Abnormal vibration detection method, device, electronic device and storage medium

Abstract

The present application provides an abnormal vibration detection method, device, electronic device, and storage medium, comprising: extracting a high-frequency vibration signal from a motor torque signal; detecting the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as a target number of sampling points and a target peak-to-peak value; self-increasing an alarm count value when the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition; and outputting an abnormal vibration result in response to the alarm count value being greater than a preset alarm threshold. In this way, by performing real-time analysis of the waveform frequency and peak value of the motor torque signal, abnormality detection can be performed, and the abnormal vibration result can be quickly output. This method does not require windowing calculations and has strong real-time performance and low computational complexity.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of motor monitoring technology, and specifically to an abnormal vibration detection method, device, electronic device, and storage medium. Background Art

[0002] In the intelligent operation and maintenance of industrial equipment, motors, as core power components, require accurate monitoring of their vibration status to ensure safe system operation and prevent sudden failures. Motor vibration signals contain real-time information about the equipment's operating conditions. Faults such as bearing wear, rotor imbalance, and gear meshing anomalies can be detected through changes in vibration characteristics.

[0003] Currently, mainstream technology approaches for motor vibration detection rely primarily on machine learning (such as support vector machines and random forests) and deep learning (such as convolutional neural networks and recurrent neural networks) to build fault diagnosis models. These methods typically involve feature extraction from vibration signals, including time-domain statistical features (such as mean, variance, and kurtosis), frequency-domain features (such as power spectral density and frequency components), and joint time-frequency features (such as wavelet transform and short-time Fourier transform). Subsequently, fault mode classification is achieved through model training. While these methods can achieve high diagnostic accuracy in scenarios with abundant historical fault data, their primary drawback is their strong dependence on historical data. Furthermore, these methods typically consume significant computing resources, making them difficult to meet the millisecond-level real-time monitoring requirements of industrial sites. In particular, in the context of sudden fault warnings for high-speed rotating machinery, data processing delays can lead to delays in fault feature identification, potentially missing optimal maintenance opportunities and potentially causing equipment downtime or safety incidents.

[0004] Therefore, how to improve the real-time performance of motor vibration detection is a technical problem that those skilled in the art urgently need to solve. Summary of the Invention

[0005] In order to improve the real-time performance of motor vibration detection, embodiments of the present application provide an abnormal vibration detection method, device, electronic device, and storage medium.

[0006] In a first aspect, an embodiment of the present application provides a method for detecting abnormal vibration, the method comprising:

[0007] Extract high-frequency vibration signal from motor torque signal;

[0008] Detecting the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as target number of sampling points and target peak-to-peak value;

[0009] When the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition, the alarm count value is automatically incremented;

[0010] In response to the alarm count value being greater than a preset alarm threshold, an abnormal vibration result is output.

[0011] In some optional implementations, extracting the high-frequency vibration signal from the motor torque signal includes:

[0012] Obtaining a motor torque signal and a cutoff frequency, wherein the motor torque signal is a signal collected and sent by a sensor;

[0013] The motor torque signal is subjected to high-pass filtering using the cutoff frequency to obtain a high-frequency vibration signal.

[0014] In some optional implementations, detecting the number of sampling points and the peak-to-peak value of the high-frequency vibration signal within a vibration cycle as a target number of sampling points and a target peak-to-peak value includes:

[0015] In response to detecting a zero-crossing point of the high-frequency vibration signal, counting sampling points of the high-frequency vibration signal and obtaining a positive maximum value and a negative maximum value of the high-frequency vibration signal;

[0016] In response to detecting the zero-crossing point of the high-frequency vibration signal in the same direction again, obtaining a sampling count value for counting the sampling points of the high-frequency vibration signal;

[0017] Determine whether the sampling count value is less than a preset sampling threshold;

[0018] If so, clearing the sampling count value, the positive maximum value, and the negative maximum value of the high-frequency vibration signal;

[0019] If not, the sampling count value is determined as the target number of sampling points, and the difference between the positive maximum value and the negative maximum value of the high-frequency vibration signal is calculated as the target peak-to-peak value.

