CN114646381A - Rotary mechanical vibration measuring method, system, equipment and storage medium - Google Patents
Rotary mechanical vibration measuring method, system, equipment and storage medium Download PDFInfo
- Publication number
- CN114646381A CN114646381A CN202210326016.6A CN202210326016A CN114646381A CN 114646381 A CN114646381 A CN 114646381A CN 202210326016 A CN202210326016 A CN 202210326016A CN 114646381 A CN114646381 A CN 114646381A
- Authority
- CN
- China
- Prior art keywords
- vibration
- video
- micro
- band
- sub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention discloses a method, a system, equipment and a storage medium for measuring the vibration of a rotating machine, comprising the following steps: preprocessing an image; extracting the amplitude and the phase of the video sub-band; analyzing the amplitude and the phase of the video sub-band to obtain the resonance frequency of the micro vibration; dynamically filtering the video sub-band obtained by decomposition, and filtering the micro-vibration video to obtain a micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video; calculating vibration displacement in each direction by combining the region of interest; and reconstructing and outputting the amplified micro-vibration sub-band video. The invention automatically filters out the main vibration frequency by utilizing the vibration image collected by the camera, and can lead the user to recognize the vibration characteristic by naked eyes after amplification treatment. Each pixel point can be regarded as a virtual sensor, so that the 'surface' vibration monitoring is realized, the vibration mode is automatically decomposed, the vibration components are determined, the vibration reasons are analyzed, the sub-pixel level displacement measurement can be realized, and the displacement monitoring requirements of high spatial resolution and high precision are met.
Description
Technical Field
The invention belongs to the technical field of vibration measurement, and relates to a method, a system, equipment and a storage medium for measuring the vibration of a rotating machine.
Background
The rotating machine is the machine form with the widest application range of the current industrial machine. Rotational movement is not permitted from the power source (internal combustion engine, electric motor, etc.), the drive form (gears, worm, etc.) to the final end actuator (vanes, wheels, etc.). The rotary machine can be said to be a softwall stone of industrial development. A large amount of periodic vibration generally exists in rotary machinery, the health condition of equipment can be analyzed, the damage of a mechanism can be identified, the working state can be judged by researching a vibration signal, the damping optimization, the noise control and the like can be deeply designed, and the rotary machinery has very important significance in the military and civil fields.
The euler video motion amplification method is a new method based on optical image detection, and has been paid much attention in recent years. The method is proposed by professor William t.freeman of the institute of labor and technology, ma 2012, and can amplify tiny vibration invisible to human eyes to a level visible to the naked eyes, thereby achieving the effect of visual enhancement. The algorithm firstly carries out image pyramid spatial decomposition on each frame in a video image sequence to obtain video sub-bands with different spatial scales, then filters out uninteresting motion frequencies by using a time domain filter, finally amplifies video signals, reconstructs an image pyramid and synthesizes and outputs the amplified video. Compared with the Lagrange method in origin and hydrodynamics, the algorithm does not need to track the motion trail of each particle, greatly improves the calculation speed and precision, can amplify the color and has very obvious advantages.
The existing rotary machine detection commonly uses a touch sensor, such as a patch accelerometer, but many problems are encountered in the testing process, such as:
1. in the measuring process, due to the quality factor of the sensor, a load effect can be brought to equipment, the physical property is changed, and even the surface of an object can be damaged.
2. Contact sensor needs to laminate the object surface, if long-term work can face the screw fixation bad, the electric joint contact scheduling problem.
3. The single-point detection of the sensor is difficult to obtain the global vibration characteristic of the measured object, and if the multi-point multi-sensor simultaneous measurement is carried out, the detection process is very complicated, huge data can be generated, and the processing difficulty is very high
4. And a vibration spectrogram is drawn after a test result is processed by a computer, so that a layman cannot visually understand the test result.
5. Displacement monitoring is also an important component of vibration detection. The existing acceleration sensor can only measure in a single point, and is low in efficiency. The laser vibration measurement method has high precision but low spatial resolution.
The Euler video motion amplification method can monitor the vibration of an object in a non-contact mode by using the camera, has no load effect of a sensor, does not need a vibration isolation table, can complete analysis tasks such as long-term monitoring and measurement, and can effectively replace manpower in severe and dangerous environments, thereby saving a large amount of labor as resources. In addition, the Euler video motion amplification algorithm can directly output the amplified video, so that the mechanical vibration state can be displayed more intuitively and efficiently, and the vibration data which are difficult to understand are visualized. Each pixel point in the video can be regarded as a virtual sensor, and the technology can process vibration data of tens of thousands of points at the same time, so that the effect of monitoring 'surface' vibration is achieved. The local phase extracted from the Euler phase video motion amplification algorithm can be converted into displacement data, and the displacement detection effect with high efficiency and high spatial resolution is realized.
