A vibration displacement measurement method and measurement system based on multi-source data fusion

Abstract

The present invention discloses a vibration displacement measurement method and measurement system based on multi-source data fusion, which belongs to the field of vibration measurement technology. The vibration displacement measurement method based on multi-source data fusion includes the following steps: obtaining motion sequence images of an elastic tube and a rigid tube through a high-speed camera, and simultaneously obtaining the vibration acceleration signal of the elastic tube through an acceleration sensor; extracting the displacement trajectory of the elastic tube and the rigid tube obtained by the high-speed camera, and separating the flow-induced vibration displacement time-history curve of the elastic tube; performing frequency domain analysis on the displacement trajectory data to determine the frequency band of the rigid tube and the elastic tube; band-pass filtering the acceleration sensor signal based on the frequency band of the flow-induced vibration, and using the time domain displacement data of the rigid tube to compensate for the error of the acceleration sensor integral trend term; performing secondary integration on the filtered acceleration sensor signal, and outputting the corrected displacement information. The vibration displacement measurement method and measurement system based on multi-source data fusion described in the present invention can solve the problem that the existing vibration measurement method cannot achieve an effective unification of measurement accuracy and engineering applicability.

Description

Technical Field

[0001] The present invention relates to the field of vibration measurement technology, and in particular to a vibration displacement measurement method and a measurement system based on multi-source data fusion. Background Art

[0002] In nuclear power plant steam generators and other equipment, flow-induced vibration (FIV) caused by fluid flowing across the tube bundle is a major cause of tube bundle failure. To prevent engineering accidents and improve the theoretical framework for FIV, the development of high-precision vibration displacement measurement technology is urgently needed.

[0003] Existing vibration displacement measurement mainly adopts two technical routes:

[0004] (1) Non-contact measurement method based on high-speed photography: The motion trajectory of the object being measured is captured by a high-speed camera device, and the displacement time history curve is obtained through image processing. Although this method can achieve intuitive measurement, it has significant limitations: First, in order to achieve effective recognition, it requires high-frame rate, high-resolution camera equipment and a supporting fill light system, resulting in high equipment costs; second, it is sensitive to environmental parameters such as the shooting field of view and lighting conditions, and its applicability is limited in confined spaces or complex working conditions; third, high-resolution continuous shooting generates massive amounts of data, which causes storage and processing pressure.

[0005] (2) Accelerometer-based integral measurement method: The vibration signal is collected by a piezoelectric accelerometer, and the displacement information is obtained through a secondary integral operation. Although this method has engineering advantages such as low cost and easy deployment, it has two key technical bottlenecks in practical application: first, environmental noise interference causes trend term errors in the integration process, which directly affects the accuracy of displacement reconstruction; second, the filter band selection in the acceleration signal preprocessing link relies too much on empirical parameters and lacks an objective correction mechanism, which can easily cause effective signal loss or noise residue.

[0006] The current technical dilemma is that although the high-speed photography method can provide benchmark data, it lacks engineering practicality, and although the acceleration integration method is easy to implement, it has accuracy defects; it is impossible to achieve an effective unity of measurement accuracy and engineering applicability. Summary of the Invention

[0007] The purpose of the present invention is to provide a vibration displacement measurement method and measurement system based on multi-source data fusion, so as to solve the problem that the existing vibration measurement methods cannot achieve effective unification of measurement accuracy and engineering applicability.

[0008] To achieve the above object, the present invention provides a vibration displacement measurement method based on multi-source data fusion, comprising the following steps:

[0009] S1. Capturing motion sequence images of the elastic tube and the rigid tube using a high-speed camera, and simultaneously collecting vibration acceleration signals of the elastic tube using an acceleration sensor;

[0010] S2. Extract the displacement trajectories of the elastic tube and the rigid tube respectively, and separate the flow-induced vibration displacement time history curve of the elastic tube through displacement vector calculation;

[0011] S3. Perform frequency domain analysis on the displacement trajectory data of the rigid tube and the elastic tube respectively, establish power spectrum density functions of the rigid tube and the elastic tube, and determine the frequency bands of the rigid tube and the elastic tube;

[0012] S4. Determine the main frequency of the rigid tube, the main frequency of the elastic tube, and the main frequency of the flow-induced vibration according to the power spectral density functions of the rigid tube and the elastic tube, and judge whether the main frequency of the rigid tube and the main frequency of the flow-induced vibration meet the frequency decoupling condition;

[0013] S5. performing band-pass filtering on the acceleration sensor signal based on the frequency band of the flow-induced vibration, and compensating for the error of the integral trend term of the acceleration sensor using the time-domain displacement data of the rigid tube;

[0014] S6. Perform a secondary integration on the filtered acceleration sensor signal and output corrected displacement information.

