AC motor fault detection method, apparatus and device, and storage medium

Abstract

The embodiment of the invention discloses an alternating current motor fault detection method and device, equipment and a storage medium, and relates to the technical field of fault detection processing. The method comprises the steps of obtaining a to-be-detected current signal of an AC motor; performing fault feature enhancement processing on the to-be-detected current signal by using a preset signal enhancement algorithm to obtain an enhanced current signal; comparing the first amplitude of the enhanced current signal with the second amplitude of a standard current signal based on the fault characteristic frequency of the AC motor; when it is determined that the difference value between the first amplitude and the second amplitude is larger than a preset threshold value, it is determined that the alternating current motor has a fault, and the fault detection can be accurately and efficiently performed on the alternating current motor by comparing the enhanced current signal subjected to fault feature enhancement processing with the standard current signal.

Description

Technical Field

[0001] The present application relates to the technical field of fault detection, and in particular to an AC motor fault detection method, device, equipment and storage medium. Background Art

[0002] AC motors are essential equipment in modern industry and daily life and are widely used in various mechanical transmission and electric drive systems. However, due to long-term operation under high speed, high load and complex vibration environment, AC motors are prone to failure. If the failure is not discovered and handled in time, it will lead to coupling performance degradation and equipment damage, and even cause significant economic losses or casualties. Therefore, timely fault detection of AC motors is crucial.

[0003] In the related technology, AC motor faults are detected through manual experience and artificial intelligence. Among them, the manual experience detection method relies on experience and has poor accuracy. Although the detection method based on artificial intelligence has a good fault diagnosis effect, it requires a large amount of data for training and has high computational complexity. Summary of the invention

[0004] The embodiments of this specification provide an AC motor fault detection method to solve the problems existing in the prior art of using signal analysis and deep learning models to detect AC motor faults.

[0005] To solve the above technical problems, the embodiments of this specification are implemented as follows:

[0006] In a first aspect, an AC motor fault detection method provided by an embodiment of this specification includes:

[0007] Obtaining the current signal to be measured of the AC motor;

[0008] Using a preset signal enhancement algorithm, the fault feature enhancement processing is performed on the current signal to be measured to obtain an enhanced current signal;

[0009] Based on the fault characteristic frequency of the AC motor, comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal;

[0010] When it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold, it is determined that the AC motor has a fault.

[0011] In a second aspect, an AC motor fault detection device provided in an embodiment of the present specification includes:

[0012] An acquisition module, used for acquiring a current signal to be measured of the AC motor;

[0013] An enhanced processing modulus is used to perform fault feature enhancement processing on the current signal to be measured using a preset signal enhancement algorithm to obtain an enhanced current signal;

[0014] A comparison module, configured to compare a first amplitude of the enhanced current signal with a second amplitude of the standard current signal based on a fault characteristic frequency of the AC motor;

[0015] The determination module is used to determine that the AC motor has a fault when it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold.

[0016] In a third aspect, an AC motor fault detection device provided in an embodiment of the present specification includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the AC motor fault detection method in scheme one.

[0017] In a fourth aspect, an embodiment of the present specification provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the AC motor fault detection method in solution one is implemented.

[0018] An embodiment of the present specification realizes the following beneficial effects: using a preset signal enhancement algorithm, the fault feature of the measured current signal is enhanced, based on the fault feature frequency of the AC motor, the first amplitude of the enhanced current signal is compared with the second amplitude of the standard current signal, and when it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold, it is determined that there is a fault in the AC motor, and by comparing the enhanced current signal with the fault feature enhancement processing with the standard current signal, accurate and efficient fault detection of the AC motor can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0020] Figure 1 A flow chart of an AC motor fault detection method provided in an embodiment of this specification;

[0021] Figure 2 A schematic diagram of an application scenario of an AC motor fault detection method provided in an embodiment of this specification;

[0022] Figure 3A schematic diagram of another application scenario of an AC motor fault detection method provided in an embodiment of this specification;

[0023] Figure 4 A schematic diagram of the structure of an AC motor fault detection device provided in an embodiment of this specification;

[0024] Figure 5 A schematic diagram of the structure of an AC motor fault detection device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of one or more embodiments of this specification clearer, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of one or more embodiments of this specification.

