Vibration source inversion experiment device and method based on weak vibration wave signal characteristics

Abstract

The invention discloses a vibration source inversion experiment device and method based on weak vibration wave signal characteristics. The vibration source inversion experiment device comprises a vibration information simulation acquisition module and a waveform information intelligent analysis module. The vibration information simulation acquisition module is used for simulating vibration wave information sent by a trapped person knocking a collapse environment heterogeneous medium; and the waveform information intelligent analysis module is used for accurately filtering clutters and extracting effective vibration wave information characteristics in a simulation environment, so as to carry out visual inversion on a vibration wave source position. According to the invention, the whole process of sound production, receiving, acquisition and processing of vibration waves can be completed autonomously, vibration wave signals for detecting survivors are generated finally, and the purpose of visualization of wave source information is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of source inversion experiments, and particularly relates to a source inversion experiment device and method based on the characteristics of weak vibration wave signals. Background Art

[0002] During natural disasters such as earthquakes, landslides, and debris flows, as well as industrial accidents such as mine explosions and roof falls, a collapsed and buried space is easily formed. Trapped people are buried deep in complex media spaces such as steel, wood, and brick-concrete walls, bringing great difficulties to rescue work. Existing rescue methods mainly rely on technologies such as radar and audio-visual detection, which have played an important role in the rescue process of collapsed disaster accidents. However, limited by problems such as short penetration distance, strong medium interference, and limited detection range, misjudgment and missed judgment of the position of trapped people are likely to occur, seriously affecting the reliability and accuracy of rescue work. Once the best rescue time is missed, irreparable casualties will be caused.

[0003] Current technical solutions mainly rely on the auditory sense and subjective perception of rescue personnel to identify the distress information of trapped people. There are many interference factors and certain randomness. At the same time, the vibration wave signals in some environments with large burial depths and complex medium compositions are weak and difficult to detect, making it difficult to accurately search for trapped people.

[0004] Therefore, designing a detection device with high precision and wide range, which can effectively and timely discover the buried people according to the weak vibration waves generated by the trapped people knocking on the pipeline, identifying and extracting the vibration wave signals in the complex medium space, and constructing a source inversion experiment device and method based on the characteristics of weak vibration wave signals, is of great significance for quickly and effectively detecting the buried people. Summary of the Invention

[0005] In order to overcome the above technical problems, the purpose of the present invention is to provide a source inversion experiment device and method based on the characteristics of weak vibration wave signals. The device and method can independently complete the whole process of generating, receiving, collecting, and processing vibration waves, and finally generate vibration wave signals for detecting survivors, achieving the purpose of visualizing the wave source information.

[0006] The technical solution adopted by the present invention is:

[0007] A source inversion experiment device based on the characteristics of weak vibration wave signals, comprising a vibration information simulation and acquisition module and a waveform information intelligent analysis module;

[0008] The vibration information simulation and acquisition module is used to simulate the vibration wave information generated by trapped people knocking on the heterogeneous medium in the collapsed environment;

[0009] The waveform information intelligent analysis module is used to accurately filter out clutter and extract the effective vibration wave information characteristics in the simulated environment, and then visually invert the position of the vibration wave source.

[0010] The vibration information simulation acquisition module includes an annular die box body (1), a vibration collector (8) and an intelligent vibrator (6); the vibration sensing collector (8) and the intelligent vibrator (6) are respectively located at both ends of the annular die box body (1) to independently emit and collect vibration waves.

[0011] The annular die box body (1) includes a box cover (2), a box body (3), a simulated pipeline (5) and a complex medium (4), and the inside of the box body (3) is filled with the simulated pipeline (5) and the complex medium (4);

[0012] The simulated pipeline (5) is horizontally placed in the middle of the box body (3), and the complex medium (4) required for the experiment is filled around the simulated pipeline (5).

[0013] A circular opening is provided on the left side wall of the box body (3) to expose one outlet of the simulated pipeline (5) to the external environment, simulating the position of the ground wellhead in the collapse environment;

[0014] One end of the simulated pipeline (5) passes through the circular opening provided on the left side wall of the box body (3), simulating the rescue position of the rescue personnel at the ground wellhead in the collapse environment, and the other end is placed at the right end inside the box body (3), simulating the position of the trapped personnel underground in the collapse environment;

[0015] Sound insulation cotton sheets (7) are provided on the remaining inner walls of the box body (3) without openings, sound insulation cotton sheets (7) are provided on the inner wall of the box cover (2), and sound insulation cotton sheets (7) are provided at the connection gap between the box body (3) and the box cover (2).