[0015] Preferably, the S2 is specifically:

[0016] S21, performing grayscale conversion and region cropping processing on the original video frames of the motion sequence image;

[0017] S22, extracting the time-domain displacement trajectory function f1(x, y) of the rigid tube and the time-domain displacement trajectory function f2(x, y) of the elastic tube respectively through motion tracking software;

[0018] S23, constructing a displacement vector calculation model to obtain a flow-induced vibration displacement trajectory function of the elastic tube, and obtaining a flow-induced vibration displacement time history curve of the elastic tube;

[0019] The displacement vector operation model is:

[0020] f(x,y)=f1(x,y)-f1(x,y);

[0021] Where f(x,y) is the flow-induced vibration displacement trajectory function of the elastic tube.

[0022] Preferably, the S3 is specifically:

[0023] S31. Establish a frequency domain decoupling analysis model, perform continuous Fourier transform on the displacements of the rigid tube and the elastic tube, and obtain frequency domain expressions; the frequency domain decoupling analysis model is:

[0024]

[0025] Where X(ω) is the frequency domain function, ω is the angular frequency, t is the time variable, j is the imaginary unit, and x(t) is the displacement at time t;

[0026] S32, calculating the discrete spectrum using a fast Fourier transform algorithm;

[0027]

[0028] Where X[k] is the discrete spectrum, N is the sampling capacity, k is the frequency, n is the number of sampling times, x[n] is the discrete time domain signal, and the frequency resolution Δf = f s / N,f s is the sampling frequency;

[0029] S33, normalizing the amplitude of the discrete spectrum to establish a standardized power spectrum density function;

[0030] P(ω)=|X(ω)| 2 / 2πT;

[0031] Where T is the signal observation time.

[0032] Preferably, in S4, the frequency decoupling condition is that the main frequency of the rigid tube is greater than or less than ±50% of the main frequency of the flow-induced vibration.

[0033] Preferably, in S5, the passband boundary of the bandpass filter is ±50% of the main frequency of the flow-induced vibration.

[0034] Preferably, in S5, the error of the integral trend term of the acceleration sensor is compensated by using the time domain displacement data of the rigid tube as follows:

[0035] The integrated displacement of the acceleration sensor is aligned with the time domain displacement data of the rigid tube, and the trend term offset of the integrated displacement of the acceleration sensor is calculated and eliminated.

[0036] A measurement system for the above-mentioned vibration displacement measurement method based on multi-source data fusion, comprising:

[0037] a water tank for storing fluid;

[0038] A gas compressor is used to provide a gas source;

[0039] The experimental tube is used to mix fluid and gas and perform vibration displacement measurement. The experimental tube is connected to the water tank through a circulation pipeline, and the gas compressor is connected to the experimental tube through a connecting pipe. The experimental tube is provided with a rigid tube and an elastic tube;

[0040] A high-speed camera 5 is located on one side of the experimental tube and is used to obtain motion sequence images of the elastic tube and the rigid tube;

[0041] An acceleration displacement sensor is provided at the free end of the elastic tube and is triggered synchronously with the high-speed camera 5;

[0042] The data processor is electrically connected to the high-speed camera 5 and the acceleration displacement sensor, and performs displacement separation and frequency band analysis processing on the motion sequence images and integral correction processing on the acceleration displacement data.

[0043] Preferably, both ends of the rigid tube are fixed inside the experimental tube; the elastic tube is a reducing tube, the section with a smaller diameter of the elastic tube is fixed inside the experimental tube, and the section with a larger diameter of the elastic tube is a free section.

[0044] Preferably, the rigid tube and the elastic tube are made of the same material, the rigid tube is a solid tube, and the elastic tube is a hollow tube.

[0045] Preferably, the optical axis of the high-speed camera 5 is located on the center plane of the rigid tube and the elastic tube.

