Acoustic-seismic combined monitoring method and device for mountain river bed load

Abstract

The invention relates to an acoustic-seismic combined monitoring method and device for mountain river bed load, and the device comprises a sensing plate which bears the impact of river bed load particles, a seismic detector which collects a vibration signal, and a plurality of microphone elements which independently collect an acoustic signal. The method comprises the following steps of: extracting first-motion waves of a plurality of collected sound signals, passing through the amplitude of each node of a sensing plate, and generating a sound source intensity distribution image, thereby realizing the identification of the spatial position of a bed load on the sensing plate, and calculating a vibration signal wave packet through a system amplitude threshold value; constructing a correlation function to obtain the maximum positive amplitude of a vibration signal wave packet, calculating the particle size of bed load particles, correcting the eccentric error of the vibration signal, improving the recognition precision of the bed load particle size, and further calculating the sediment transport rate in real time. According to the method, the sound signal and the vibration signal are combined, the eccentricity error of the high-frequency geophone signal is recognized and corrected through the spatial position, the recognition precision of the grain size of the bed load is improved through the corrected geophone signal, and inversion calculation of the sediment transport rate is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bed load measurement, in particular to a sound-vibration combined monitoring method and device for bed load of mountain river. BACKGROUND

[0002] The measurement of bed load can be traced back to the early 20th century. The main measurement method is to lay sand collection pool or sampler in the river channel for direct collection and measurement, including pit (slot) method, instrument measurement method, sand wave method, etc. The important value of direct measurement method is that it can provide correction and testing for other methods. However, in the actual measurement process, due to the factors such as riverbed condition, sampler size, sampling time, etc., the direct measurement method is low in efficiency and cannot realize continuous sampling.

[0003] In addition, for mountain rivers with large flow and steep valleys, due to the complexity of water flow conditions and riverbed topography, the installation cost of the sampler is often large, and the bed load sediment transport rate has great spatial and temporal variability in time and space, which brings great challenges to accurately determine the bed load sediment transport volume. Therefore, the monitoring method for indirectly and continuously measuring bed load has gradually developed since the 1980s to the beginning of this century. These methods do not directly sample the bed load, but use different types of sensors to monitor the complex signals generated by the bed load transport process to calculate the bed load sediment transport volume. By monitoring the bed load transport, bed load particle-monitoring system, vibration and acoustic signals generated by the collision of bed load particles and riverbed, the correlation function between these signal characteristic values (such as amplitude, characteristic frequency, power spectral density, etc.) and bed load characteristics is systematically established, which can be used for inversion of bed load sediment transport rate after calibration.

[0004] However, for the calibrated monitoring system, random eccentric impact caused by spatial variability of bed load can still bring more than 50% prediction error. At present, there are few monitoring technologies and equipment that can accurately correct such errors and can operate all-weather and adapt to the complex conditions of mountain rivers. SUMMARY

[0005] The first aspect of the present application aims to solve the technical problem that the predicted bed load particle size and sediment transport rate are not accurate due to the difference in signals caused by the spatial variability of bed load. A sound-vibration combined monitoring method and device for bed load of mountain river are provided, which can measure by combining sound signals and vibration signals, eliminate eccentric vibration errors of bed load impact on the surface of the device, improve the accuracy of particle size identification, and further improve the accuracy of sediment transport rate calculation.

[0006] In order to achieve the above-mentioned purpose, the present application provides a sound-vibration combined monitoring method for bed load of mountain river, comprising the following steps:

[0007] S1, placing a monitoring device on the overflow dam, the monitoring device comprising a sensor plate arranged at the top and an internal seismic detector and a plurality of microphone elements, the sensor plate receiving the impact of the bed load of the mountain river, the seismic detector collecting vibration signals, and each microphone element independently collecting a sound signal sequence;

[0008] S2, picking up the first arrival wave sequence of the sound signal sequence collected by each microphone element through a time-frequency analysis method, calculating the amplitude of each node of the sensor plate based on a sound signal propagation model and a beam forming method, and generating a sound source intensity distribution image, and identifying the spatial position of the bed load on the sensor plate according to the sound source intensity distribution image and the vibration signal intensity;

[0009] S3, calculating the vibration signal wave packet through Hilbert transform combined with a system amplitude threshold, constructing a correlation function of the maximum positive amplitude of the vibration signal wave packet and the particle size of the bed load, and calculating the pulse number of the vibration signal wave packet according to the wave peak of the maximum positive amplitude of the vibration signal wave packet;

[0010] S4, calculating the preliminary particle size of the bed load through the maximum positive amplitude of the vibration signal wave packet, correcting the eccentric error of the vibration signal using the spatial position, and obtaining the final particle size of the bed load;

[0011] S5, based on the pulse number of the monitoring vibration signal wave packet, real-time calculating the sediment discharge rate.

