Motor abnormal sound detection method and device

Abstract

The present invention relates to the field of motor manufacturing technology, and provides a method and device for detecting abnormal noise in a motor. The method comprises: obtaining a source vibration signal after the motor is running at steady speed; determining a steady-speed vibration signal segment in the steady-speed running interval and a tail-speed vibration signal segment in the tail-speed running interval in the source vibration signal; determining all frequency multiples in the steady-speed running interval based on the steady-speed vibration signal segment; determining the vibration characteristics at each of the frequency multiples in the tail-speed vibration signal segment, and determining that the motor has abnormal noise when the characteristic value of the vibration characteristic at any frequency multiple exceeds a characteristic threshold. Since the abnormal noise of the motor is caused by the resonance characteristics at the frequency multiples of the motor vibration signal, the present invention can accurately detect the abnormal noise of the motor by detecting the number of order lines and / or resonance energy at the frequency multiples in the tail-speed vibration signal segment in the tail-speed running interval of the motor, and the detection results have good consistency.

Description

Technical Field

[0001] The present invention relates to the technical field of motor manufacturing, and in particular to a method and device for detecting abnormal noise of a motor. Background Art

[0002] During the motor production process, due to factors such as components, processes, and assembly, abnormal noises such as harsh tail sounds and dragging sounds may occur during motor operation, seriously affecting the quality of the motor and the user experience of the corresponding home appliance. Existing methods for detecting abnormal motor noise mostly rely on manual testing on the production line, that is, manual listening to determine whether the motor has abnormal noise. Some high-speed motors are very loud, reaching up to 90 decibels at full speed, which is very harmful to the human ear. Prolonged listening can easily cause fatigue, affecting the quality of detection and leading to inaccurate test results. In addition, manual listening detection methods are highly subjective and manual experience varies greatly. Different people listening to the same motor may obtain different test results, resulting in poor consistency of test results and inability to standardize test standards. Summary of the Invention

[0003] The present invention provides a method and device for detecting abnormal motor sounds, which are used to solve the technical problems in the prior art of manual listening detection resulting in inaccurate detection of abnormal motor sounds and poor consistency of detection results.

[0004] The present invention provides a method for detecting abnormal noise of a motor, comprising the following steps:

[0005] Obtain the source vibration signal after the motor runs at a steady speed;

[0006] Determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal;

[0007] determining all frequency multiples of the steady-speed operation interval based on the steady-speed vibration signal segment;

[0008] The vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, and when a characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold, it is determined that abnormal sound exists in the motor.

[0009] According to a motor abnormal sound detection method provided by the present invention, determining a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal, comprising:

[0010] Determining a stopping time point in a steady speed interval and a stopping time point in a tail speed interval when the motor is running based on the source vibration signal;

[0011] The signal segment before the steady speed interval stop time point is divided into a steady speed vibration signal segment, and the signal segment between the steady speed interval stop time point and the tail speed interval stop time point is divided into a tail speed vibration signal segment.

[0012] According to a motor abnormal sound detection method provided by the present invention, based on the source vibration signal, determining the stopping time point in the steady speed range when the motor is running, the method includes:

[0013] The main frequency of the source vibration signal is detected, and the moment when the main frequency begins to decrease is determined as the stopping time point of the steady speed interval.

[0014] According to a motor abnormal sound detection method provided by the present invention, the main frequency of the source vibration signal is detected, and the moment when the main frequency begins to decrease is determined as the stop time point of the steady speed interval, including:

[0015] Starting from the starting point of the source vibration signal, steady-speed detection segments of a first predetermined duration are selected in sequence, and the first main frequency of the vibration signal in the currently selected steady-speed detection segment is calculated; when the first main frequency is less than the second main frequency of the vibration signal in the previously selected steady-speed detection segment, the starting time of the currently selected steady-speed detection segment is determined as the stop time point of the steady-speed interval.

[0016] According to a motor abnormal sound detection method provided by the present invention, there is an offset time length between the starting time of each currently selected steady-speed detection segment and the starting time of the previously selected steady-speed detection segment, and the offset time length is less than the first predetermined time length.

[0017] According to a motor abnormal sound detection method provided by the present invention, based on the source vibration signal, determining the stopping time point in the tail speed interval when the motor is running, the method includes:

[0018] Starting from the stop time point of the steady speed interval, the vibration energy of the source vibration signal is detected. When the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold, the start time of the currently selected tail speed detection segment is determined as the stop time point of the tail speed interval.

[0019] According to a motor abnormal sound detection method provided by the present invention, starting from the stop time point of the steady speed interval, the vibration energy of the source vibration signal is detected, and when the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold, the start time of the currently selected tail speed detection segment is determined as the stop time point of the tail speed interval, including:

[0020] Starting from the stop time point of the steady speed interval, tail speed detection segments of a second predetermined duration are sequentially selected, and a current vibration energy of the vibration signal in the currently selected tail speed detection segment is calculated; when a ratio of the current vibration energy to the initial vibration energy of the vibration signal in the first tail speed detection segment is less than a ratio threshold, the start time of the currently selected tail speed detection segment is determined as the stop time point of the tail speed interval.