[0046] The advantages and positive effects of the vibration displacement measurement method and measurement system based on multi-source data fusion described in the present invention are:

[0047] 1. The present invention is based on the environmental vibration separation technology of the rigid tube, which effectively eliminates the coupling effect of the equipment foundation vibration on the measurement results, which is conducive to improving the measurement accuracy.

[0048] 2. The present invention optimizes the frequency band and compensates for the integral error in the acceleration signal processing process through the flow-induced vibration displacement data of the elastic tube, so that the maximum error of the displacement measurement is controlled within 5%, thereby improving the accuracy of the acceleration displacement measurement.

[0049] 3. This invention breaks through the stringent requirements of traditional high-speed photography methods on shooting conditions. While retaining the benchmark calibration function, it expands the applicable scenarios of the system within the wide frequency band of 0-250Hz.

[0050] 4. The present invention guides filtering processing through frequency band characteristic parameters, reduces the amount of invalid data calculations, increases the vibration signal processing speed by 15 times, and reduces storage requirements by 90%.

[0051] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a flow chart of a measurement method according to an embodiment of the present invention;

[0053] Figure 2 Schematic diagram of the measurement system structure according to an embodiment of the present invention;

[0054] Figure 3 Schematic diagram of the elastic tube structure in the measurement system according to an embodiment of the present invention;

[0055] Figure 4 Motion sequence images of the elastic tube and the rigid tube according to an embodiment of the present invention;

[0056] Figure 5 The image after grayscale conversion and region cropping according to the embodiment of the present invention;

[0057] Figure 6 The displacement time-history curves of the rigid tube and the elastic tube of the embodiment of the present invention are shown; wherein the measured value is the displacement time-history curve of the elastic tube, the environmental interference is the displacement time-history curve of the rigid tube, and the correction value is the displacement time-history curve of the flow-induced vibration of the elastic tube;

[0058] Figure 7 The frequency domain characteristic diagrams of the rigid tube and the elastic tube of the embodiment of the present invention are shown in FIG. 1 , wherein the measured value is the frequency domain characteristic diagram of the elastic tube, the environmental interference is the frequency domain characteristic diagram of the rigid tube, and the correction value is the frequency domain characteristic diagram of the flow-induced vibration of the elastic tube.

[0059] Figure 8 The elastic pipe flow-induced vibration displacement data calculated by the modified acceleration sensor according to the embodiment of the present invention and the elastic pipe flow-induced vibration displacement data obtained by a high-speed camera;

[0060] Figure 9 This is the uncorrected elastic pipe flow-induced vibration displacement data of the present invention.

[0061] Reference numerals

[0062] 1. Base; 2. Water tank; 3. Gas compressor; 4. Experimental tube; 5. High-speed camera; 6. Elastic tube; 7. Accelerometer. DETAILED DESCRIPTION

[0063] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or the orientations or positional relationships in which the inventive product is usually placed when in use. These are only for the convenience of describing the present invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention. In the description of the present invention, it should also be noted that, unless otherwise expressly specified and limited, the terms "setting", "installation" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the internal parts of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0064] In this application, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. In the event of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application. In order to accurately describe the technical content in this application and to accurately understand the present invention, the following explanations or definitions are given for the terms used in this specification before describing the specific embodiments:

[0065] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0066] Example

[0067] like Figure 1 A vibration displacement measurement method based on multi-source data fusion includes the following steps:

[0068] S1, obtain the motion sequence images of the elastic tube 6 and the rigid tube through the high-speed camera 5, such as Figure 4 At the same time, the acceleration sensor 7 collects the vibration acceleration signal of the elastic tube 6.

[0069] A Photron FASTCAM high-speed camera was used, with its optical axis strictly coplanar with the center planes of the elastic tube 6 and the rigid tube to eliminate three-dimensional projection errors caused by parallax. Camera parameter calibration was performed with a resolution of 2048 × 2048 pixels and a frame rate of 500 fps. Non-uniformity correction was performed using a built-in blackbody radiation source. The optical system was adjusted to obtain a clear imaging area with a depth of field of 15 mm at an aperture of f / 5.6, ensuring that the entire travel of the tube bundle remained within the focal plane. A PCB 3305A ICP accelerometer 7 (sensitivity 50 mV / (m·s⁻²), frequency response 0.5-5000 Hz ±3 dB) was also configured. A / D conversion was performed using a DH5922 dynamic signal analyzer with a sampling frequency of 500 Hz (meeting the Nyquist-Shannon sampling theorem). Synchronous signal acquisition between the high-speed camera 5 and the accelerometer 7 was achieved using the DH5922 dynamic data acquisition system, with a synchronization error of ≤0.1 ms.