[0012] Preferably, step S2 comprises S21, picking up the first arrival wave sequence of the sound signal sequence collected by each microphone element in the monitoring device, calculating the Fourier transform of the first arrival wave sequence to obtain a seismic source detection signal m, and the calculation formula is:

[0013] m=[m1(f),...,m N (f)] T (1)

[0014] Wherein, m i (f) is a component of N-dimensional vector m obtained by fast Fourier transform (FFT) of the sound signal; i=1,…,N; N is the number of microphone elements; [...] T represents matrix transposition;

[0015] S22, building a sound signal propagation model at the position of the microphone element, scanning an assumed sound source at any node of the plane where the sensor plate is located in the monitoring device, the unit intensity of the assumed sound source being 1, and the sound signal amplitude at the microphone element caused by the assumed sound source with unit intensity being s k,l :

[0016]

[0017] Wherein, x l is the coordinate vector of the microphone element l; ξ kis the coordinate vector of node k in the scanning plane; c is the sound velocity of the propagation medium; i is the imaginary unit, i 2 = -1.

[0018] S23, calculating the real impact vibration sound source amplitude A of the moving mass particle according to the seismic source detection signal and the sound signal amplitude s , and the specific calculation is as follows:

[0019]

[0020] wherein m is the seismic source detection signal; s is the sound signal amplitude at the microphone element; ||s|| is the matrix of multiple microphone elements; s * is the complex conjugate of s.

[0021] S24, sequentially scanning each node on the sensing plate and calculating the amplitude at any grid node to obtain a sound source intensity distribution image.

[0022] Preferably, the specific calculation method in S3 is as follows:

[0023] S31, performing Hilbert transform on the vibration signal S(t) to obtain and combining the system threshold value, so that the input moving mass vibration signal forms a respective independent vibration signal wave packet;

[0024] S32, calculating and monitoring the maximum positive amplitude of the vibration signal wave packet, and constructing the vibration signal wave packet maximum positive amplitude and moving mass particle size correlation function as follows:

[0025]

[0026] wherein, is the mean value of the monitored vibration signal wave packet maximum positive amplitude, and is D is the test moving mass particle size in the known calibration range; and α and β are two calibration coefficients calibrated by a large number of tests or field monitoring data;

[0027] S33, using the partial peak value calculation method to count the wave peaks of the maximum positive amplitude of the vibration signal, and defining each peak value as an effective pulse combined with the system threshold value, to obtain the pulse number I of any vibration signal wave packet, and the specific calculation is as follows:

[0028] I = k b M t (5)

[0029] wherein, k b is the correlation coefficient, and for a certain moving mass particle size component j, its value is k b,j ; M t is the moving mass sediment discharge in a certain period of time, and for a certain component j, its value is M t,j .

[0030] The specific calculation method of S4 is preferably as follows:

[0031] The preliminary particle size D0 is obtained by combining the S32 correlation function with the average of the maximum positive amplitude of the monitored vibration signal wave packet, and the specific calculation is as follows:

[0032]

[0033] In the formula, A Max is the average of the maximum positive amplitude of the monitored vibration signal wave packet; and α and β are two calibration coefficients calibrated by a large number of tests or field monitoring data;

[0034] The particle size of the moving mass is calculated by monitoring the amplitude of the vibration signal wave packet, the eccentric error of the vibration signal is corrected by combining the spatial position inversion coordinates, and the monitoring precision of the moving mass particle size is improved, and the specific calculation is as follows:

[0035]

[0036] In the formula, D E,j is the particle size of the moving mass of the group j after correction by monitoring signal inversion calculation and considering the eccentric distance; α C is the calibrated coefficient after correction, and satisfies: lgα C =a1d e +b1; β C is another calibrated coefficient after correction, and satisfies: lgβ C =a2d e +b2; d e is the eccentric distance, which is determined by the center coordinates of the sound source image inverted from the sound signal sequence.

