Motor abnormal sound detection method and device

Abstract

The invention relates to the technical field of motor manufacturing, and provides a motor abnormal sound detection method and device, and the method comprises the steps: obtaining a source vibration signal after a motor operates at a steady speed; determining a steady-speed vibration signal section of a motor steady-speed operation interval and a tail-speed vibration signal section of a tail-speed operation interval in the source vibration signal; based on the steady-speed vibration signal segment, determining all frequency multiplications of the steady-speed operation interval; and determining vibration characteristics at each frequency multiplication position in the tail speed vibration signal section, and judging that abnormal sound exists in the motor under the condition that the characteristic value of the vibration characteristic at any frequency multiplication position exceeds a characteristic threshold value. Because the abnormal sound of the motor is caused by the resonance characteristic at the frequency doubling position of the motor vibration signal, the abnormal sound of the motor can be accurately detected by detecting the number of order lines and / or resonance energy at the frequency doubling position of the tail speed vibration signal section of the motor tail speed operation interval, and the detection result has 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 parts, processes and assembly, abnormal sounds such as harsh tail sounds and dragging sounds may occur during the operation of the motor, which seriously affects the quality of the motor and the user experience of the corresponding home appliances. Most of the existing methods for detecting abnormal motor sounds are manual detection on the production line, that is, manual listening to determine whether the motor has abnormal sounds. Some high-speed motors have a loud running sound, up to 90 decibels at full speed, which is very harmful to the human ear. In addition, long-term listening can easily cause fatigue, affect the quality of detection, and lead to inaccurate test results. In addition, the manual listening detection method is highly subjective, and manual experience varies greatly. For the same motor, different people may get different test results when listening to the sound, and the consistency of the test results is poor, and the test standards cannot be unified. Summary of the invention

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

[0004] The present invention provides a method for detecting abnormal noise of a motor, comprising the following steps: Obtain source vibration signal after the motor runs at 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; Based on the steady-speed vibration signal segment, determining all frequency multiples of the steady-speed operation interval; 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 characteristics at any multiple frequency exceeds a characteristic threshold, it is determined that an abnormal sound exists in the motor.

[0005] 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 comprises: Based on the source vibration signal, determining a stop time point in a steady speed interval and a stop time point in a tail speed interval when the motor is running; 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.

[0006] According to a motor abnormal sound detection method provided by the present invention, based on the source vibration signal, determining the stop time point in the steady speed interval when the motor is running, comprises: The main frequency of the source vibration signal is detected, and the moment when the main frequency starts to decrease is determined as the stop time point of the steady speed interval.

[0007] 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 starts to decrease is determined as the stop time point of the steady speed interval, including: Starting from the starting point of the source vibration signal, steady-speed detection segments of a first predetermined length 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.

[0008] 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.

[0009] According to a motor abnormal sound detection method provided by the present invention, based on the source vibration signal, determining the stop time point in the tail speed interval when the motor is running, comprises: 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.

[0010] 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 section is determined 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 the second predetermined duration are selected in sequence, and the current vibration energy of the vibration signal in the currently selected tail speed detection segment is calculated; 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 ratio threshold, the start time of the currently selected tail speed detection segment is determined to be the stop time point of the tail speed interval.

[0011] 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 interval are determined, including: Performing Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment; Performing fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram; All the multiple frequencies on the Fourier frequency distribution diagram are extracted.

[0012] 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 the vibration characteristics at each of the multiple frequencies in the tail speed vibration signal segment are determined, including: 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.

[0013] 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 multiple frequency in the order line distribution diagram is counted, including: 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 in the order line distribution diagram along the time axis of the order line distribution diagram.

[0014] According to a motor abnormal sound detection method provided by the present invention, the resonance energy at the frequency doubling in the spectrogram is calculated, comprising: Performing bandpass filtering on the waveform at the frequency doubling in the spectrogram; The statistical value of the amplitude of the waveform after filtering is calculated, and the statistical value is determined to be the resonance energy at the corresponding frequency doubling.