[0070] S2. Extract the displacement trajectories of the elastic tube 6 and the rigid tube respectively, and separate the flow-induced vibration displacement time history curve of the elastic tube 6 by displacement vector calculation.

[0071] Specifically:

[0072] S21, grayscale conversion and region cropping processing are performed on the original video frame of the motion sequence image, such as Figure 5 shown.

[0073] The original video frame contains a wealth of information, but may contain interference factors such as noise and redundant background, hindering the subsequent identification of the tube's motion trajectory. Therefore, grayscale conversion and region cropping are performed on the original video frame. Grayscale conversion converts the color image to grayscale, reducing the complexity introduced by color information while preserving the image's brightness characteristics for easier processing. Region cropping selects the area containing the rigid tube and the elastic tube 6, removing irrelevant background components. This optimizes the boundary features of the rigid and elastic tubes 6, improving the efficiency and accuracy of subsequent processing.

[0074] S22 , respectively extracting the time-domain displacement trajectory function f1 (x, y) of the rigid tube and the time-domain displacement trajectory function f2 (x, y) of the elastic tube 6 through existing motion tracking software.

[0075] Because the rigid tube is rigidly connected to the test bench and has a high structural stiffness, its motion trajectory only reflects the vibration characteristics of the equipment foundation. Its time-domain displacement trajectory function, f1(x,y), represents the temporal variation of the equipment foundation vibration in the x and y directions. The motion response of the elastic tube 6 results from the coupling of flow-induced vibration and ambient vibration. The extracted time-domain displacement trajectory function, f2(x,y), captures the displacement variations in the x and y directions resulting from the combined effects of these two factors.

[0076] S23, construct a displacement vector calculation model, obtain the flow-induced vibration displacement trajectory function of the elastic tube 6, and obtain the flow-induced vibration displacement time history curve of the elastic tube 6. Figure 6 shown.

[0077] The displacement vector operation model is:

[0078] f(x,y)=f1(x,y)-f1(x,y);

[0079] Wherein, f(x, y) is the flow-induced vibration displacement trajectory function of the elastic tube 6.

[0080] To determine the vibration displacement time history of elastic tube 6 under flow-induced vibration, the influence of ambient vibration must be eliminated. Since f1(x, y) represents the displacement caused by the equipment's foundation vibration (i.e., ambient vibration), and f2(x, y) represents the displacement of elastic tube 6 under the combined effects of flow-induced and ambient vibrations, subtracting these two factors effectively eliminates the common-mode interference of ambient vibration, yielding the vibration displacement time history f(x, y) of elastic tube 6 caused solely by flow-induced vibration.

[0081] S3. Perform frequency domain analysis on the displacement trajectory data of the rigid tube and the elastic tube 6 respectively, establish power spectrum density functions of the rigid tube and the elastic tube 6 , and determine the frequency bands of the rigid tube and the elastic tube 6 .

[0082] Specifically:

[0083] S31. In order to quantify the frequency spectrum characteristics of the vibration signals of the rigid tube and the elastic tube 6, a frequency domain decoupling analysis model is established, and the displacements of the rigid tube and the elastic tube 6 are respectively subjected to continuous Fourier transform to obtain frequency domain expressions.

[0084] The frequency domain decoupling analysis model is:

[0085]

[0086] Where X(ω) is the frequency domain function, ω is the angular frequency, t is the time variable, j is the imaginary unit, and x(t) is the displacement at time t.

[0087] Through this transformation, we can analyze the distribution of the signal in different frequency components, understand which frequencies the signal contains and the relative strength of each frequency component.

[0088] S32. Since the actual collected signal is discrete, it is necessary to discretize the time domain signal. After discretization, the discrete spectrum is calculated using the fast Fourier transform algorithm. The formula is:

[0089]

[0090] Where X[k] is the discrete spectrum, N is the sampling capacity, k is the frequency, n is the number of sampling times, x[n] is the discrete time domain signal, and the frequency resolution Δf = f s / N,f s is the sampling frequency.