[0020] In some optional embodiments, the method further comprises:

[0021] When the target number of sampling points meets a third preset condition, or the target peak-to-peak value meets a fourth preset condition, the alarm count value is decremented.

[0022] In some optional embodiments, the first preset condition is that the target number of sampling points is less than the vibration period threshold, the second preset condition is that the target peak-to-peak value is greater than the vibration floating threshold, the third preset condition is that the product of the target number of sampling points and a preset multiple is greater than the vibration period threshold, and the fourth preset condition is that the target peak-to-peak value is less than the product of the vibration floating threshold and a preset fraction.

[0023] In some optional implementations, before the alarm count value is incremented, the method further includes:

[0024] Initialize the alarm count value.

[0025] In some optional implementations, outputting the abnormal vibration result includes:

[0026] Control the buzzer to beep, and / or control the indicator light to flash, and / or send a text message, email, or push message to the target device.

[0027] In a second aspect, an embodiment of the present application provides an abnormal vibration detection device, the device comprising:

[0028] A signal extraction module is used to extract high-frequency vibration signals from motor torque signals;

[0029] A sampling module is used to detect the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as the target number of sampling points and target peak-to-peak value;

[0030] A self-increasing module, configured to self-increase the alarm count value when the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition;

[0031] The abnormal module is used to output an abnormal vibration result in response to the alarm count value being greater than a preset alarm threshold.

[0032] In a third aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation method in the first aspect.

[0033] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by one or more processors, implements the method described in any implementation manner in the first aspect.

[0034] In order to improve the real-time performance of motor vibration detection, the embodiments of the present application provide an abnormal vibration detection method, device, electronic device, and storage medium. The method first extracts a high-frequency vibration signal from the motor torque signal; then detects the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as the target number of sampling points and target peak-to-peak value; then, when the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition, the alarm count value is self-incremented; finally, in response to the alarm count value being greater than a preset alarm threshold, the abnormal vibration result is output. In this way, by analyzing the waveform frequency and peak value of the motor torque signal in real time and performing abnormality detection, the abnormal vibration result can be quickly output. This method does not require windowing calculations and has strong real-time performance and low computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Other features, objects, and advantages of the present application will become more apparent upon reading the detailed description of the non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating specific embodiments and are not to be considered as limiting the present application. In the drawings:

[0036] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present application may be applied;

[0037] Figure 2 is a flow chart of an embodiment of an abnormal vibration detection method according to the present application;

[0038] Figure 3 is a flow chart of another embodiment of the abnormal vibration detection method according to the present application;

[0039] Figure 4 is a structural schematic diagram of an embodiment of an abnormal vibration detection device according to the present application;

[0040] Figure 5 It is a structural diagram of a computer system of an electronic device suitable for implementing an embodiment of the present application. DETAILED DESCRIPTION

[0041] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0042] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0043] Figure 1An exemplary system architecture 100 is shown to which embodiments of the abnormal vibration detection method, apparatus, electronic device, and storage medium of the present application can be applied.

[0044] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. Network 104 is a medium for providing communication links between terminal devices 101, 102, 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0045] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as motor anomaly detection applications, voice recognition applications, short video social applications, audio and video conferencing applications, live video applications, document editing applications, input method applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0046] Terminal devices 101, 102, and 103 can be hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various electronic devices with display screens, including but not limited to smartphones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, Moving Picture Experts Group Audio Layer 3), MP4 players (Moving Picture Experts Group Audio Layer IV, Moving Picture Experts Group Audio Layer 4), laptop computers, and desktop computers, etc. When terminal devices 101, 102, and 103 are software, they can be installed in the terminal devices listed above. They can be implemented as multiple software or software modules (for example, to provide motor anomaly detection services), or as a single software or software module. No specific limitations are given here.