[0016] The types of the simulated pipeline (5) include straight pipelines, bent pipelines and broken pipelines, respectively simulating the characteristics of various shapes of pipelines existing in the collapse environment;

[0017] The types of the complex medium (4) include soil, concrete, rock and soil and mixed media, respectively simulating the environmental characteristics existing in the collapse environment;

[0018] According to the requirements of the experimental environment settings, soil, concrete and rock and soil media are filled respectively to simulate the propagation effects of vibration wave signals under the conditions of single media such as soil, concrete and rock and soil;

[0019] The mixed medium is prepared by mixing soil:concrete:rock and soil in a ratio of 1:1:1 to simulate the propagation effect of vibration wave signals under the condition of non-uniform media; study the influence laws of the medium composition, shape and structure of the collapsed body on the propagation characteristics of vibration waves; compare the propagation characteristics of vibration waves in single media and multi-media.

[0020] The vibration collector (8) includes four groups of gecko-wireless vibration sensors, which are used to adsorb at any position on the side wall of the opening of the ring die box body (1); it is powered by a built-in 20000mAH high-density lithium thionyl chloride battery, and adopts NB-IOT / Lora / 5G communication methods, with ultra-high sensitivity, and can collect vibration waves from dozens of HZ to 3000HZ;

[0021] The gecko-wireless vibration sensors are installed at arbitrary coordinate positions A(x 1 , y 1 , z 1 ), B(x 2 , y 2 , z 2 ), C(x 3 , y 3 , z 3 ), D(x 4 , y 4 , z 4 ); it provides a data analysis basis for the subsequent 4-point time difference positioning technology of the vibration source inversion.

[0022] The waveform information intelligent analysis module includes a vibration wave data collector (9), a signal amplifier (10), a signal conditioner (11) and a data processor (14);

[0023] The vibration wave data collector (9) collects and summarizes the multi-vibration wave signals collected by the vibration collector (8), and then through the signal amplifier (10), the weak signals are amplified and transmitted to the signal conditioner (11); the signal conditioner (11) is connected to the data processor (14).

[0024] The signal conditioner (11) includes a wavelet denoising unit (12) and a Fast ICA clutter suppression and filtering unit (13), which are used to achieve primary noise reduction and separation and fine denoising of multi-vibration source signals.

[0025] The wavelet denoising unit (12) is a primary noise reduction method for multi-vibration source signals. By establishing a wavelet transform multi-resolution analysis algorithm, the wavelet coefficients corresponding to the noise in the 200hz-7000hz frequency band are removed, and the wavelet decomposition coefficients of the original signal are retained. Then, the processed coefficients are wavelet reconstructed to obtain the primary noise reduction signal;

[0026] The Fast ICA clutter suppression and filtering unit (13) is a separation and fine denoising method. It further filters the clutter of the obtained primary noise reduction signal. By applying the Fast ICA clutter suppression and filtering unit (13), the observed signal is decomposed into multiple independent components, and the components related to the target signal are retained, and the components related to the clutter of 10hz-200hz are suppressed or filtered to process signals with complex backgrounds and noises.

[0027] The data processor (14) includes a waveform information visualization unit (15) and a wave source inversion unit (16). The waveform information visualization unit 15 uses frequency domain analysis technology to convert the vibration signal into an amplitude-frequency curve, and determines the direction of the vibration source based on the appearance of the amplitude-frequency curve. Subsequently, the time difference positioning technology of the wave source inversion unit 16 is used to invert the vibration source, so as to obtain the specific position coordinates of the vibration source and realize the visualization of wave source information.

[0028] After the vibration wave signal is emitted, the wavelet noise reduction unit (12) initially receives the vibration wave signal parameters and performs preliminary noise reduction. After the high-frequency noise is filtered out, the Fast ICA clutter suppression filter unit (13) receives the preliminarily noise-reduced vibration wave signal and filters out the low-frequency noise signal, and obtains an effective vibration wave signal. The effective vibration wave signal is transmitted to the waveform information visualization unit (15), and the direction of the vibration source is determined based on the appearance of the amplitude-frequency curve. Subsequently, the time difference positioning technology of the wave source inversion unit (16) is used to invert the specific position information of the vibration source, which can provide a basis for the accurate positioning of trapped personnel.