[0091] The fast Fourier transform algorithm is a method for efficiently calculating discrete Fourier transforms, which greatly reduces the amount of calculation and can quickly and accurately obtain discrete spectra, thereby performing frequency domain analysis on discrete time domain signals.

[0092] S33. In order to analyze the energy distribution of the signal more intuitively, the amplitude of the discrete spectrum is normalized and a normalized power spectrum density function is established. The formula of the normalized power spectrum density function is:

[0093] P(ω)=|X(ω)| 2 / 2πT;

[0094] Where T is the signal observation time.

[0095] The above formula normalizes the amplitude of the frequency domain signal, allowing the spectra of different signals to be compared on the same scale. The power spectral density function represents the energy distribution of a signal at different frequencies, clearly showing which frequencies the signal's energy is primarily concentrated in.

[0096] S4. Determine the main frequency of the rigid tube, the main frequency of the elastic tube 6 and the main frequency of the flow-induced vibration according to the power spectrum density functions of the rigid tube and the elastic tube 6, and judge whether the main frequency of the rigid tube and the main frequency of the flow-induced vibration meet the frequency decoupling condition.

[0097] The frequency decoupling condition is that the main frequency of the rigid tube is greater than or less than the main frequency of the flow-induced vibration by ±50%.

[0098] The frequency domain characteristic decomposition diagram of the rigid tube and elastic tube 6 is as follows Figure 7 As shown in the figure, by observing the frequency domain characteristic diagrams of the rigid tube and the elastic tube 6, it is found that the rigid tube power spectrum forms the main frequency characteristic of environmental vibration at 6.2Hz, while the elastic tube 6 vibration spectrum shows a characteristic peak of flow-induced vibration at 23.6Hz. The two main frequency components are significantly separated by 17.4Hz in the frequency domain, meeting the frequency decoupling criterion for fluid-structure coupling systems and verifying the accurate extraction of the flow-induced vibration characteristic frequency.

[0099] S5. Band-pass filtering is performed on the signal of the acceleration sensor 7 based on the frequency band of the flow-induced vibration, and the error of the integral trend term of the acceleration sensor 7 is compensated using the time-domain displacement data of the rigid tube.

[0100] A bandpass filter was designed, and a dual-channel cascaded filtering architecture was constructed using the MATLAB platform. This achieved amplitude attenuation in the environmental interference frequency band (4-8 Hz) while preserving the integrity of the vibration signal in the characteristic frequency band (20-27 Hz). The passband boundaries in the bandpass filter parameter matrix were set to ±50% of the main frequency of flow-induced vibration, i.e., 0.5 to 1.5 times the main frequency of flow-induced vibration. During signal processing, the acceleration signal was passed through this filter, locking the signal processing frequency band within the ±50% frequency range of the main frequency of flow-induced vibration. This effectively extracted frequency components related to flow-induced vibration, providing strong support for subsequent vibration analysis and research.

[0101] The error of the integral trend term of acceleration sensor 7 is compensated by the time domain displacement data of the rigid tube as follows:

[0102] Align the integrated displacement of the acceleration sensor 7 with the time-domain displacement data of the rigid tube. Integrating the acceleration signal yields displacement information, but the resulting displacement data may exhibit trend errors due to factors such as measurement error and signal noise. To compensate for this error, reference displacement data is introduced: the flow-induced vibration displacement data of the elastic tube 6, processed by the high-speed camera 5 and vectorized with the rigid tube motion data. First, align the time-domain data of the integrated acceleration displacement and the reference displacement to ensure accurate correspondence on the time axis.

[0103] Calculate and eliminate the trend offset of the acceleration zone sensor's integrated displacement. After aligning the time domain data, calculate the trend offset of the integrated displacement. By comparing the acceleration integrated displacement with the baseline displacement data, you can identify the difference in the trend of the integrated displacement from the baseline displacement. Over a period of time, the acceleration integrated displacement may show a linear growth or decay trend, while the baseline displacement may be relatively stable. This difference between the two is the trend offset. After calculating the trend offset, subtract it from the acceleration integrated displacement data to eliminate the trend error. Assuming that the calculation shows that the trend offset of the integrated displacement over a period of time is a linear function y = ax + b (x represents time, a and b are constants), subtracting this function value from the integrated displacement data will make the integrated displacement data closer to the actual displacement, improve the accuracy of the displacement data, and provide a more reliable basis for subsequent analysis and applications based on the displacement data.

[0104] S6. Perform secondary integration on the filtered acceleration sensor 7 signal and output corrected displacement information.

[0105] Figure 8 The flow-induced vibration displacement data of the elastic tube 6 calculated by the modified acceleration sensor 7 and the flow-induced vibration displacement data of the elastic tube 6 obtained by the high-speed camera 5; Figure 9 is the uncorrected flow-induced vibration displacement data of the elastic tube 6. Figure 8 、 Figure 9 Tests were conducted within the flow velocity range of 0.5-1.8 m / s, and the maximum relative error between the two methods was ≤5%, a 62% reduction in the average error compared to the traditional acceleration integration method, effectively expanding the applicability of the sensor method in complex working conditions.

[0106] like Figure 2 A measurement system for implementing the above-mentioned vibration displacement measurement method based on multi-source data fusion includes:

[0107] The water tank 2 is used to store fluid.

[0108] The gas compressor 3 is used to provide a gas source.

[0109] The test tube 4 is used to mix fluid and gas and perform vibration displacement measurements. It is connected to the water tank 2 via a circulation line, and the gas compressor 3 is connected to the test tube 4 via a connecting pipe. A rigid tube and an elastic tube 6 are located within the test tube 4. Made of aluminum alloy, the fluid and gas enter through the bottom of the test tube 4, mix within it, and then flow out of the top of the tube 4 and return to the water tank 2. The fluid and gas mixture flowing within the test tube 4 causes flow-induced vibrations in the elastic tube 6.

[0110] The high-speed camera 5 is located on one side of the experimental tube 4 and is used to obtain motion sequence images of the elastic tube 6 and the rigid tube.

[0111] The acceleration displacement sensor is arranged at the free end of the elastic tube 6 and is triggered synchronously with the high-speed camera 5 .

[0112] The data processor is electrically connected to the high-speed camera 5 and the acceleration displacement sensor, and performs displacement separation and frequency band analysis on the motion sequence images and integral correction on the acceleration displacement data.

[0113] The water tank 2, the gas compressor 3, the experimental tube 4, and the high-speed camera 5 are all fixed on the base 1, and the base 1 is fixed on the ground.

[0114] Both ends of the rigid tube are fixed inside the test tube 4. The rigid tube is a solid tube, so that the rigid tube is mainly affected by the vibration of the equipment, and the vibration of the rigid tube caused by the fluid can be ignored.

[0115] like Figure 3 As shown, the elastic tube 6 is a reducing tube, with a diameter of 8mm-15mm at one end and 22mm-28mm at the other. The smaller end of the elastic tube 6 is fixed inside the test tube 4, while the larger end of the elastic tube 6 is the free end. The acceleration and displacement sensor is fixed in a groove 50mm from the free end of the elastic tube 6.

[0116] The rigid tube and the elastic tube 6 are made of the same material. The end of the elastic tube 6 with a larger diameter is a hollow tube with a wall thickness of 1 mm.

[0117] The optical axis of the high-speed camera 5 is located on the center plane of the rigid tube and the elastic tube 6 .

[0118] Therefore, the use of the vibration displacement measurement method and measurement system based on multi-source data fusion described in the present invention can solve the problem that existing vibration measurement methods cannot achieve effective unification of measurement accuracy and engineering applicability.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A vibration displacement measurement method based on multi-source data fusion, characterized in that: The following steps are involved: S1. Capturing motion sequence images of the elastic tube and the rigid tube using a high-speed camera, and simultaneously collecting vibration acceleration signals of the elastic tube using an acceleration sensor; S2. Extract the displacement trajectories of the elastic tube and the rigid tube respectively from the motion sequence images, and separate the flow-induced vibration displacement time history curve of the elastic tube through displacement vector calculation; S3. Perform frequency domain analysis on the displacement trajectory data of the rigid tube and the elastic tube respectively, establish power spectrum density functions of the rigid tube and the elastic tube, and determine the frequency bands of the rigid tube and the elastic tube; S4. Determine the main frequency of the rigid tube, the main frequency of the elastic tube, and the main frequency of the flow-induced vibration based on the power spectral density functions of the rigid tube and the elastic tube, and judge whether the main frequency of the rigid tube and the main frequency of the flow-induced vibration meet the frequency decoupling condition; S5. performing band-pass filtering on the acceleration sensor signal based on the frequency band of the flow-induced vibration, and compensating for the error of the integral trend term of the acceleration sensor using the time-domain displacement data of the rigid tube; S6. Perform a secondary integration on the filtered acceleration sensor signal and output corrected displacement information.

2. The vibration displacement measurement method based on multi-source data fusion according to claim 1, characterized in that: The S2 is specifically: S21, performing grayscale conversion and region cropping processing on the original video frames of the motion sequence image; S22, extracting the time-domain displacement trajectory function f1(x, y) of the rigid tube and the time-domain displacement trajectory function f2(x, y) of the elastic tube respectively through motion tracking software; S23, constructing a displacement vector calculation model to obtain a flow-induced vibration displacement trajectory function of the elastic tube, and obtaining a flow-induced vibration displacement time history curve of the elastic tube; The displacement vector operation model is: f(x,y)=f1(x,y)-f1(x,y); Where f(x,y) is the flow-induced vibration displacement trajectory function of the elastic tube.

3. The vibration displacement measurement method based on multi-source data fusion according to claim 1, characterized in that: The S3 is specifically: S31. Establish a frequency domain decoupling analysis model, perform continuous Fourier transform on the displacements of the rigid tube and the elastic tube, and obtain frequency domain expressions; the frequency domain decoupling analysis model is: Where X(ω) is the frequency domain function, ω is the angular frequency, t is the time variable, j is the imaginary unit, and x(t) is the displacement at time t; S32, calculating the discrete spectrum using a fast Fourier transform algorithm; Where X[k] is the discrete spectrum, N is the sampling capacity, k is the frequency, n is the number of sampling times, x[n] is the discrete time domain signal, and the frequency resolution Δf = f s / N,f s is the sampling frequency; S33, normalizing the amplitude of the discrete spectrum to establish a standardized power spectrum density function; P(ω)=|X(ω)| 2 / 2πT; Where T is the signal observation time.

4. The vibration displacement measurement method based on multi-source data fusion according to claim 1, characterized in that: In the above S4, the frequency decoupling condition is that the main frequency of the rigid tube is greater than or less than ±50% of the main frequency of the flow-induced vibration.

5. The vibration displacement measurement method based on multi-source data fusion according to claim 1, characterized in that: In the above-mentioned S5, the passband boundary of the bandpass filter is ±50% of the main frequency of the flow-induced vibration.

6. The vibration displacement measurement method based on multi-source data fusion according to claim 1, characterized in that: In S5, the error of the integral trend term of the acceleration sensor is compensated using the time domain displacement data of the rigid tube as follows: The integrated displacement of the acceleration sensor is aligned with the time domain displacement data of the rigid tube, and the trend term offset of the integrated displacement of the acceleration sensor is calculated and eliminated.

7. A measurement system for implementing the vibration displacement measurement method based on multi-source data fusion according to any one of claims 1 to 6, characterized in that: include: a water tank for storing fluid; A gas compressor is used to provide a gas source; The experimental tube is used to mix fluid and gas and perform vibration displacement measurement. The experimental tube is connected to the water tank through a circulation pipeline, and the gas compressor is connected to the experimental tube through a connecting pipe. The experimental tube is provided with a rigid tube and an elastic tube; A high-speed camera 5 is located on one side of the experimental tube and is used to obtain motion sequence images of the elastic tube and the rigid tube; An acceleration displacement sensor is provided at the free end of the elastic tube and is triggered synchronously with the high-speed camera 5; The data processor is electrically connected to the high-speed camera 5 and the acceleration displacement sensor, and performs displacement separation and frequency band analysis processing on the motion sequence images and integral correction processing on the acceleration displacement data.

8. The measurement system according to claim 7, characterized in that: The two ends of the rigid tube are fixed inside the experimental tube; the elastic tube is a reducing tube, the smaller diameter section of the elastic tube is fixed inside the experimental tube, and the larger diameter section of the elastic tube is a free section.

9. The measurement system according to claim 8, characterized in that: The rigid tube and the elastic tube are made of the same material; the rigid tube is a solid tube, and the elastic tube is a hollow tube.

10. The measurement system according to claim 7, characterized in that: The optical axis of the high-speed camera 5 is located on the center plane of the rigid tube and the elastic tube.

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