[0037] The specific calculation method of S5 is preferably as follows:

[0038] The moving mass group sand transport volume is calculated by monitoring the pulse number of the vibration signal wave packet:

[0039]

[0040] In the formula, M t,j is the value of a certain group j; k b,j is the value of a certain moving mass particle size group j; and I j is the pulse number of a certain group j of moving mass.

[0041] The preferred device for monitoring the bed load of mountain rivers by combining acoustic shock comprises a monitoring body, a sensing plate, a geophone and a microphone element arranged on the monitoring body, the top end of the monitoring body is open, the sensing plate is installed at the top end opening of the monitoring body, the sensing plate and the monitoring body form a working chamber, the geophone is installed at the center of the bottom surface of the sensing plate, and the microphone element is installed at the bottom of the working chamber.

[0042] In order to make the impact identified by the sensing plate be buffered and the working chamber be sealed. Preferably, an ultra-elastic buffer pad is arranged between the monitoring body and the sensing plate, the monitoring body comprises a high-strength angle steel frame arranged around the inner wall, the ultra-elastic buffer pad is arranged above the angle steel frame, and the sensing plate is connected with the angle steel frame through fastening bolts; the ultra-elastic buffer pad adopts an annular structure. The sensing plate and the ultra-elastic buffer pad are installed on the angle steel frame in the monitoring body through the fastening bolts, which can not only provide stable support and sealing, but also form a buffering effect, thereby reducing the damage of river water invasion to the electrical devices inside the monitoring body and the damage of water flow pressure to the inner wall of the monitoring body.

[0043] Preferably, the microphone elements are uniformly arranged in an array at the bottom of the working chamber, and the plurality of microphone elements independently collect acoustic signals.

[0044] Preferably, the monitoring body is installed on the overflow section of the reinforced concrete overflow dam, and the top of the sensing plate, the overflow section and the riverbed are located on the same horizontal plane.

[0045] The beneficial effects of the present application are as follows:

[0046] By combining the acoustic signal and the vibration signal, when the geophone collects the vibration signal propagated, each microphone element independently collects the acoustic signal inside the monitoring device, the spatial position of the bed load can be identified through the beam forming algorithm, the eccentric error of the high-frequency geophone signal is corrected by combining the microphone array signal and the high-frequency geophone signal through the spatial position identification, the identification accuracy of the bed load particle size is improved through the corrected geophone signal, and the sand transport rate inversion calculation is further realized by combining the time parameter. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The figure is a structural schematic diagram of the present application.

[0048] Figure 2 The figure is a structural cross-sectional view of the present application.

[0049] Figure 3 The figure is a local enlarged view of the structure of the present application.

[0050] Figure 4 The figure is a use effect diagram of the present application.

[0051] The reference signs include: 1, monitoring body; 2, sensing plate; 3, geophone; 4, microphone element; 5, angle steel frame; 6, super-elastic buffer pad; 7, fastening bolt; 8, reinforced concrete overflow dam; 9, flow cross section. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments clearer, the present application is further described in detail below in combination with the drawings and embodiments. When the following description relates to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementation manners described in the following exemplary embodiments do not represent all the implementation manners consistent with the present disclosure. Instead, they are only examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0053] In the present disclosure, the orientation words such as "inner" and "outer" are defined according to the contour of the corresponding parts themselves unless otherwise stated. The terms such as "first", "second" and the like used in the present disclosure are used to distinguish one element from another element, and do not have sequentiality and importance.

[0054] Embodiment 1

[0055] S1, placing a monitoring device on the overflow dam, the monitoring device comprising a sensing plate arranged on the top and a geophone and a plurality of microphone elements inside, the sensing plate receiving the impact of the bed load of the mountain river, the geophone collecting vibration signals, and each microphone element independently collecting a sound signal sequence;

[0056] S2, picking up the first arrival wave sequence of the sound signal sequence collected by each microphone element through a time-frequency analysis method, calculating the amplitudes of each node of the sensing plate based on a signal propagation model and a beam forming method and generating a sound source intensity distribution image, and identifying the spatial position of the bed load on the sensing plate according to the sound source intensity distribution image and the vibration signal intensity;

