WO2021036663A1 - Procédé de détection d'anomalie de vis fixe pour dispositif et produits associés - Google Patents

Procédé de détection d'anomalie de vis fixe pour dispositif et produits associés Download PDF

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Publication number
WO2021036663A1
WO2021036663A1 PCT/CN2020/105619 CN2020105619W WO2021036663A1 WO 2021036663 A1 WO2021036663 A1 WO 2021036663A1 CN 2020105619 W CN2020105619 W CN 2020105619W WO 2021036663 A1 WO2021036663 A1 WO 2021036663A1
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preset
test point
video
target
vibration data
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PCT/CN2020/105619
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English (en)
Chinese (zh)
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高风波
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深圳市豪视智能科技有限公司
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Publication of WO2021036663A1 publication Critical patent/WO2021036663A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H9/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts

Definitions

  • This application relates to the technical field of vibration detection, and specifically relates to a detection method for abnormality of a fixing screw of a device and related products.
  • vibration detection is an important part. For example, when the equipment is running, if the fixing screws on the equipment are abnormal, the equipment may be unstable. Therefore, it is necessary to correct the equipment when it is unstable. The vibration of the equipment is detected to provide a reference for the maintenance of the equipment.
  • the accelerometer requires a long preparation and installation time, requires physical contact with the system under test during the test (therefore, it will change the vibration response of the system under test), and can only test a limited number of discrete points, so In order to better maintain the equipment, it is necessary to detect the vibration of the equipment caused by the abnormal screw more accurately and reliably.
  • the embodiment of the present application provides a method for detecting an abnormality of a fixing screw of a device and related products, which can extract the vibration data of the fixing screw through a shooting video of the fixing screw on the device, so as to detect the abnormality of the fixing screw of the device more accurately.
  • the first aspect of the embodiments of the present application provides a method for detecting abnormality of a fixing screw of a device, which is applied to a vibration detection device, and the method includes:
  • the vibration data determine at least one target test point whose vibration data does not meet a preset condition among the plurality of test points, mark the at least one target test point as an abnormal test point, and compare the The target video area corresponding to at least one target test point is displayed.
  • a second aspect of the embodiments of the present application provides a device for detecting an abnormality of a fixing screw of a device, which is applied to a vibration detection device, and the device includes:
  • An acquiring unit configured to acquire a shooting video for a fixing screw set on a preset component on the device to be tested
  • a processing unit configured to process the shot video according to a preset motion amplification algorithm to obtain an enlarged video; and extract vibration data of a plurality of test points for the fixed screw from the enlarged video;
  • a determining unit configured to determine, according to the vibration data, at least one target test point whose vibration data does not meet a preset condition among the plurality of test points, and mark the at least one target test point as an abnormal test point;
  • the display unit is configured to display the target video area corresponding to the at least one target test point in the enlarged video.
  • a third aspect of the embodiments of the present application provides a vibration detection device, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured Executed by the foregoing processor, the foregoing program includes instructions for executing the steps in the method described in the first aspect of the embodiments of the present application.
  • the fourth aspect of the embodiments of the present application provides a computer-readable storage medium.
  • the above-mentioned computer-readable storage medium is used to store a computer program, and the above-mentioned computer program is executed by a processor to implement the method described in the first aspect of the embodiments of the present application. Part or all of the steps described in the method.
  • the fifth aspect of the embodiments of the present application provides a computer program product.
  • the computer program product includes a non-transitory computer-readable storage medium storing a computer program.
  • the computer program is operable to cause a computer to execute Part or all of the steps described in the method described in one aspect.
  • FIG. 1A is a system architecture diagram of a method for detecting abnormality of a fixing screw of a device according to an embodiment of the application;
  • FIG. 1B is a schematic flowchart of a method for detecting abnormality of a fixing screw of a device according to an embodiment of the application;
  • FIG. 2 is a schematic flowchart of another method for detecting abnormality of a fixed screw of a device provided by an embodiment of the application;
  • FIG. 3 is a schematic flowchart of another method for detecting abnormality of a fixing screw of a device provided by an embodiment of the application;
  • FIG. 4 is a schematic structural diagram of a vibration detection device provided by an embodiment of the application.