However, the traditional euler video motion amplification algorithm has some defects:
1. the core of the euler video motion amplification algorithm is to filter out the interested motion time frequency and amplify and derive the motion time frequency, which requires that the filter parameters need to be manually input when amplifying the video. In practice, however, it is difficult to know the specific frequency of the motion of interest, especially in the mechanical motion scenario where the motion is complex. More importantly, the amplification effect is directly influenced by the fact that the filter parameters are not set well. Therefore, the application of the technology in the field of mechanical vibration monitoring is greatly limited by the problem of setting the parameters of the filter.
2. Vibration components of rotary machines are generally complex, and how to decompose signals and restore the vibration components is important for positioning fault reasons and monitoring mechanical states. The existing Euler algorithm can not realize modal decomposition for a moment and needs to be optimized.
In summary, the existing vibration measurement technology cannot meet the actual vibration monitoring requirement of the rotating machine. There is an urgent need for a vibration detection device that can perform non-contact monitoring, has high spatial resolution, has low requirements for users, can visually display results, and can automatically filter.
Disclosure of Invention
The present invention is directed to solving the problems in the prior art, and provides a rotational mechanical vibration measurement method, system, device, and storage medium. The invention automatically filters out the main vibration frequency by utilizing the vibration image collected by the camera, and can lead the user to recognize the vibration characteristic by naked eyes after amplification treatment. In addition, each pixel point can be regarded as a virtual sensor, so that the surface vibration monitoring is realized, the vibration mode is automatically decomposed, the vibration components are determined, the vibration reason is analyzed, the sub-pixel level displacement measurement can be realized, and the displacement monitoring requirements of high spatial resolution and high precision are met.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
a rotary mechanical vibration measurement method, comprising the steps of:
intercepting an interested area of the image data to obtain a preprocessed image;
decomposing the preprocessed image to obtain a video sub-band, and extracting the amplitude and the phase of the video sub-band;
analyzing the amplitude and the phase of the video sub-band, and separating the background layer, the micro vibration layer and the noise layer to obtain the pixel positions and the frequency distribution of the background layer, the micro vibration layer and the noise layer;
separating the micro-vibration according to the pixel positions and frequency distribution of the background layer, the micro-vibration layer and the noise layer to obtain the resonance frequency of the micro-vibration;
identifying the frequency range of the resonance frequency, carrying out dynamic filtering on the video sub-band obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video;
phase difference data are obtained according to the phase diagram of each sub-band, and vibration displacement in each direction is calculated by combining the region of interest;
and amplifying the micro-vibration sub-band video, and reconstructing and outputting the amplified micro-vibration sub-band video.
The method is further improved in that:
the method for separating the micro vibration according to the pixel positions and the frequency distribution of the background layer, the micro vibration layer and the noise layer to obtain the resonance frequency of the micro vibration comprises the following steps:
acquiring pixel position and frequency distribution of a micro vibration layer and main frequencies of a background layer and a noise layer;
uniformly selecting n points in the micro vibration layer, wherein n is more than or equal to 1, and recording amplitude data of each frame at the corresponding position;
performing VMD modal decomposition on each frame of amplitude data to obtain modal vibration data of each order;
calculating the power spectrum of each order of modal vibration data, extracting the frequency corresponding to the maximum value in the power spectrum, and removing the main frequencies of a background layer and a noise layer;
and outputting and saving the modal data of each order.
The identifying the frequency range of the resonance frequency, dynamically filtering the video sub-band obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and the phase diagram of each sub-band of the micro-vibration video, comprises:
removing background and noise interference in the time domain amplitude data to obtain a time domain amplitude of the micro vibration;
s conversion is carried out on the time domain amplitude of the micro vibration to obtain frequency distribution data of each moment;
performing cluster analysis on the frequency data at each moment to obtain instantaneous center frequency and fluctuation range;
designing a time-frequency filtering mask according to the instantaneous central frequency and the fluctuation range;
s transformation is carried out on each video sub-band according to the amplitude and the phase of the video sub-band;
filtering each video sub-band data after S transformation by using a time-frequency filtering mask;
and carrying out S inverse transformation on each filtered video sub-band data to obtain the dynamically filtered micro-vibration sub-band video.
The method for obtaining phase difference data according to the phase diagram of each sub-band and calculating the vibration displacement in each direction by combining the interested region comprises the following steps:
obtaining a phase diagram of each sub-band of the micro vibration layer;
the first frame is unchanged, and the difference is made between the other frames and the previous frame to obtain phase difference data;
according to the region of interest, storing phase difference data of each point;
calculating displacement difference data of each frame by using a displacement model;
and accumulating the displacement difference of each frame to obtain vibration displacement data of each party.