[0021] According to a motor abnormal sound detection method provided by the present invention, based on the steady-speed vibration signal segment, all multiple frequencies of the steady-speed operation range are determined, including:

[0022] performing a Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment;

[0023] Performing a fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram;

[0024] All the multiple frequencies on the Fourier frequency distribution graph are extracted.

[0025] According to a motor abnormal sound detection method provided by the present invention, the vibration characteristics include: the number of order lines and / or resonance energy, and determining the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment includes:

[0026] generating a spectrogram corresponding to the tail speed vibration signal segment;

[0027] Generate an order line distribution diagram based on the spectrogram, count the number of order lines at each frequency doubling in the order line distribution diagram; and / or calculate the resonance energy at the frequency doubling in the spectrogram.

[0028] According to a motor abnormal sound detection method provided by the present invention, an order line distribution diagram is generated based on the spectrogram, and the number of order lines at each frequency octave is counted in the order line distribution diagram, including:

[0029] Filtering and denoising the spectrogram;

[0030] Performing edge detection on the filtered and denoised spectrogram to obtain the order line distribution diagram;

[0031] The number of order lines is counted at the multiple frequency positions along the time axis of the order line distribution diagram.

[0032] According to a motor abnormal sound detection method provided by the present invention, calculating the resonance energy at the frequency doubling in the spectrogram includes:

[0033] Performing bandpass filtering on the waveform at the frequency doubling in the spectrogram;

[0034] Calculate the statistical value of the amplitude of the filtered waveform and determine the statistical value as the resonance energy at the corresponding frequency doubling.

[0035] The present invention also provides a motor abnormal sound detection device, comprising the following modules:

[0036] A source vibration signal acquisition module is used to obtain the source vibration signal after the motor runs at a steady speed;

[0037] a signal segment determination module, configured to determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal;

[0038] a frequency multiplication determination module, configured to determine all frequency multiplications in the steady-speed operation interval based on the steady-speed vibration signal segment;

[0039] The abnormal sound judgment module is used to determine the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment, and judge that the motor has abnormal sound when the characteristic value of the vibration characteristic at any multiple frequency exceeds the characteristic threshold.

[0040] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the program, the motor abnormal sound detection method as described above is implemented.

[0041] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the motor abnormal sound detection method described in any one of the above is implemented.

[0042] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-described methods for detecting abnormal motor sound.

[0043] The present invention provides a method and device for detecting abnormal motor sound, which obtains a source vibration signal after the motor is running at steady speed; determines a steady-speed vibration signal segment in the steady-speed running interval and a tail-speed vibration signal segment in the tail-speed running interval in the source vibration signal; determines all the frequency multiples in the steady-speed running interval based on the steady-speed vibration signal segment; determines the vibration characteristics at each of the frequency multiples in the tail-speed vibration signal segment, and determines that the motor has abnormal sound when the characteristic value of the vibration characteristics at any frequency multiple exceeds the characteristic threshold. Since the abnormal sound of the motor is caused by the resonance characteristics at the frequency multiples of the motor vibration signal, and in the tail-speed running interval, the motor that produces abnormal sound is more likely to resonate at the frequency multiples and more likely to produce abnormal vibration characteristics, the abnormal sound of the motor can be accurately detected by detecting the vibration characteristics at the frequency multiples of the tail-speed vibration signal segment in the tail-speed running interval of the motor, and the detection results have good consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is one of the flow charts of the motor abnormal sound detection method provided by the present invention.

[0046] Figure 2 This is the second flow chart of the motor abnormal sound detection method provided by the present invention.

[0047] Figure 3 This is the third flow chart of the motor abnormal sound detection method provided by the present invention.

[0048] Figure 4 It is a schematic diagram of a spectrogram generated in the motor abnormal sound detection method provided by the present invention.

[0049] Figure 5 It is a schematic diagram of the spectrogram after filtering and denoising in the motor abnormal sound detection method provided by the present invention.

[0050] Figure 6 It is an order line distribution diagram generated based on the spectrogram in the motor abnormal sound detection method provided by the present invention.

[0051] Figure 7 This is the fourth flow chart of the motor abnormal sound detection method provided by the present invention.

[0052] Figure 8 It is a structural schematic diagram of the motor abnormal sound detection device provided by the present invention.

[0053] Figure 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0055] It should be noted that, in the description of the present invention, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising the elements. Terms such as "upper" and "lower" indicate positions or relationships based on those shown in the accompanying drawings and are intended solely to facilitate the description of the present invention and simplify the description. They are not intended to indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation, and are therefore not to be construed as limitations on the present invention. Unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be broadly construed, for example, to mean fixed, removable, or integral; mechanical or electrical; direct or indirect through an intermediary; or internal communication between two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] The terms "first," "second," and the like in the present invention are used to distinguish similar objects, and are not used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, such that embodiments of the present invention can be implemented in orders other than those illustrated or described herein. Furthermore, the objects distinguished by "first," "second," and the like generally refer to a class of objects, and do not limit the number of objects. For example, the first object may be one or more.

[0057] In related technologies, abnormal noise detection of motors mainly relies on manual listening. However, long-term listening can easily cause fatigue, affecting the detection quality and leading to inaccurate detection results. In addition, the manual listening detection method is highly subjective and manual experience varies greatly. Different people may get different detection results when listening to the same motor, resulting in poor consistency in the detection results and the inability to unify the detection standards.