  • FIG. 5 is a schematic structural diagram of a device for detecting abnormality of a fixing screw of a device according to an embodiment of the application.
  • FIG. 1A is a schematic structural diagram of a detection system for an abnormality of a fixed screw of a device according to an embodiment of the present application.
  • the detection system includes: a device to be detected and a vibration detection device, wherein the device to be detected is provided with Fix the screws.
  • the vibration detection devices involved in the embodiments of the present application may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to wireless modems, as well as various forms of users.
  • Equipment user equipment, UE
  • mobile station mobile station, MS
  • terminal device terminal device
  • the devices mentioned above are collectively referred to as vibration detection devices.
  • the vibration involved in the embodiments of the present application refers to the reciprocating motion of an object relative to a stationary reference object or an object in a balanced state.
  • the vibration generated by the device to be tested during operation may include mechanical vibration generated by the internal interaction of the device to be tested, for example, engine vibration or gear vibration, or mechanical vibration due to external force.
  • the equipment to be tested will mechanically vibrate at a fixed frequency during operation, and when the equipment to be tested fails, the vibration frequency of the equipment to be tested will also change, for example, when the fixed screws on the equipment to be tested Looseness may cause changes in the vibration of the equipment to be tested during operation. Therefore, the vibration detection equipment can be used to perform vibration testing on the equipment to be tested, and the abnormality of the fixing screws can be estimated, so as to facilitate the maintenance of the equipment to be tested.
  • FIG. 1B is a schematic flowchart of a method for detecting abnormality of a fixing screw of a device according to an embodiment of the present application.
  • the method for detecting an abnormality of a fixing screw of a device provided by an embodiment of the present application is applied to a vibration detection device, and the method for detecting an abnormality of a fixing screw of the device may include the following steps:
  • the above-mentioned preset component is a component provided with fixing screws on the equipment to be tested, and the preset component may be, for example, a base of the equipment to be tested.
  • the vibration detection device can obtain the shooting video for the fixed screw on the device to be detected through the camera.
  • the inspector can aim the camera of the vibration detection device at the fixing screw on the device to be tested, and the vibration detection device can take a video of the device to be tested containing vibration and the fixing screw.
  • the vibration detection device may receive the shooting video transmitted by other devices, and the other device refers to an electronic device that stores the shooting video.
  • the preset motion amplification algorithm may include at least one of the following: Lagrangian motion amplification algorithm, Euler motion amplification algorithm, complex phase motion amplification algorithm, RIESZ pyramid motion amplification algorithm.
  • the motion amplification algorithm can be used to amplify the fixed screw and the minute vibration near the fixed screw in the shooting video to obtain an enlarged video.
  • processing the captured video according to a preset motion zoom algorithm to obtain the zoomed video may include the following steps:
  • the pixels in each frame of the multiple frames of video images contain RGB color information.
  • RGB is a color standard in the industry, and each pixel contains red (R).
  • R red
  • YIQ is the television system standard of the National Television Standards Committee (NTSC).
  • NTSC National Television Standards Committee
  • Y is the brightness component that provides black-and-white TV and color TV
  • I represents the chromaticity component of the color from orange to cyan
  • Q represents the chromaticity component of the color from purple to yellow-green.
  • a multi-frame video image can be converted from the RGB color space to the YIQ color space to obtain a multi-frame reference image.
  • the pixels of each reference image in the multi-frame reference image include luminance component Y, chrominance component I, and Chrominance component Q.
  • the RGB color information of each pixel of each video image in the multi-frame video image can be converted by the following conversion formula to obtain the YIQ color information of each pixel:
  • the brightness information in the multiple frames of reference images may be subjected to Fourier transform (fast fourier transform, FFT) processing to obtain multiple frames of target images.
  • FFT processing can be performed on the brightness information of each pixel of each reference image in the multi-frame reference image, and the brightness change in the time domain corresponding to the same pixel in the multi-frame reference image can be converted into the phase change in the frequency domain. .