[0047] In some cases, the abnormal vibration detection method provided in this application may be executed by the terminal devices 101, 102, and 103. Accordingly, the abnormal vibration detection apparatus may be provided in the terminal devices 101, 102, and 103. In this case, the system architecture 100 may not include the server 105.

[0048] In some cases, the abnormal vibration detection method provided in this application can be jointly performed by the terminal devices 101, 102, 103 and the server 105. For example, the step of "extracting a high-frequency vibration signal from the motor torque signal" can be performed by the terminal devices 101, 102, 103, and the steps of "detecting the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as the target number of sampling points and target peak-to-peak value" can be performed by the server 105. This application does not limit this. Accordingly, the abnormal vibration detection device can also be respectively set in the terminal devices 101, 102, 103 and the server 105.

[0049] In some cases, the abnormal vibration detection method provided in this application can be executed by the server 105. Accordingly, the abnormal vibration detection device can also be set in the server 105. In this case, the system architecture 100 may not include the terminal devices 101, 102, and 103.

[0050] It should be noted that server 105 can be either hardware or software. When server 105 is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When server 105 is software, it can be implemented as multiple software programs or software modules (for example, to provide distributed services), or as a single software program or software module. This is not specifically limited here.

[0051] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0052] Continue to refer Figure 2 , which shows a process 200 according to an embodiment of the abnormal vibration detection method of the present application, the abnormal vibration detection method includes the following steps:

[0053] Step 201: extracting a high-frequency vibration signal from a motor torque signal.

[0054] The sensor collects and transmits the torque change signal generated by the motor during operation, known as the motor torque signal, which reflects the motor load status. The signal is relatively stable during normal operation, but it may contain high-frequency vibration components when a fault occurs, such as bearing wear. High-frequency vibration signals are high-frequency vibration components and are typically associated with motor faults (for example, the frequency of a bearing fault may be above 100 Hz). The high-frequency vibration signal is extracted from the motor torque signal to isolate high-frequency vibrations that may indicate a fault and eliminate low-frequency interference (such as load fluctuations). Optionally, a filter with a cutoff frequency (such as 80 Hz) can be used to attenuate low-frequency components while retaining high-frequency vibrations.

[0055] This eliminates low-frequency interference (such as torque fluctuations during normal motor startup and shutdown), improving the signal-to-noise ratio of fault-related vibration signals (such as vibrations above 100 Hz caused by bearing wear) by 3-5 dB. The accuracy of identifying fault characteristics (such as sudden peak-to-peak changes) in the filtered signal is significantly improved.

[0056] Step 202 : Detect the number of sampling points and the peak-to-peak value of the high-frequency vibration signal within a vibration cycle, and use them as the target number of sampling points and the target peak-to-peak value.

[0057] The time it takes for a vibration signal to complete one full oscillation corresponds to the time from one peak to the next (or from one trough to the next). The number of sampling points is the number of sampling points within a vibration cycle, which is equal to the product of the cycle time and the sampling frequency. The peak-to-peak value is the difference between the maximum positive and maximum negative values ​​in the waveform, reflecting the vibration amplitude.

[0058] A zero crossing is the point where a signal crosses zero from negative to positive or vice versa. A vibration cycle is defined by the interval between two adjacent zero crossings in the same direction of a high-frequency vibration signal (e.g., from a rising edge zero crossing to the next rising edge zero crossing). Within a vibration cycle, the target number of sampling points and the target peak-to-peak value can be used to quantify the vibration characteristics for subsequent analysis.

[0059] This eliminates the need for spectrum analysis algorithms, reduces computational complexity, and lowers CPU usage. The cycle calculation delay is ≤ 1 sampling cycle, providing real-time performance that meets the requirements for high-speed motor vibration monitoring.

[0060] Step 203 : When the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition, the alarm count value is automatically incremented.

[0061] The first preset condition is a threshold condition for the number of sampling points (e.g., N < 150 sampling points, corresponding to high-frequency vibration). The second preset condition is a threshold condition for the peak-to-peak value (e.g., peak-to-peak value > 2.5V, corresponding to large vibration). The alarm count value is a counter that accumulates the number of abnormalities and is initially set to 0. During implementation, the alarm count value can be increased by 1 if the number of sampling points is less than the vibration period threshold (e.g., the period is too short, corresponding to a high-frequency vibration signal), or if the peak-to-peak value is greater than the vibration fluctuation threshold (e.g., the vibration amplitude is too large). The vibration period threshold and vibration fluctuation threshold can be set based on needs and experience and are not limited here.

[0062] Step 204: When the alarm count value is greater than the preset alarm threshold, an abnormal vibration result is output.

[0063] To avoid single false positives, this embodiment sets a preset alarm threshold, the critical value for triggering an alarm (e.g., 5). The logic rule is: when the alarm count exceeds the preset threshold, the motor is deemed to be vibrating abnormally and an alarm is output. Output methods include on-site audible and visual alarms (e.g., buzzer, LED light), remote notifications (e.g., SMS, email, app push), or system linkage (e.g., triggering a PLC shutdown protection).

[0064] In summary, the abnormal vibration detection method provided in the above-mentioned embodiments of the present application only involves basic operations such as signal extraction, extreme value comparison, and counting judgment. By performing graded output based on the alarm count value, operation and maintenance personnel can quickly determine the urgency of the fault and, combined with historical data (such as a continuously shortening cycle and increasing amplitude), locate different types of faults such as bearing wear and poor gear meshing. By analyzing the waveform frequency and peak value of the motor torque signal in real time and performing anomaly detection, this method can quickly output abnormal vibration results. In addition, this method does not require windowing calculations, and has strong real-time performance and low computational complexity.

[0065] Continue to refer Figure 3 , which shows a process 300 according to an embodiment of the abnormal vibration detection method of the present application, the abnormal vibration detection method includes the following steps:

[0066] Step 301: Acquire the motor torque signal and cutoff frequency.

[0067] The motor torque signal represents the change in output torque during motor operation and is typically acquired by a torque sensor. During normal operation, the signal is relatively stable, but during fault conditions, high-frequency fluctuations may occur. The cutoff frequency is a key parameter of a high-pass filter. Signals above this frequency pass through, while signals below this frequency are attenuated. The cutoff frequency is measured in Hertz (Hz). The cutoff frequency can be set based on experience and is not a specific limit here.

[0068] Step 302 : Perform high-pass filtering on the motor torque signal using a cutoff frequency to obtain a high-frequency vibration signal.

[0069] High-pass filtering is a signal processing method that allows high-frequency signals to pass and attenuates low-frequency signals. It is used to extract high-frequency vibration components from motor torque, filter out low-frequency trends (such as 0-50Hz) caused by motor load changes, and retain fault-related high-frequency vibrations (such as above 100Hz).

[0070] Step 303 : In response to detecting the zero-crossing point of the high-frequency vibration signal, counting the sampling points of the high-frequency vibration signal, and obtaining the positive maximum value and the negative maximum value of the high-frequency vibration signal.

[0071] Step 304 : In response to detecting the zero-crossing point of the high-frequency vibration signal in the same direction again, obtaining a sampling count value for counting the sampling points of the high-frequency vibration signal.

[0072] When the zero crossing point in the same direction is detected again, it indicates that a complete vibration cycle has ended.

[0073] Step 305: Determine whether the sampling count value is less than a preset sampling threshold.

[0074] The preset sampling threshold is used to determine the minimum number of sampling points (such as 3 points) to determine whether the cycle is valid and filter high-frequency glitches. The preset sampling threshold can be set according to needs and is not limited here.

[0075] Step 306: If yes, clear the sampling count value, the positive maximum value, and the negative maximum value of the high-frequency vibration signal.

