WO2021052021A1

WO2021052021A1 - Vibration measurement system

Info

Publication number: WO2021052021A1
Application number: PCT/CN2020/105618
Authority: WO
Inventors: 高风波
Original assignee: 深圳市豪视智能科技有限公司
Priority date: 2019-04-26
Filing date: 2020-07-29
Publication date: 2021-03-25
Also published as: CN110595605A

Abstract

A vibration measurement system comprises a video acquisition device (101), an environmental data acquisition device (102), and a measurement apparatus (103). The video acquisition device (101), the environmental data acquisition device (102), and the measurement apparatus (103) are portable integrated apparatuses. The video acquisition device (101) comprises a camera (104). The measurement apparatus (103) comprises a processor (105) and a display screen (106), and is communicatively connected to the camera (104) and the environmental data acquisition device (102). The camera (104) acquires a first video of a measurement object and transmits same to the measurement apparatus (103). The environmental data acquisition device (102) acquires humidity information and transmits same to the measurement apparatus (103). The processor (105) processes the received first video according to a preset vibration measurement algorithm so as to obtain a target video file, determines a vibration coefficient of the measurement object according to the target video file and the humidity information, and outputs abnormality indication information. The system improves real-time measurement results, and effectively improves the convenience of performing vibration measurement.

Description

Vibration detection system

Technical field

This application relates to the technical field of industrial detection, and in particular to a vibration detection system.

Background technique

All mechanical and motion systems will produce a variety of vibrations, some of which reflect the normal motion state of the system, while others reflect the abnormal motion state of the system (for example, internal system failures, unbalanced shaft connections, etc.) ), therefore, to predictively maintain system equipment, vibration detection is an important part.

At present, most of the vibration detection uses accelerometer equipment. Although it is more accurate and reliable, the accelerometer requires a long preparation and installation time. During the test, it needs to be in physical contact with the system under test, which will change the vibration response of the system under test. It can test limited discrete points, and the non-contact vibration detection equipment currently used mainly includes laser Doppler vibrometers, but laser Doppler vibrometers are expensive, and the measurement results are affected by the temperature and light of the test environment, and It can only test system equipment in a small area, and its use is greatly restricted.

Summary of the invention

The embodiments of the present application provide a vibration detection system, which can effectively implement non-contact vibration detection, reduce the cost of equipment, and improve the accuracy and real-time performance of detection results.

In the first aspect, an embodiment of the present application provides a vibration detection system. The vibration detection system includes a video collection device, an environmental data collection device, and a detection device, the collection device, the environmental data collection device, and the detection device It is a portable integrated device, the video acquisition device includes a camera, the detection device includes a processor and a display screen, and the detection device is in communication connection with the camera and the environmental data acquisition device, wherein:

The camera is used to obtain a first video of an object to be detected, and transmit the first video to the detection device;

The environmental data collection device is used to collect humidity information around the object to be detected, and transmit the humidity information to the detection device;

The processor is configured to process the received first video according to a preset vibration detection algorithm to obtain a target video file with a motion amplification effect of the object to be detected, wherein the motion amplification effect refers to the The movement situation of the area where the object to be detected moves is enlarged in the target video;

The processor is further configured to determine the vibration coefficient of the object to be detected according to the target video file and the humidity information, and output abnormality prompt information.

It can be seen that in the embodiments of the present application, the vibration detection system includes a video acquisition device, an environmental data acquisition device, and a detection device. The acquisition device, the environmental data acquisition device, and the detection device are portable integrated devices. The video acquisition device includes a camera, and the detection device includes The processor and the display screen, the detection equipment are in communication connection with the camera and the environmental data acquisition device, wherein: the camera is used to obtain the first video of the object to be detected, and the first video is transmitted to the detection equipment; the environmental data acquisition device is used to collect the The humidity information around the object is detected, and the humidity information is transmitted to the detection device; the processor is used to process the received first video according to the preset vibration detection algorithm to obtain the target video file with the motion amplification effect of the object to be detected; the processor also It is used to determine the vibration coefficient of the object to be detected according to the target video file and humidity information, and output abnormal prompt information; the above system is beneficial to improve the adaptability of the shooting process and the real-time performance of the detection results. Moreover, the camera is used to shoot the object to be detected The first video effectively realizes non-contact vibration detection, reduces equipment costs, and processes the first video with vibration detection algorithms to obtain target video files with motion amplification effects, and then determines abnormal data, which is beneficial to improve vibration detection In addition, the use of a portable integrated device that integrates the acquisition device and the detection device effectively improves the convenience of vibration detection.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

Fig. 1A is a schematic diagram of a portable integrated device of a vibration detection system disclosed in an embodiment of the present application;

Fig. 1B is a schematic diagram of an image of a vibration coefficient disclosed in an embodiment of the present application;

FIG. 1C is a schematic diagram of a display interface for abnormal data disclosed in an embodiment of the present application;

FIG. 1D is a schematic diagram of another display interface for abnormal data disclosed in an embodiment of the present application.

detailed description

In order to enable those skilled in the art to better understand the solutions of the application, the technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by a person of ordinary skill in the art without creative work shall fall within the protection scope of this application.

The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific sequence. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes unlisted steps or units, or optionally also includes Other steps or units inherent to these processes, methods, products or equipment.

Reference to "embodiments" herein means that a specific feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art clearly and implicitly understand that the embodiments described herein can be combined with other embodiments.

As shown in FIG. 1A, FIG. 1A is a schematic diagram of a portable integrated device of a vibration detection system provided by an embodiment of the present application. The vibration detection system includes a video acquisition device 101, an environmental data acquisition device 102, and a detection device 103. The video acquisition device 101, the environmental data acquisition device 102, and the detection device 103 are portable integrated devices, and the video acquisition device 101 includes a camera 104. The detection device 103 includes a processor 105 and a display screen 106. The detection device 103 is in communication connection with the camera 104 and the environmental data collection device 102, wherein:

The camera 104 is configured to obtain a first video of the object to be detected, and transmit the first video to the detection device 103;

The environmental data collection device 102 is configured to collect humidity information around the object to be detected, and transmit the humidity information to the detection device 103;

The processor 105 is configured to process the received first video according to a preset vibration detection algorithm to obtain a target video file with a motion amplification effect of the object to be detected, wherein the motion amplification effect refers to all The movement situation of the area where the object to be detected moves is enlarged in the target video;

The processor 105 is further configured to determine the vibration coefficient of the object to be detected according to the target video file and the humidity information, and output abnormality prompt information.

Wherein, the portable integrated device may include various handheld devices with wireless communication functions (as shown in FIG. 1A), wearable devices, computing devices or other processing devices connected to a wireless modem, as well as various forms of user equipment ( User Equipment, UE), terminal device (terminal device), etc.

The processor 105 is located on the main board 106 of the integrated device, and is communicatively connected with the camera 104 and the display screen 106.

The camera may be a camera in an integrated device, for example, a front or rear camera of a mobile device, which is not limited here. The vibration detection system may also include a tripod, which is used to stabilize the portable integrated device. equipment.

Wherein, the specific implementation manners for collecting the humidity information around the object to be detected may be various, for example, it may be determining the humidity information according to the surface humidity of the object to be detected, or it may be based on the object to be detected. The humidity in the surrounding air determines the humidity information, which is not limited here.

Wherein, the abnormal data may include a target video file (the video file is a vibration video of the object to be detected with a motion amplification effect), vibration data, abnormal type, maintenance plan, and output abnormal data according to the vibration data The specific implementation method is to first determine the abnormal type of the object to be detected and multiple maintenance plans based on the vibration data. The specific implementation methods for outputting the abnormal data can be various, for example, outputting a target video file. The files can be displayed as dynamic video images of different frequency bands, or can be output target video files and vibration data, or can be output real scene pictures and vibration data of the object to be detected, etc., which are not limited here.

In a possible example, in terms of processing the received first video according to a preset vibration detection algorithm to obtain a target video file with a motion amplification effect of the object to be detected, the processor is specifically configured to :

Converting the multi-frame images in the first video from the three primary colors RGB color space to the YIQ color space, and obtaining the brightness Y information of the multi-frame image;

Performing Fourier transform on the luminance Y information of the multi-frame image to obtain the frequency domain phase information of the multi-frame image to form a second video file containing the frequency domain phase information;

A video motion amplification algorithm is executed on the second video file to obtain the target video file with a motion amplification effect of the object to be detected.

Among them, YIQ is the television system standard (National Television Standards Committee, NTSC). Y is the Luminance signal (Brightness) that provides black-and-white TV and color TV. I stands for In-phase, the color ranges from orange to cyan, and Q stands for Quadrature-phase, and the color ranges from purple to yellow-green.

Wherein, the first video is divided into multiple frames of images, and the conversion from RGB color space to YIQ color space is performed, and the conversion relationship is:

Y＝0.299*R+0.587*G+0.114*B;

I=0.596*R–0.275*G–0.321*B;

Q=0.212*R-0.523*G+0.311*B.

Wherein, the specific implementation manner of executing the video motion amplification algorithm on the second video file to obtain the target video file with the motion amplification effect of the object to be detected is by executing the video motion amplification algorithm on the second video file , The enlarged Y channel image is obtained, and then the enlarged Y channel image is added to the converted I and Q channel images, and then reversely converted into RGB color space to obtain the target video file.

It can be seen that in this example, the vibration detection system amplifies the brightness Y information through a video motion amplification algorithm to obtain a target video file with a motion amplification effect, which is beneficial to improve the visibility of the vibration effect in the target video file.

In this possible example, in terms of performing a video motion amplification algorithm on the second video file to obtain the target video file with a motion amplification effect of the object to be detected, the processor is specifically configured to:

Performing spatial decomposition on the second video file to obtain image information of multiple scales;

Determining the resonance frequency of the object to be detected according to the image information and the object to be detected;

Determine the target frequency band according to the resonance frequency;

Performing time-domain band-pass filtering on the image information of the multiple scales to obtain the phase change signal of the target frequency band;

Amplify the phase change signal of the target frequency band, and perform a pyramid reconstruction operation to obtain the target video file with a motion amplification effect.

Among them, the material or shape or size of the object to be tested will correspond to different resonance frequencies. The processor can determine the resonance frequency of the object to be tested based on prior knowledge, such as mechanical equipment: the resonance frequency should be around 100Hz, etc. Not limited.

Wherein, the specific implementation manners for determining the target frequency band according to the resonance frequency may be various, for example, it may be determining the frequency band where the resonance frequency is located as the target frequency band, or determining the resonance frequency band The frequency bands in the preset range symmetrical on the left and right sides are the target frequency bands, etc., which are not limited here.

Wherein, the pyramid reconstruction operation is performed to obtain the target video file with the motion amplification effect, and the processor performs the pyramid reconstruction operation to obtain the Y channel image with the motion amplification effect, and the target with the motion amplification effect is obtained according to the Y channel image. The specific implementation of the video file is as described above.

It can be seen that in this example, the vibration detection system determines the target frequency band according to the resonance frequency band of the object to be detected, which is beneficial to improve the rationality of the target frequency band determination, thereby improving the effectiveness of vibration detection and effectively avoiding missing abnormal vibration frequency bands; the vibration detection system is targeting When the second video file executes the target video amplifying algorithm, different target frequency bands are selected for signal amplification according to the different objects to be detected, and the signal is amplified in a targeted manner, instead of performing signal amplification algorithms on all frequency bands, which is conducive to improvement. The intelligence of vibration detection and the improvement of the speed of vibration detection.

In a possible example, in terms of determining the vibration coefficient of the object to be detected according to the target video file and the humidity information, and outputting abnormality prompt information, the processor is specifically configured to:

Determine the vibration data of the object to be detected according to the target video file;

Determine the environmental coefficient of the object to be detected according to the object to be detected and the humidity information;

Determine the vibration coefficient according to the environmental coefficient and the vibration data;

And output abnormal prompt information according to the vibration data and the vibration coefficient.

Wherein, the vibration detection system determines the vibration coefficient according to the environmental coefficient and the vibration data, which is beneficial to dynamically determining the vibration detection result, and is beneficial to improve the accuracy of the vibration detection.

It can be seen that, in this example, when the vibration detection system uses the video motion amplification algorithm to process the second video file, the vibration coefficient is determined according to the environmental coefficient and the vibration data, which is beneficial to improve the rationality of vibration detection.

In this possible example, in the aspect of determining the vibration data of the object to be detected according to the target video file, the processor is specifically configured to:

Using a phase correlation algorithm to calculate the multiple frames of images in the target video file to obtain the first cross power spectrum between each frame of images in the target video file;

Processing the first cross cross power spectrum according to an interpolation filtering method to obtain a second cross cross power spectrum after frequency domain noise is filtered;

Perform inverse Fourier transform on the second cross cross power spectrum to determine the vibration data of the object to be detected.

Among them, the phase correlation algorithm uses the following formula to calculate the first cross cross power spectrum:

In the above formula, Fa is the Fourier transform of a frame image,

Is the Fourier transformed conjugate signal of the b-frame image, and the lower side of the division formula is the modulus of the correlation product of the two Fourier transformed signals. R is the first cross power spectrum (including frequency domain noise) of the calculation result of this step.

Wherein, in terms of processing the first cross cross power spectrum according to the interpolation filtering method to obtain the second cross cross power spectrum after filtering the frequency domain noise, the processor uses an adaptive filter bank to reconstruct the signal, according to The position of the correlation peak of R adaptively selects the filter bank for filtering, and then performs inverse Fourier transform after filtering, and then performs phase comparison (phase-by-phase comparison). At this time, the sliding window adaptive matching method is used to estimate and extract the vibration Parameter to obtain the second cross cross power spectrum R′ after filtering the frequency domain noise.

Among them, the inverse Fourier transform is performed on the second cross cross power spectrum, and the vibration data can be obtained by comparing phase by phase. The calculation formula is as follows.

In the above formula,

Indicates that the inverse Fourier transform is performed on the second cross cross power spectrum, and r is obtained as the vibration data.

It can be seen that in this example, the vibration detection system uses an adaptive filter bank to perform interpolation filtering during the calculation of vibration data to remove frequency noise, which reduces the impact of noise on the vibration data and improves the accuracy of the vibration data.

In a possible example, in the aspect of determining the environmental coefficient of the object to be detected according to the object to be detected and the humidity information, the processor is specifically configured to:

Determining the material type of the object to be detected;

Determining the standard humidity of the object to be tested according to the material type;

When 0.5|U ₀ |≤|U ₁ |≤1.5|U ₀ |, it is determined that the environmental coefficient of the object to be measured is 1,

When |U ₁ |<0.5|U ₀ |, or |U ₁ |>1.5|U ₀ |, the environmental coefficient of the object to be tested is 2, where U ₀ represents the standard humidity of the object to be tested, U ₁ represents the humidity information.

Wherein, the standard humidity includes the most suitable environmental humidity for the material type of the object to be detected.

It can be seen that in this example, the vibration detection system determines the environmental coefficient according to the material type, which improves the real-time performance of vibration detection, which is beneficial to improve the accuracy of vibration detection.

In a possible example, when determining the vibration coefficient according to the environmental coefficient and the vibration data, the processor is specifically configured to:

Determine the magnitude of the vibration amplitude of the object to be detected according to the vibration data;

Substituting the vibration amplitude and the environmental coefficient into the preset vibration coefficient formula, the vibration coefficient is calculated, K=F ^L , where K is the vibration coefficient, F is the vibration amplitude, and L is The environmental factor.

Wherein, the vibration coefficient is used to determine whether the object to be detected is in an abnormal state, and the vibration coefficient is affected by the magnitude of the vibration amplitude and the environmental coefficient. When the vibration coefficient is greater than a first preset coefficient, the to-be-detected The subject is in an abnormal state.

Wherein, according to the vibration data, the vibration amplitude of the object to be detected is determined to be 4, and the vibration amplitude 4 and the environmental coefficient 2 are substituted into a preset vibration coefficient formula, and the vibration coefficient is calculated as K =4 ² =16, where the first preset coefficient is 10, and when it is determined that the vibration coefficient is greater than the first preset coefficient, the object to be detected is in an abnormal state.

Wherein, considering the influence of different environments on the object to be detected, the vibration coefficient is dynamically determined. Even if the vibration amplitude is the same, when the environmental coefficient is different, the vibration coefficient will be affected, and the vibration coefficient will be affected. The vibration detection system determines whether the object to be detected is in an abnormal state.

Wherein, as shown in FIG. 1B, when the environmental coefficient is 1, the vibration coefficient K=F, where K is the vibration coefficient, F is the amplitude of the vibration, and the image of the vibration coefficient is shown in the figure As shown by T1 in 1B; when the environmental coefficient is 2, the vibration coefficient K=F ² , where K is the vibration coefficient, F is the vibration amplitude, and the image of the vibration coefficient is shown in the figure As shown in T2 in 1B.

It can be seen that in this example, the vibration detection system determines the vibration coefficient according to the magnitude of the vibration and the environmental coefficient. Taking into account the impact of different environments on the object to be detected, the vibration coefficient is dynamically determined, which is beneficial to improve the vibration detection performance. Accuracy and efficiency.

In a possible example, in terms of outputting abnormal prompt information, the processor is specifically configured to:

Determining that the object to be detected is in an abnormal state according to the vibration coefficient;

Determining multiple maintenance solutions for the object to be detected according to the vibration data;

The target video file of the object to be detected and various maintenance solutions for the object to be detected are output on the display interface of the display screen.

Among them, the processor prestores different objects to be detected corresponding to the mapping relationship between the vibration data and the maintenance plan. Therefore, the processor can determine the target mapping relationship between the vibration data and the maintenance plan according to the object to be detected, and then follow the vibration data. Determine a variety of maintenance programs.

In this possible example, in terms of determining multiple maintenance solutions for the object to be detected according to the vibration data, the processor is specifically configured to:

Determining the abnormal probability of the object to be detected for multiple abnormal types according to the vibration data and the vibration coefficient;

When it is detected that the abnormality probability of the first abnormality type is greater than the preset probability threshold, determining the first maintenance plan corresponding to the first abnormality type;

The abnormal probability curve of the object to be detected for the first abnormal type and the first maintenance plan are output through the display interface of the display screen.

Wherein, the specific implementation manner of determining the abnormal probability of the object to be detected for multiple abnormal types according to the vibration data may be that the processor prestores a preset training model, and the processor inputs the vibration data into the preset The training model can obtain the abnormal probability of the object to be detected for multiple abnormal types.

It can be seen that in this example, the vibration detection system determines the abnormal probability of the object to be detected for multiple abnormal types according to the preset training model, which improves the intelligence of the vibration detection system, and when any abnormal type is detected When the abnormal probability is greater than the preset probability threshold, the vibration data and the target video file are output, which is beneficial to improve the timeliness of vibration maintenance.

In a possible example, after outputting the target video file of the object to be detected and various maintenance solutions for the object to be detected in the display interface of the display screen, the processor is specifically configured to:

When a drag operation for any one of the multiple maintenance programs is detected, the video file after the target maintenance program is executed on the object to be detected is displayed on the display screen.

Wherein, the start position of the drag operation is any position in the display area of the target maintenance plan, and the end position of the drag operation is any position in the display area of the target video file.

For example, as shown in FIG. 1C, the target video file is displayed on the upper part of the display interface of the display screen, and multiple maintenance schemes are displayed on the lower part. When a drag operation for any target maintenance scheme is detected, for example, for maintenance During the drag operation of Scheme A, the video file after executing the target maintenance scheme can be displayed below the target video file, covering multiple maintenance schemes, as shown in Figure 1D, so that the target video file and the target maintenance scheme are executed The later video files can be displayed for comparison.

It can be seen that in this example, the vibration detection system outputs the target video file and multiple maintenance plans, and after detecting a drag operation for any target maintenance plan, it outputs the predicted video file that performs the target maintenance plan, which is convenient for the user Observe the effect of the target maintenance program, and improve the intelligence of vibration detection and maintenance.

The embodiments of the application are described in detail above, and specific examples are used in this article to illustrate the principles and implementation of the application. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the application; at the same time, for Those of ordinary skill in the art, based on the ideas of the application, will have changes in the specific implementation and the scope of application. In summary, the content of this specification should not be construed as limiting the application.

Claims

A vibration detection system, characterized in that the vibration detection system includes a video acquisition device, an environmental data acquisition device, and a detection device, the video acquisition device, the environmental data acquisition device, and the detection device are portable integrated devices, The video acquisition device includes a camera, the detection device includes a processor and a display screen, and the detection device is in communication connection with the camera and the environmental data acquisition device, wherein:

The camera is used to obtain a first video of an object to be detected, and transmit the first video to the detection device;

The environmental data collection device is used to collect humidity information around the object to be detected, and transmit the humidity information to the detection device;

The processor is configured to process the received first video according to a preset vibration detection algorithm to obtain a target video file with a motion amplification effect of the object to be detected, wherein the motion amplification effect refers to the The movement situation of the area where the object to be detected moves is enlarged in the target video;

The processor is further configured to determine the vibration coefficient of the object to be detected according to the target video file and the humidity information, and output abnormality prompt information.
The system according to claim 1, wherein in the aspect of processing the received first video according to a preset vibration detection algorithm to obtain a target video file with a motion amplification effect of the object to be detected, The processor is specifically used for:

Converting the multi-frame images in the first video from the three primary colors RGB color space to the YIQ color space, and obtaining the brightness Y information of the multi-frame image;

Performing Fourier transform on the luminance Y information of the multi-frame image to obtain the frequency domain phase information of the multi-frame image to form a second video file containing the frequency domain phase information;

A video motion amplification algorithm is executed on the second video file to obtain the target video file with a motion amplification effect of the object to be detected.
The system according to claim 2, wherein, in terms of performing a video motion amplification algorithm on the second video file to obtain the target video file with a motion amplification effect of the object to be detected, the processor Specifically used for:

Performing spatial decomposition on the second video file to obtain image information of multiple scales;

Determining the resonance frequency of the object to be detected according to the image information and the object to be detected;

Determine the target frequency band according to the resonance frequency;

Performing time-domain band-pass filtering on the image information of the multiple scales to obtain the phase change signal of the target frequency band;

Amplify the phase change signal of the target frequency band, and perform a pyramid reconstruction operation to obtain the target video file with a motion amplification effect.
The system according to claim 1, wherein, in the aspect of determining the vibration coefficient of the object to be detected according to the target video file and the humidity information, and outputting abnormal prompt information, the processor specifically uses in:

Determine the vibration data of the object to be detected according to the target video file;

Determine the environmental coefficient of the object to be detected according to the object to be detected and the humidity information;

Determine the vibration coefficient according to the environmental coefficient and the vibration data;

And output abnormal prompt information according to the vibration data and the vibration coefficient.
The system according to claim 4, wherein in the aspect of determining the vibration data of the object to be detected according to the target video file, the processor is specifically configured to:

Using a phase correlation algorithm to calculate the multiple frames of images in the target video file to obtain the first cross power spectrum between each frame of images in the target video file;

Processing the first cross cross power spectrum according to an interpolation filtering method to obtain a second cross cross power spectrum after frequency domain noise is filtered;

Perform inverse Fourier transform on the second cross cross power spectrum to determine the vibration data of the object to be detected.
The system according to any one of claims 4 or 5, wherein, in the aspect of determining the environmental coefficient of the object to be detected according to the object to be detected and the humidity information, the processor specifically uses in:

Determining the material type of the object to be detected;

Determining the standard humidity of the object to be tested according to the material type;

When 0.5|U 0 |≤|U 1 |≤1.5|U 0 |, it is determined that the environmental coefficient of the object to be measured is 1,

When |U 1 |<0.5|U 0 |, or |U 1 |>1.5|U 0 |, the environmental coefficient of the object to be tested is 2, where U 0 represents the standard humidity of the object to be tested, U 1 represents the humidity information.
The system according to any one of claims 4-6, wherein, in terms of determining the vibration coefficient according to the environmental coefficient and the vibration data, the processor is specifically configured to:

Determine the magnitude of the vibration amplitude of the object to be detected according to the vibration data;

Substituting the vibration amplitude and the environmental coefficient into the preset vibration coefficient formula, the vibration coefficient is calculated, K=F L , where K is the vibration coefficient, F is the vibration amplitude, and L is The environmental factor.
The system according to any one of claims 1-7, wherein, in terms of outputting abnormal prompt information, the processor is specifically configured to:

Determining that the object to be detected is in an abnormal state according to the vibration coefficient;

Determining multiple maintenance solutions for the object to be detected according to the vibration data;

The target video file of the object to be detected and various maintenance solutions for the object to be detected are output on the display interface of the display screen.
The system according to claim 8, wherein, in terms of determining multiple maintenance solutions for the object to be detected according to the vibration data, the processor is specifically configured to:

Determining the abnormal probability of the object to be detected for multiple abnormal types according to the vibration data and the vibration coefficient;

When it is detected that the abnormality probability of the first abnormality type is greater than the preset probability threshold, determining the first maintenance plan corresponding to the first abnormality type;

The abnormal probability curve of the object to be detected for the first abnormal type and the first maintenance plan are output through the display interface of the display screen.
The system according to any one of claims 1-7, wherein the target video file of the object to be detected and various maintenance for the object to be detected are output in the display interface of the display screen. After the solution, the processor is specifically used for:

When a drag operation for any one of the multiple maintenance programs is detected, the video file after the target maintenance program is executed on the object to be detected is displayed on the display screen, where all The start position of the drag operation is any position in the display area of the target maintenance plan, and the end position of the drag operation is any position in the display area of the target video file.