  • the multi-frame target image can be processed according to any one of the Lagrangian motion amplification algorithm, Euler motion amplification algorithm, complex phase motion amplification algorithm, and RIESZ pyramid motion amplification algorithm to obtain multi-frame zoomed images.
  • processing the multi-frame target image according to the motion magnification algorithm to obtain a multi-frame magnified image may include the following steps:
  • each frame of the target image can be calibrated to obtain stable multiple motion feature points.
  • multiple motion feature points refer to feature points whose motion amplitude is less than a preset range, so as to be consistent with the stillness in the target video.
  • the point background point
  • the trajectory vector uses numerical values to describe the motion direction, motion distance, and brightness change of the motion feature point; then clustering algorithm is used to analyze the multiple motion feature points.
  • the trajectory vector is clustered to obtain the K-type motion layer, and the K-type motion layer is divided according to the correlation and similarity of the trajectory vector, so that different motion layers can contain different types of motion, so as to select the small motion in the K-type motion layer
  • the corresponding motion layer is enlarged to obtain an enlarged motion layer.
  • the multi-frame target image can be magnified by the Lagrangian motion magnification algorithm to obtain a multi-frame magnified image.
  • processing the multi-frame target image according to the motion magnification algorithm to obtain a multi-frame magnified image may include the following steps:
  • a Gaussian pyramid is used to decompose a multi-frame target image, that is, a set of multi-frame target images whose size is halved layer by layer constitutes a pyramid structure.
  • Each level of image in the structure is the result of low-pass filtering of the previous level of image and interlaced sampling.
  • Pyramid decomposition is to perform spatial filtering on multiple frames of target images, decompose to obtain frequency bands of different spatial frequencies, and amplify these frequency bands respectively. Because frequency bands at different spatial frequencies correspond to different signal-to-noise ratios, the lower the spatial frequency, the less image noise and the higher the signal-to-noise ratio. Therefore, different amplification factors can be set for each layer of spatial frequency bands. For example, a linearly variable magnification factor can be used to amplify frequency bands of different frequencies. In the pyramid structure, from the top to the bottom, the magnifications are sequentially reduced.
  • time-domain band-pass filtering can be performed on each frequency band to obtain the transformed signal of interest, that is, the transformed signal corresponding to the target frequency band, and only the transformation corresponding to the target frequency band The signal is amplified.
  • ideal band-pass filters, Butterworth band-pass filters, second-order infinite impulse response filters, etc. can be used.
  • ⁇ (t) represents the displacement signal
  • Amplify I(x,t) by ⁇ times, that is, amplify the displacement signal ⁇ (t), and the amplified signal is:
  • magnification is related to the spatial frequency and satisfies the following relationship:
  • the spatial frequency is ⁇
  • the spatial wavelength of the target frequency band is ⁇
  • ⁇ 2 ⁇ / ⁇
  • the maximum value of ⁇ can be determined by the displacement function of the target frequency band and the transformed signal. A max ⁇ .
  • the amplified signal After the amplified signal is obtained, it is combined with the original frequency band again, and then pyramid reconstruction, such as Laplace pyramid transformation reconstruction, is used to obtain multiple frames of enlarged images.
  • pyramid reconstruction such as Laplace pyramid transformation reconstruction
  • phase correlation calculation, interpolation filtering, and inverse Fourier transform processing DFFT processing can be performed on the enlarged image in the enlarged video to obtain the vibration data of the pixels in the enlarged image.
  • extracting vibration data of multiple test points for the fixing screw from the enlarged video may include the following steps:
  • the first cross cross power spectrum between the multiple frames of the zoomed-in images in the zoomed-in video may be calculated according to a preset phase correlation algorithm.
  • the following formula may be used to calculate the first cross cross power spectrum.
  • R is a first cross crosspower, F.
  • F * 'b of the b-th frame image signal of the conjugated Fourier transform in addition to two lower Fourier formula The modulus of the correlation product of the transformed signal.