[0076] If the sampling count value is less than the preset sampling threshold, the high-frequency vibration signal is considered to be high-frequency glitch interference, the data is discarded, and the counter and extreme value are reset.

[0077] If not, step 307 , determine the sampling count value as the target number of sampling points, and calculate the difference between the maximum positive value and the maximum negative value of the high-frequency vibration signal as the target peak-to-peak value.

[0078] If the sampling count value is greater than or equal to the preset sampling threshold value: confirm that the cycle is valid, execute: use the sampling count value as the target number of sampling points, and use the difference between the maximum positive value and the maximum negative value as the target peak-to-peak value.

[0079] Step 308 : When the target number of sampling points meets the first preset condition or the target peak-to-peak value meets the second preset condition, the alarm count value is automatically incremented.

[0080] The first preset condition is that the target number of sampling points is less than the vibration period threshold, and the second preset condition is that the target peak-to-peak value is greater than the vibration fluctuation threshold. The vibration period threshold and the vibration fluctuation threshold can be set as needed and are not limited here. For example, the vibration period threshold can be set to 175, and the vibration fluctuation threshold can be set to 2.5V.

[0081] Too few sampling points (too short a period) may indicate a vibration fault (such as a damaged bearing outer ring). Excessive peak-to-peak value indicates abnormal vibration amplitude, which may be caused by imbalance or looseness.

[0082] Optionally, before the alarm count value is first incremented, the alarm count value is initialized to accumulate the number of abnormal events. Initialization is usually performed when the system is started or after a manual reset.

[0083] Step 309: When the target number of sampling points meets the third preset condition, or the target peak-to-peak value meets the fourth preset condition, the alarm count value is decremented.

[0084] The third preset condition is that the product of the target number of sampling points and the preset multiple is greater than the vibration period threshold. The fourth preset condition is that the target peak-to-peak value is less than the product of the vibration fluctuation threshold and the preset fraction. The preset multiple and preset fraction can be set as needed and are not limited here. For example, the preset multiple is 3 and the preset fraction is 1 / 2. In addition, when the vibration returns to normal, the alarm count is gradually reduced to avoid continuous false alarm triggering. Optionally, the lower limit alarm count value can be set to ≥ 0 to prevent negative overflow.

[0085] Step 310: When the alarm count value is greater than the preset alarm threshold, an abnormal vibration result is output.

[0086] The preset alarm threshold is the critical condition that triggers an alarm (for example, C > 5). This threshold can be adjusted based on the device's priority and the level of environmental interference. Abnormal vibration detection outputs can take various forms: audible and visual alarms (such as a flashing red LED and a buzzer), digital signal output (such as a relay closure), and data upload (such as sending data to the cloud via a protocol). Specifically, the system can control a buzzer to sound an alarm, a flashing indicator light, or send a text message, email, or push notification to the target device.

[0087] In summary, the above-described embodiments of the present application provide a method for detecting abnormal vibrations that can calculate the frequency and peak value of a data waveform in real time and make effective judgments. By setting a triple threshold for graded evaluation, the false alarm rate of transient interference is significantly reduced. Furthermore, by dynamically dividing the vibration period, the vibration frequency and amplitude are calculated in real time without the need for windowing calculations, resulting in strong real-time performance and low computational complexity.

[0088] Further references Figure 4 As an implementation of the methods shown in the above figures, the present application provides an embodiment of an abnormal vibration detection device. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0089] like Figure 4 As shown, the abnormal vibration detection device 400 of this embodiment includes: a signal extraction module 401 , a sampling module 402 , a self-adding module 403 and an abnormality module 404 .