[0015] The present invention also provides a motor abnormal sound detection device, comprising the following modules: A source vibration signal acquisition module is used to acquire the source vibration signal after the motor runs at a steady speed; A signal segment determination module, used 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 multiple determination module, used for determining all frequency multiples 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.

[0016] 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 in any one of the above is implemented.

[0017] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the motor abnormal sound detection method as described in any one of the above is implemented.

[0018] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for detecting abnormal sound of a motor as described above is implemented.

[0019] The method and device for detecting abnormal sound of a motor provided by the present invention obtain the source vibration signal after the motor runs at a steady speed; determine the steady speed vibration signal segment of the steady speed running interval of the motor and the tail speed vibration signal segment of the tail speed running interval in the source vibration signal; determine all the multiple frequencies of the steady speed running interval based on the steady speed vibration signal segment; determine the vibration characteristics at each multiple frequency in the tail speed vibration signal segment, and judge that the motor has abnormal sound when the characteristic value of the vibration characteristics at any multiple frequency exceeds the characteristic threshold. Since the abnormal sound of the motor is caused by the resonance characteristics at the multiple frequency of the motor vibration signal, and in the tail speed running interval, the motor that generates abnormal sound is more likely to form resonance at the multiple frequency and more likely to generate abnormal vibration characteristics, therefore, by detecting the vibration characteristics of the tail speed vibration signal segment at the multiple frequency in the tail speed running interval of the motor, the abnormal sound of the motor can be accurately detected, and the detection result has good consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. 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 creative work.

[0021] Figure 1 This is one of the flow charts of the motor abnormal sound detection method provided by the present invention.

[0022] Figure 2 This is the second flow chart of the motor abnormal sound detection method provided by the present invention.

[0023] Figure 3 This is the third flow chart of the motor abnormal sound detection method provided by the present invention.

[0024] Figure 4It is a schematic diagram of a spectrogram generated in the motor abnormal sound detection method provided by the present invention.

[0025] 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.

[0026] Figure 6 It is an order line distribution diagram generated according to the spectrogram in the motor abnormal sound detection method provided by the present invention.

[0027] Figure 7 This is the fourth flow chart of the motor abnormal sound detection method provided by the present invention.

[0028] Figure 8 It is a structural schematic diagram of the motor abnormal sound detection device provided by the present invention.

[0029] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] It should be noted that in the description of the present invention, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the 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.

[0032] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0033] In the related art, abnormal sound detection of motors mainly relies on manual listening. However, long-term listening can easily cause fatigue, which affects the detection quality and leads 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 for the same motor, and the consistency of the detection results is poor, and the detection standards cannot be unified.

[0034] In view of the above technical problems existing in the prior art, an embodiment of the present invention provides a method for detecting abnormal sound of a motor, such as Figure 1 As shown, the process includes the following steps S110 to S140.

[0035] Step S110: Acquire the source vibration signal after the motor runs at a steady speed. After the motor is turned on, it will reach a steady speed state, that is, it will run at a stable speed. The vibration signal of the motor after entering the steady speed state can be collected by a vibration sensor (for example, an accelerometer). In this step, the source vibration signal is obtained by acquiring the vibration signal of the motor after entering the steady speed state collected by the vibration sensor.

[0036] Specifically, before the motor is turned on, the motor is first placed in the rubber, and then a soft clamping mechanism is used to clamp the motor from both sides, effectively avoiding the abnormal shaking of the motor caused by the start-stop torque when the motor is started and stopped, making the source vibration signal collected more accurate. After the motor is tightened, the vibration sensor is brought into contact with the motor surface to collect the vibration signal after the motor enters a steady-speed running state.