  • the filter bank can be adaptively selected for filtering according to the position of the correlation peak of the first cross cross power spectrum R to obtain the filtered second cross cross power spectrum R′.
  • performing interpolation filtering according to the first cross cross power spectrum to obtain the second cross cross power spectrum after interpolation filtering may include the following steps:
  • the first cross cross power spectrum R is a frequency domain signal, which includes one or more correlation peaks.
  • the state change signal corresponding to each correlation peak can be obtained.
  • Each state change signal can reflect the state change of a certain position in the amplified video. Therefore, a predetermined length of the target state change signal segment can be extracted from the multiple state change signals to obtain multiple target state change signal segments .
  • the state change information includes vibration data and other noise information. For example, changes in illumination can also cause state changes in the video screen, and the vibration data can reflect the operating conditions of the object to be vibrated.
  • the vibration of the equipment to be tested is periodic when it is running, and the state change caused by the vibration is also periodic.
  • the state change caused by noise is often not periodic, and when the operating condition of the device to be tested is analyzed according to the vibration of the device to be tested, it shows periodic vibration. It can be used to reflect the operating conditions of the device to be tested, because the non-periodic vibration is often caused by the external environment, not by the device to be tested itself, and this part of the non-periodic signal cannot be used to analyze the device to be tested. Health status. Acquire noise signals that are not caused by self-vibration by acquiring non-periodic signals in the state change signals.
  • aperiodic signals are often signals that have little effect or no effect or even interference in analyzing the operating conditions of the device to be tested, this part of the aperiodic signal can be removed, so that the state change signal obtained from the amplified video, More useful information.
  • each state change signal is a periodic signal.
  • a target state change signal segment with a preset length can be extracted first, the target frequency of the target change signal segment can be obtained, and then the state The frequencies of other parts in the change signal are compared with the target frequency. If the frequencies of other parts in the state change signal are not consistent with the target frequency, the state change signal can be regarded as a non-periodic signal.
  • the preset length can be set by a user to a certain value, or it can be self-adapted according to the length of the signal during signal processing. For example, the preset length can be set to 1/10 of the length of the state change signal.
  • the window size of the sliding window can be set according to the target frequency.
  • the window size of the sliding window can be set to be consistent with the target frequency, so that only signals with the same frequency as the target frequency can pass through the sliding window.
  • signals that are inconsistent with the target frequency cannot pass through the sliding window.
  • the state change signal cannot pass through the corresponding sliding window, it means that there is a signal segment whose frequency is inconsistent with the target frequency in the state change signal, that is, the state change signal is a non-periodic signal. In this way, by judging whether the frequencies of other parts of the state change signal are consistent with the target frequency by means of sliding windows, conclusions can be obtained conveniently and quickly, and the amount of calculation is smaller.
  • the filtered second cross cross power spectrum R' can be subjected to inverse Fourier transform, and phase comparison (phase-by-phase comparison) can be performed.
  • the sliding window adaptive matching method can be used to extract the distance fixation screw preset Vibration data of pixels corresponding to multiple test points within the distance range. The calculation formula is as follows:
  • F -1 ⁇ R' ⁇ is the inverse Fourier transform of the second cross cross power spectrum R'
  • r is the vibration data of the pixels in the zoomed-in video, so that the vibrations of all the pixels in the zoomed-in video can be obtained data.
  • the target position of the fixing screw can be obtained, and then the vibration data of the pixel points corresponding to the multiple test points within the preset distance range from the target position can be determined.
  • the vibration data includes at least one of the following: vibration amplitude, frequency, phase, and time-domain waveform.
  • the vibration data of the pixels corresponding to the multiple test points within the preset distance range near the fixed screw in the enlarged video can be selected to obtain multiple sets of vibration data. Therefore, each of the multiple sets of vibration data can be further selected based on the vibration data. The group of vibration data determines whether the corresponding test point is an abnormal test point.