[0029] The inside of the annular mold box body (1) in the vibration information simulation acquisition module is filled with a complex medium (4) and a simulation pipeline (5) to simulate the collapsed environment after the disaster. An intelligent vibrator (6) is arranged at one end of the box body to autonomously start and generate vibration wave information. The vibration information is collected by the vibration collector (8) at the other end of the annular mold box body and then transmitted to the waveform information intelligent analysis module;

[0030] The vibration wave data collector (9) in the waveform information intelligent analysis module summarizes the vibration information received by the vibration collector (8) and transmits it to the vibration signal amplifier (10) to amplify the weak vibration wave signal. Then, the wavelet noise reduction unit (12) performs primary noise reduction on the vibration wave signal. The vibration wave signal after primary noise reduction continues to be transmitted to the Fast ICA clutter suppression filter unit (13) to separate and finely denoise the multi-vibration source signals and extract the effective vibration wave signal; the vibration waveform information visualization unit (14) receives the effective vibration signal, converts the vibration signal into an amplitude-frequency curve using frequency domain analysis, and simultaneously uses the time difference positioning technology to invert the vibration source, so as to obtain the specific position coordinates of the vibration source and realize the visualization of wave source information.

[0031] A method for inverting the vibration source of weak vibration wave signal characteristics, the method comprising the following steps:

[0032] Step 1: Annular mold box body filling: Arrange the simulation pipeline 5 in the middle position of the box body 3, install the intelligent vibrator 6 inside the vibration end wall surface of the simulation pipeline 5, fill the complex medium 4 required for the experiment around the simulation pipeline 5, and cover the box cover 2 after filling;

[0033] Step 2: Install the vibration collector 8: Install the four groups of gecko-wireless vibration sensors on the four positions of the side wall of the opening of the ring die box body 3 respectively, and record the coordinates of the four positions with the center of the opening as the axis, so as to carry out the subsequent vibration source inversion work;

[0034] Step 3: Connect the intelligent waveform analysis module: Connect the vibration wave data collector 9, signal amplifier 10, signal conditioner 11 and data processor 14 in sequence;

[0035] Step 4: Start the vibration information simulation acquisition module: Click the start module of the data processor 14, the device starts, the intelligent vibrator 6 knocks on the simulation pipeline (5) to generate a vibration wave signal, which is transmitted to the side of the opening through the ring die box body 1 and detected by the gecko-wireless vibration sensor;

[0036] Step 5: Start the intelligent waveform analysis module: The vibration wave data collector 9 receives the vibration wave signal and transmits it to the signal amplifier 10. After the weak signal is amplified, it enters the signal conditioner 11. Through the wavelet noise reduction unit 12 and the Fast ICA clutter suppression filter unit 13, the primary noise reduction and separation of the multi-vibration source signal can be carried out for fine denoising, and the effective vibration wave signal can be extracted;

[0037] Step 6: The data processor performs waveform information visualization processing and vibration source position inversion work.

[0038] The specific content of the said Step 5 is as follows:

[0039] 501: The vibration wave data collector 9 receives the vibration wave signal and transmits it to the signal amplifier 10. After the weak signal is amplified, it enters the signal conditioner 11. The amplified signal contains a large amount of stray signals and needs to be filtered again;

[0040] The signal gain processing is realized by the signal amplifier 10. The vibration wave signal form of the output signal is amplified by adjusting the current gain or voltage gain. The signal amplifier 10 works bidirectionally and amplifies the signal intensity of both reception and transmission at the same time;

[0041] When performing signal gain processing, the influence of noise also needs to be considered. Noise will interfere with the signal transmission and reception, reducing the signal-to-noise ratio and clarity of the signal. Therefore, after the signal gain processing, filtering needs to be carried out again. The mean filtering method is adopted for filtering. The specific operation method is: sum up multiple sampling values and take the average value to eliminate random errors.

[0042] 502: The wavelet noise reduction unit (12) is a primary noise reduction method for multi-vibration source signals, by establishing a wavelet transform multi-resolution analysis algorithm;

[0043] Remove the wavelet coefficients corresponding to the noise in the frequency band of 200 hz - 7000 hz, retain the wavelet decomposition coefficients of the original signal, and then perform wavelet reconstruction on the processed coefficients to obtain a primary noise reduction signal;

[0044] Wavelet coefficient removal is based on the characteristic that the wavelet decomposition coefficients of noise and signal have different intensity distributions in different frequency bands. Remove the wavelet coefficients corresponding to the noise in each frequency band, retain the wavelet decomposition coefficients of the original signal, and then perform wavelet reconstruction on the processed coefficients to obtain a pure signal. After wavelet transform, the wavelet coefficient amplitudes of the vibration signal are larger and the number is smaller, while the wavelet coefficient amplitudes of the noise are smaller and the number is larger. Therefore, set a threshold to classify the absolute values of the amplitudes, directly set the wavelet coefficients with small amplitudes to zero, and then perform shrinkage reconstruction on the remaining coefficients.