[0037] Step S120: Determine the steady-speed vibration signal segment of the steady-speed operation interval of the motor 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 operation interval in which the rotor of the motor continues to rotate under the action of inertia after the motor is powered off. Since the present embodiment needs to detect the abnormal sound of the motor in the tail-speed operation interval, it is necessary to divide the vibration signal segments of the steady-speed operation interval and the tail-speed operation interval respectively, so as to perform corresponding processing on the respective vibration signal segments subsequently.

[0038] Step S130: Based on the steady-speed vibration signal segment, determine all the frequency multiples in the steady-speed operation range. Among them, the frequency multiples of vibration are frequency components in the vibration signal whose frequencies are integer multiples of the fundamental frequency, and 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 sound of the motor (such as harsh tail sound and dragging sound) is caused by the resonance characteristics at the frequency multiples, so the abnormal sound of the motor can be detected by the frequency multiples. Moreover, in this step, only the steady-speed vibration signal segment is used to determine the frequency multiples, which can determine the frequency multiples more quickly than using the entire source vibration signal to determine the frequency multiples.

[0039] 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.

[0040] Among them, the characteristic threshold can be set according to the actual situation. Specifically, for a certain model of motor, a batch of normal samples (motors without abnormal sounds) and a batch of abnormal samples (motors with abnormal sounds) can be selected, and the vibration characteristic distribution of each type of sample at the double frequency can be calculated respectively. According to the principle of priority detection rate or priority accuracy, the characteristic threshold can be dynamically adjusted. For example: the vibration characteristic is the order line. The simplest way to determine the priority detection rate of the threshold of the number of order lines is: the number of order lines of the abnormal samples at the double frequency is more than 8, then the threshold of the number of order lines can be determined to be 8.

[0041] In the motor abnormal sound detection method of this embodiment, since the abnormal sound of the motor is caused by the resonance characteristics of the motor vibration signal at the frequency multiple, and in the tail speed operation range, the motor that generates abnormal sound is more likely to form resonance at the frequency multiple and more likely to generate more order lines, therefore, by detecting the vibration characteristics of the tail speed vibration signal segment at the frequency multiple in the tail speed operation range of the motor, the abnormal sound of the motor can be accurately detected, and the detection results have good consistency. In addition, the entire detection process does not require manual listening, avoiding damage to the human ear when the motor is running at full speed.

[0042] In some embodiments, step S120 specifically includes the following steps S121 and S122.

[0043] Step S121: Based on the source vibration signal, determine the stop time point of the steady speed interval and the stop time point of the tail speed interval when the motor is running. Since the main frequency of the motor will change significantly from the steady speed operation interval to the tail speed operation interval after power failure and shutdown, in this step, the point where the main frequency changes in the source vibration signal can be detected as the stop time point of the steady speed interval, and the stop time point of the tail speed interval can be the point where the vibration stops.

[0044] 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.

[0045] In this embodiment, by detecting the stopping time point of the steady speed interval and the stopping time point of 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.

[0046] In some embodiments, in step S121, based on the source vibration signal, determining the stop time point of the steady speed interval when the motor is running specifically includes: 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. When the motor is in the steady speed operation interval, the main frequency of the source vibration signal remains basically unchanged. After the motor stops and enters the tail speed operation interval, the main frequency of the corresponding source vibration signal gradually decreases due to the gradual decrease in speed. Therefore, the moment when the main frequency begins to decrease can be determined as the stop time point of the steady speed interval.

[0047] Specifically, the moment when the main frequency starts to decrease can be detected in the following manner (but not limited to): starting from the starting point of the source vibration signal, select the steady-speed detection segments of the first 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, the starting moment of the currently selected steady-speed detection segment is determined as the stop time point of the steady-speed interval. That is, using a mechanism similar to a sliding window, each steady-speed detection segment of the first predetermined duration is regarded as a window, and the first main frequency corresponding to the current 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, it means that the current steady-speed detection segment has entered the tail speed vibration signal segment area, and therefore, the starting moment of the current steady-speed detection segment is determined as the stop time point of the steady-speed interval.