[0026] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0027] An AC motor fault detection method provided in the embodiment of the specification is specifically described in conjunction with the accompanying drawings.

[0028] Figure 1 A flowchart of an AC motor fault detection method provided in an embodiment of this specification.

[0029] like Figure 1 As shown, the process may include the following steps:

[0030] Step 110: Acquire the current signal to be measured of the AC motor.

[0031] In the embodiments of this specification, a current sensor is used to collect three-phase current signals when the AC motor is in operation, and the current signals within a preset time period are taken as a group. Multiple groups of current signals under different working conditions can be collected.

[0032] Step 120: using a preset signal enhancement algorithm, perform fault feature enhancement processing on the current signal to be measured to obtain an enhanced current signal.

[0033] In the embodiments of this specification, when an AC motor fails, it will cause abnormal harmonics in the current signal. By analyzing and monitoring the harmonics in the current signal to be measured, the failure of the motor can be discovered in time.

[0034] The fault characteristics of the current signal exist in the harmonics. Since the fundamental frequency of the current signal is too strong, the harmonics of the current signal are submerged. The preset signal enhancement algorithm can be used to enhance the harmonics that characterize the fault characteristics so that they can be displayed in the spectrum.

[0035] By using a preset signal enhancement algorithm, each group of current signals to be measured is subjected to fault feature enhancement processing to obtain multiple enhanced current signals.

[0036] Step 130: Based on the fault characteristic frequency of the AC motor, compare the first amplitude of the enhanced current signal with the second amplitude of the standard current signal.

[0037] In the embodiments of this specification, fault characteristic frequency refers to a specific vibration frequency caused by a component failure during the operation of the current motor. These frequencies can be identified through spectrum analysis and manifested as abnormal changes in the amplitude of certain frequency components.

[0038] When the AC motor is operating normally, its current, vibration and other parameters usually fluctuate within a specific frequency range. The three-phase normal current signal of the AC motor in normal operation is collected, and the three-phase normal current signal is enhanced by a preset signal enhancement algorithm to obtain a normal enhanced current signal after fault feature enhancement processing, and the normal enhanced current signal is used as the standard current signal.

[0039] By comparing the amplitude of the spectrum corresponding to the enhanced current signal at the fault characteristic frequency with the amplitude of the spectrum corresponding to the standard current signal at the fault characteristic frequency, it can be determined whether the current running state of the motor deviates from the normal state.

[0040] Step 140: When it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold, it is determined that the AC motor has a fault.

[0041] In the embodiment of this specification, if the difference between the first amplitude and the second amplitude is less than or equal to the preset threshold, it indicates that the operating state of the AC motor corresponding to the enhanced current signal is normal. If the difference between the first amplitude and the second amplitude is greater than the preset threshold, it indicates that there is a fault in the operating state of the AC motor corresponding to the enhanced current signal. The difference between the amplitudes of multiple groups of normal state signals and the amplitudes of standard signals can be used to calculate the mean μ and the standard deviation σ. The preset threshold can be set to μ+3σ. If the difference between the amplitude of the processed current signal to be measured and the amplitude of the processed standard current signal exceeds μ+3σ, it can be considered that it is faulty.

[0042] In practical applications, the amplitude of each enhanced current signal is compared with the second amplitude of the standard current signal, so as to obtain the operating state of the AC motor under different working conditions.

[0043] It should be understood that the order of some steps in the methods described in one or more embodiments of this specification can be interchanged according to actual needs, or some steps can be omitted or deleted.

[0044] In the embodiments of the present specification, a preset signal enhancement algorithm is used to enhance the fault characteristics of the current signal to be measured. Based on the fault characteristic frequency of the AC motor, the first amplitude of the enhanced current signal is compared with the second amplitude of the standard current signal. When it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold, it is determined that a fault exists in the AC motor. By comparing the enhanced current signal processed with fault characteristic enhancement with the standard current signal, accurate and efficient fault detection of the AC motor can be achieved.