[0090] The signal extraction module 401 is used to extract the high-frequency vibration signal from the motor torque signal;

[0091] The sampling module 402 is configured to detect the number of sampling points and the peak-to-peak value of the high-frequency vibration signal within a vibration cycle as target number of sampling points and target peak-to-peak value;

[0092] The self-increment module 403 is configured to self-increment the alarm count value when the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition;

[0093] Abnormal module 404, for outputting abnormal vibration result in response to the alarm count value being greater than the preset alarm threshold

[0094] In this embodiment, the specific processing of the abnormal vibration detection device 400 and the technical effects thereof can be referred to respectively. Figure 2 The relevant descriptions of step 201, step 202, step 203 and step 204 in the corresponding embodiment are not repeated here.

[0095] In some optional implementations, the signal extraction module 401 includes:

[0096] an acquisition unit, configured to acquire a motor torque signal and a cutoff frequency, wherein the motor torque signal is a signal collected and sent by a sensor;

[0097] The filtering unit is used to perform high-pass filtering on the motor torque signal using the cutoff frequency to obtain a high-frequency vibration signal.

[0098] In some optional implementations, the sampling module 402 includes:

[0099] a counting unit, configured to count the sampling points of the high-frequency vibration signal in response to detecting a zero-crossing point of the high-frequency vibration signal, and obtain a positive maximum value and a negative maximum value of the high-frequency vibration signal;

[0100] a counting and statistics unit, configured to obtain a sampling count value for counting sampling points of the high-frequency vibration signal in response to detecting a zero-crossing point of the high-frequency vibration signal in the same direction again;

[0101] A judging unit, configured to judge whether the sampling count value is less than a preset sampling threshold;

[0102] a clearing unit, configured to clear the sample count value, the positive maximum value, and the negative maximum value of the high-frequency vibration signal if the sample count value is zero;

[0103] The result unit is configured to, if not, determine the sampling count value as the target number of sampling points, and calculate the difference between the positive maximum value and the negative maximum value of the high-frequency vibration signal as the target peak-to-peak value.

[0104] In some optional embodiments, the device further comprises:

[0105] The self-decrement module is used to self-decrement the alarm count value when the target number of sampling points meets a third preset condition or the target peak-to-peak value meets a fourth preset condition.

[0106] In some optional embodiments, the first preset condition is that the target number of sampling points is less than the vibration period threshold, the second preset condition is that the target peak-to-peak value is greater than the vibration floating threshold, the third preset condition is that the product of the target number of sampling points and a preset multiple is greater than the vibration period threshold, and the fourth preset condition is that the target peak-to-peak value is less than the product of the vibration floating threshold and a preset fraction.

[0107] In some optional embodiments, the device further comprises:

[0108] An initialization module is used to initialize the alarm count value.

[0109] In some optional implementations, the exception module 404 includes:

[0110] Buzzer unit, used to control the buzzer to make a buzzer sound;

[0111] and / or, a flashing unit, for controlling the indicator light to flash;

[0112] And / or, a push unit, configured to send a text message, email, or push message to a target device.

[0113] It should be noted that the implementation details and technical effects of each module and unit in the abnormal vibration detection device 400 provided in the embodiment of the present application can be referred to the description of other embodiments in the present application, and will not be repeated here.

[0114] Reference below Figure 5 , which shows a structural diagram of a computer system 500 suitable for implementing the electronic device of the present application. Figure 5 The computer system 500 shown is only an example and should not limit the functions and scope of use of the embodiments of the present application.

[0115] like Figure 5 As shown, computer system 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. RAM 503 also stores various programs and data required for the operation of computer system 500. Processing device 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to bus 504.

[0116] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the computer system 500 to communicate with other devices wirelessly or by wire to exchange data. Figure 5 The computer system 500 of the electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0117] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present application are performed.

[0118] It should be noted that the computer-readable medium referred to in this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wire, optical cable, RF (radio frequency), or any suitable combination thereof.

[0119] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0120] The computer readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can realize the following operation: Figure 2 The illustrated embodiment and its alternative implementations illustrate a method for detecting abnormal vibrations.

[0121] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0122] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0123] The units or modules involved in the embodiments described in this application may be implemented in software or hardware, wherein the name of a unit or module does not, in some cases, limit the unit itself.

