time motor working data of the current power generation executing electric equipment within the motor power sampling detection time period, split the real-time motor working data according to the sampling time interval, and generate multiple sampled motor working data, wherein the sampling time interval is preset; generate motor sampling power curves according to each of the sampled motor working data, wherein the number of the motor adopted power curves is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve; calculate the actual change slope of each motor adopted power curve and the estimated change slope of the estimated motor power curve, wherein one average change slope corresponds to one motor sampling power curve; determine whether there is an actual change slope greater than or equal to the fault fluctuation slope in each of the actual change slopes, wherein the fault toggle slope is pre-stored; if the judgment is yes, generate a current motor fault warning, and send the current motor fault warning to the motor maintenance management subject; if the judgment is no, calculate the real-time average slope according to each of the actual change slopes, and calculate the estimated average slope according to each of the estimated change slopes; The motor power difference value is generated according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula: Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

5. A power equipment motor operation fault diagnosis system, characterized in that: The system comprises: A motor working time generation module is used to obtain the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, generate the total amount of raw materials required for the current power generation according to the basic data of the power equipment and the current power generation demand, and generate the estimated motor working time according to the total amount of raw materials required for the current power generation; A motor working curve generating module, used for setting a motor power sampling detection time period according to the estimated working time, and generating an estimated working power curve according to the estimated working time and the total amount of raw materials required for current power generation; A motor power difference generating module, used for obtaining the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, and calculating the motor power difference value with the estimated working power curve according to the real-time motor working data; The motor fault inspection and repair judgment module is used to judge whether the motor power difference value is greater than or equal to the pre-stored standard power difference value. If it is judged to be yes, a current motor fault warning is generated, and the current motor fault warning is sent to the motor maintenance management body, and is used to prompt the motor maintenance management body to inspect the currently used motor in the current power generation execution power equipment.

6. The electric power equipment motor operation fault diagnosis system according to claim 5, characterized in that: The motor working time generation module is also used for: Obtaining the current power generation demand and the basic data of the power equipment of the current power generation executing power equipment, and obtaining the current motor type and the actual service life of the motor currently used in the current power generation executing power equipment according to the basic data of the power equipment; Acquire the standard service life of the currently used motor according to the current motor type; Obtain the number of motor maintenance and abnormal shutdowns of the currently used motor during the actual service life; The current electric equipment wear coefficient is generated based on the actual service life, standard service life, motor maintenance times and abnormal shutdown times according to the following formula: Among them, P is the current wear coefficient of the power equipment, T is the actual service life, Re is the number of motor maintenance, Tsd is the standard service life, Ar is the pre-stored fixed maintenance coefficient, and C is the number of abnormal shutdowns; Obtain standard power equipment corresponding to the current power generation demand, wherein the total amount of standard power generation raw materials corresponding to the standard power equipment is the total amount of power generation raw materials to be evaluated; generate the total amount of raw materials for current power generation demand based on the total amount of power generation raw materials to be evaluated and the wear coefficient of the current power equipment; generate an estimated motor working time based on the total amount of raw materials for current power generation demand and the current average power of the current power generation execution power equipment, wherein the current average power is preset.

7. The electric power equipment motor operation fault diagnosis system according to claim 6, characterized in that: The motor working curve generating module is also used for: The overload working time difference of the estimated working time exceeding the preset working duration of the currently used motor is calculated based on the estimated working time; the overload working level is generated based on the overload working time difference, and the motor power sampling detection quantity is generated based on the overload working level; the motor power sampling detection time period is set in the time period in which the estimated working time exceeds the preset working duration based on the motor power sampling detection quantity; the estimated working power curve is generated based on the estimated working time, the current average power of the current power generation executing power equipment and the total amount of raw materials required for current power generation.

8. The electric power equipment motor operation fault diagnosis system according to claim 7, characterized in that: The motor power difference generation module is also used for: Acquire the real-time motor working data of the current power generation executing electric power equipment within the motor power sampling detection time period, split the real-time motor working data according to the sampling time interval, and generate multiple sampled motor working data, wherein the sampling time interval is preset; generate motor sampling power curves according to each of the sampled motor working data, wherein the number of the motor adopted power curves is multiple, and each of the motor sampling power curves corresponds to an estimated motor power curve in the estimated working power curve; calculate the actual change slope of each of the motor adopted power curves and the estimated change slope of the estimated motor power curve, wherein , one of the average change slopes corresponds to one motor sampling power curve; judging whether there is an actual change slope greater than or equal to the fault fluctuation slope among the actual change slopes, wherein the fault toggle slope is pre-stored; if the judgment is yes, generating a current motor fault warning, and sending the current motor fault warning to the motor maintenance management body; if the judgment is no, calculating a real-time average slope according to each of the actual change slopes, and calculating an estimated average slope according to each of the estimated change slopes; generating a motor power difference value according to each of the actual change slopes, each of the estimated change slopes, the real-time average slope and the estimated average slope based on the following formula: Among them, Y is the motor power difference value, n is the number of sampled motor working data, Ksi is the i-th estimated change slope, Kci is the i-th actual change slope, Kv2 is the estimated average slope, and Kv1 is the real-time average slope.

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 according to any one of claims 1 to 4 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 according to any one of claims 1 to 4 are implemented.

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