  • determining at least one target test point whose vibration data does not satisfy a preset condition among the plurality of test points according to the vibration data may include the following steps:
  • the vibration amplitude is in the preset vibration amplitude range; the frequency is in the preset frequency range; the phase is in the preset phase range; the time domain waveform is matched with the preset reference time domain waveform to obtain A matching value, the matching value being in a preset matching value range;
  • determining whether the test point is a target test point according to the vibration data corresponding to the test point may include: determining whether the vibration data corresponding to the test point meets the aforementioned requirements. Condition, if the vibration amplitude is in the preset vibration amplitude range; the frequency is in the preset frequency range; the phase is in the preset phase range; the time domain waveform is matched with the preset reference time domain waveform to obtain the matching value, matching If the value is within the preset matching value range, the test point is not the target test point. If the vibration data corresponding to the test point does not meet any of the above conditions, the test point can be determined as the target test point. And mark the test point as an abnormal test point.
  • At least one target test point and non-target test points other than the target test point among the plurality of test points can be determined, and the target test point can be marked as an abnormal test point.
  • the target video area corresponding to at least one target test point in the zoomed-in video may be displayed, specifically, the target video area corresponding to at least one target test point in the zoomed-in video may be displayed.
  • the preset component is the base of the device to be tested. In the embodiment of the present application, it may further include the following steps:
  • A1 Obtain the position of each target test point in the base in the at least one target test point to obtain at least one position
  • A2 Determine a shock reduction strategy according to the at least one location and the vibration data of each target test point in the at least one target test point.
  • the position of each target test point on the base can be determined, and if there is a target position in the first position area in at least one position, the vibration reduction strategy can be further determined according to the vibration data of the target test point at the target position.
  • determining a vibration reduction strategy according to the at least one location and the vibration data of each target test point in the at least one target test point may include the following steps:
  • A22 For the vibration data of each target test point in the at least one target test point, determine a vibration amplitude deviation value according to the vibration amplitude and a preset vibration amplitude threshold; determine the frequency according to the frequency and the preset frequency threshold Deviation value; determining a frequency deviation value according to the phase and a preset phase threshold; determining a time-domain waveform deviation value according to the matching value and the preset matching value threshold;
  • the vibration The amplitude deviation value is greater than the first preset deviation value; the frequency deviation value is greater than the second preset deviation value; the frequency deviation value is greater than the third preset deviation value; the time domain waveform deviation value is greater than the fourth preset deviation value.
  • the vibration amplitude threshold corresponding to the vibration amplitude, the frequency threshold corresponding to the frequency, the phase threshold corresponding to the phase, and the matching value threshold corresponding to the matching value can be preset. Therefore, for the vibration data of each target test point in at least one target test point, the vibration amplitude and the preset vibration amplitude threshold value can be determined to determine the vibration amplitude deviation value; the frequency deviation value is determined according to the frequency and the preset frequency threshold value; and the frequency deviation value is determined according to the phase Determine the frequency deviation value with the preset phase threshold; determine the time-domain waveform deviation value according to the matching value and the preset matching value threshold.
  • the vibration amplitude deviation value is greater than the first preset Deviation value; the frequency deviation value is greater than the second preset deviation value; the frequency deviation value is greater than the third preset deviation value; the time domain waveform deviation value is greater than the fourth preset deviation value.
  • the anti-vibration plate strategy is the strategy of adding anti-vibration plates to the base.
  • the effect of shock absorption can be achieved by the anti-vibration plate.
  • the vibration detection device can obtain the shooting video for the fixing screws set on the preset component on the device to be detected, and process the shooting video according to the preset motion amplification algorithm to obtain the enlarged video, from Extract the vibration data of multiple test points for the fixed screw from the enlarged video, determine at least one target test point whose vibration data does not meet the preset conditions among the multiple test points according to the vibration data, and mark the at least one target test point as an abnormal test point , And display the target video area corresponding to at least one target test point in the enlarged video.
  • the vibration data of the fixed screw can be extracted from the video of the fixed screw on the device, and the test point with abnormal vibration near the fixed screw can be determined based on the vibration data Therefore, the abnormality of the fixing screw of the device can be detected more accurately.