The displacement model is as follows:
wherein x isiRepresenting the displacement difference between the horizontal direction of the picture and the picture of the previous frame, i representing the frame of the picture, alpha representing a filter attenuation compensation constant, L representing an image pyramid scaling compensation constant, and delta thetaiA phase difference between a local phase corresponding to the ith frame and the previous frame is represented, J represents a convolution compensation constant, P represents a proportional conversion constant of a unit pixel and an actual size, and
calculating to obtain the image, wherein p is the unit pixel size of the photosensitive chip of the camera, u is the object distance, v is the image distance, and yiAnd the displacement difference between the vertical direction of the picture and the picture of the previous frame is represented.
A rotary machine vibration measurement system comprising:
the video acquisition and preprocessing module is used for intercepting an interested area of the image data to obtain a preprocessed image;
the pyramid decomposition module is used for decomposing the preprocessed image to obtain a video sub-band and extracting the amplitude and the phase of the video sub-band;
the motion clustering analysis module is used for analyzing the amplitude and the phase of the video sub-band, separating the background layer, the micro vibration layer and the noise layer and obtaining the pixel position and the frequency distribution of the background layer, the micro vibration layer and the noise layer;
the vibration mode self-decomposition module is used for separating micro vibration according to the pixel positions and frequency distribution of the background layer, the micro vibration layer and the noise layer to obtain the resonance frequency of the micro vibration;
the dynamic filtering module is used for identifying the frequency range of the resonance frequency, dynamically filtering the video sub-bands obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video;
the vibration displacement calculation module is used for obtaining phase difference data according to the phase diagram of each sub-band and calculating vibration displacement in each direction by combining the interested region;
and the Euler video motion amplification module is used for amplifying the micro-vibration sub-band video and reconstructing and outputting the amplified micro-vibration video.
A terminal device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of the method as described above when executing said computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method as described above.
Compared with the prior art, the invention has the following beneficial effects:
the invention takes a rotary machine as a target verification object, and builds a set of vibration monitoring system combining software and hardware based on the Euler video motion amplification method as a basic algorithm, and has the following advantages:
firstly, the method comprises the following steps: no mass load interferes with the vibration. The vibration is monitored in a non-contact manner by utilizing the video, and the self vibration state of the rotary machine cannot be influenced
Secondly, the method comprises the following steps: can work for a long time. The machine vision can be matched with a monitoring camera for use, and because the machine vision does not have human eye vision fatigue, the machine vision can complete analysis tasks such as long-term monitoring and measurement, and can effectively replace manpower in severe and dangerous environments, thereby saving a large amount of labor and resources.
Thirdly, the method comprises the following steps: large-area monitoring, and surface monitoring instead of traditional point monitoring. Each pixel point in the video can be regarded as a virtual sensor, and the vibration state of the whole picture is monitored at the same time, so that high spatial resolution monitoring is realized.
Fourthly: and outputting the video after visual enhancement, and identifying the vibration by naked eyes. By utilizing an Euler video motion amplification algorithm, vibration enhancement is derived, the vibration problem can be rapidly identified, and the working efficiency of personnel is improved.
Fifth, the method comprises the following steps: micro-amplitude displacement measurement can be realized. Local phase change of the pixel points of the micro vibration layer is monitored and converted into micro displacement, and precision measurement of the sub-pixel scale can be achieved to the maximum extent.
Sixth: the filter parameters are automatically determined, and manual input is avoided. In most cases, the dominant frequency information of the minute vibrations cannot be predicted in advance, making it difficult to determine the filter parameters. Secondly, many vibration main frequencies are changed in a time domain, and a high-quality result is difficult to obtain by a fixed filter parameter. The system can realize the automatic operation of the algorithm and improve the quality of output video by automatically designing the dynamic filter.
Seventh: and the vibration mode is automatically decomposed. The components of the vibration signals are generally complex, and in practical application, each original vibration signal needs to be efficiently separated, and the difficulty of analyzing data by personnel is reduced. The algorithm can automatically and efficiently output modal shape data of each order by analyzing local phase vibration and utilizing a VMD modal decomposition algorithm.
Drawings
In order to more clearly explain the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a block diagram of the system of the present invention.
Fig. 3 is a schematic flow chart of a rotational mechanical vibration measurement method based on euler video motion amplification according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a rotational mechanical vibration measurement apparatus based on euler video motion amplification according to an embodiment of the present invention.
Fig. 5 is a schematic view of a modal auto-decomposition process.
Fig. 6 is a schematic diagram of a dynamic filter parameter automatic determination process.