[0045] based on Figure 1 The method in this specification also provides some specific implementation plans of the method, which are described below.

[0046] Optionally, the method described in the embodiments of this specification uses a preset signal enhancement algorithm to perform fault feature enhancement processing on the current signal to be measured to obtain an enhanced current signal, which may specifically include:

[0047] Filtering the current signal to be measured by using a symmetrical mean baseband filtering algorithm to obtain a filtered current signal;

[0048] Performing dimension reduction processing on the filtered current signal using a dimension reduction algorithm to obtain a dimension reduced current signal;

[0049] The energy operator algorithm is used to perform feature enhancement processing on the dimension-reduced current signal to obtain an enhanced current signal.

[0050] In the embodiment of this specification, a symmetrical mean baseband filtering algorithm is used to filter the current signal to be measured, and the three-phase current signal is converted from the time domain to the frequency domain through Fourier transform, the current frequency domain signal is symmetrically averaged, and the frequency domain current signal is converted into the time domain current signal through inverse Fourier transform. The baseband can be filtered and weakened by the symmetrical mean baseband filtering algorithm to achieve the effect of enhancing other frequency parts. The formula of the symmetrical mean baseband filtering algorithm is:

[0051]

[0052] Among them, F i (k) is the Kth Fourier transform coefficient of the i-th phase current, I i is the one-dimensional current time domain signal of the i-th phase, and They are all complex terms, N is the current length, and m×60 is the fundamental frequency index.

[0053] Figure 2A schematic diagram of an application scenario of an AC motor fault detection method provided in an embodiment of this specification.

[0054] like Figure 2 As shown in the figure, a is the current signal to be measured of the AC motor. The fundamental frequency of the signal is too strong, causing the corresponding harmonics of the signal to be submerged. b is the filtered current signal processed by the symmetrical mean fundamental frequency filtering algorithm. It can be seen that the harmonic components of the signal are correspondingly highlighted.

[0055] Dimensionality reduction algorithms are used to reduce the dimension of data, thereby achieving data compression, reducing the complexity of three-phase information processing, removing redundant information, extracting key features, and removing some noise in the data.

[0056] The filtered three-phase current [I u ,I v ,I w ], the signal dimension reduction is performed by unsupervised learning dimensionality reduction method, and the three-phase current is formed into a matrix X = [I u ,I v ,I w ], respectively calculate the original distance of the current signal, the original distance calculation formula is:

[0057] d ij =||X i -X j ||, where i is the number of rows in the matrix X and j is the number of rows in the matrix X. <j。

[0058] Then, a one-dimensional vector Z is randomly generated and the distance of the one-dimensional vector Z is calculated. The one-dimensional vector distance calculation formula is: δ ij =||Z i -Z j ||.

[0059] The signal dimension reduction is achieved by minimizing the direct difference between the high-dimensional distance and the low-dimensional distance through the objective function. The objective function formula is:

[0060] Among them, E is the function that needs to be optimized to ensure that the gap between the original three-phase current and the signal after dimensionality reduction is minimized.

[0061] The signal obtained after dimensionality reduction is a one-dimensional signal. By inputting the reduced current signal into the energy operator algorithm, the instantaneous energy of the signal can be calculated, and the energy of the signal can be enhanced. The fault component in the signal often has higher energy. The generalized energy operator can effectively enhance this part of the signal, thereby highlighting the fault characteristics.

[0062] The one-dimensional feature signal Z is enhanced by the improved energy operator formula, and Z=Y is set. The specific improvement is to and Substitute it into the original energy operator formula. The one-dimensional characteristic signal Z is improved by the improved energy operator to enhance the fault characteristics.

[0063] The original energy operator formula is: ψ(Y(n))=Y(n) 2 -Y'(n)×Y"(n)

[0064] The improved energy operator formula is:

[0065]

[0066] Among them, ψ(Y(n)) is the enhanced current signal, and Y(n) represents the signal point of signal Y at time n.