[0124] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the disclosure herein is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned disclosure. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for detecting abnormal vibration, characterized in that: include: Extract high-frequency vibration signal from motor torque signal; Detecting the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as target number of sampling points and target peak-to-peak value; When the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition, the alarm count value is automatically incremented; In response to the alarm count value being greater than a preset alarm threshold, outputting an abnormal vibration result; The detecting of the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as the target number of sampling points and target peak-to-peak value includes: In response to detecting a zero-crossing point of the high-frequency vibration signal, counting sampling points of the high-frequency vibration signal and obtaining a positive maximum value and a negative maximum value of the high-frequency vibration signal; In response to detecting the zero-crossing point of the high-frequency vibration signal in the same direction again, obtaining a sampling count value for counting the sampling points of the high-frequency vibration signal; Determine whether the sampling count value is less than a preset sampling threshold; If so, clearing the sampling count value, the positive maximum value, and the negative maximum value of the high-frequency vibration signal; If not, the sampling count value is determined as the target number of sampling points, and the difference between the positive maximum value and the negative maximum value of the high-frequency vibration signal is calculated as the target peak-to-peak value.

2. The method according to claim 1, characterized in that The step of extracting the high-frequency vibration signal from the motor torque signal comprises: Obtaining a motor torque signal and a cutoff frequency, wherein the motor torque signal is a signal collected and sent by a sensor; The motor torque signal is subjected to high-pass filtering using the cutoff frequency to obtain a high-frequency vibration signal.

3. The method according to claim 1, characterized in that The method further comprises: When the target number of sampling points meets a third preset condition or the target peak-to-peak value meets a fourth preset condition, the alarm count value is decremented.

4. The method according to claim 3, characterized in that The first preset condition is that the target number of sampling points is less than the vibration period threshold, the second preset condition is that the target peak-to-peak value is greater than the vibration floating threshold, the third preset condition is that the product of the target number of sampling points and a preset multiple is greater than the vibration period threshold, and the fourth preset condition is that the target peak-to-peak value is less than the product of the vibration floating threshold and a preset fraction.

5. The method according to claim 1, characterized in that Before the step of self-increasing the alarm count value, the method further comprises: Initialize the alarm count value.

6. The method according to claim 1, wherein The output abnormal vibration result includes: Control the buzzer to beep, and / or control the indicator light to flash, and / or send a text message, email, or push message to the target device.

7. An abnormal vibration detection device, characterized in that: include: A signal extraction module is used to extract high-frequency vibration signals from motor torque signals; A sampling module is used to detect the number of sampling points and peak-to-peak value of the high-frequency vibration signal within a vibration cycle as the target number of sampling points and target peak-to-peak value; A self-increasing module, configured to self-increase the alarm count value when the target number of sampling points meets a first preset condition or the target peak-to-peak value meets a second preset condition; an abnormality module, configured to output an abnormal vibration result in response to the alarm count value being greater than a preset alarm threshold; Wherein, the sampling module includes: a counting unit, configured to count the sampling points of the high-frequency vibration signal in response to detecting a zero-crossing point of the high-frequency vibration signal, and obtain a positive maximum value and a negative maximum value of the high-frequency vibration signal; a counting and statistics unit, configured to obtain a sampling count value for counting sampling points of the high-frequency vibration signal in response to detecting a zero-crossing point of the high-frequency vibration signal in the same direction again; A judging unit, configured to judge whether the sampling count value is less than a preset sampling threshold; a clearing unit, configured to clear the sample count value, the positive maximum value, and the negative maximum value of the high-frequency vibration signal if the sample count value is zero; The result unit is configured to, if not, determine the sampling count value as the target number of sampling points, and calculate the difference between the positive maximum value and the negative maximum value of the high-frequency vibration signal as the target peak-to-peak value.

8. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by one or more processors, the method according to any one of claims 1 to 6 is implemented.

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