Fig. 7 is a schematic flow chart of vibration displacement calculation.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. are used for indicating the orientation or positional relationship based on the orientation or positional relationship shown in the drawings or the orientation or positional relationship which is usually arranged when the product of the present invention is used, the description is merely for convenience and simplicity, and the indication or suggestion that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus, cannot be understood as limiting the present invention. Furthermore, the terms "first," "second," and the like are used solely to distinguish one from another, and are not to be construed as indicating or implying relative importance.
Furthermore, the term "horizontal", if present, does not mean that the component is required to be absolutely horizontal, but may be slightly inclined. For example, "horizontal" merely means that the direction is more horizontal than "vertical" and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the embodiments of the present invention, it should be further noted that unless otherwise explicitly stated or limited, the terms "disposed," "mounted," "connected," and "connected" should be interpreted broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, an embodiment of the present invention discloses a method for measuring rotational mechanical vibration, including the following steps:
s1, intercepting the interested area of the image data to obtain a preprocessed image;
s2, decomposing the preprocessed image to obtain a video sub-band, and extracting the amplitude and the phase of the video sub-band;
s3, analyzing the amplitude and the phase of the video sub-band, separating the background layer, the micro vibration layer and the noise layer to obtain the pixel positions and the frequency distribution of the background layer, the micro vibration layer and the noise layer; the specific method comprises the following steps:
s3-1, acquiring the pixel position and frequency distribution of the micro vibration layer and the main frequency of the background layer and the noise layer;
s3-2, uniformly selecting n points in the micro vibration layer, wherein n is more than or equal to 1, and recording amplitude data of each frame at the corresponding position;
s3-3, performing VMD modal decomposition on each frame of amplitude data to obtain modal vibration data of each order;
s3-4, calculating the power spectrum of each order of modal vibration data, extracting the frequency corresponding to the maximum value in the power spectrum, and eliminating the main frequency of a background layer and a noise layer;
and S3-5, outputting and saving the modal data of each order.
S4, separating the micro vibration according to the pixel position and frequency distribution of the background layer, the micro vibration layer and the noise layer to obtain the resonance frequency of the micro vibration;
s5, identifying the frequency range of the resonance frequency, dynamically filtering the video sub-bands obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and the phase diagram of each sub-band of the micro-vibration video; the specific method comprises the following steps:
s5-1, removing background and noise interference in the time domain amplitude data to obtain the time domain amplitude of the micro vibration;
s5-2, carrying out S transformation on the time domain amplitude of the micro vibration to obtain frequency distribution data at each moment;
s5-3, performing cluster analysis on the frequency data at each moment to obtain instantaneous center frequency and fluctuation range;
s5-4, designing a time-frequency filtering mask according to the instantaneous center frequency;
s5-5, according to the amplitude and the phase of the video sub-band, S transformation is carried out on each video sub-band;
s5-6, filtering each video sub-band data after S transformation by using a time-frequency filtering mask;
and S5-7, carrying out S inverse transformation on the filtered video sub-data to obtain the dynamically filtered micro-vibration sub-band video.
S6, phase difference data are obtained according to the phase diagram of each sub-band, and vibration displacement in each direction is calculated by combining the region of interest; the specific method comprises the following steps:
s6-1, acquiring a phase diagram of each sub-band of the micro vibration layer;
s6-2, the first frame is not changed, and the difference is made between the other frames and the previous frame to obtain phase difference data;
s6-3, storing phase difference data of each point according to the region of interest;
s6-4, calculating displacement difference data of each frame by using a displacement model; the displacement model is as follows:
wherein x isiRepresenting the displacement difference between the horizontal direction of the picture and the picture of the previous frame, i representing the frame of the picture, alpha representing a filter attenuation compensation constant, L representing an image pyramid scaling compensation constant, and delta thetaiA phase difference between a local phase corresponding to the ith frame and the previous frame is represented, J represents a convolution compensation constant, P represents a proportional conversion constant of a unit pixel and an actual size, and
calculating to obtain the target image, wherein p is the unit pixel size of the photosensitive chip of the camera, u is the object distance, v is the image distance, and yiAnd the displacement difference between the vertical direction of the picture and the picture of the previous frame is represented.
And S6-5, accumulating the displacement difference of each frame to obtain vibration displacement data of each party.
And S7, amplifying the micro-vibration sub-band video, and reconstructing and outputting the amplified micro-vibration sub-band video.