[0045] Wavelet reconstruction is based on the inverse process of wavelet decomposition. Select a combination of reconstruction algorithms to gradually reconstruct the processed coefficients to restore the original signal.

[0046] 503: Fast ICA clutter suppression filtering unit (13), which is a separation and fine denoising method. Further clutter filtering is performed on the obtained primary noise reduction signal. The method of clutter filtering is to decompose the observed signal into multiple independent components by applying the Fast ICA clutter suppression filtering unit (13), retain the components related to the target signal, suppress or filter the components related to the clutter of 10 hz - 200 hz, and process signals with complex backgrounds and noise. The specific steps are as follows:

[0047] First, perform signal preprocessing: perform mean removal and whitening preprocessing on the primary noise reduction signal. Mean removal eliminates the DC component of the signal, and whitening preprocessing eliminates the correlation between signals, enabling subsequent algorithms to effectively separate independent components. Then, implement the Fast ICA algorithm: input the preprocessed signal into the Fast ICA algorithm, and solve for independent components through an iterative optimization algorithm. In each iteration, the algorithm updates the weights of the independent components based on the current estimated values until the convergence condition is met or the preset number of iterations is reached. Finally, perform independent component selection and clutter suppression: After obtaining the independent components, select appropriate independent components according to the actual application scenario to reconstruct the original signal. The independent components related to the clutter of 10 hz - 200 hz will be filtered or suppressed, while the independent components related to the target signal will be retained.

[0048] The specific content of step six is as follows:

[0049] 601: Use frequency domain analysis technology to perform Fourier transform on the collected vibration wave information to obtain the amplitude value of the vibration signal. The formula is as follows:

[0050]

[0051] where ξ represents frequency, and A p (), respectively represent the amplitude and phase functions of the frequency-domain signal ;

[0052] 602: According to the Fourier transform result in the above formula, the vibration signal is further transformed into an amplitude-frequency curve, and the direction of the vibration source can be judged according to the appearance of the amplitude-frequency curve;

[0053] 603: Using the time-difference positioning technology of the wave source inversion unit, the installation point coordinates of four groups of gecko-wireless vibration sensors are known as A(x 1 , y 1 , z 1 ), B(x 2 , y 2 , z 2 ), C(x 3 , y 3 , z 3 ), D(x 4 , y 4 , z 4 ); the coordinates of the vibration wave emission point to be obtained are E(x, y, z). Let the times when the vibration sensors collect the vibration waves be T 1 , T 2 , T 3 ; based on the 4-point time-difference positioning principle, there is

[0054]

[0055] That is:

[0056]

[0057] where:

[0058]

[0059] where V is the propagation speed of the vibration wave in the annular film box body. Finally, by solving (x, y, z), the position of the vibration source can be inverted and the vibration source information in the experiment can be visualized.

[0060] Advantages of the present invention:

[0061] 1. Starting from the perspective of the effective rescue information that the trapped person in the collapsed and buried space knocks on the surrounding environmental medium to generate vibration waves, the present invention proposes a method to accurately identify the effective characteristics of the vibration waves and then invert the position of the vibration source, greatly avoiding the influence of many interference factors when relying on the hearing and subjective feelings of rescue personnel to identify the distress information of the trapped person, and ensuring the accuracy and timeliness of rescue detection.

[0062] 2. The present invention takes the identification of the characteristics of knocking vibration waves in the complex medium of the collapsed body as the starting point. Through the vibration information simulation acquisition module, it simulates the collapsed multi-component heterogeneous medium and independently and intelligently emits vibration wave information. The waveform information intelligent analysis module accurately filters out clutter and extracts the effective vibration wave information characteristics in the simulated environment, and then visually inverses the position of the vibration wave source, providing a theoretical basis for the positioning and accurate search of trapped persons after the disaster.

[0063] 3. The method adopted by the present invention has simple steps and can independently complete the whole process of generating, emitting, receiving, and collecting vibration waves, quickly and accurately detecting the weak vibration wave signals required in the simulated collapsed environment, and using the frequency domain analysis method and the time difference positioning technology to quantitatively identify the position of the vibration source, realizing the visualization of the wave source information.

[0064] In summary, the present invention has a novel and reasonable design. It can effectively and timely discover the buried persons according to the weak vibration waves generated by the trapped persons knocking on the pipeline. For the identification and extraction of vibration wave signals in the complex medium space, it is beneficial to improve the research on the vibration source inversion mechanism of weak vibration wave signal characteristics, and can provide a reference for realizing the quick and effective detection of buried persons, which is convenient for popularization and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic structural connection diagram of the experimental device adopted by the present invention.

[0066] Figure 2 It is a top view of the internal layout position of the annular die box of the present invention.

[0067] Figure 3 It is a schematic diagram of the simulated pipeline type of the present invention.

[0068] Figure 4 It is a schematic diagram of the vibration wave positioning layout of the present invention

[0069] Figure 5 It is a schematic diagram of the time difference positioning method of the present invention

[0070] Figure 6 It is a flow block diagram of the method of the present invention.

[0071] REFERENCE SIGNS:

[0072] 1 - annular die box; 2 - box cover; 3 - box body; 4 - complex medium; 5 - simulated pipeline; 6 - intelligent vibration end; 7 - sound insulation cotton sheet; 8 - vibration collector; 9 - data collector; 10 - signal amplifier; 11 - signal conditioner; 12 - noise reduction unit; 13 - clutter filtering unit; 14 - data processor; 15 - visualization unit; 16 - wave source position inversion unit; 17 - start switch. DETAILED DESCRIPTION OF THE INVENTION

[0073] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0074] As Figures 1 to 5 shown, an experimental device and method for source inversion based on the characteristics of weak vibration wave signals according to the present invention includes two major parts: a vibration information simulation acquisition module and a waveform information intelligent analysis module; a complex medium 4 and a simulation pipeline 5 are filled inside the annular mold box body 1 in the vibration information simulation acquisition module to simulate the collapsed environment after a disaster. An intelligent vibrator 6 is arranged at one end of the box body to independently generate vibration wave information. After the fluctuation information is collected by the vibration collector 8 at the other end of the annular mold box body, it is transmitted to the waveform information intelligent analysis module. The vibration wave data collector 9 in the waveform information intelligent analysis module summarizes the fluctuation information received by the vibration collector 8 and transmits it to the fluctuation signal amplifier 10 to amplify the weak vibration wave signal. Then, the vibration wave signal is subjected to primary noise reduction by the wavelet noise reduction unit 12. The vibration wave signal after primary noise reduction continues to be transmitted to the Fast ICA clutter suppression and filtering unit 13 to separate and finely denoise the multi-vibration source signals and extract the effective vibration wave signal. The vibration waveform information visualization unit 14 receives the effective fluctuation signal, converts the vibration signal into an amplitude-frequency curve using frequency domain analysis, and at the same time inversely calculates the vibration source using the time difference positioning technology, so as to obtain the specific position coordinates (x, y, z) of the vibration source and realize the visualization of the wave source information.

[0075] In this embodiment, the annular mold box body includes a box body 3, a box cover 2, a simulation pipeline 5, and a complex medium 4, and the simulation pipeline 5 and the complex medium 4 are filled inside the box body.

[0076] In this embodiment, a circular opening is provided on the left side wall surface of the box body 3 so that one outlet of the simulation pipeline 5 is exposed to the external environment, thereby simulating the position of the ground wellhead in the collapsed environment. Sound insulation cotton sheets 7 are provided on the remaining inner walls of the box body 3 without openings, sound insulation cotton sheets 7 are provided on the inner wall of the box cover 2, and sound insulation cotton sheets 7 are provided at the connection gap between the box body 3 and the box cover 2.

[0077] In this embodiment, the types of the simulation pipeline 5 include straight pipelines, bent pipelines, and broken pipelines, respectively simulating the characteristics of various shaped pipelines existing in the collapsed environment. The types of the complex medium 4 include soil, concrete, rock and mixed media, respectively simulating the environmental characteristics existing in the collapsed environment.

[0078] In this embodiment, the vibration collector 8 and the intelligent vibration end 6 are respectively located at both ends of the annular mold box body 1 to independently emit and collect vibration waves.

[0079] In this embodiment, the vibration collector 8 includes four groups of gecko-wireless vibration sensors, which can be firmly adsorbed at any position on the side wall of the opening of the ring die box body, powered by a built-in 20000mAH high-density lithium thionyl chloride battery, and uses NB-IOT / Lora / 5G communication methods, with ultra-high sensitivity, and can collect vibration waves from dozens of HZ to 3000HZ.

[0080] In this embodiment, the vibration wave data collector 9 collects and summarizes the multi-vibration wave signals collected by the vibration sensing collector, and then through the signal amplifier 10, the weak signals are amplified and transmitted to the signal conditioner 11.

[0081] In this embodiment, the signal conditioner 11 includes a noise reduction unit 12 and a clutter suppression and filtering unit 13.

[0082] In this embodiment, the noise reduction unit 12 and the clutter filtering unit 13 are respectively wavelet primary noise reduction and Fast ICA clutter suppression and filtering, which can achieve primary noise reduction and separation and fine denoising of multi-vibration source signals, and can filter acoustic signals of 200hz - 7000hz and 10hz - 200hz respectively, and extract effective vibration wave signals.

[0083] In this embodiment, the data processor 14 includes a waveform information visualization unit 15, a wave source inversion unit 16 and a start switch 17. The start switch 17 controls the start and stop of the entire experimental device. The waveform information visualization unit 15 uses frequency domain analysis technology to convert the vibration signal into an amplitude-frequency curve, and can judge the general direction of the vibration source according to the appearance of the amplitude-frequency curve. Subsequently, the time difference positioning technology of the wave source inversion unit 16 is used to invert the vibration source, so as to obtain the specific position coordinates of the vibration source and realize the visualization of wave source information.

[0084] As Figure 4 shown, a vibration source inversion experimental device and method based on the characteristics of weak vibration wave signals includes the following steps:

[0085] Step 1: Ring die box body filling: Arrange the simulation pipeline in the middle of the box body, install the intelligent vibrator on the inner side of the vibration end wall of the simulation pipeline, fill the complex medium required for the experiment around the simulation pipeline, and cover the box cover after filling.

[0086] Step 2: Install the vibration collector: Install four groups of gecko-wireless vibration sensors at four points on the side wall of the opening of the ring die box body respectively, and record the coordinates of the four points with the center of the opening as the axis, so as to carry out subsequent vibration source inversion work.

[0087] Step 3: Connect the waveform information intelligent analysis module: Connect the vibration wave data collector, signal amplifier, signal conditioner and data processor in sequence.

[0088] Step 4: Start the vibration information simulation acquisition module: Click the start module of the data processor, and the device starts. The intelligent vibrator knocks on the simulated pipeline to generate a vibration wave signal, which is transmitted to the opening side through the ring mold box and detected by the gecko-wireless vibration sensor.

[0089] Step 5: Start the waveform information intelligent analysis module: The vibration wave data collector receives the vibration wave signal and transmits it to the signal amplifier. After amplifying the weak signal, it enters the signal conditioner. Through the wavelet noise reduction unit and the FastICA clutter suppression filter unit, the primary noise reduction and fine denoising of the multi-vibration source signal can be performed to extract the effective vibration wave signal.

[0090] Step 6: The data processor performs waveform information visualization processing and wave source position inversion.

[0091] Among them, when performing Step 6, it can be achieved through the following specific steps:

[0092] 601. Use the frequency domain analysis technology to perform Fourier transform on the collected vibration wave information to obtain the amplitude value of the vibration signal. The formula is as follows:

[0093]

[0094] Among them, ξ represents frequency, and A p () respectively represent the amplitude and phase functions of the frequency domain signal .

[0095] 602. According to the Fourier transform result in the above formula, further transform the vibration signal into an amplitude-frequency curve, and the approximate direction of the vibration source can be judged according to the appearance of the amplitude-frequency curve.

[0096] 603. Use the time difference positioning technology of the wave source inversion unit. It is known that the installation point coordinates of four groups of gecko-wireless vibration sensors are A(x 1 , y 1 , z 1 ), B(x 2 , y 2 , z 2 ), C(x 3 , y 3 , z 3 ), D(x 4 , y 4 , z 4 ); The coordinates of the vibration wave emission point to be obtained are E(x, y, z). Let the times when the vibration sensors collect the vibration wave be T 1 , T 2 , T 3 ; Based on the 4-point time difference positioning principle, there is

[0097]

[0098] That is:

[0099]

[0100] Wherein:

[0101]

[0102] Where V is the propagation speed of the vibration wave in the annular film box body, and finally solving (x, y, z) can invert the vibration source position and visualize the experimental vibration source information.

[0103] The above are only the preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes, and equivalent structural changes made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A vibration source inversion experimental device based on the characteristics of weak vibration wave signals, characterized in that: It includes vibration information simulation acquisition module and waveform information intelligent analysis module; The vibration information simulation collection module is used to simulate the vibration wave information emitted by trapped personnel hitting the non-uniform medium in the collapsed environment; The waveform information intelligent analysis module is used to accurately filter out clutter and extract effective vibration wave information features in a simulated environment, and then perform a visual inversion of the vibration wave source position.

2. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 1 is characterized in that: The vibration information simulation collection module comprises a ring die box (1), a vibration collector (8) and an intelligent vibrator (6); the vibration sensor collector (8) and the intelligent vibrator (6) are respectively located at two ends of the ring die box (1) to autonomously emit and collect vibration waves.

3. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 2 is characterized in that: The ring die box (1) comprises a box cover (2), a box (3), a simulated pipeline (5) and a complex medium (4), and the simulated pipeline (5) and the complex medium (4) are filled inside the box (3); The simulation pipeline (5) is horizontally placed in the middle of the box (3), and the surrounding of the simulation pipeline (5) is filled with the complex medium (4) required for the experiment; A circular opening is provided on the left wall of the box (3) for exposing one side outlet of the simulated pipeline (5) to the external environment, simulating the wellhead position on the ground in a collapse environment; One end of the simulation pipeline (5) passes through a circular opening provided on the left wall of the box (3) to simulate the rescue position of the ground wellhead rescue personnel in the collapse environment, and the other end is placed at the right end inside the box (3) to simulate the position of the trapped personnel in the well in the collapse environment; The inner walls of the box body (3) that are not open are all provided with sound insulation cotton sheets (7), the inner wall of the box cover (2) is provided with sound insulation cotton sheets (7), and the gap between the box body (3) and the box cover (2) is provided with sound insulation cotton sheets (7).

4. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 3 is characterized in that: The types of simulated pipelines (5) include straight pipelines, bent pipelines, and broken pipelines, which respectively simulate the characteristics of pipelines of various shapes existing in the collapse environment; The types of complex media (4) include soil, concrete, rock and soil, and mixed media, which respectively simulate the environmental characteristics existing in the collapse environment; According to the experimental environment setting requirements, fill the soil, concrete, and rock media respectively to simulate the propagation effect of vibration wave signals under single medium conditions such as soil, concrete, and rock; The mixed medium is soil: concrete: rock soil = 1:1:1 ratio, simulating the propagation effect of vibration wave signals under non-uniform medium conditions; studying the influence of the composition, morphology and structure of the collapsed medium on the vibration wave propagation characteristics; comparing the vibration wave propagation characteristics in single medium and multi-media.

5. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 2 is characterized in that: The vibration collector (8) comprises four groups of gecko-wireless vibration sensors, which are used to be adsorbed on any position of the side wall of the opening of the ring mold box (1); they are powered by a built-in 20000mAH high-density lithium-ion battery and use NB-IOT / Lora / 5G communication methods to collect vibration waves ranging from tens of Hz to 3000 Hz; The gecko-wireless vibration sensor is installed at arbitrary coordinate positions, namely A (x1, y1, z1), B (x2, y2, z2), C (x3, y3, z3), and D (x4, y4, z4); and provides data analysis for subsequent vibration source inversion 4-point time difference positioning.

6. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 1 is characterized in that: The waveform information intelligent analysis module comprises a vibration wave data collector (9), a signal amplifier (10), a signal conditioner (11) and a data processor (14); The vibration wave data collector (9) collects and summarizes the multiple vibration wave signals collected by the vibration collector (8), and then amplifies the weak signals through the signal amplifier (10) and transmits them to the signal conditioner (11); the signal conditioner (11) is connected to the data processor (14).

7. The vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 6 is characterized in that: The signal conditioner (11) comprises a wavelet noise reduction unit (12) and a Fast ICA clutter suppression and filtering unit (13), which are used to realize primary noise reduction and separate fine noise reduction for multiple vibration source signals; The wavelet denoising unit (12) is a primary denoising method for multi-vibration source signals, which removes the wavelet coefficients corresponding to the noise in the 200 Hz-7000 Hz frequency band by establishing a wavelet transform multi-resolution analysis algorithm, retains the wavelet decomposition coefficients of the original signal, and then performs wavelet reconstruction on the processed coefficients to obtain a primary denoised signal; The Fast ICA clutter suppression and filtering unit (13) is a separation fine denoising method, which performs clutter filtering on the obtained primary noise reduction signal. By applying the Fast ICA clutter suppression and filtering unit (13), the observed signal is decomposed into multiple independent components, the components related to the target signal are retained, and the components related to the clutter of 10 Hz-200 Hz are suppressed or filtered out, so as to process the signal with complex background and noise; The data processor (14) comprises a waveform information visualization unit (15) and a wave source inversion unit (16). The waveform information visualization unit (15) converts the vibration signal into an amplitude-frequency curve using a frequency domain analysis technique, and determines the direction of the vibration source according to the appearance of the amplitude-frequency curve. Subsequently, the vibration source is inverted using a time difference determination technique of the wave source inversion unit (16), thereby obtaining the specific position coordinates of the vibration source and realizing wave source information visualization.