  • FIG. 2 is a schematic flowchart of another method for detecting abnormality of a fixed screw of a device provided by an embodiment of the present application.
  • the method for detecting abnormality of a fixed screw of a device provided by the embodiment of the present application is applied to a vibration detection device ,
  • the detection method for the abnormality of the fixed screw of the device includes:
  • the vibration detection device can obtain the shooting video for the fixing screws set on the preset component on the device to be detected, divide the shooting video into multiple frames of video images, and divide the multiple frames of video images from RGB colors.
  • the space is converted to YIQ color space to obtain a multi-frame reference image, Fourier transform FFT processing is performed on the brightness information in the multi-frame reference image, and a multi-frame target image is obtained.
  • the multi-frame target image is processed according to the motion amplification algorithm to obtain a multi-frame target image.
  • Frame magnified images combine multiple magnified images to obtain a magnified video, extract vibration data of multiple test points for the fixed screw from the magnified video, and determine the vibration data of multiple test points that do not meet the preset conditions according to the vibration data
  • At least one target test point at least one target test point is marked as an abnormal test point, and the target video area corresponding to at least one target test point in the zoomed-in video is displayed.
  • the vibration data of the fixed screw can be extracted by the motion zoom algorithm, And according to the vibration data, determine the test point of abnormal vibration near the fixing screw, so that the abnormality of the fixing screw of the device can be detected more accurately.
  • FIG. 3 is a schematic flowchart of a method for detecting abnormality of a fixing screw of a device according to an embodiment of the present application.
  • the method for detecting abnormality of a fixed screw of a device provided by an embodiment of the present application is applied to a vibration detection device, and the method for detecting abnormality of a fixed screw of the device may include the following steps:
  • the vibration detection device can obtain the shooting video for the fixing screws set on the preset component on the device to be detected, and process the shooting video according to the preset motion zoom algorithm to obtain the zoomed video.
  • the video extracts the vibration data of multiple test points for the fixed screw, determines at least one target test point whose vibration data does not meet the preset condition among the multiple test points according to the vibration data, and marks the at least one target test point as an abnormal test point,
  • the target video area corresponding to at least one target test point in the zoomed-in video is displayed, and the position of each target test point in the at least one target test point on the base is obtained, and at least one position is obtained.
  • the vibration data of each target test point in the test point determines the vibration reduction strategy.
  • the vibration data of the fixed screw can be extracted from the video of the fixed screw on the device, and the test point with abnormal vibration near the fixed screw can be determined based on the vibration data, so that, It can detect the abnormality of the fixed screw of the equipment more accurately.
  • it can also provide the corresponding shock absorption strategy for the abnormal test point, which is conducive to the maintenance of the equipment to be tested.
  • the image information determining apparatus includes hardware structures and/or software modules corresponding to each function.
  • the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed by hardware or computer software-driven hardware depends on the specific application and design constraint conditions of the technical solution. Professionals and technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of this application.
  • the embodiment of the present application may divide the image information determining apparatus into functional units according to the foregoing method examples.
  • each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit. It should be noted that the division of units in the embodiments of the present application is illustrative, and is only a logical function division, and there may be other division methods in actual implementation.
  • FIG. 4 is a schematic structural diagram of a vibration detection device disclosed in an embodiment of the present application.
  • the vibration detection device includes a processor, a memory, a communication interface, and one or more programs. Or multiple programs are stored in the above-mentioned memory and configured to be executed by the above-mentioned processor, and the above-mentioned programs include instructions for executing the following steps:
  • the vibration data determine at least one target test point whose vibration data does not meet a preset condition among the plurality of test points, mark the at least one target test point as an abnormal test point, and compare the The target video area corresponding to at least one target test point is displayed.
  • the foregoing program includes instructions for executing the following steps:
  • the multiple frames of enlarged images are synthesized to obtain the enlarged video.
  • the motion amplification algorithm may include at least one of the following: Lagrangian motion amplification algorithm, Euler motion amplification algorithm, complex phase motion amplification algorithm, RIESZ pyramid motion amplification algorithm.
  • the above program includes instructions for executing the following steps:
  • vibration data of pixels corresponding to a plurality of test points within a preset distance from the fixing screw are selected.
  • the vibration data includes at least one of the following: vibration amplitude, frequency, phase, and time-domain waveform. It is determined according to the vibration data that the vibration data does not satisfy a preset value among the multiple test points.
  • the above-mentioned program includes instructions for performing the following steps:
  • the vibration amplitude is in the preset vibration amplitude range; the frequency is in the preset frequency range; the phase is in the preset phase range; the time domain waveform is matched with the preset reference time domain waveform to obtain A matching value, the matching value being in a preset matching value range;
  • test point corresponding to a pixel point that does not meet any of the foregoing conditions is the target test point, and at least one target test point is obtained.
  • the preset component is the base of the device to be tested, and the above program further includes instructions for executing the following steps:
  • a shock reduction strategy is determined according to the at least one location and the vibration data of each target test point in the at least one target test point.
  • the program further includes instructions for executing the following steps :
  • each target test point in the at least one target test point determine a vibration amplitude deviation value according to the vibration amplitude and a preset vibration amplitude threshold; determine a frequency deviation value according to the frequency and the preset frequency threshold Determine the frequency deviation value according to the phase and the preset phase threshold; determine the time-domain waveform deviation value according to the matching value and the preset matching value threshold;
  • the shock absorber strategy of the shock absorption strategy determines the shock absorber strategy of the shock absorption strategy: the vibration amplitude deviation The value is greater than the first preset deviation value; the frequency deviation value is greater than the second preset deviation value; the frequency deviation value is greater than the third preset deviation value; the time domain waveform deviation value is greater than the fourth preset deviation value.
  • FIG. 5 is a schematic structural diagram of a device for detecting an abnormality of a fixing screw of a device disclosed in an embodiment of the present application, which is applied to a vibration detection device.
  • the device for detecting an abnormality of a fixing screw of the device includes an acquiring unit 501 , The processing unit 502, the determining unit 503, and the display unit 504, wherein:
  • the acquiring unit 501 is configured to acquire a shooting video of a fixing screw set on a preset component on the device to be tested;
  • the processing unit 502 is configured to process the shooting video according to a preset motion amplification algorithm to obtain an enlarged video; and extract vibration data for multiple test points of the fixed screw from the enlarged video;
  • the determining unit 503 is configured to determine at least one target test point whose vibration data does not meet a preset condition among the plurality of test points according to the vibration data, and mark the at least one target test point as an abnormal test point;
  • the display unit 504 is configured to display the target video area corresponding to the at least one target test point in the zoomed-in video.
  • the processing unit 502 is specifically configured to:
  • the multiple frames of enlarged images are synthesized to obtain the enlarged video.
  • the motion amplification algorithm may include at least one of the following: Lagrangian motion amplification algorithm, Euler motion amplification algorithm, complex phase motion amplification algorithm, RIESZ pyramid motion amplification algorithm.
  • the processing unit 502 is specifically configured to:
  • vibration data of pixels corresponding to a plurality of test points within a preset distance from the fixing screw are selected.
  • the vibration data includes at least one of the following: vibration amplitude, frequency, phase, and time-domain waveform, and it is determined according to the vibration data that the vibration data does not meet a preset condition at least A target test point, the determining unit 503 is specifically configured to:
  • the vibration amplitude is in the preset vibration amplitude range; the frequency is in the preset frequency range; the phase is in the preset phase range; the time domain waveform is matched with the preset reference time domain waveform to obtain A matching value, the matching value being in a preset matching value range;
  • test point corresponding to a pixel point that does not meet any of the foregoing conditions is the target test point, and at least one target test point is obtained.
  • the preset component is a base of the device to be tested
  • the acquiring unit 501 is further configured to acquire the position of each target test point in the base in the at least one target test point to obtain at least one position;
  • the determining unit 503 is further configured to determine a vibration reduction strategy according to the at least one location and the vibration data of each target test point in the at least one target test point.
  • the determining unit 503 is specifically configured to:
  • each target test point in the at least one target test point determine a vibration amplitude deviation value according to the vibration amplitude and a preset vibration amplitude threshold; determine a frequency deviation value according to the frequency and the preset frequency threshold Determine the frequency deviation value according to the phase and the preset phase threshold; determine the time-domain waveform deviation value according to the matching value and the preset matching value threshold;
  • the shock absorber strategy of the shock absorption strategy determines the shock absorber strategy of the shock absorption strategy: the vibration amplitude deviation The value is greater than the first preset deviation value; the frequency deviation value is greater than the second preset deviation value; the frequency deviation value is greater than the third preset deviation value; the time domain waveform deviation value is greater than the fourth preset deviation value.
  • the vibration detection device can obtain the shooting video of the fixed screw set on the preset component on the device to be detected, and process the shooting video according to the preset motion amplification algorithm to obtain the enlarged video , Extract the vibration data of multiple test points for the fixed screw from the enlarged video, determine at least one target test point whose vibration data does not meet the preset condition among the multiple test points according to the vibration data, and mark the at least one target test point as abnormal Test points, and display the target video area corresponding to at least one target test point in the enlarged video.
  • the vibration data of the fixed screw can be extracted from the video of the fixed screw on the device, and the vibration data near the fixed screw can be determined according to the vibration data.
  • the test point can detect the abnormality of the fixing screw of the device more accurately.
  • An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program causes the computer to execute any of the fixing screws for the device as described in the above method embodiments. Part or all of the steps of the abnormal detection method.
  • the embodiments of the present application also provide a computer program product.
  • the computer program product includes a non-transitory computer-readable storage medium storing a computer program.
  • the computer program causes a computer to execute any of the methods described in the above-mentioned method embodiments. Part or all of the steps of the method of detecting abnormality of the fixing screws of the equipment.
  • the disclosed device may be implemented in other ways.
  • the device embodiments described above are merely illustrative, for example, the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical or other forms.
  • 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 units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each functional unit in each embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be realized in the form of hardware or software program module.
  • the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer readable memory.
  • the technical solution of the present application essentially or the part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory.
  • a number of instructions are included to enable a computer device (which may be a personal computer, a vibration detection device, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned memory includes: U disk, read-only memory (read-only memory, ROM), random access memory (random access memory, RAM), mobile hard disk, magnetic disk, or optical disk and other media that can store program codes.
  • the program can be stored in a computer-readable memory, and the memory can include: a flash disk , Read-only memory, random access device, magnetic or optical disk, etc.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

L'invention concerne un procédé de détection d'anomalie d'une vis fixe pour un dispositif. Le procédé consiste à : obtenir une vidéo photographique pour une vis fixe disposée dans un composant prédéfini sur un dispositif à détecter (101) ; traiter la vidéo photographique selon un algorithme d'amplification de mouvement prédéfini pour obtenir une vidéo d'amplification (102) ; extraire des données de vibration d'une pluralité de points de test pour la vis fixe à partir de la vidéo d'amplification (103) ; et déterminer au moins un point de test cible dont les données de vibration ne satisfont pas une condition prédéfinie dans la pluralité de points de test selon les données de vibration, marquer le au moins un point de test cible en tant que point de test anormal et afficher une région vidéo cible correspondant à l'au moins un point de test cible dans la vidéo d'amplification (104). Selon le procédé, les données de vibration peuvent être extraites au moyen de la vidéo photographique de la vis fixe et les points de test avec une vibration anormale à proximité de la vis fixe sont déterminés en fonction des données de vibration, de sorte que l'anomalie de la vis fixe du dispositif puisse être détectée plus précisément. La présente invention concerne en outre un appareil et un dispositif pour détecter l'anomalie de la vis fixe du dispositif.
PCT/CN2020/105619 2019-04-26 2020-07-29 Procédé de détection d'anomalie de vis fixe pour dispositif et produits associés WO2021036663A1 (fr)

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