As shown in fig. 2, an embodiment of the present invention discloses a rotary mechanical vibration measurement system, including:
the video acquisition and preprocessing module is used for intercepting an interested area of the image data to obtain a preprocessed image;
the pyramid decomposition module is used for decomposing the preprocessed image to obtain a video sub-band and extracting the amplitude and the phase of the video sub-band;
the motion clustering analysis module is used for analyzing the amplitude and the phase of the video sub-band, separating the background layer, the micro vibration layer and the noise layer and obtaining the pixel positions and the frequency distribution of the background layer, the micro vibration layer and the noise layer;
the vibration mode self-decomposition module is used for separating micro vibration according to the pixel positions and frequency distribution of the background layer, the micro vibration layer and the noise layer to obtain the resonance frequency of the micro vibration;
the dynamic filtering module is used for identifying the frequency range of the resonance frequency, dynamically filtering the video sub-bands obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video;
the vibration displacement calculation module is used for obtaining phase difference data according to the phase diagram of each sub-band and calculating vibration displacement in each direction by combining the interested region;
and the Euler video motion amplification module is used for amplifying the micro-vibration sub-band video and reconstructing and outputting the amplified micro-vibration sub-band video.
As shown in fig. 3, the embodiment of the present invention discloses a rotational mechanical vibration measurement system based on euler video motion amplification, which comprises four parts, wherein a computer system and processing algorithm part 100 is used for storing and processing video images, receiving user instructions, and displaying algorithm results. Industrial camera 200 and a mount section for capturing video of rotating mechanical motion, securing the camera and buffering jitter interference. The power supply system 300 provides a stable source of power to the various subsystems. The light supplement lamp 400 and the fixing frame are used for supplementing the shooting brightness, and the problem that the illumination intensity is insufficient in some shooting environments is solved.
The system of the invention has the following working procedures:
step 1, selecting a proper measuring position: generally against the object being measured (perpendicular to the direction of vibration of the object). In addition, the image background is required to be single and fixed, and is visually and obviously distinguished from a measured object, otherwise, the algorithm effect is influenced.
And 2, adjusting the camera fixing buffer support to enable the plane of the camera to be horizontal, and stably supporting the rubber pad at the bottom of the support and the ground.
Step 3, adjusting camera parameters: and accessing a power supply and connecting the data line to the port of the computer. And opening an image interface, and adjusting the focal length of the lens and the size of the aperture to make the image clear.
Step 4, supplementary lighting: and turning on the light supplement lamp, and adjusting the intensity and distance of the light source to ensure uniform illumination.
And step 5, running an algorithm: then an image buffer is set, the collected image is stored, and then an algorithm is introduced to start analysis processing.
As shown in fig. 4, an embodiment of the present invention discloses a rotational mechanical vibration measurement method based on euler video motion amplification, including the following steps:
step 1, an industrial camera acquires a vibration image and imports image data into a computer.
And 2, after the video acquisition and preprocessing module 110 acquires the image data, allowing a user to define and intercept an interested area, and converting the video format to complete preprocessing.
And 3, decomposing the preprocessed image into video sub-bands with different scales and different directions by the complex pyramid decomposition module 120, and extracting the amplitude and the phase from the video sub-bands.
Step 4, the motion cluster analysis module 130 may analyze the video vibration, separate the background layer, the minute vibration layer, and the noise layer, and obtain the pixel position and frequency distribution of each layer.
And step 6, the dynamic filtering module 150 can automatically identify the frequency range of the micro vibration at each moment, dynamically filter the sub-band video decomposed by the pyramid, and filter the micro vibration video with high quality, so as to facilitate subsequent amplification.
Step 7, after the phase diagram of the micro-vibration is obtained by the vibration displacement calculation module 160, the local phase difference is substituted into the displacement model to calculate the vibration displacement in each direction.
In step 8, the euler video motion amplification module 170 may amplify the micro vibration layer and reconstruct and output the amplified video.
Step 9, the output display module 180 is a man-machine interface, which can receive user instructions, output calculation results, store and convert videos.
As shown in fig. 5, the method for automatically decomposing the vibration mode of the present invention is as follows:
step 141: and acquiring the position and frequency information of the micro-vibration pixel points output by the clustering analysis module, and the dominant frequency of the background and the noise.
Step 142: uniformly selecting n points (n is at least 1) in the micro vibration layer, and recording the amplitude data of each frame at the corresponding position.
Step 143: and performing VMD modal decomposition on the data of each point respectively to obtain modal vibration data of each order.
Step 144: and calculating power spectrums of the data of each mode.
Step 145: and extracting the frequency corresponding to the maximum value of the power spectrum, removing the background and noise dominant frequency obtained in the step 141, and removing the duplication.
Step 146: and outputting and saving the modal data of each order.
As shown in fig. 6, the dynamic filtering processing method of the present invention is as follows:
step 151: and acquiring time domain amplitude data extracted in modal decomposition.
Step 152: and acquiring information of a noise layer and a background layer in clustering analysis.
Step 153: and removing noise and background interference from the time domain amplitude data subjected to modal decomposition to obtain the time domain amplitude of the micro vibration.
Step 154: and performing S conversion to obtain frequency distribution data (namely a frequency matrix) at each moment.