8. A method for using a vibration source inversion experimental device based on weak vibration wave signal characteristics according to any one of claims 1 to 7, characterized in that: The method comprises the following steps: Step 1: Filling the ring mold box: Arrange the simulated pipeline (5) in the middle of the box (3), install the intelligent vibrator (6) on the inner side of the vibration end wall of the simulated pipeline (5), fill the surrounding area of ​​the simulated pipeline (5) with the complex medium (4) required for the experiment, and close the box cover (2) after the filling is completed; Step 2: Install the vibration collector (8): install four sets of gecko-wireless vibration sensors at four points on the side wall of the opening of the ring mold box (3), and record the coordinates of the four points with the center of the opening as the axis, so as to carry out subsequent vibration source inversion work; Step 3: Connecting the waveform information intelligent analysis module: connecting the vibration wave data collector (9), the signal amplifier (10), the signal conditioner (11) and the data processor (14) in sequence; Step 4: Start the vibration information simulation acquisition module: Click the start module of the data processor (14), the device starts, the intelligent vibrator 6 knocks the simulated pipeline (5), generates a vibration wave signal, which is transmitted to the opening side through the ring mold box 1 and detected by the gecko-wireless vibration sensor; Step 5: The waveform information intelligent analysis module is started: the vibration wave data collector (9) receives the vibration wave signal and transmits it to the signal amplifier (10). After the weak signal is processed, it enters the signal conditioner 11. After the wavelet noise reduction unit 12 and the Fast ICA clutter suppression and filtering unit (13), the primary noise reduction and separation and fine noise removal of the multi-vibration source signal can be performed to extract the effective vibration wave signal; Step 6: The data processor performs waveform information visualization and wave source position inversion.

9. The method for using the vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 8 is characterized in that: The step five is specifically as follows: 501: The vibration wave data collector (9) receives the vibration wave signal and transmits it to the signal amplifier (10). After the weak signal is subjected to gain processing, it enters the signal conditioner (11). The amplified signal contains a large amount of stray signals and needs to be filtered again; The signal gain processing is realized by a signal amplifier (10), and the output signal in the form of a vibration wave signal is amplified by adjusting the current gain or the voltage gain. The signal amplifier (10) is bidirectional and amplifies the strength of the received and transmitted signals at the same time. After the signal gain processing, it is necessary to filter again. The filtering adopts the mean filtering method, summing up multiple sampling values ​​and taking the average value to eliminate random errors. 502: The wavelet denoising unit (12) is a primary denoising method for multi-vibration source signals by establishing a wavelet transform multi-resolution analysis algorithm; The wavelet coefficients corresponding to the noise in the frequency band of 200 Hz-7000 Hz are removed, the wavelet decomposition coefficients of the original signal are retained, and then the processed coefficients are reconstructed by wavelet to obtain the primary noise reduction signal; 503: Fast ICA clutter suppression filtering unit (13), for separating the fine denoising method, further clutter filtering is performed on the obtained primary denoised signal. The clutter filtering method is to decompose the observed signal into multiple independent components by applying the Fast ICA clutter suppression filtering unit (13), retain the components related to the target signal, suppress or filter out the components related to the clutter of 10 Hz-200 Hz, and process the signal with complex background and noise.

10. The method for using the vibration source inversion experimental device based on the characteristics of weak vibration wave signals according to claim 8 is characterized in that: The step six is ​​specifically as follows: 601: Using frequency domain analysis technology, the collected vibration wave information is Fourier transformed to obtain the secondary value of the vibration signal, which is shown as follows: Where ξ represents the frequency, A p ( ), Represents frequency domain signals The magnitude and phase functions of 602: According to the Fourier transform result in the above formula, the vibration signal is further transformed into an amplitude-frequency curve, and the direction of the vibration source can be determined according to the appearance of the amplitude-frequency curve; 603: Using the time difference positioning technology of the wave source inversion unit, the coordinates of the installation points of the four groups of gecko-wireless vibration sensors are known to be A(x1, y1, z1), B(x2, y2, z2), C(x3, y3, z3), and D(x4, y4, z4); the coordinates of the vibration wave emission point to be determined are E(x, y, z), and the time when the vibration sensor collects the vibration wave is T1, T2, and T3 respectively; based on the principle of 4-point time difference positioning, we have Right now: in: Where V is the propagation speed of the vibration wave in the ring-mode box. The final solution (x, y, z) can be used to invert the vibration source position and visualize the experimental vibration source information.

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