[0048] In this embodiment, a mechanism similar to a sliding window is used to sequentially calculate the main frequency of the vibration signal in each steady speed detection segment, and the stop time point of the steady speed interval can be quickly determined by detecting that the main frequency becomes smaller. The main frequency is calculated by calculating the frequency energy distribution of the waveform corresponding to the vibration signal of the steady speed detection segment, and selecting the frequency corresponding to the maximum vibration energy in the frequency energy distribution as the main frequency.

[0049] 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, each of the currently selected steady speed detection segments has an offset duration between the start time and the start time of the previously selected steady speed detection segment, and the offset duration is less than the first predetermined duration, that is, there is an overlap between the two steady speed detection segments. Both 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.

[0050] 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 step of determining the stop time point in the steady speed interval when the motor is running based on the source vibration signal is 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 20 milliseconds backward from the starting point of the previous steady-speed detection segment, and taking the 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 20 milliseconds backward from the starting point of the previous steady-speed detection segment, and taking the 200-ms steady-speed detection segment as the current steady-speed detection segment.

[0051] 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 reduction exceeds the error range, when the difference between the first main frequency and the second main frequency of the vibration signal in the previous steady-speed detection section selected exceeds the error range, it is considered that the main frequency is reduced, that is, the first main frequency is less than the second main frequency.

[0052] In some embodiments, in step S121, based on the source vibration signal, determining the stop time point of the tail speed interval when the motor is running, includes: 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 the ratio threshold, determining the starting moment of the currently selected tail speed detection segment as the stop time point of the tail speed interval. Since the speed of the motor will gradually slow down after entering the tail speed operation interval, the vibration signal of the tail speed vibration signal segment will also become weaker and weaker accordingly, that is, the vibration energy will become smaller and smaller, so the stop time point of the tail speed interval can be determined by the characteristic of the reduction of vibration energy.

[0053] Specifically, the vibration energy of the source vibration signal can be detected in the following manner (but not limited to) to determine the stop time point of the tail speed interval: starting from the stop time point of the steady speed interval, the tail speed detection segments of the second predetermined time length are selected in sequence, and the current vibration energy of the vibration signal in 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 time length is regarded 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 connected or overlapped. 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, the starting time of the currently selected tail speed detection segment is determined to be the stop time point of the tail speed interval.

[0054] It should be noted that: in the tail speed operation interval, the motor speed decreases, the vibration signal weakens, and after the vibration signal weakens to a certain extent, even if there is an abnormal sound, the abnormal sound is very small, less than the critical value that can be tolerated by human hearing, or even the abnormal sound cannot be heard. Therefore, the stop time point in the tail speed interval can be the moment when the vibration energy of the vibration signal is reduced to the point where the abnormal sound is less than the critical value, which can reduce the amount of data in the tail speed vibration signal segment, thereby improving the abnormal sound detection efficiency. 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 the ratio threshold, it means that the current vibration energy has been reduced to the point where the abnormal sound is less than the critical value. This ratio threshold can be determined in advance by artificial listening when the abnormal sound reaches a tolerable critical value or even when the abnormal sound cannot be heard, and then the ratio is calculated based on the vibration energy threshold and the initial vibration energy. For example, the ratio threshold can be 75%~95%.

[0055] 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.

[0056] Specifically, taking the second predetermined time length as 50 milliseconds as an example, the step of determining the stop time point in 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 millisecond 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 millisecond 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 and the initial vibration energy corresponding to the current tail speed detection segment, 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 time of the current 50 millisecond 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 millisecond tail speed detection segment as the current tail speed detection segment, and calculating the vibration energy of the vibration signal therein.

[0057] In some embodiments, the step S130 specifically includes: A Hilbert Transform is performed on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment.

[0058] Performing Fast Fourier Transform (FFT) on the envelope spectrum to obtain a Fourier frequency distribution diagram.

[0059] All the multiple frequencies on the Fourier frequency distribution diagram are extracted.