[0067] By using a symmetric mean baseband filtering algorithm, a dimensionality reduction algorithm and an energy operator algorithm to perform a series of processing on the measured current signal, an enhanced current signal can be obtained, the amplitude of which is enhanced at the fault characteristic frequency, thereby improving the accuracy and sensitivity of fault detection.

[0068] In order to quickly and accurately determine the current operating state of the AC motor, optionally, the fault in the embodiment of this specification is a shaft misalignment fault. Before comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor, the method may further include:

[0069] Based on the inherent properties of the AC motor, the characteristic frequency of the shaft misalignment fault is calculated; the inherent properties at least include fundamental frequency, number of motor pole pairs, slip rate, and number of slots.

[0070] In the embodiments of this specification, different fault types correspond to different fault characteristic frequencies, and the fault characteristic frequencies of different fault types can be calculated in advance. When the fault is a shaft misalignment fault, the characteristic frequency of the shaft misalignment fault is calculated through the inherent properties of the AC motor such as the base frequency, the number of motor pole pairs, the slip rate, the number of slots, etc.

[0071] When a misalignment fault occurs, the air gap magnetic permeability becomes uneven along the circumferential direction, thereby inducing harmonic components in the stator current. The characteristic frequency f of the misalignment fault is e The calculation formula is:

[0072]

[0073] Among them, n d =0 means static eccentricity, n d =1,2,3,... represents dynamic eccentricity, f represents fundamental frequency, p represents the number of pole pairs, R represents the number of slots, s represents the slip rate, k represents an arbitrary constant, and v represents the time harmonic order (v=±1,±3,±5,...).

[0074] Optionally, in the embodiments of this specification, comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor may specifically include:

[0075] Based on Fourier transform, converting the enhanced current signal into an enhanced frequency spectrum, and converting the standard current signal into a standard frequency spectrum;

[0076] Determine a first amplitude corresponding to the fault characteristic frequency in the enhanced spectrum graph, and a second amplitude corresponding to the fault characteristic frequency in the standard spectrum graph;

[0077] The first magnitude is compared to the second magnitude.

[0078] In the embodiment of this specification, the pre-processed enhanced current signal is input into the Fourier transform algorithm to obtain its spectrum representation, that is, the corresponding enhanced spectrum diagram. The enhanced spectrum diagram shows the amplitude and phase information of the enhanced current signal at each frequency.

[0079] The preprocessed standard current signal is input into the Fourier transform algorithm to obtain its spectrum representation, that is, the corresponding standard spectrum diagram. The standard spectrum diagram shows the amplitude and phase information of the standard current signal at each frequency.

[0080] After obtaining the enhanced spectrum and the standard spectrum, it is necessary to determine the position of the fault characteristic frequency in the spectrum and extract the corresponding amplitude. The first amplitude is compared with the second amplitude to determine whether the motor has a fault.

[0081] In practical applications, multiple groups of three-phase normal current signals under normal operating conditions of the AC motor can be collected, and the multiple groups of three-phase normal current signals can be processed to obtain multiple amplitudes at the fault characteristic frequency, and the average value of the multiple amplitudes is used as the second amplitude.

[0082] Figure 3 A schematic diagram of another application scenario of an AC motor fault detection method provided in an embodiment of this specification.

[0083] like Figure 3 As shown, the spectrum diagram shows a standard spectrum diagram (Normal) under normal operating conditions, and three enhanced spectrum diagrams (Misalignment Small, Misalignment Middle, Misalignment Big). F1 to F5 are frequency positions corresponding to the fault characteristic frequencies, respectively. The amplitudes at positions F1 to F5 in the three enhanced spectrum diagrams are significantly higher than the amplitudes at positions F1 to F5 in the standard spectrum diagram, which indicates that there is a fault in the operating state of the AC motor corresponding to the three enhanced spectrum diagrams.