[0057] S3, calculating the vibration signal wave packet by Hilbert transform combined with a system amplitude threshold, constructing a correlation function of the maximum positive amplitude of the vibration signal wave packet and the particle size of the bed load, and calculating the pulse number of the vibration signal wave packet according to the wave peak of the maximum positive amplitude of the vibration signal wave packet;

[0058] S4, calculating the preliminary particle size of the bed load through the maximum positive amplitude of the vibration signal wave packet, correcting the eccentric error of the vibration signal using the spatial position, and obtaining the final particle size of the bed load;

[0059] S5, calculating the sediment discharge rate in real time based on the pulse number of the monitoring vibration signal wave packet.

[0060] The seismic detector in the embodiment collects high-frequency vibration signals, and the recognizable vibration signal frequency range is above 1 Hz, that is, the vibration signal with a frequency greater than 1 Hz can be effectively collected.

[0061] The sensing plate in the embodiment extracts the intersection points of the grids as the collected nodes by uniformly dividing the grids, and the density of the grids can be self-defined to adjust the number and accuracy of the nodes.

[0062] The system threshold is the noise that can be monitored, and the noise level needs to be detected before monitoring, the effective signal needs to be extracted for operation, and the noise needs to be eliminated. The system threshold detected in the embodiment is a value that can be effectively recognized beyond the noise level, which is 5-10 times the noise, 0.02-0.1 decibel, and the optimal value in the embodiment is 0.02 decibel.

[0063] Preferably, the specific steps in S2 are:

[0064] Step S2 includes S21, picking up the first arrival wave sequence of the sound signal sequence collected by each microphone element in the monitoring device, calculating the Fourier transform of the first arrival wave sequence to obtain a source detection signal m, and the calculation formula is:

[0065] m=[m1(f),...,m N (f)] T (1)

[0066] Wherein, m i (f) is a component of an N-dimensional vector m obtained by fast Fourier transform (FFT) of the sound signal; i=1,…,N; N is the number of microphone elements; [...] T represents matrix transposition;

[0067] S22, building an acoustic signal propagation model at the position of the microphone element, scanning the hypothetical sound source of any node on the plane where the sensing plate is located in the monitoring device, the unit intensity of the hypothetical sound source is 1, and the sound signal amplitude at the microphone element caused by the unit intensity of the hypothetical sound source is s k,l :

[0068]

[0069] Wherein, x l is the coordinate vector of the microphone element l; ξ k is the coordinate vector of the node k on the scanning plane; c is the sound speed of the propagation medium; i is an imaginary number, i 2 =-1;

[0070] Specifically, formula (2) can be obtained by and , and Δt k,j is the signal time delay.

[0071] S23, calculating the real impact shock vibration sound source amplitude A of the granular particles of the push-movement substance according to the seismic source detection signal and the sound signal amplitude s , and the specific calculation is as follows:

[0072]

[0073] Wherein, m is the seismic source detection signal; s is the sound signal amplitude at the microphone element; ||s|| is the matrix of multiple microphone elements; s * is the complex conjugate of s.

[0074] S24, sequentially scanning each node on the sensing plate and calculating the amplitude at any grid node to obtain a sound source intensity distribution image.

[0075] Preferably, the specific calculation method in S3 is:

[0076] S31, performing Hilbert transform on the vibration signal S(t) to obtain and combining the system threshold, so that the input push-movement substance vibration signal forms a respective independent vibration signal wave packet;

[0077] S32, calculating and monitoring the maximum positive amplitude of the vibration signal wave packet, and constructing the vibration signal wave packet maximum positive amplitude and push-movement substance particle size correlation function as follows:

[0078]

[0079] In the formula, is the mean value of the monitored vibration signal wave packet maximum positive amplitude, and is D is the test push-movement substance particle size in the known calibration range; and α and β are two calibration coefficients, which are calibrated by a large number of tests or field monitoring data;

[0080] Wherein, The maximum positive amplitude of the vibration signal wave packet in a single impact event is obtained by multiple sampling and then averaging.

[0081] S33, using a partial peak value calculation method to count the wave peaks of the maximum positive amplitude of the vibration signal, and defining each peak value as an effective pulse combined with the system threshold, to obtain the pulse number I of any vibration signal wave packet, and the specific calculation is as follows:

[0082] I=k b M t (5)

[0083] In the formula, k b is the correlation coefficient, and for a push-movement substance particle size component j, its value is k b,j ; M tThe value of the bed load sediment transport volume for a certain component j for a certain period of time is M t,j .