[0058] In view of the above technical problems existing in the existing related technologies, the embodiment of the present invention provides a method for detecting abnormal noise of a motor, such as Figure 1 As shown, the process includes the following steps S110 to S140.

[0059] Step S110: Acquire the source vibration signal after the motor reaches steady speed. After the motor is powered on, it reaches a steady speed, i.e., it runs at a stable rotational speed. A vibration sensor (e.g., an accelerometer) can be used to acquire the vibration signal of the motor after it enters the steady speed state. In this step, the source vibration signal is obtained by acquiring the vibration signal of the motor after it enters the steady speed state from the vibration sensor.

[0060] Specifically, before starting the motor, the system places it in a rubber sealant and then uses a flexible clamping mechanism to clamp the motor from both sides. This effectively prevents abnormal motor shaking caused by the start-stop torque during startup and shutdown, ensuring more accurate source vibration signals. After the motor is tightened, a vibration sensor is placed in contact with the motor surface to collect vibration signals after the motor enters a steady-state operation.

[0061] Step S120: Determine the steady-speed vibration signal segment of the motor's steady-speed operation interval and the tail-speed vibration signal segment of the tail-speed operation interval in the source vibration signal. The steady-speed operation interval is the interval in which the motor is in a steady-speed operation state, and the tail-speed operation interval is the operating interval in which the motor's rotor continues to rotate due to inertia after power is removed from the motor. Because this embodiment requires detecting abnormal noise from the motor in the tail-speed operation interval, it is necessary to divide the vibration signal segments of each of the steady-speed operation interval and the tail-speed operation interval to facilitate subsequent processing of each vibration signal segment.

[0062] Step S130: Based on the steady-speed vibration signal segment, all the frequency multiples in the steady-speed operation range are determined. The frequency multiples of vibration are frequency components in the vibration signal whose frequencies are integer multiples of the fundamental frequency. They are an important indicator in the diagnosis of mechanical faults or abnormalities. The fundamental frequency (also called the main frequency) is the main frequency component of the vibration of the mechanical equipment (motor). The abnormal sounds of the motor (such as harsh tail sounds and dragging sounds) are all caused by the resonance characteristics at the frequency multiples. Therefore, the abnormal sounds of the motor can be detected by frequency multiples. Moreover, in this step, only the steady-speed vibration signal segment is used to determine the frequency multiples. Compared with using the entire source vibration signal to determine the frequency multiples, the frequency multiples can be determined more quickly.

[0063] Step S140: Determine the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment. When the characteristic value of the vibration characteristics at any multiple frequency exceeds the characteristic threshold, it is determined that the motor has abnormal sound. The vibration characteristics may be vibration characteristics such as amplitude, vibration energy, and order line.

[0064] The characteristic threshold can be set based on actual conditions. Specifically, for a certain model of motor, a batch of normal samples (motors without abnormal noise) and a batch of abnormal samples (motors with abnormal noise) can be selected. The vibration characteristic distribution of each type of sample at the frequency doubling can be calculated. The characteristic threshold can be dynamically adjusted based on the principle of priority detection rate or priority accuracy. For example, if the vibration characteristic is order lines, the simplest method for determining the priority detection rate of the order line number threshold is: if the number of order lines at the frequency doubling of the abnormal samples is greater than 8, then the order line number threshold can be determined as 8.

[0065] In this embodiment of the motor abnormal sound detection method, abnormal motor sound is caused by the resonance characteristics of the motor vibration signal at the frequency multiplication. Furthermore, in the tail-speed operating range, the motor generating abnormal sound is more likely to resonate at the frequency multiplication and produce more order lines. Therefore, by detecting the vibration characteristics of the tail-speed vibration signal segment at the frequency multiplication in the tail-speed operating range, abnormal motor sound can be accurately detected with good consistency. Furthermore, the entire detection process does not require manual listening, avoiding damage to the human ear when the motor is running at full speed.

[0066] In some embodiments, step S120 specifically includes the following steps S121 and S122.

[0067] Step S121: Based on the source vibration signal, determine the stopping time points in the steady speed interval and the stopping time points in the tail speed interval during motor operation. Because the motor's main vibration frequency changes significantly from the steady speed interval to the tail speed interval after power failure, in this step, the point where the main frequency changes in the source vibration signal can be detected as the stopping time point in the steady speed interval, and the stopping time point in the tail speed interval can be the point where vibration stops.

[0068] Step S122: dividing the signal segment before the steady speed interval stop time point into a steady speed vibration signal segment, and dividing the signal segment between the steady speed interval stop time point and the tail speed interval stop time point into a tail speed vibration signal segment.

[0069] In this embodiment, by detecting the stopping time points of the steady speed interval and the tail speed interval in the source vibration signal, the source vibration signal can be accurately divided into the steady speed vibration signal segment and the tail speed vibration signal segment.

[0070] In some embodiments, determining the steady-speed interval stop time point during motor operation based on the source vibration signal in step S121 specifically includes: detecting the dominant frequency of the source vibration signal, and determining the moment when the dominant frequency begins to decrease as the steady-speed interval stop time point. When the motor is in the steady-speed operation range, the dominant frequency of the source vibration signal remains substantially unchanged. After the motor stops and enters the tail-speed operation range, the dominant frequency of the corresponding source vibration signal gradually decreases due to the gradual decrease in speed. Therefore, the moment when the dominant frequency begins to decrease can be determined as the steady-speed interval stop time point.

[0071] Specifically, the moment when the dominant frequency begins to decrease can be detected using (but not limited to) the following method: starting from the starting point of the source vibration signal, a first predetermined duration steady-speed detection segment is sequentially selected, and the first dominant frequency of the vibration signal within the currently selected steady-speed detection segment is calculated. If the first dominant frequency is less than the second dominant frequency of the vibration signal within the previously selected steady-speed detection segment, the start time of the currently selected steady-speed detection segment is determined as the steady-speed interval stop time point. That is, using a mechanism similar to a sliding window, each steady-speed detection segment of the first predetermined duration is treated as a window, and the first dominant frequency corresponding to the current steady-speed detection segment is calculated. If the first dominant frequency is less than the second dominant frequency of the vibration signal within the previously selected steady-speed detection segment, it indicates that the current steady-speed detection segment has entered the tail-speed vibration signal segment region. Therefore, the start time of the current steady-speed detection segment is determined as the steady-speed interval stop time point.

[0072] In this embodiment, a mechanism similar to a sliding window is used to sequentially calculate the dominant frequency of the vibration signal within each steady-speed detection segment. By detecting when the dominant frequency decreases, the stopping time of the steady-speed interval can be quickly determined. The dominant frequency is calculated by calculating the frequency energy distribution of the waveform corresponding to the vibration signal in the steady-speed detection segment and selecting the frequency corresponding to the maximum vibration energy within the frequency energy distribution as the dominant frequency.

[0073] If the steady speed detection segments are connected end to end, the determined steady speed interval stop time point will have a large time error, and the time error is around the first predetermined duration. In order to more accurately determine the steady speed interval stop time point, further, the starting time of each currently selected steady speed detection segment and the starting time of the previously selected steady speed detection segment have an offset duration that is less than the first predetermined duration, that is, there is overlap between the two steady speed detection segments. The first predetermined duration and the offset duration can be set according to actual conditions. The smaller the setting values ​​of the first predetermined duration and the offset duration, the smaller the error, that is, the more accurate the determined steady speed interval stop time point. For example, the first predetermined duration is 150-300 milliseconds, and the offset duration is 15-30 milliseconds.

[0074] Specifically, taking the vibration frequency of the motor when running as 0-5000 Hz, the first predetermined time length as 200 milliseconds, and the offset time length as 20 milliseconds as an example, the steps of determining the stopping time point of the steady speed interval when the motor is running based on the source vibration signal are as follows: Figure 2 As shown, it includes: starting from the starting point of the source vibration signal, taking a 200-ms steady-speed detection segment, that is, the first steady-speed detection segment; calculating the frequency energy distribution of the waveform of the steady-speed detection segment, and selecting the frequency corresponding to the maximum vibration energy within 0~5000Hz as the main frequency; offsetting the starting point of the previous steady-speed detection segment by 20 milliseconds, and again taking a 200-ms steady-speed detection segment as the current steady-speed detection segment; calculating the frequency energy distribution of the waveform of the current steady-speed detection segment, and selecting the frequency corresponding to the maximum vibration energy within 0~5000Hz as the main frequency; judging whether the main frequency is reduced, that is, whether the main frequency corresponding to the current steady-speed detection segment is reduced relative to the main frequency corresponding to the previous steady-speed detection segment, if so, determining the starting time of the current 200-ms steady-speed detection segment as the stop time point of the motor steady-speed interval, otherwise, jumping to the step of offsetting the starting point of the previous steady-speed detection segment by 20 milliseconds, and again taking a 200-ms steady-speed detection segment as the current steady-speed detection segment.

[0075] It can be understood that: when the motor is in the steady-speed operation range, its main frequency remains basically unchanged within the allowable error range (±10Hz). Therefore, when the main frequency decreases by more than the error range, and the difference between the first main frequency and the second main frequency of the vibration signal in the previously selected steady-speed detection section exceeds the error range, it is considered that the main frequency has decreased, that is, the first main frequency is less than the second main frequency.

[0076] In some embodiments, determining the stopping time point of the tail speed interval during motor operation based on the source vibration signal in step S121 includes: starting from the steady speed interval stopping time point, detecting the vibration energy of the source vibration signal, and determining the starting moment of the currently selected tail speed detection segment as the tail speed interval stopping time point when the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold. Since the speed of the motor gradually slows down after entering the tail speed operation interval, the vibration signal of the tail speed vibration signal segment will correspondingly become weaker, that is, the vibration energy will become smaller and smaller. Therefore, the tail speed interval stopping time point can be determined by the characteristic of decreasing vibration energy.

[0077] Specifically, the vibration energy of the source vibration signal can be detected to determine the end-speed interval stop time point using (but not limited to) the following method: starting at the steady-speed interval stop time point, tail-speed detection segments of a second predetermined duration are sequentially selected, and the current vibration energy of the vibration signal within the currently selected tail-speed detection segment is calculated. That is, using a mechanism similar to a sliding window, each tail-speed detection segment of the second predetermined duration is treated as a window, and the current vibration energy corresponding to the current tail-speed detection segment is calculated. The two adjacent tail-speed detection segments can be contiguous or overlap. If the ratio of the current vibration energy to the initial vibration energy of the vibration signal within the first tail-speed detection segment is less than a ratio threshold, the starting moment of the currently selected tail-speed detection segment is determined to be the end-speed interval stop time point.

[0078] It should be noted that in the tail-speed operating range, the motor speed decreases and the vibration signal weakens. Once the vibration signal weakens to a certain extent, even if there is abnormal sound, it is very small, below the critical value that can be tolerated by human hearing, or even inaudible. Therefore, the tail-speed interval stopping time point can be the moment when the vibration energy of the vibration signal decreases to the point where the abnormal sound is less than this critical value. This can reduce the amount of data in the tail-speed vibration signal segment, thereby improving the efficiency of abnormal sound detection. In this embodiment, when the ratio of the current vibration energy to the initial vibration energy of the vibration signal in the first tail-speed detection segment is less than a proportional threshold, it indicates that the current vibration energy has decreased to the point where the abnormal sound is less than the critical value. This proportional threshold can be determined in advance through manual listening when the abnormal sound reaches a tolerable critical value or even becomes inaudible. The vibration energy threshold is then calculated based on the ratio of the vibration energy threshold to the initial vibration energy. For example, the proportional threshold can be 75% to 95%.

[0079] The second predetermined time length can be set according to actual conditions. The smaller the second predetermined time length setting value is, the smaller the error is, that is, the more accurate the determined stop time point in the tail speed interval is. For example, the second predetermined time length is 40-60 milliseconds.

[0080] Specifically, taking the second predetermined time length as 50 milliseconds as an example, the step of determining the stopping time point of the steady speed interval when the motor is running based on the source vibration signal is as follows: Figure 3As shown, it includes: starting from the stop time point of the steady speed interval, taking a 50-ms tail speed detection segment, that is, the first tail speed detection segment, and calculating the initial vibration energy of the vibration signal in the tail speed detection segment; taking the next 50-ms tail speed detection segment as the current tail speed detection segment, and calculating the vibration energy of the vibration signal therein; comparing the vibration energy corresponding to the current tail speed detection segment with the initial vibration energy, and judging whether the ratio of the vibration energy corresponding to the current tail speed detection segment to the initial vibration energy is less than 95%, that is, whether the vibration energy corresponding to the previous tail speed detection segment is less than 95% of the initial vibration energy; if so, determining the starting moment of the current 50-ms tail speed detection segment as the stop time point of the motor tail speed interval; otherwise, jumping to the step of taking the next 50-ms tail speed detection segment as the current tail speed detection segment, and calculating the vibration energy of the vibration signal therein.

[0081] In some embodiments, step S130 specifically includes:

[0082] Performing a Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment.

[0083] Performing Fast Fourier Transform (FFT) on the envelope spectrum to obtain a Fourier frequency distribution diagram.

[0084] All the multiple frequencies on the Fourier frequency distribution graph are extracted.

[0085] In this embodiment, a Fourier frequency distribution diagram is obtained by performing Hilbert transform and fast Fourier transform on the steady-speed vibration signal segment, so that all the frequency multiples can be extracted from the Fourier frequency distribution diagram.

[0086] In some embodiments, the vibration characteristics include: the number of order lines and / or resonance energy, and the step S140 specifically includes:

[0087] Generate the spectrogram corresponding to the tail speed vibration signal segment, such as Figure 4 As shown in FIG, the tail velocity vibration signal segment can be converted into a spectrogram by short-time Fourier transform (STFT), in which the horizontal axis represents time and the vertical axis represents frequency.

[0088] An order line distribution diagram is generated based on the spectrogram, the number of order lines at each frequency doubling is counted in the order line distribution diagram, and / or the resonance energy at the frequency doubling in the spectrogram is calculated.

[0089] Specifically, if Figure 4In the figure, it can be understood that 50Hz is the base frequency (main frequency), and 100Hz, 150Hz, 200Hz and 250Hz are all multiple frequencies. All multiple frequencies may produce resonance bands. Different models of motors have different probabilities of producing resonance bands at different multiple frequencies. For example: Figure 4 In the example, the resonance energy at the 100Hz and 200Hz harmonics is high, creating resonance bands and causing loud noise. However, the resonance energy at the 150Hz and 250Hz harmonics is low, resulting in quiet or even inaudible noise. In practical applications, specific harmonics can be monitored for a specific motor model. This involves calculating the resonance energy at a specific harmonic. This harmonic is the historical harmonic found in the spectrogram when that motor model produced noise during historical testing. This reduces the amount of resonance energy calculation and improves computational efficiency.

[0090] In this embodiment, the number of order lines and resonance energy are calculated simultaneously. Only when both exceed a threshold value is the motor determined to be free of abnormal noise. This calculation not only reveals the motor's order information as it changes with speed but also reveals its resonance characteristics, enabling more accurate detection of abnormal motor noise. Furthermore, key performance data such as the number of order lines, resonance energy, and duration of abnormal noise (the duration of the tail-speed operating range) can be quantified during the detection process, providing a data source for motor fault analysis.

[0091] In some embodiments, generating an order line distribution graph based on the spectrogram, and counting the number of order lines at each octave in the order line distribution graph includes:

[0092] The spectrogram is filtered and denoised to obtain a filtered and denoised spectrogram. Specifically, the spectrogram may be subjected to meijering filtering to remove interference from certain shapes (such as burrs) in the spectrogram, and fast non-local average denoising may be performed. Figure 5 As shown, relative to Figure 4 , the noise points in the filtered and denoised spectrogram are significantly reduced, which makes it possible to generate a more accurate order line distribution diagram based on the filtered and denoised spectrogram.

[0093] The filtered and denoised spectrogram is subjected to edge detection. Specifically, canny edge detection can be performed to obtain the order line distribution diagram. The order line distribution diagram is as follows: Figure 6 As shown, the horizontal axis represents time and the vertical axis represents frequency.

[0094] The number of order lines in the order line distribution diagram is counted along the time axis of the order line distribution diagram at the double frequency. Specifically, a straight line parallel to the time axis is generated at the double frequency of the order line distribution diagram. This straight line intersects with the order lines in the order line distribution diagram, and the number of intersections is the number of order lines.

[0095] In some embodiments, calculating the resonance energy at the frequency doubling in the spectrogram includes:

[0096] Bandpass filtering is performed on the waveform at the octave in the spectrogram to obtain a waveform in a specific frequency range (i.e., at the octave). At the same time, the burrs and DC components on the waveform can be removed, making the calculation of the resonance energy more accurate.

[0097] Calculate the statistical value of the waveform amplitude after filtering and determine the statistical value as the resonance energy at the corresponding frequency doubling. The statistical value can be the root mean square (RMS) value of the waveform amplitude or the absolute value of the waveform amplitude.

[0098] In a specific embodiment, the motor abnormal sound detection method is as follows: Figure 7 As shown, the following steps are included.

[0099] The source vibration signal after the motor runs at a steady speed is obtained. The vibration sensor collects the vibration signal after the motor starts to run at a steady speed. The vibration signal collected by the vibration sensor is the source vibration signal.

[0100] Based on the change in the dominant frequency of the source vibration signal, the steady-speed interval stop time point of the motor is determined, that is, the moment when the dominant frequency begins to decrease is determined as the steady-speed interval stop time point, thereby determining the steady-speed vibration signal segment of the motor in the steady-speed operation range. Specifically, starting from the starting point of the source vibration signal, a first predetermined duration steady-speed detection segment is sequentially selected, and the first dominant frequency of the vibration signal within the currently selected steady-speed detection segment is calculated; if the first dominant frequency is less than the second dominant frequency of the vibration signal within the previously selected steady-speed detection segment, the starting moment of the currently selected steady-speed detection segment is determined as the steady-speed interval stop time point.

[0101] Based on the vibration energy attenuation of the source vibration signal, the stopping time point of the tail speed interval of the motor is determined. Starting from the stopping time point of the steady speed interval, the vibration energy of the source vibration signal is detected. When the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold, the starting moment of the currently selected tail speed detection segment is determined to be the stopping time point of the tail speed interval.

[0102] For the steady-speed operation range of the motor, a Hilbert transform is performed on the steady-speed vibration signal segment in the steady-speed operation range to obtain an envelope spectrum, and a fast Fourier transform is performed on the envelope spectrum to obtain a Fourier frequency distribution diagram. All multiple frequencies are extracted from the Fourier frequency distribution diagram to obtain a multiple frequency list.

[0103] For the tail-speed operation range of the motor, short-time Fourier transform is performed on the tail-speed vibration signal segment of the tail-speed operation range to generate a spectrogram. Meijering filtering is performed on the spectrogram, and fast non-local average denoising is performed to obtain a denoised spectrogram. Canny edge detection is performed on the denoised spectrogram to obtain a distribution diagram of order lines.

[0104] Calculate the number of order lines and resonance energy at each frequency multiplication. If the number of order lines or resonance energy at any frequency multiplication exceeds their respective thresholds, determine that the motor has abnormal sound. Specifically, if the number of order lines and resonance energy at all frequencies are within the threshold range, determine that the motor has no abnormal sound.

[0105] The motor abnormal sound detection device provided by the present invention is described below. The motor abnormal sound detection device described below and the motor abnormal sound detection method described above can be referenced to each other.

[0106] The motor abnormal sound detection device according to the embodiment of the present invention is as follows: Figure 8 As shown, the following functional modules 810 to 840 are included.

[0107] The source vibration signal acquisition module 810 is used to acquire the source vibration signal after the motor runs at a steady speed.

[0108] The signal segment determination module 820 is configured to determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal.

[0109] The frequency multiplication determination module 830 is configured to determine all frequency multiplications in the steady-speed operation interval based on the steady-speed vibration signal segment.

[0110] The abnormal sound judgment module 840 is used to determine the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment, and determine that the motor has abnormal sound when the characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold.

[0111] In the motor abnormal sound detection device of this embodiment, abnormal motor sound is caused by the resonance characteristics of the motor vibration signal at the frequency multiplication. Furthermore, in the tail-speed operating range, the motor generating abnormal sound is more likely to resonate at the frequency multiplication and produce more order lines. Therefore, by detecting the vibration characteristics of the tail-speed vibration signal segment at the frequency multiplication in the tail-speed operating range, abnormal motor sound can be accurately detected with high consistency. Furthermore, the entire detection process does not require manual listening, avoiding damage to the human ear when the motor is running at full speed.

[0112] In some embodiments, the signal segment determination module 820 includes the following modules.

[0113] The stopping time point determination module is used to determine the stopping time point in the steady speed interval and the stopping time point in the tail speed interval when the motor is running based on the source vibration signal.

[0114] The interval division module is used to divide the signal segment before the steady speed interval stop time point into a steady speed vibration signal segment, and divide the signal segment between the steady speed interval stop time point and the tail speed interval stop time point into a tail speed vibration signal segment.

[0115] In some embodiments, the stop time point determination module is specifically used to detect the main frequency of the source vibration signal, and determine the moment when the main frequency begins to decrease as the stop time point in the steady speed interval.

[0116] In some embodiments, the stop time point determination module is specifically used to start from the starting point of the source vibration signal, select the first steady-speed detection segment of a predetermined duration in sequence, and calculate the first main frequency of the vibration signal in the currently selected steady-speed detection segment; when the first main frequency is less than the second main frequency of the vibration signal in the previously selected steady-speed detection segment, determine the starting time of the currently selected steady-speed detection segment as the stop time point of the steady-speed interval.

[0117] In some embodiments, there is an offset duration between the start time of each of the currently selected steady-speed detection segments and the start time of the previously selected steady-speed detection segment, and the offset duration is less than the first predetermined duration.

[0118] In some embodiments, the stop time point determination module is specifically used to detect the vibration energy of the source vibration signal starting from the stop time point of the steady speed interval, and when the ratio of the vibration energy to the initial vibration energy at the start of detection is less than the ratio threshold, determine the starting time of the currently selected tail speed detection segment as the stop time point of the tail speed interval.

[0119] In some embodiments, the stop time point determination module is specifically used to start from the steady speed interval stop time point, sequentially select the tail speed detection segment of the second predetermined duration, and calculate the current vibration energy of the vibration signal in the currently selected tail speed detection segment; when the ratio of the current vibration energy to the initial vibration energy of the vibration signal in the first tail speed detection segment is less than the ratio threshold, determine the starting moment of the currently selected tail speed detection segment as the tail speed interval stop time point.

[0120] In some embodiments, the frequency multiplication determination module 830 includes the following modules.

[0121] The Hilbert transform module is used to perform a Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment.

[0122] The fast Fourier transform module is used to perform fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram.

[0123] The frequency multiplication extraction module is used to extract all the frequency multiplications on the Fourier frequency distribution diagram.

[0124] In some embodiments, the vibration characteristics include: the number of order lines and / or resonance energy. The abnormal sound judgment module 840 specifically includes the following modules.

[0125] The spectrogram generating module is used to generate a spectrogram corresponding to the tail speed vibration signal segment.

[0126] an order line statistics module for generating an order line distribution diagram based on the spectrogram, and counting the number of order lines at each frequency octave in the order line distribution diagram; and / or a resonance energy calculation module for calculating the resonance energy at the frequency octave in the spectrogram.

[0127] In some embodiments, the order line statistics module is specifically used to filter and denoise the spectrogram; perform edge detection on the filtered and denoised spectrogram to obtain the order line distribution diagram; and count the number of order lines at the octave in the order line distribution diagram along the time axis of the order line distribution diagram.

[0128] In some embodiments, the resonance energy calculation module is specifically used to perform bandpass filtering on the waveform at the frequency doubling in the spectrogram; calculate the statistical value of the amplitude of the waveform after filtering, and determine the statistical value as the resonance energy at the corresponding frequency doubling.

[0129] Figure 9 An example of a physical structure diagram of an electronic device is shown below. Figure 9 As shown, the electronic device may include: a processor 910, a communications interface 920, a memory 930, and a communication bus 940. The processor 910, the communications interface 920, and the memory 930 communicate with each other via the communication bus 940. The processor 910 may invoke logic instructions in the memory 930 to execute a method for detecting abnormal motor noise, which includes the following steps.

[0130] Obtain the source vibration signal after the motor runs at steady speed.

[0131] Determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal.

[0132] Based on the steady-speed vibration signal segment, all frequency multiples of the steady-speed operation interval are determined.

[0133] The vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, and when a characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold, it is determined that abnormal sound exists in the motor.

[0134] Furthermore, the logic instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0135] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the motor abnormal sound detection method provided by the above methods, which includes the following steps.

[0136] Obtain the source vibration signal after the motor runs at steady speed.

[0137] Determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal.

[0138] Based on the steady-speed vibration signal segment, all frequency multiples of the steady-speed operation interval are determined.

[0139] The vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, and when a characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold, it is determined that abnormal sound exists in the motor.

[0140] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the motor abnormal sound detection method provided by the above methods is implemented, and the method includes the following steps.

[0141] Obtain the source vibration signal after the motor runs at steady speed.

[0142] Determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal.

[0143] Based on the steady-speed vibration signal segment, all frequency multiples of the steady-speed operation interval are determined.

[0144] The vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, and when a characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold, it is determined that abnormal sound exists in the motor.

[0145] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0146] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for detecting abnormal noise of a motor, characterized in that: include: Obtain the source vibration signal after the motor runs at a steady speed; Determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal; determining all frequency multiples of the steady-speed operation interval based on the steady-speed vibration signal segment; The vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, and when a characteristic value of the vibration characteristic at any multiple frequency exceeds a characteristic threshold, it is determined that abnormal sound exists in the motor.

2. The method for detecting abnormal motor noise according to claim 1, wherein: Determining a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal includes: Determining a stopping time point in a steady speed interval and a stopping time point in a tail speed interval when the motor is running based on the source vibration signal; The signal segment before the steady speed interval stop time point is divided into a steady speed vibration signal segment, and the signal segment between the steady speed interval stop time point and the tail speed interval stop time point is divided into a tail speed vibration signal segment.

3. The method for detecting abnormal motor noise according to claim 2, wherein: Determining a stopping time point in a steady speed interval when the motor is running based on the source vibration signal includes: The main frequency of the source vibration signal is detected, and the moment when the main frequency begins to decrease is determined as the stopping time point of the steady speed interval.

4. The method for detecting abnormal motor noise according to claim 3, wherein: Detecting the main frequency of the source vibration signal and determining the moment when the main frequency begins to decrease as the stop time point of the steady speed interval includes: Starting from the starting point of the source vibration signal, steady-speed detection segments of a first predetermined duration are selected in sequence, and the first main frequency of the vibration signal in the currently selected steady-speed detection segment is calculated; when the first main frequency is less than the second main frequency of the vibration signal in the previously selected steady-speed detection segment, the starting time of the currently selected steady-speed detection segment is determined as the stop time point of the steady-speed interval.

5. The method for detecting abnormal motor noise according to claim 4, wherein: The start time of each of the currently selected steady-speed detection segments and the start time of the previously selected steady-speed detection segment have an offset duration, and the offset duration is less than the first predetermined duration.

6. The method for detecting abnormal motor noise according to claim 2, wherein: Determining a stopping time point in a tail speed interval when the motor is running based on the source vibration signal includes: Starting from the stop time point of the steady speed interval, the vibration energy of the source vibration signal is detected. When the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold, the start time of the currently selected tail speed detection segment is determined as the stop time point of the tail speed interval.

7. The method for detecting abnormal motor noise according to claim 6, wherein: Starting from the stop time point of the steady speed interval, detecting the vibration energy of the source vibration signal, and when the ratio of the vibration energy to the initial vibration energy at the start of detection is less than a ratio threshold, determining the start time of the currently selected tail speed detection segment as the stop time point of the tail speed interval, including: Starting from the stop time point of the steady speed interval, tail speed detection segments of a second predetermined duration are sequentially selected, and a current vibration energy of the vibration signal in the currently selected tail speed detection segment is calculated; when a ratio of the current vibration energy to the initial vibration energy of the vibration signal in the first tail speed detection segment is less than a ratio threshold, the start time of the currently selected tail speed detection segment is determined as the stop time point of the tail speed interval.

8. The method for detecting abnormal motor noise according to claim 1, wherein: Determining all frequency multiples of the steady-speed operation range based on the steady-speed vibration signal segment includes: performing a Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment; Performing a fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram; All the multiple frequencies on the Fourier frequency distribution graph are extracted.

9. The method for detecting abnormal motor noise according to any one of claims 1 to 8, characterized in that: The vibration characteristics include: the number of order lines and / or resonance energy, and determining the vibration characteristics at each of the multiple frequencies in the tail velocity vibration signal segment includes: generating a spectrogram corresponding to the tail speed vibration signal segment; Generate an order line distribution diagram based on the spectrogram, count the number of order lines at each frequency doubling in the order line distribution diagram; and / or calculate the resonance energy at the frequency doubling in the spectrogram.

10. The method for detecting abnormal motor noise according to claim 9, wherein: Generating an order line distribution diagram based on the spectrogram, and counting the number of order lines at each octave in the order line distribution diagram, comprising: Filtering and denoising the spectrogram; Performing edge detection on the filtered and denoised spectrogram to obtain the order line distribution diagram; The number of order lines is counted at the multiple frequency positions along the time axis of the order line distribution diagram.

11. The method for detecting abnormal motor noise according to claim 9, wherein: Calculating the resonance energy at the frequency doubling in the spectrogram includes: Performing bandpass filtering on the waveform at the frequency doubling in the spectrogram; Calculate the statistical value of the amplitude of the filtered waveform and determine the statistical value as the resonance energy at the corresponding frequency doubling.

12. A motor abnormal sound detection device, characterized in that: include: A source vibration signal acquisition module is used to obtain the source vibration signal after the motor runs at a steady speed; a signal segment determination module, configured to determine a steady-speed vibration signal segment in a steady-speed operation interval of the motor and a tail-speed vibration signal segment in a tail-speed operation interval in the source vibration signal; a frequency multiplication determination module, configured to determine all frequency multiplications in the steady-speed operation interval based on the steady-speed vibration signal segment; The abnormal sound judgment module is used to determine the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment, and judge that the motor has abnormal sound when the characteristic value of the vibration characteristic at any multiple frequency exceeds the characteristic threshold.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the motor abnormal sound detection method according to any one of claims 1 to 11 is implemented.

14. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for detecting abnormal noise of a motor according to any one of claims 1 to 11 is implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting abnormal noise of a motor according to any one of claims 1 to 11 is implemented.

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