[0084] The frequency spectrum amplitude at the fault frequency is used for judgment. The amplitude of a normal signal at the fault frequency is often very low. Before the test, a large number of normal signals are used to establish a normal amplitude benchmark at the fault frequency. During the test, if there is a significant change in the amplitude, it is a fault.

[0085] Furthermore, increasing the fault frequencies of different fault types can increase the detection of different fault types, such as the fault frequencies of broken rotor bar faults, bearing faults (bearing inner ring fault, bearing outer ring fault, bearing roller damage fault, etc.). By obtaining the fault characteristic frequencies corresponding to different fault types and comparing the amplitudes at different fault characteristic frequencies with the amplitudes at corresponding positions in the standard spectrum diagram, the fault type of the AC motor can be determined.

[0086] In practical applications, the fault characteristics of the current signal to be measured are enhanced by using the symmetric mean baseband filtering algorithm, the dimensionality reduction algorithm and the energy operator algorithm, and the enhanced current signal is converted into an enhanced spectrum diagram, and the standard current signal is converted into a standard spectrum diagram. In the enhanced spectrum diagram, the amplitude corresponding to the fault characteristic frequency is found and recorded as the first amplitude. In the standard spectrum diagram, the amplitude corresponding to the same frequency point is found and recorded as the second amplitude. The difference between the first amplitude and the second amplitude is compared with the preset threshold to determine whether the AC motor has a fault. By comparing the enhanced current signal with the fault characteristic enhancement processing with the standard current signal, accurate and efficient fault detection of the AC motor can be achieved, and the operating reliability and fault diagnosis accuracy of the AC motor can be improved, which is of great significance for ensuring production continuity, reducing maintenance costs and improving production safety.

[0087] Figure 4 This is a schematic diagram of the structure of an AC motor fault detection device proposed in an embodiment of this specification.

[0088] The AC motor fault detection device described in the embodiments of this specification may include:

[0089] An acquisition module 402 is used to acquire a current signal to be measured of the AC motor;

[0090] Enhanced processing module 404, used to perform fault feature enhancement processing on the current signal to be measured by using a preset signal enhancement algorithm to obtain an enhanced current signal;

[0091] A comparison module 406, configured to compare the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor;

[0092] The determination module 408 is configured to determine that a fault exists in the AC motor when it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold.

[0093] Optionally, the method described in the embodiments of this specification uses a preset signal enhancement algorithm to perform fault feature enhancement processing on the current signal to be measured to obtain an enhanced current signal, which may specifically include:

[0094] Filtering the current signal to be measured by using a symmetrical mean baseband filtering algorithm to obtain a filtered current signal;

[0095] Performing dimension reduction processing on the filtered current signal using a dimension reduction algorithm to obtain a dimension reduced current signal;

[0096] The energy operator algorithm is used to perform feature enhancement processing on the dimension-reduced current signal to obtain an enhanced current signal.

[0097] Optionally, the fault described in the embodiment of this specification is a shaft misalignment fault. Before comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor, the device may further include:

[0098] Based on the inherent properties of the AC motor, the characteristic frequency of the shaft misalignment fault is calculated; the inherent properties at least include fundamental frequency, number of motor pole pairs, slip rate, and number of slots.

[0099] Optionally, in the embodiments of this specification, comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor may specifically include:

[0100] Based on Fourier transform, converting the enhanced current signal into an enhanced frequency spectrum, and converting the standard current signal into a standard frequency spectrum;

[0101] Determine a first amplitude corresponding to the fault characteristic frequency in the enhanced spectrum graph, and a second amplitude corresponding to the fault characteristic frequency in the standard spectrum graph;

[0102] The first magnitude is compared to the second magnitude.

[0103] Based on the same idea, the embodiments of this specification also provide a device corresponding to the above method.

[0104] Figure 5 The following is a schematic diagram of the structure of an AC motor fault detection device provided in an embodiment of this specification. Figure 5 As shown, an AC motor fault detection device provided in an embodiment of this specification includes a memory 530, a processor 510 and a computer program 520 stored in the memory, and the processor 510 executes the computer program 520 to implement the AC motor fault detection method described in any of the above embodiments.

[0105] An AC motor fault detection device provided in an embodiment of this specification may include a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the AC motor fault detection method described in any of the above embodiments.

[0106] An embodiment of the present specification provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the AC motor fault detection method described in any of the above embodiments can be implemented.

[0107] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. Figure 5 As for the device shown, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0108] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0109] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0110] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0111] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0112] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0121] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0122] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for detecting an AC motor fault, characterized in that: include: Obtaining the current signal to be measured of the AC motor; Using a preset signal enhancement algorithm, the fault feature enhancement processing is performed on the current signal to be measured to obtain an enhanced current signal; Based on the fault characteristic frequency of the AC motor, comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal; When it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold, it is determined that the AC motor has a fault.

2. The method according to claim 1, characterized in that: The method of performing fault feature enhancement processing on the current signal to be measured by using a preset signal enhancement algorithm to obtain an enhanced current signal specifically includes: Filtering the current signal to be measured by using a symmetrical mean baseband filtering algorithm to obtain a filtered current signal; Performing dimension reduction processing on the filtered current signal by using a dimension reduction algorithm to obtain a dimension reduced current signal; The energy operator algorithm is used to perform feature enhancement processing on the dimension-reduced current signal to obtain an enhanced current signal.

3. The method according to claim 1, characterized in that The fault is a shaft misalignment fault. Before comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor, the method further includes: Based on the inherent properties of the AC motor, the characteristic frequency of the shaft misalignment fault is calculated; the inherent properties at least include fundamental frequency, number of motor pole pairs, slip rate, and number of slots.

4. The method according to claim 1, characterized in that: The comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor specifically includes: Based on Fourier transform, converting the enhanced current signal into an enhanced frequency spectrum, and converting the standard current signal into a standard frequency spectrum; Determine a first amplitude corresponding to the fault characteristic frequency in the enhanced spectrum graph, and a second amplitude corresponding to the fault characteristic frequency in the standard spectrum graph; The first magnitude is compared to the second magnitude.

5. An AC motor fault detection device, characterized in that: include: An acquisition module, used for acquiring a current signal to be measured of the AC motor; An enhanced processing modulus is used to perform fault feature enhancement processing on the current signal to be measured using a preset signal enhancement algorithm to obtain an enhanced current signal; A comparison module, configured to compare a first amplitude of the enhanced current signal with a second amplitude of the standard current signal based on a fault characteristic frequency of the AC motor; The determination module is used to determine that the AC motor has a fault when it is determined that the difference between the first amplitude and the second amplitude is greater than a preset threshold.

6. The device according to claim 5, characterized in that The method of performing fault feature enhancement processing on the current signal to be measured by using a preset signal enhancement algorithm to obtain an enhanced current signal specifically includes: Filtering the current signal to be measured by using a symmetrical mean baseband filtering algorithm to obtain a filtered current signal; Performing dimension reduction processing on the filtered current signal using a dimension reduction algorithm to obtain a dimension reduced current signal; The energy operator algorithm is used to perform feature enhancement processing on the dimension-reduced current signal to obtain an enhanced current signal.

7. The device according to claim 5, characterized in that The fault is a shaft misalignment fault. Before comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor, the device further includes: Based on the inherent properties of the AC motor, the characteristic frequency of the shaft misalignment fault is calculated; the inherent properties at least include fundamental frequency, number of motor pole pairs, slip rate, and number of slots.

8. The device according to claim 5, characterized in that The comparing the first amplitude of the enhanced current signal with the second amplitude of the standard current signal based on the fault characteristic frequency of the AC motor specifically includes: Based on Fourier transform, converting the enhanced current signal into an enhanced frequency spectrum, and converting the standard current signal into a standard frequency spectrum; Determine a first amplitude corresponding to the fault characteristic frequency in the enhanced spectrum graph, and a second amplitude corresponding to the fault characteristic frequency in the standard spectrum graph; The first magnitude is compared to the second magnitude.

9. An AC motor fault detection device, comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 4.

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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