[0084] Preferably, the specific calculation method of S4 is as follows:

[0085] The preliminary particle size D0 is obtained by combining the S32 correlation function with the average value of the maximum positive amplitude of the monitored vibration signal wave packet, and the specific calculation is as follows:

[0086]

[0087] In the formula, A Max is the average value of the maximum positive amplitude of the monitored vibration signal wave packet; and α and β are two calibration coefficients calibrated by a large number of tests or field monitoring data;

[0088] The bed load particle size is calculated by monitoring the vibration signal wave packet amplitude, the eccentric error of the vibration signal is corrected by combining the spatial position inversion coordinates, the bed load particle size monitoring precision is improved, and the specific calculation is as follows:

[0089]

[0090] In the formula, D E,j is the grouped bed load particle size of component j calculated by monitoring the signal inversion and considering the eccentric distance correction; α C is the calibrated coefficient after correction, which satisfies: lgα C =a1d e +b1; β C is another calibrated coefficient after correction, which satisfies: lgβ C =a2d e +b2; d e is the eccentric distance determined by the center coordinates of the sound source image inverted from the sound signal sequence.

[0091] Preferably, the specific calculation method of S5 is as follows:

[0092] The bed load group sediment transport volume is calculated by monitoring the pulse number of the vibration signal wave packet:

[0093]

[0094] In the formula, M t,j is the value of a certain component j; k b,j is the value of a certain bed load particle size component j; and I j is the pulse number of a certain component j of the bed load.

[0095] Specifically, by grouping the continuous particle size after dispersion, for example, grouping each component j according to 10mm, 20mm, 30mm, 50mm, according to formula (4) in step S32, the monitored vibration signal wave packet maximum positive amplitude and the constructed correlation function are used to calibrate the particle size of the bedload.

[0096] After the sensing plate 2 is impacted by the river bedload particles, the seismic detector collects the vibration signals transmitted, each microphone element independently collects the acoustic signals inside the monitoring device, and the spatial position of the bedload is identified through the beamforming algorithm. Combined with the microphone array signal and the high-frequency seismic detector signal, the eccentric error of the high-frequency seismic detector signal is corrected through the spatial position identification, and the identification accuracy of the bedload particle size is improved through the corrected detector signal. The device can realize long-term, continuous and high-precision monitoring of the mountain river bedload, and the cost is controllable, and is suitable for popularization and use.

[0097] Embodiment 2

[0098] As shown in Figures 1-4 The present application also provides an acoustic and seismic combined monitoring device for mountain river bedload, which comprises a monitoring body 1, a sensing plate 2, a seismic detector 3 and a microphone element 4 arranged on the monitoring body 1. The top end of the monitoring body 1 is open, the sensing plate 2 is installed at the top end opening of the monitoring body 1, the sensing plate 2 and the monitoring body 1 form a working chamber, the seismic detector 3 is installed at the center position of the lower bottom surface of the sensing plate 2, and the microphone element 4 is installed on the bottom plate of the working chamber.

[0099] In order to buffer the impact identified by the sensing plate 2 and seal the working chamber, an ultra-elastic buffer pad 6 is arranged between the monitoring body 1 and the sensing plate 2. The monitoring body 1 comprises an angle steel frame 5 arranged around the inner wall, the ultra-elastic buffer pad 6 is arranged above the angle steel frame 5, and the sensing plate 2 is connected with the angle steel frame 5 through a fastening bolt 7. The ultra-elastic buffer pad 6 adopts an annular structure.

[0100] The sensing plate 2 and the ultra-elastic buffer pad 6 are installed on the angle steel frame 5 in the monitoring body 1 through the fastening bolt 7, which can not only provide stable support and sealing, but also form a buffering effect, reduce the damage of river water invasion to the electrical devices inside the monitoring body 1 and the damage of water pressure to the inner wall of the monitoring body 1.

[0101] In order to make the connection of the fastening bolt 7 tight and stable, the pre-tightening torque of the fastening bolt 7 is not less than 12N·m, and the outer steel frame of the monitoring body 1 is made of high-strength low-carbon steel with a yield strength of not less than 235MPa, a thickness of 10mm and air and water tightness.