Step 155: and performing cluster analysis on the frequency data at each moment to obtain the instantaneous center frequency and the fluctuation range.
Step 156: and designing a time-frequency filtering mask by using the instantaneous frequency information obtained in the previous step.
Step 157: and acquiring a secondary pyramid decomposition result (residual error is not included), and performing S transformation on each sub-band.
Step 158: and filtering the sub-band data obtained in the 157 step by using a mask plate in the 156 step.
Step 159: and performing S inverse transformation to obtain the dynamically filtered micro-vibration sub-band video.
As shown in fig. 7, the processing method of the vibration displacement calculation of the present invention is as follows:
step 161: and acquiring a processing result of the dynamic filtering module, wherein the processing result is mainly a phase diagram of each sub-band of the micro vibration layer.
Step 162: the first frame is unchanged, and the difference between the other frames and the previous frame is obtained to obtain phase difference data.
Step 163: the user selectable point detection or global micro-vibration is monitored.
Step 164: and obtaining a tiny vibration signal expressed by phase difference of the selected pixel point. And storing the phase difference data of each point according to the interested area selected by the user.
Step 165: using displacement model equations
The displacement difference data per frame is calculated.
Step 166: and outputting the displacement difference data of each point in each direction.
Step 167: and accumulating the displacement difference of each frame to obtain vibration displacement data of each party.
An embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. The processor realizes the steps of the above-mentioned method embodiments when executing the computer program. Alternatively, the processor implements the functions of the modules/units in the above device embodiments when executing the computer program.
The computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to implement the invention.
The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device may include, but is not limited to, a processor, a memory.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc.
The memory may be used for storing the computer programs and/or modules, and the processor may implement various functions of the terminal device by executing or executing the computer programs and/or modules stored in the memory and calling data stored in the memory.
The modules/units integrated in the terminal device may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A method of measuring rotational mechanical vibration, comprising the steps of:
intercepting an interested area of the image data to obtain a preprocessed image;
decomposing the preprocessed image to obtain a video sub-band, and extracting the amplitude and the phase of the video sub-band;
analyzing the amplitude and the phase of the video sub-band, and separating a background layer, a micro vibration layer and a noise layer to obtain the pixel positions and the frequency distribution of the background layer, the micro vibration layer and the noise layer;
separating the micro-vibration according to the pixel positions and frequency distribution of the background layer, the micro-vibration layer and the noise layer to obtain the resonance frequency of the micro-vibration;
identifying the frequency range of the resonance frequency, carrying out dynamic filtering on the video sub-band obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video;
phase difference data are obtained according to the phase diagram of each sub-band, and vibration displacement in each direction is calculated by combining the region of interest;
and amplifying the micro-vibration sub-band video, and reconstructing and outputting the amplified micro-vibration sub-band video.
2. A rotational mechanical vibration measurement method according to claim 1, wherein the separating the minute vibrations from the pixel positions and frequency distributions of the background layer, the minute vibration layer, and the noise layer to obtain the resonance frequencies of the minute vibrations includes:
acquiring pixel position and frequency distribution of a micro vibration layer and main frequencies of a background layer and a noise layer;
uniformly selecting n points in the micro vibration layer, wherein n is more than or equal to 1, and recording amplitude data of each frame at the corresponding position;
performing VMD modal decomposition on each frame of amplitude data to obtain modal vibration data of each order;
calculating the power spectrum of each order of modal vibration data, extracting the frequency corresponding to the maximum value in the power spectrum, and removing the main frequencies of a background layer and a noise layer;
and outputting and saving the modal data of each order.
3. A rotational mechanical vibration measurement method according to claim 1, wherein the identifying the frequency range of the resonance frequency, dynamically filtering the decomposed video subbands, and filtering the microvibration video to obtain the microvibration subband video and the phase map of each subband of the microvibration subband video comprises:
removing background and noise interference in the time domain amplitude data to obtain a time domain amplitude of the micro vibration;
s transformation is carried out on the time domain amplitude of the micro vibration to obtain frequency distribution data of each moment;
performing cluster analysis on the frequency data at each moment to obtain instantaneous center frequency and fluctuation range;
designing a time-frequency filtering mask according to the instantaneous central frequency and the fluctuation range;
s transformation is carried out on each video sub-band according to the amplitude and the phase of the video sub-band;
filtering each video sub-band data after S transformation by using a time-frequency filtering mask;
and carrying out S inverse transformation on each filtered video sub-band data to obtain the dynamically filtered micro-vibration sub-band video.