[0060] 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 multiple frequencies can be extracted from the Fourier frequency distribution diagram.

[0061] In some embodiments, the vibration characteristics include: the number of order lines and / or resonance energy, and the step S140 specifically includes: Generate a spectrogram corresponding to the tail speed vibration signal segment, such as Figure 4 As shown in FIG. 1 , 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.

[0062] 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.

[0063] Specifically, Figure 4In the figure, it can be understood that 50Hz is the base frequency (main frequency), 100Hz, 150Hz, 200Hz and 250Hz are all multiple frequencies, all multiple frequencies may produce resonance bands, and different models of motors have different probabilities of producing resonance bands at different multiple frequencies, for example: Figure 4 In the example, there is a large resonance energy at the multiples of 100Hz and 200Hz, which produces a resonance band and leads to a large abnormal sound, while the resonance energy at the multiples of 150Hz and 250Hz is small, and the abnormal sound is small or even inaudible. In practical applications, the specific multiples can be monitored according to the specific model of motor, that is, the resonance energy at the specific multiples can be calculated. The specific multiples are the historical multiples in the spectrogram when the motor of the specific model produces abnormal sound in the historical detection, thereby reducing the calculation amount of the resonance energy and improving the calculation efficiency.

[0064] In this embodiment, the number of order lines and the resonance energy can be calculated at the same time. Only when both do not exceed the threshold value can it be determined that the motor has no abnormal sound. By calculating the number of order lines and the resonance energy, not only the order information of the motor changing with the speed can be reflected, but also the resonance characteristics of the motor can be reflected, so that the abnormal sound of the motor can be detected more accurately. In addition, during the detection process, key performance data such as the number of order lines, the resonance energy, and the duration of the abnormal sound (the duration of the tail speed operation interval) can be quantified, providing an analysis data source for motor fault analysis.

[0065] In some embodiments, 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 comprises: The spectrogram is filtered and denoised to obtain a filtered and denoised spectrogram. Specifically, the spectrogram may be meijering filtered to remove interference from some 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 enables the subsequent generation of a more accurate order line distribution diagram based on the filtered and denoised spectrogram.

[0066] 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.

[0067] The number of order lines is counted along the time axis of the order line distribution diagram at the double frequency in the order line distribution diagram. Specifically, a straight line parallel to the time axis is generated at the double frequency of the order line distribution diagram, and the straight line intersects with the order lines in the order line distribution diagram, and the number of intersections is the number of order lines.

[0068] In some embodiments, calculating the resonance energy at the frequency doubling in the spectrogram comprises: The waveform at the double frequency in the spectrogram is band-pass filtered to obtain a waveform in a specific frequency range (i.e., at the double frequency). At the same time, the burrs and DC components on the waveform can be removed, so that the calculation of the resonance energy is more accurate.

[0069] The statistical value of the waveform amplitude after filtering is calculated, and the statistical value is determined to be the resonance energy at the corresponding frequency doubling. The statistical value may be the root mean square value (RMS) of the waveform amplitude, or the absolute value of the waveform amplitude.

[0070] In a specific embodiment, the motor abnormal sound detection method is as follows: Figure 7 As shown, the following steps are included.

[0071] 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.

[0072] Based on the change of the main frequency of the source vibration signal, the stop time point of the steady speed interval of the motor is determined, that is, the moment when the main frequency begins to decrease is determined as the stop time point of the steady speed interval, thereby determining the steady speed vibration signal segment of the motor in the steady speed operation interval. Specifically, starting from the starting point of the source vibration signal, the first predetermined time length of the steady speed detection segment is 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 moment of the currently selected steady speed detection segment is determined as the stop time point of the steady speed interval.

[0073] Based on the attenuation of the vibration energy of the source vibration signal, the stop time point of the tail speed interval of the motor is determined, and 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 beginning of the detection is less than a ratio threshold, the starting moment of the currently selected tail speed detection segment is determined to be the stop time point of the tail speed interval.

[0074] For the steady-speed operation range of the motor, the steady-speed vibration signal segment in the steady-speed operation range is Hilbert transformed to obtain an envelope spectrum, the envelope spectrum is fast Fourier transformed to obtain a Fourier frequency distribution diagram, and all multiple frequencies are extracted from the Fourier frequency distribution diagram to obtain a multiple frequency list.

[0075] 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, which is then subjected to meijering filtering and fast non-local average denoising to obtain a denoised spectrogram. Canny edge detection is performed on the denoised spectrogram to obtain a distribution diagram of order lines.

[0076] The number of order lines and the resonance energy at each multiple frequency are calculated. When the number of order lines or the resonance energy at any multiple frequency exceeds their respective thresholds, it is determined that the motor has abnormal sound. Specifically, when the number of order lines and the resonance energy at all multiple frequencies are within the threshold range, it is determined that the motor has no abnormal sound.

[0077] 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 referred to each other.

[0078] The abnormal sound detection device of the motor according to the embodiment of the present invention is as follows: Figure 8 As shown, the following functional modules 810 to 840 are included.

[0079] The source vibration signal acquisition module 810 is used to acquire the source vibration signal after the motor runs at a steady speed.

[0080] The signal segment determination module 820 is used to determine the steady-speed vibration signal segment of the motor steady-speed operation interval and the tail-speed vibration signal segment of the tail-speed operation interval in the source vibration signal.

[0081] The frequency multiple determination module 830 is used to determine all frequency multiples in the steady speed operation interval based on the steady speed vibration signal segment.

[0082] 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 judge that the motor has abnormal sound when the characteristic value of the vibration characteristic at any multiple frequency exceeds the characteristic threshold.

[0083] In the motor abnormal sound detection device of this embodiment, since the abnormal sound of the motor is caused by the resonance characteristics of the motor vibration signal at the frequency doubling, and in the tail speed operation range, the motor that generates abnormal sound is more likely to form resonance at the frequency doubling and more likely to generate more order lines, therefore, by detecting the vibration characteristics of the tail speed vibration signal segment at the frequency doubling in the tail speed operation range of the motor, the abnormal sound of the motor can be accurately detected, and the detection results have good consistency. In addition, the entire detection process does not require manual listening, avoiding damage to human ears when the motor is running at full speed.

[0084] In some embodiments, the signal segment determination module 820 includes the following modules.

[0085] The stop time point determination module is used to determine the stop time point in the steady speed interval and the stop time point in the tail speed interval when the motor is running based on the source vibration signal.

[0086] 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.

[0087] 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.

[0088] 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 steady-speed detection segments of the first 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.

[0089] 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.

[0090] 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 a ratio threshold, determine the starting time of the currently selected tail speed detection segment as the stop time point of the tail speed interval.

[0091] In some embodiments, the stop time point determination module is specifically used to start from the steady speed interval stop time point, select the tail speed detection segments of the second predetermined duration in sequence, 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 a ratio threshold, determine the starting time of the currently selected tail speed detection segment as the tail speed interval stop time point.

[0092] In some embodiments, the frequency multiplication determination module 830 includes the following modules.

[0093] 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.

[0094] The fast Fourier transform module is used to perform fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram.

[0095] The frequency multiple extraction module is used to extract all the frequency multiples on the Fourier frequency distribution diagram.

[0096] In some embodiments, the vibration characteristics include: the number of order lines and / or resonance energy, and the abnormal sound judgment module 840 specifically includes the following modules.

[0097] The spectrogram generating module is used to generate a spectrogram corresponding to the tail speed vibration signal segment.

[0098] An order line statistics module is used to generate an order line distribution diagram based on the spectrogram, and count the number of order lines at each frequency doubling in the order line distribution diagram; and / or a resonance energy calculation module is used to calculate the resonance energy at the frequency doubling in the spectrogram.

[0099] 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.

[0100] In some embodiments, the resonance energy calculation module is specifically used to perform bandpass filtering on the waveform at the double frequency 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 double frequency.

[0101] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9 As shown, the electronic device may include: a processor 910, a communication interface 920, a memory 930 and a communication bus 940, wherein the processor 910, the communication interface 920 and the memory 930 communicate with each other through the communication bus 940. The processor 910 may call the logic instructions in the memory 930 to execute the motor abnormal sound detection method, which includes the following steps.

[0102] Get the source vibration signal after the motor runs at a steady speed.

[0103] 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.

[0104] Based on the steady-speed vibration signal segment, all multiple frequencies of the steady-speed operation interval are determined.

[0105] 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 characteristics at any multiple frequency exceeds a characteristic threshold, it is determined that an abnormal sound exists in the motor.

[0106] In addition, the logic instructions in the above-mentioned memory 930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0107] 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-mentioned methods, which includes the following steps.

[0108] Get the source vibration signal after the motor runs at a steady speed.

[0109] 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.

[0110] Based on the steady-speed vibration signal segment, all multiple frequencies of the steady-speed operation interval are determined.

[0111] 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 characteristics at any multiple frequency exceeds a characteristic threshold, it is determined that an abnormal sound exists in the motor.

[0112] 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.

[0113] Get the source vibration signal after the motor runs at a steady speed.

[0114] 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.

[0115] Based on the steady-speed vibration signal segment, all multiple frequencies of the steady-speed operation interval are determined.

[0116] 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 characteristics at any multiple frequency exceeds a characteristic threshold, it is determined that an abnormal sound exists in the motor.

[0117] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0118] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0119] 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 embodiments of the present invention.

Claims

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

2. The method for detecting abnormal motor sound according to claim 1, characterized in that: 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 comprises: Based on the source vibration signal, determining a stop time point in a steady speed interval and a stop time point in a tail speed interval when the motor is running; 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 sound according to claim 2, characterized in that: Determining a stop 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 starts to decrease is determined as the stop time point of the steady speed interval.

4. The method for detecting abnormal motor sound according to claim 3, characterized in that: Detecting the main frequency of the source vibration signal and determining the time when the main frequency starts 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 length 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 sound according to claim 4, characterized in that: There is an offset duration 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 duration is less than the first predetermined duration.

6. The method for detecting abnormal motor sound according to claim 2, characterized in that: Determining a stop 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, 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.

7. The method for detecting abnormal motor noise according to claim 6, characterized in that: 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 the second predetermined duration are selected in sequence, and the current vibration energy of the vibration signal in the currently selected tail speed detection segment is calculated; 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 ratio threshold, the start time of the currently selected tail speed detection segment is determined to be the stop time point of the tail speed interval.

8. The method for detecting abnormal motor noise according to claim 1, characterized in that: Based on the steady-speed vibration signal segment, all multiple frequencies of the steady-speed operation interval are determined, including: Performing Hilbert transform on the steady-speed vibration signal segment to obtain an envelope spectrum of the steady-speed vibration signal segment; Performing fast Fourier transform on the envelope spectrum to obtain a Fourier frequency distribution diagram; All the multiple frequencies on the Fourier frequency distribution diagram are extracted.

9. The method for detecting abnormal noise of a motor 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 speed 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 noise of a motor according to claim 9, characterized in that: 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, comprises: 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 in the order line distribution diagram along the time axis of the order line distribution diagram.

11. The method for detecting abnormal motor noise according to claim 9, characterized in that: Calculating the resonance energy at the frequency doubling in the spectrogram comprises: Performing bandpass filtering on the waveform at the frequency doubling in the spectrogram; The statistical value of the amplitude of the waveform after filtering is calculated, and the statistical value is determined to be 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 acquire the source vibration signal after the motor runs at a steady speed; A signal segment determination module, used 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 multiple determination module, used for determining all frequency multiples 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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