[0102] The angle steel frame 5 is an equilateral angle steel in a ring shape, and the length of the contact edge with the inner wall of the monitoring body 1 is not less than 50 mm, and the thickness is not less than 6 mm.

[0103] The microphone elements 4 are uniformly arranged at the bottom of the working chamber, and multiple microphone elements 4 independently collect sound signals.

[0104] Four microphone elements 4 are arranged in the embodiment, which are uniformly and symmetrically arranged at the bottom plates of the opposite working chambers of the geophone 3. The actual number of the microphone elements 4 can be flexibly adjusted according to the actual measurement situation.

[0105] The monitoring body 1 is installed on the flow section 9 of the reinforced concrete overflow dam 8, the reinforced concrete overflow dam 8 is poured with impact-resistant and wear-resistant fiber concrete, the top of the sensing plate 2, the flow section 9 and the riverbed are located on the same horizontal plane.

[0106] The data transmission lines are connected to the geophone 3 and the microphone elements 4, and the data transmission lines pass through the monitoring body 1 and are connected to the external signal processor.

[0107] The above is only an embodiment of the present application, and the specific structure and characteristics of the scheme are not described in detail. It should be pointed out that for those skilled in the art, without departing from the structure of the present application, a number of modifications and improvements can be made, which should be regarded as the protection scope of the present application, and these will not affect the effect and practicality of the present application. The protection scope of the present application should be subject to the content of its claims, and the specific implementation mode and the like in the specification can be used to explain the content of the claims.

Claims

1. A method for combined acoustic and seismic monitoring of bed load in mountain rivers, characterized in that: The method comprises the following steps: S1, placing a monitoring device on the overflow dam, the monitoring device comprising a sensing plate arranged on the top and an internal seismic detector and a plurality of microphone elements, the sensing plate receiving the impact of the bed load of the mountain river, the seismic detector collecting vibration signals, and each microphone element independently collecting a sound signal sequence; S2, picking up the first arrival wave sequence of each sound signal sequence by a time-frequency analysis method, calculating the amplitude of each node of the sensing plate based on a sound signal propagation model and a beam forming method, and generating a sound source intensity distribution image, and identifying the spatial position of the bed load on the sensing plate according to the sound source intensity distribution image and the vibration signal intensity; S3, calculating the vibration signal wave packet by Hilbert transform combined with a system amplitude threshold, constructing a correlation function of the maximum positive amplitude of the vibration signal wave packet and the particle size of the bed load, and calculating the pulse number of the vibration signal wave packet according to the wave peak of the maximum positive amplitude of the vibration signal wave packet; S4, calculating the preliminary particle size of the bed load by the maximum positive amplitude of the vibration signal wave packet, correcting the eccentric error of the vibration signal by using the spatial position, and obtaining the final particle size of the bed load; S5, calculating the sediment discharge rate in real time based on the pulse number of the monitoring vibration signal wave packet.

2. The method according to claim 1, wherein the method is characterized in that: Step S2 comprises: m = [m1(f),...,m N (f)] T (1) where m i (f) is a component of an N-dimensional vector m obtained by a Fast Fourier Transform (FFT) of the acoustic signal; i = 1,..., N; N is the number of microphone elements; [...] T denotes the matrix transpose; S22, a sound signal propagation model at the position of the microphone element is built, the sound signal propagation model including a hypothetical sound source at any node of the plane where the sensing panel is located in the scanning monitoring device, the unit intensity of the hypothetical sound source being 1, and the sound signal amplitude at the microphone element caused by the hypothetical sound source with the unit intensity being s k,l : where x l is the coordinate vector of the microphone element l; ξ k is the coordinate vector of the node k on the scan plane; c is the sound speed of the propagation medium; i is the imaginary unit, i 2 = -1. S23, calculating the real impact shock vibration sound source amplitude A of the granular plutos according to the seismic source detection signal and the sound signal amplitude s The specific calculation is as follows: where m is the source detection signal; s is the acoustic signal amplitude at the microphone element; ||s|| is the matrix of the plurality of microphone elements; s * is the complex conjugate of s. S21, picking up the first arrival wave sequence of the sound signal sequence collected by each microphone element in the monitoring device, calculating the Fourier transform of the first arrival wave sequence, and obtaining a seismic source detection signal m, the calculation formula being:

3. The method according to claim 1, wherein the method is characterized in that: S24, sequentially scanning each node on the sensing plate, and calculating the amplitude at any grid node to obtain a sound source intensity distribution image. S31, the Hilbert transform is carried out to the vibration signal S (t) to obtain And combined with the system threshold, so that the input pushover vibration signal forms a respective independent vibration signal wave packet; The specific calculation method in S3 is: In the formula, The mean value of the maximum positive amplitude of the wave packet of the vibration signal is monitored, and the mean value of the maximum positive amplitude of the wave packet of the vibration signal is monitored. D is the test push plasmid diameter in the known calibration range; and α and β are two calibration coefficients calibrated by a large number of tests or field monitoring data. S32, calculating and monitoring the maximum positive amplitude of the vibration signal wave packet, and constructing a correlation function of the maximum positive amplitude of the vibration signal wave packet and the particle size of the bed load as follows: I = k b M t (5) In the formula, k b The correlation coefficient is k; for a certain drifting particle size fraction j, its value is k. b,j M t This refers to the amount of bedload sediment transported over a certain period of time.

4. The method according to claim 1, wherein the method is characterized in that: S33, using a partial peak value calculation method to count the wave peak of the maximum positive amplitude of the vibration signal, defining each peak value as an effective pulse combined with a system threshold, obtaining the pulse number I of any vibration signal wave packet, and the specific calculation being as follows: The specific calculation method of S4 is: In the formula, A Max The mean value of the maximum positive amplitude of the wave packet of the vibration signal is monitored; and α and β are two calibration coefficients calibrated by a large number of tests or field monitoring data. Obtaining the preliminary particle size D0 by the correlation function of S32 combined with the mean value of the maximum positive amplitude of the monitoring vibration signal wave packet, and the specific calculation being as follows: where D E,j is the calculated and corrected size of the group of particles of component j by inversion of the monitoring signal; a C is the calibrated coefficient after correction, which satisfies: lg a C = a1d e + b1; β C is another calibrated coefficient after correction, which satisfies: lg β C = a2d e + b2; d e is the eccentricity, which is determined by the center coordinates of the acoustic source image inverted from the acoustic signal sequence.

5. The method according to claim 1, wherein the method is characterized by: Calculating the particle size of the bed load by monitoring the amplitude of the vibration signal wave packet, correcting the eccentric error of the vibration signal by combining the spatial position inversion coordinates, and improving the monitoring precision of the particle size of the bed load, and the specific calculation being as follows: The specific calculation method of S5 is: where M t,j is the bed load transport of a certain bed load grain size fraction j; k b,j is the value of a certain bed load grain size fraction j; I j is the number of pulses of a certain fraction j of bed load.

6. A sound-vibration combined monitoring device for bed load of mountain rivers, for implementing the sound-vibration combined monitoring method for bed load of mountain rivers according to any one of claims 1-5, characterized in that: Calculating the sediment discharge of the bed load group by monitoring the pulse number of the vibration signal wave packet:

7. The acoustic shock combined monitoring device for bed load of mountain river according to claim 6, characterized in that: The monitoring body, the sensing plate, the seismic detector, and the microphone element are arranged on the monitoring body, the top end of the monitoring body is open, the sensing plate is installed at the top end opening of the monitoring body, the sensing plate and the monitoring body form a working chamber, the seismic detector is installed at the center of the bottom surface of the sensing plate, and the microphone element is installed at the bottom of the working chamber. An ultra-elastic buffer pad is arranged between the monitoring body and the sensing plate, the monitoring body comprises an angle steel frame arranged around the inner wall, the ultra-elastic buffer pad is arranged above the angle steel frame, and the sensing plate is connected with the angle steel frame through fastening bolts; the ultra-elastic buffer pad adopts a ring structure.

8. The acoustic shock combined monitoring device for bed load of mountain river according to claim 6, characterized in that: The microphone elements are evenly arranged at the bottom of the working chamber, and multiple microphone elements independently collect sound signals.

9. The acoustic shock combined monitoring device for bed load of mountain river according to claim 6, characterized in that: The monitoring body is installed on the flow section of the reinforced concrete overflow dam, and the top of the sensing plate, the flow section and the riverbed are located on the same horizontal plane.

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