4. A rotational mechanical vibration measurement method according to claim 1, wherein the obtaining phase difference data from the phase map of each subband, and calculating vibration displacement in each direction in combination with the region of interest, comprises:
obtaining a phase diagram of each sub-band of the micro vibration layer;
the first frame is unchanged, and the difference is made between the other frames and the previous frame to obtain phase difference data;
according to the region of interest, storing phase difference data of each point;
calculating displacement difference data of each frame by using a displacement model;
and accumulating the displacement difference of each frame to obtain vibration displacement data of each party.
5. A method of rotational mechanical vibration measurement according to claim 4, wherein the displacement model is as follows:
wherein x isiRepresenting the displacement difference between the horizontal direction of the picture and the picture of the previous frame, i representing the frame of the picture, alpha representing a filter attenuation compensation constant, L representing an image pyramid scaling compensation constant, and delta thetaiA phase difference between a local phase corresponding to the ith frame and the previous frame is represented, J represents a convolution compensation constant, P represents a proportional conversion constant of a unit pixel and an actual size, and
calculating to obtain the target image, wherein p is the unit pixel size of the photosensitive chip of the camera, u is the object distance, v is the image distance, and yiAnd the displacement difference between the vertical direction of the picture and the picture of the previous frame is represented.
6. A rotary machine vibration measurement system, comprising:
the video acquisition and preprocessing module is used for intercepting an interested area of the image data to obtain a preprocessed image;
the pyramid decomposition module is used for decomposing the preprocessed image to obtain a video sub-band and extracting the amplitude and the phase of the video sub-band;
the motion clustering analysis module is used for analyzing the amplitude and the phase of the video sub-band, separating the background layer, the micro vibration layer and the noise layer and obtaining the pixel position and the frequency distribution of the background layer, the micro vibration layer and the noise layer;
the vibration mode self-decomposition module is used for separating micro vibration according to the pixel positions and frequency distribution of the background layer, the micro vibration layer and the noise layer to obtain the resonance frequency of the micro vibration;
the dynamic filtering module is used for identifying the frequency range of the resonance frequency, dynamically filtering the video sub-bands obtained by decomposition, and filtering the micro-vibration video to obtain the micro-vibration sub-band video and a phase diagram of each sub-band of the micro-vibration video;
the vibration displacement calculation module is used for obtaining phase difference data according to the phase diagram of each sub-band and calculating vibration displacement in each direction by combining the interested region;
and the Euler video motion amplification module is used for amplifying the micro-vibration sub-band video and reconstructing and outputting the amplified micro-vibration video.
7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1-5 when executing the computer program.
8. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210326016.6A CN114646381B (en) | 2022-03-30 | 2022-03-30 | Rotary mechanical vibration measuring method, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210326016.6A CN114646381B (en) | 2022-03-30 | 2022-03-30 | Rotary mechanical vibration measuring method, system, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114646381A true CN114646381A (en) | 2022-06-21 |
| CN114646381B CN114646381B (en) | 2023-01-24 |
Family
ID=81995426
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210326016.6A Active CN114646381B (en) | 2022-03-30 | 2022-03-30 | Rotary mechanical vibration measuring method, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114646381B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114993452A (en) * | 2022-07-14 | 2022-09-02 | 湖南大学 | Structure micro-vibration measurement method and system based on broadband phase motion amplification |
| CN115453427A (en) * | 2022-10-18 | 2022-12-09 | 云南电网有限责任公司电力科学研究院 | Method and device for monitoring transient mechanical state of transformer winding |
| CN116399440A (en) * | 2023-06-08 | 2023-07-07 | 中国船舶集团有限公司第七一九研究所 | Propeller vibration measuring device and method |
| CN117615244A (en) * | 2024-01-22 | 2024-02-27 | 四川群源科技有限公司 | Driving method and device of image pickup equipment and electronic equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106657713A (en) * | 2016-12-30 | 2017-05-10 | 华中科技大学 | Video motion amplification method |
| CN109063763A (en) * | 2018-07-26 | 2018-12-21 | 合肥工业大学 | Video minor change amplification method based on PCA |
| JP2019087126A (en) * | 2017-11-09 | 2019-06-06 | 日本電信電話株式会社 | Image processing device, image processing method and image processing program |
| CN111277833A (en) * | 2020-01-20 | 2020-06-12 | 合肥工业大学 | Multi-passband filter-based multi-target micro-vibration video amplification method |
| JP2020170907A (en) * | 2019-04-01 | 2020-10-15 | 学校法人五島育英会 | Monitoring system and monitoring method |
| CN112254801A (en) * | 2020-12-21 | 2021-01-22 | 浙江中自庆安新能源技术有限公司 | Micro-vibration vision measurement method and system |
| CN114222033A (en) * | 2021-11-01 | 2022-03-22 | 三峡大学 | Adaptive Euler video amplification method based on empirical mode decomposition |
-
2022
- 2022-03-30 CN CN202210326016.6A patent/CN114646381B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106657713A (en) * | 2016-12-30 | 2017-05-10 | 华中科技大学 | Video motion amplification method |
| JP2019087126A (en) * | 2017-11-09 | 2019-06-06 | 日本電信電話株式会社 | Image processing device, image processing method and image processing program |
| CN109063763A (en) * | 2018-07-26 | 2018-12-21 | 合肥工业大学 | Video minor change amplification method based on PCA |
| JP2020170907A (en) * | 2019-04-01 | 2020-10-15 | 学校法人五島育英会 | Monitoring system and monitoring method |
| CN111277833A (en) * | 2020-01-20 | 2020-06-12 | 合肥工业大学 | Multi-passband filter-based multi-target micro-vibration video amplification method |
| CN112254801A (en) * | 2020-12-21 | 2021-01-22 | 浙江中自庆安新能源技术有限公司 | Micro-vibration vision measurement method and system |
| CN114222033A (en) * | 2021-11-01 | 2022-03-22 | 三峡大学 | Adaptive Euler video amplification method based on empirical mode decomposition |
Non-Patent Citations (2)
| Title |
|---|
| 王浩林 等: "基于相位光流法的结构振动微小位移测量", 《计算机系统应用》 * |
| 郑佳艳 等: "基于欧拉放大和灰度均值差法的桥梁动态响应研究", 《公路工程》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114993452A (en) * | 2022-07-14 | 2022-09-02 | 湖南大学 | Structure micro-vibration measurement method and system based on broadband phase motion amplification |
| CN114993452B (en) * | 2022-07-14 | 2023-03-24 | 湖南大学 | Structure micro-vibration measurement method and system based on broadband phase motion amplification |
| CN115453427A (en) * | 2022-10-18 | 2022-12-09 | 云南电网有限责任公司电力科学研究院 | Method and device for monitoring transient mechanical state of transformer winding |
| CN116399440A (en) * | 2023-06-08 | 2023-07-07 | 中国船舶集团有限公司第七一九研究所 | Propeller vibration measuring device and method |
| CN116399440B (en) * | 2023-06-08 | 2023-08-04 | 中国船舶集团有限公司第七一九研究所 | Propeller vibration measuring device and method |
| CN117615244A (en) * | 2024-01-22 | 2024-02-27 | 四川群源科技有限公司 | Driving method and device of image pickup equipment and electronic equipment |
| CN117615244B (en) * | 2024-01-22 | 2024-04-02 | 四川群源科技有限公司 | Driving method and device of image pickup equipment and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114646381B (en) | 2023-01-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114646381B (en) | Rotary mechanical vibration measuring method, system, equipment and storage medium | |
| Liu et al. | Machine vision based online detection of PCB defect | |
| Chen et al. | Modal identification of simple structures with high-speed video using motion magnification | |
| CN1183781C (en) | Property modeling for real time human being visual system | |
| CN104093016B (en) | A kind of dirty detection method of camera module and system | |
| JP2009180583A (en) | Method and device for evaluating luminance nonuniformity of display | |
| CN113421224A (en) | Cable structure health monitoring method and system based on vision | |
| JP4972004B2 (en) | Image conversion method and program | |
| Peng et al. | A visual vibration characterization method for intelligent fault diagnosis of rotating machinery | |
| Zang et al. | Phase-based vibration frequency measurement from videos recorded by unstable cameras | |
| Lu et al. | Observation of tower vibration based on subtle motion magnification | |
| CN109862351B (en) | Camera module resolution detection method | |
| CN110994802A (en) | Method and device for monitoring running state of power transmission conductor | |
| Li et al. | Vehicle seat detection based on improved RANSAC-SURF algorithm | |
| Lu et al. | A new grinding surface roughness measurement method based on image quality algorithm and BP neural network | |
| Ravi Kumar et al. | Morphological real time video edge detection in Labview | |
| Xie et al. | Characteristic enhancement of RV reducer under non-stationary condition based on WDT-IF-SS-VMD | |
| CN202008348U (en) | Test sieve automatic calibrating device based on Labview | |
| Zhang et al. | Diagnosis of bearing fault signals based on empirical standard autoregressive power spectrum signal decomposition method | |
| Chaudhary et al. | Measurement of the size and spacing of standard wire sieves using an image processing system and wavelet transform | |
| Zheng et al. | Bridge vibration virtual sensor based on eulerian video magnification and gray mean difference | |
| Min et al. | Research on Rapid Detection of Tooth Profile Parameters of the Clothing Wires Based on Image Processing | |
| CN219347954U (en) | Signal transmitting module for measuring vibration signals | |
| CN115239648B (en) | R-angle protrusion point cloud extraction method, device, equipment and storage medium | |
| CN118093553B (en) | Laser intelligent detection system and method for manufacturing ultra-high precision equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |