Testing device based on sound wave sensing and pipeline blockage position determining method

Abstract

The invention discloses a test device based on sound wave sensing and a pipeline blockage position determination method, and aims to solve the problems of large sound wave detection blind area, multi-parameter splitting and the like in an existing test room filling and pipe blockage simulation test. The invention provides a laboratory simulation test device and method for filling and pipe plugging multi-parameter correlation analysis based on distributed optical fiber acoustic sensing. According to the device, sound wave generation and propagation of filling slurry under the real filling pipe conveying working condition are simulated, and the distributed sound wave sensing technology is combined, so that accurate recognition of the mine filling body pipe blocking area is achieved. According to the invention, the simulation of filling and pipe plugging in the laboratory is upgraded from'discrete parameter static monitoring 'to a'global sound field reconstruction-multi-parameter correlation diagnosis' closed-loop test system, the prediction accuracy of filling and pipe plugging is remarkably improved, and a high-reliability laboratory support platform is provided for research and development of a filling and pipe plugging prevention and control technology.

Description

Technical Field

[0001] This invention belongs to the field of safety monitoring technology for mine backfilling pipelines, specifically relating to a test device based on acoustic wave sensing and a method for determining the location of pipeline blockage. Background Technology

[0002] Blockage in filling pipelines is a bottleneck restricting the efficiency of solid waste disposal in mines. The resulting slurry flow turbulence and pressure imbalance seriously threaten the safe operation of the filling system. Existing laboratory monitoring methods for filling slurry pipeline transportation mostly rely on discrete sensors to construct the test system and static threshold-triggered alarm devices. This results in inaccurate prediction of blockage location and insufficient detection and early warning timeliness when extrapolating test results to engineering practice.

[0003] Currently, there are two major problems with laboratory filling pipe blockage control technology: First, the sensor network topology is discretized, and the acoustic signal acquisition only covers a limited number of monitoring points, making it impossible to construct the frequency-division energy distribution across the entire filling pipe, resulting in insufficient accuracy in tracing abnormal signals; Second, the test devices mostly use independent parameter control, and acoustic, mechanical, and rheological data lack fusion analysis, making it difficult to determine the blockage point of the filling pipe through multi-parameter correlation inversion, resulting in insufficient accuracy in locating the blockage point and inaccurate prediction. Summary of the Invention

[0004] The purpose of this invention is to provide a test device and a method for determining the location of pipe blockage based on acoustic wave sensing, so as to solve the problems of insufficient accuracy in locating blockage points in filled pipes and inadequate prediction accuracy in the existing technology.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] An acoustic wave sensing-based test device includes a circulating filling pipe, a filling device, a simulated pipe block, a fiber optic acoustic monitoring device, multiple pressure sensors, and a data processing module.

[0007] The simulated pipe block can be placed at any position inside the circulating filling pipe; the circulating filling pipe is also equipped with at least one discharge valve;

[0008] The filling device includes a hopper and a filling pump. The hopper is equipped with a stirrer. The hopper can hold slurry. The output end of the hopper is connected to the input end of the filling pump. The output end of the filling pump is connected to a circulating filling pipeline.

[0009] The fiber optic acoustic monitoring device is used to detect the acoustic wave signal generated by the vibration of the simulated pipe block and input the acoustic wave signal into the data processing module.

[0010] The pressure sensor is used to detect the pressure signal of the circulating filling pipe and input the pressure signal into the data processing module.

[0011] The data processing module is used for:

[0012] Receive sound wave signals and extract frequency-division energy data and sound pressure data from the sound wave signals;

[0013] The deformation amount at the corresponding position of the cyclic filling pipe is determined based on the sound pressure data;

[0014] Receive pressure signals and determine the slurry flow rate at the corresponding position in the circulating filling pipeline based on the pressure signals;

[0015] The actual location of the simulated blockage is determined based on the frequency division energy data, deformation, and slurry flow rate.

[0016] The present invention also has the following features:

[0017] Furthermore, the fiber optic acoustic monitoring device includes an optical pulse generation module, an optical quantity detection module, a single-mode armored optical cable, and a circulator;

[0018] The single-mode armored optical cable is installed inside the circulating filling pipe;

[0019] The optical pulse generation module includes a narrow linewidth laser, an optical fiber coupler, an acousto-optic modulator, and an erbium-doped fiber amplifier.

[0020] The light intensity detection module includes a polarization diversity receiver and a photodetector;

[0021] The first output terminal of the fiber coupler is connected to the input terminal of the polarization diversity receiver, and the second output terminal is connected to the input terminal of the acousto-optic modulator; the output terminal of the acousto-optic modulator is connected to the input terminal of the erbium-doped fiber amplifier.

[0022] The output end of the erbium-doped fiber amplifier is connected to the first end of the circulator, the second end of the circulator is connected to the single-mode armored optical cable, and the third end of the circulator is connected to the input end of the polarization diversity receiver of the optical quantity detection module.

[0023] The output of the polarization diversity receiver is connected to the input of the photodetector;

[0024] The output terminal of the photodetector is connected to the data processing module.

[0025] Furthermore, the data processing module includes: three SRAM interfaces, an acoustic wave acquisition control module, a pressure sensor A / D acquisition control module, and a controller;

[0026] The input terminal of the acoustic wave acquisition and control module serves as the first input terminal of the data processing module and the output terminal of the photodetector; the two output terminals of the acoustic wave acquisition and control module are respectively connected to the controller through two SRAM interfaces.

[0027] The input terminal of the pressure sensor A / D acquisition and control module is connected to each pressure sensor as the second input terminal of the data processing module; the output terminal of the pressure sensor A / D acquisition and control module is connected to the controller through the SRAM interface.

[0028] Furthermore, the pressure sensor is a corrosion-resistant ceramic piezoresistive sensor;

[0029] The narrow linewidth laser mentioned above is UNL-1550-3-20;

[0030] The fiber optic coupler mentioned above is a YG-WBC;

[0031] The aforementioned acousto-optic modulator is AOM-1550-80-A;

[0032] The erbium-doped fiber amplifier mentioned above uses GY-EDFA-PL;

[0033] The SRAM interface mentioned above uses CY7C1049CV33;

[0034] The circulator described above uses YG-FCIR;

[0035] The polarization diversity receiver described above uses PMFC;

[0036] The photodetector mentioned is a DAS-BPD-200M.

[0037] Furthermore, a single-mode armored optical cable is laid inside the circulating filling pipe along its central axis directly above it, and is fixed with pre-tension clamps at 1.0m intervals.

[0038] Furthermore, it also includes an amplification circuit for the sound wave acquisition module and an amplification circuit for the pressure acquisition module;

[0039] The output terminal of the photodetector is connected to the first input terminal of the data processing module through the amplification circuit of the acoustic wave acquisition module;

[0040] Each of the pressure sensors is connected to the second input terminal of the data processing module via a pressure acquisition and amplification circuit.

[0041] A method for determining the location of pipe blockage based on acoustic wave sensing, the method being based on the aforementioned acoustic wave sensing-based experimental device, wherein the data processing module determines the actual location of the simulated pipe blockage through the following steps:

[0042] Step 1: The acoustic wave acquisition and control module extracts the acoustic wave frequency division energy data and sound pressure data from the acoustic wave signal and transmits them to the controller through two SRAM interfaces respectively.

[0043] Step 2: The controller uses the least squares method to preprocess the sound wave frequency division energy data, minimizing the historical weighted sum of the sound wave data to obtain the preprocessed sound wave frequency division energy data.

[0044] Step 3: The controller decomposes the preprocessed acoustic wave frequency division energy data to obtain multi-layer acoustic wave frequency division energy data; calculates the power spectral density of the low-frequency approximation coefficient and high-frequency detail coefficient of each layer of acoustic wave frequency division energy data to determine the energy peak value;

[0045] Step 4: The controller determines the strain amplitude based on the sound pressure data, and then determines the pipe deformation at various points in the cyclic filling pipe based on the strain amplitude.

[0046] Step 5: Calculate the fluid velocity at each pressure sensor based on the pressure detected at that location, and determine the actual location of the simulated blockage based on the frequency division energy data, sound pressure data, and slurry flow rate.

[0047] Furthermore, step 3 includes the following sub-steps:

[0048] Step 31: Based on Parseval's theorem, calculate the power spectral density of the preprocessed acoustic wave frequency-division energy data using the following formula:

[0049]

[0050] Where Z represents the characteristic impedance of the dielectric;

[0051] P represents sound pressure level;

[0052] P(t) represents the time-domain signal of the acoustic wave signal;

[0053] |P(f)| 2 Indicates power spectral density;

[0054] t represents time;

[0055] Step 32: Decompose the acoustic wave frequency division energy data according to equal frequency band bandwidth or use wavelet basis to decompose the acoustic wave frequency division energy data to obtain M layers of acoustic wave frequency division energy data, denoted as [f low,i f high,i ];

[0056] f low,i The acoustic frequency division energy data represents the low-frequency approximation coefficients of the i-th layer acoustic frequency division energy data;

[0057] f high,i The acoustic frequency division energy data represents the high-frequency detail coefficients of the i-th layer acoustic frequency division energy data;

[0058] i represents the layer number, i = 1, 2, ..., M;

[0059] Step 33: Using the following formula, calculate the power spectral density of the low-frequency approximation coefficient and high-frequency detail coefficient of the acoustic wave frequency division energy data for each layer; thereby determining the energy peak value of the acoustic wave frequency division energy data for each layer.

[0060]

[0061] Among them, E i Indicates power spectral density;

[0062] Δf represents the frequency interval;

[0063] f low Indicates the low-frequency approximation coefficient;

[0064] f high This represents the high-frequency detail coefficient.

[0065] Furthermore, step 4 includes the following sub-steps:

[0066] Step 41, calculate the bulk modulus using the following formula:

[0067] K = ρc 2

[0068] Where K represents the bulk modulus of the filling slurry;

[0069] ρ represents the density of the slurry;

[0070] c represents the speed of sound waves;

[0071] Step 42, based on the sound pressure amplitude P, calculate the strain amplitude ε using the following formula:

[0072] ε=P / ρc 2

[0073] Step 43: Calculate the pipe deformation at various points in the cyclic filling pipe using the following formula;

[0074] ε=△L / L

[0075] Where △L represents the amount of pipe deformation;

[0076] L represents the circumference of the inner wall of the cyclic filling pipe.

[0077] Furthermore, step 5 includes the following sub-steps:

[0078] Step 51, use the following formula to calculate the slurry flow velocity v at each pressure sensor:

[0079]

[0080] Where p represents the slurry pressure, in Pa;

[0081] ρ represents the density of the slurry, kg / m³3 ;

[0082] g represents gravitational acceleration;

[0083] C is a constant;

[0084] z represents the liquid level height of the slurry in the circulating filling pipe;

[0085] Step 52: Determine the actual location of the simulated blockage according to the weighting coefficients of the frequency division energy data, pipeline deformation, and slurry flow velocity.

[0086] Compared with the prior art, the present invention has the following technical effects:

[0087] This invention relates to a test device and method for determining the location of pipe blockage based on acoustic wave sensing. Addressing the problems of large acoustic wave detection blind spots and fragmented multi-parameter analysis in existing laboratory filling and pipe blockage simulation tests, this invention proposes a laboratory simulation test device and method based on distributed fiber optic acoustic sensing and multi-parameter correlation analysis for filling and pipe blockage. This device simulates the generation and propagation of acoustic waves in real filling and pipeline transportation conditions using filling slurry, and combines this with distributed acoustic wave sensing technology to achieve accurate identification of the blockage area in the mine filling body. This invention upgrades laboratory filling and pipe blockage simulation from "discrete parameter static monitoring" to a closed-loop test system of "global sound field reconstruction - multi-parameter correlation diagnosis," significantly improving the prediction accuracy of filling and pipe blockage and providing a high-reliability laboratory support platform for the research and development of filling and pipe blockage prevention and control technologies. Attached Figure Description

[0088] Figure 1 This is a schematic diagram of the pipe blockage detection simulation test device based on acoustic wave sensing of the present invention;

[0089] Figure 2 This is a schematic diagram of the fiber optic acoustic monitoring device of the present invention;

[0090] Figure 3 This is a flowchart of the method for determining the location of pipe blockage based on acoustic wave sensing according to the present invention;

[0091] Figure 4 This is a simulation diagram of the frequency division energy in step 3 of one embodiment of the present invention;

[0092] Figure 5 This is a diagram of pipe deformation in step 4 of one embodiment of the present invention;

[0093] Figure 6 This is a slurry flow rate diagram for step 5 in one embodiment of the present invention;

[0094] Figure 7 This is a schematic diagram of the simulated pipe-blocking block in the circulating filling pipe in this invention. Detailed Implementation

[0095] It should be noted that, unless otherwise specified, all components in this invention are components known in the prior art.

[0096] The following are specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments. All equivalent modifications made based on the technical solutions of this application fall within the protection scope of the present invention.

[0097] like Figure 1-3 As shown in Figure 7, a test device based on acoustic wave sensing includes a circulating filling pipe, a filling device, a simulated pipe block, a fiber optic acoustic monitoring device, multiple pressure sensors, and a data processing module.

[0098] Simulated plugging blocks can be placed at any position within the circulating filling pipe;

[0099] The filling device includes a hopper and a filling pump. The hopper is equipped with an agitator. The hopper can hold slurry. The output end of the hopper is connected to the input end of the filling pump, and the output end of the filling pump is connected to the circulating filling pipeline.

[0100] The filling slurry is placed in the hopper according to the specified ratio; after the filling raw material is stirred in the mixing system, it is placed in the heavy hopper; then it is circulated in the pipeline by the filling pump and the simulated pipe blockage module to carry out pipe blockage simulation test.

[0101] The fiber optic acoustic monitoring device is used to detect the acoustic wave signal generated by the vibration of the simulated pipe block and input the acoustic wave signal into the data processing module.

[0102] The pressure sensor is used to detect the pressure signal in the circulating filling pipe and input the pressure signal into the data processing module;

[0103] The data processing module is used for:

[0104] Receive sound wave signals and extract frequency-division energy data and sound pressure data from the sound wave signals;

[0105] The deformation amount at the corresponding position of the cyclic filling pipe is determined based on the sound pressure data;

[0106] Receive pressure signals and determine the slurry flow rate at the corresponding position in the circulating filling pipeline based on the pressure signals;

[0107] The actual location of the simulated blockage is determined based on the frequency division energy data, deformation, and slurry flow rate.

[0108] Furthermore, the fiber optic acoustic monitoring device includes an optical pulse generation module, an optical quantity detection module, a single-mode armored optical cable, and a circulator;

[0109] Single-mode armored optical cables are installed inside the circulating filling pipe;

[0110] The optical pulse generation module includes a narrow linewidth laser, an optical fiber coupler, an acousto-optic modulator, and an erbium-doped fiber amplifier;

[0111] The light intensity detection module includes a polarization diversity receiver and a photodetector;

[0112] The first output of the fiber coupler is connected to the input of the polarization diversity receiver, and the second output is connected to the input of the acousto-optic modulator; the output of the acousto-optic modulator is connected to the input of the erbium-doped fiber amplifier.

[0113] The output of the erbium-doped fiber amplifier is connected to the first end of the circulator, the second end of the circulator is connected to the single-mode armored optical cable, and the third end of the circulator is connected to the input of the polarization diversity receiver of the optical quantity detection module.

[0114] The output of the polarization diversity receiver is connected to the input of the photodetector.

[0115] The output of the photodetector is connected to the data processing module.

[0116] At least one discharge valve is also installed on the circulating filling pipeline.

[0117] Specifically, the functions of each part are as follows:

[0118] Narrow-linewidth lasers are used to emit highly stable, narrow-linewidth laser light as a light source in sensing systems. Their output is connected to the input of an optical fiber coupler to ensure efficient transmission of optical signals.

[0119] The fiber coupler splits the optical signal emitted by the narrow linewidth laser into two paths: the first output is connected to the first input of the optical intensity detection module to detect the intensity change of the optical signal; the second output is connected to the first input of the acousto-optic modulation module to modulate the laser emitted by the narrow linewidth laser into a linear frequency sweeping optical pulse, which is then output to the erbium-doped fiber amplifier.

[0120] An acousto-optic modulator uses radio frequency signals to modulate the narrow linewidth laser emitted by a narrow linewidth laser into a linear sweep frequency optical pulse. This pulse is then used to modulate the light emitted by the laser into a linear sweep frequency optical pulse signal through gating and output to an erbium-doped fiber amplifier.

[0121] Erbium-doped fiber amplifiers amplify the power of the optical pulses output from the acousto-optic modulation module, which are then injected into the single-mode logging steel fiber via a circulator.

[0122] Fiber optic circulators are used to separate the transmitted optical signal from the received reflected signal. At the transmitting end: the high-power optical pulse output from the erbium-doped fiber amplifier in the optical pulse generation module enters through the first port of the circulator, exits from the second port, and is transmitted to the sensing fiber. At the receiving end: the reflected signal returning from the sensing fiber enters through the second port of the circulator, exits from the third port, and is transmitted to the polarization diversity receiver of the optical quantity detection module.

[0123] The photodetector module includes a polarization diversity receiver and a balanced photodetector. The functions of each part are as follows: the mixed optical signal of the local optical pulse output from the fiber coupler and the reflected light enters the polarization diversity receiver.

[0124] The polarization diversity receiver decomposes the mixed optical signal into two orthogonal polarization components: a horizontal polarization component and a vertical polarization component. The phases of these two polarization components are adjusted by optical phase delayers to ensure the stability of the subsequent interference signal. The two phase-adjusted polarization components then interfere with a reference optical signal, and the resulting interferometric signals are transmitted to the inputs of two photodetectors.

[0125] The photodetector converts the received interference light signal into an electrical signal and outputs it to the data processing system via a coaxial cable.

[0126] Furthermore, the data processing module includes: three SRAM interfaces, an acoustic wave acquisition and control module, a pressure sensor A / D acquisition and control module, and a controller.

[0127] It should be noted that those skilled in the art will understand that the controller has peripheral circuitry, including but not limited to modules such as a system clock, power supply module, and data storage module. Since the above content is conventional in the field, those skilled in the art are capable of implementing it based on conventional knowledge and it is not part of the scope of this embodiment; therefore, it will not be elaborated upon here.

[0128] The input terminal of the acoustic wave acquisition and control module serves as the first input terminal of the data processing module and the output terminal of the photodetector; the two output terminals of the acoustic wave acquisition and control module are connected to the controller through two SRAM interfaces respectively.

[0129] The input terminal of the pressure sensor A / D acquisition and control module is connected to each pressure sensor as the second input terminal of the data processing module; the output terminal of the pressure sensor A / D acquisition and control module is connected to the controller through the SRAM interface.

[0130] Specifically, the pressure sensor uses a corrosion-resistant ceramic piezoresistive sensor;

[0131] As a preferred embodiment, a single-mode armored optical cable is laid inside the circulating filling pipe directly above its own central axis, and is fixed with pre-tension clamps at 1.0m intervals to ensure the installation strength of the single-mode armored optical cable.

[0132] As a preferred embodiment, it also includes an acoustic wave acquisition module amplification circuit and a pressure acquisition amplification circuit;

[0133] The output of the photodetector is connected to the first input of the data processing module through the amplification circuit of the acoustic wave acquisition module.

[0134] Each pressure sensor is connected to the second input terminal of the data processing module via a pressure acquisition and amplification circuit.

[0135] Specifically, the specific selection of components in the embodiments is shown in Table 1.

[0136] Table 1 Component Model List

[0137]

[0138]

[0139] A method for determining the location of pipe blockage based on acoustic wave sensing, the method is based on the aforementioned acoustic wave sensing-based experimental device, and the data processing module determines the actual location of the simulated pipe blockage through the following steps:

[0140] Step 1: The acoustic wave acquisition and control module extracts the acoustic wave frequency division energy data and sound pressure data from the acoustic wave signal and transmits them to the controller through two SRAM interfaces respectively.

[0141] Step 2: The controller uses the least squares method to preprocess the sound wave frequency division energy data, minimizing the historical weighted sum of the sound wave data to obtain the preprocessed sound wave frequency division energy data.

[0142] Step 3: The controller decomposes the preprocessed acoustic wave frequency division energy data to obtain multi-layer acoustic wave frequency division energy data; calculates the power spectral density of the low-frequency approximation coefficient and high-frequency detail coefficient of each layer of acoustic wave frequency division energy data to determine the energy peak value;

[0143] Step 4: The controller determines the strain amplitude based on the sound pressure data, and then determines the pipe deformation at various points in the cyclic filling pipe based on the strain amplitude.

[0144] Step 5: Calculate the fluid velocity at each pressure sensor location based on the pressure detected, and determine the actual location of the simulated blockage based on the frequency-division energy data, sound pressure data, and slurry flow rate. Specifically, Step 3 includes the following sub-steps:

[0145] Step 31: Based on Parseval's theorem, calculate the power spectral density of the preprocessed acoustic wave frequency-division energy data using the following formula:

[0146]

[0147] Where Z represents the characteristic impedance of the dielectric;

[0148] P represents sound pressure level;

[0149] P(t) represents the time-domain signal of the acoustic wave signal;

[0150] |P(f)| 2 Indicates power spectral density;

[0151] t represents time;

[0152] Step 32: Decompose the acoustic wave frequency division energy data according to equal frequency band bandwidth or use wavelet basis to decompose the acoustic wave frequency division energy data to obtain M layers of acoustic wave frequency division energy data, denoted as [f low,i f high,i ];

[0153] f low,i The acoustic frequency division energy data represents the low-frequency approximation coefficients of the i-th layer acoustic frequency division energy data;

[0154] f high,i The acoustic frequency division energy data represents the high-frequency detail coefficients of the i-th layer acoustic frequency division energy data;

[0155] i represents the layer number, i = 1, 2, ..., M;

[0156] Step 33: Using the following formula, calculate the power spectral density of the low-frequency approximation coefficient and high-frequency detail coefficient of the acoustic wave frequency division energy data for each layer; thereby determining the energy peak value of the acoustic wave frequency division energy data for each layer.

[0157]

[0158] Among them, E i Indicates power spectral density;

[0159] Δf represents the frequency interval;

[0160] f low Indicates the low-frequency approximation coefficient;

[0161] f high This represents the high-frequency detail coefficient.

[0162] Specifically, step 4 includes the following sub-steps:

[0163] Step 41, calculate the bulk modulus using the following formula:

[0164] K = ρc 2

[0165] Where K represents the bulk modulus of the filling slurry;

[0166] ρ represents the density of the slurry;

[0167] c represents the speed of sound waves;

[0168] Step 42, based on the sound pressure amplitude P, calculate the strain amplitude ε using the following formula:

[0169] ε=P / ρc 2

[0170] Step 43: Calculate the pipe deformation at various points in the cyclic filling pipe using the following formula;

[0171] ε=△L / L

[0172] Where △L represents the amount of pipe deformation;

[0173] L represents the circumference of the inner wall of the cyclic filling pipe.

[0174] Specifically, step 5 includes the following sub-steps:

[0175] Step 51: Calculate the slurry velocity *v* at each pressure sensor. In the pipe, the relationship between fluid pressure and velocity can be derived from basic principles of fluid mechanics and the law of conservation of energy, requiring calculation in conjunction with Bernoulli's equation. For incompressible steady flow, the energy conservation equation along the streamline is as follows:

[0176]

[0177] Where p represents the slurry pressure, in Pa;

[0178] ρ represents the density of the slurry, kg / m³ 3 ;

[0179] g represents gravitational acceleration;

[0180] C is a constant;

[0181] z represents the liquid level height of the slurry in the circulating filling pipe;

[0182] Slurry flow rate diagram as follows Figure 6 As shown;

[0183] Step 52: Determine the actual location of the simulated pipe block based on the three possible locations of the simulated pipe block;

[0184] The blockage index I(x) is calculated using the following formula:

[0185] I(x) = w E ·Enorm (x)+w △L ·△L norm (x)+w v ·V norm (x)

[0186] Among them, w E Represents frequency division energy

[0187] Determine the actual location of the simulated pipe block;

[0188] Step 52 is as follows:

[0189] 52-1, Parameter Normalization

[0190] E norm (x)=(E i (x)–E min ) / (E max -E min )

[0191] Among them, E i (x) is the frequency-division energy at any point in the filling pipe;

[0192] E max It is the maximum value of the frequency-division energy distribution in the filling pipe;

[0193] E min It is the minimum value of the frequency-division energy distribution in the filling pipeline;

[0194] E norm (x) is the normalized value of the frequency-division energy distribution in the filling pipe.

[0195] △L norm (x)=(△L i (x)–△L min ) / (△L max -△L min )

[0196] Among them, △L i (x) represents the deformation at any point in the filling pipe;

[0197] △L max It is the maximum value of the deformation of the filling pipe;

[0198] △L min It is the minimum value of the deformation of the filling pipe;

[0199] △L norm (x) is the normalized value of the deformation of the filling pipe.

[0200] V norm (x)=(V i (x)–V min ) / (Vmax -V min )

[0201] Among them, V i (x) is the flow velocity at any point in the filling pipe;

[0202] V max It is the maximum flow velocity in the filling pipe;

[0203] V min It is the minimum flow velocity in the filling pipe;

[0204] V norm (x) is the normalized value of the flow velocity in the filling pipe.

[0205] 52-2, Weight Assignment

[0206] Let the weighting coefficients for frequency division energy, pipe deformation, and slurry velocity be w, respectively. E w △L w v (w E +w △L +w v =1), where w E ∈(0,1),w △L ∈(0,1),w v ∈(0,1).

[0207] The weighting coefficients need to be determined based on experimental or historical data, which are contents that can be directly determined by those skilled in the art based on the actual situation.

[0208] Pipe blockage index: I(x) = w E *E norm (x)+w △L *△L norm (x)+w v *V norm (x)

[0209] The actual location of the blockage in the filling pipeline is the monitoring point with the highest blockage index.

Claims

1. A test device based on acoustic wave sensing, characterized by, It includes a circulating filling pipe, a filling device, a simulated pipe block, a fiber optic acoustic monitoring device, multiple pressure sensors, and a data processing module; The simulated pipe block can be placed at any position inside the circulating filling pipe; the circulating filling pipe is also equipped with at least one discharge valve; The filling device includes a hopper and a filling pump. The hopper is equipped with a stirrer. The hopper can hold slurry. The output end of the hopper is connected to the input end of the filling pump. The output end of the filling pump is connected to a circulating filling pipeline. The fiber optic acoustic monitoring device is used to detect the acoustic wave signal generated by the vibration of the simulated pipe block and input the acoustic wave signal into the data processing module. The pressure sensor is used to detect the pressure signal of the circulating filling pipe and input the pressure signal into the data processing module. The data processing module is used for: Receive sound wave signals and extract frequency-division energy data and sound pressure data from the sound wave signals; The deformation amount at the corresponding position of the cyclic filling pipe is determined based on the sound pressure data; Receive pressure signals and determine the slurry flow rate at the corresponding position in the circulating filling pipeline based on the pressure signals; The actual location of the simulated blockage is determined based on the frequency division energy data, deformation, and slurry flow rate.

2. The acoustic wave sensing-based test device according to claim 1, wherein The fiber optic acoustic monitoring device includes an optical pulse generation module, an optical quantity detection module, a single-mode armored optical cable, and a circulator; The single-mode armored optical cable is installed inside the circulating filling pipe; The optical pulse generation module includes a narrow linewidth laser, an optical fiber coupler, an acousto-optic modulator, and an erbium-doped fiber amplifier. The light intensity detection module includes a polarization diversity receiver and a photodetector; The first output terminal of the fiber coupler is connected to the input terminal of the polarization diversity receiver, and the second output terminal is connected to the input terminal of the acousto-optic modulator; the output terminal of the acousto-optic modulator is connected to the input terminal of the erbium-doped fiber amplifier. The output end of the erbium-doped fiber amplifier is connected to the first end of the circulator, the second end of the circulator is connected to the single-mode armored optical cable, and the third end of the circulator is connected to the input end of the polarization diversity receiver of the optical quantity detection module. The output of the polarization diversity receiver is connected to the input of the photodetector; The output terminal of the photodetector is connected to the data processing module.

3. The acoustic wave sensing based test device of claim 2, wherein, The data processing module includes: three SRAM interfaces, an acoustic wave acquisition and control module, a pressure sensor A / D acquisition and control module, and a controller; The input terminal of the acoustic wave acquisition and control module serves as the first input terminal of the data processing module and the output terminal of the photodetector; the two output terminals of the acoustic wave acquisition and control module are respectively connected to the controller through two SRAM interfaces. The input terminal of the pressure sensor A / D acquisition and control module is connected to each pressure sensor as the second input terminal of the data processing module; the output terminal of the pressure sensor A / D acquisition and control module is connected to the controller through the SRAM interface.

4. The acoustic wave sensor-based test device of claim 3, wherein, The pressure sensor described is a corrosion-resistant ceramic piezoresistive sensor. The narrow linewidth laser mentioned above is UNL-1550-3-20; The fiber optic coupler mentioned above is a YG-WBC; The aforementioned acousto-optic modulator is AOM-1550-80-A; The erbium-doped fiber amplifier mentioned above uses GY-EDFA-PL; The SRAM interface adopts CY7C1049CV33; The circulator adopts YG-FCIR; The polarization diversity receiver adopts PMFC; The photoelectric detector adopts DAS-BPD-200M.

5. The acoustic wave sensing-based test device according to claim 2, wherein The single-mode armored optical cable is laid along the center axis of the circulating filling pipeline, and a pre-tension clamp is used to fix every 1.0 m.

6. The acoustic wave sensor-based test device of claim 3, wherein, The sound wave acquisition module amplification circuit and the pressure acquisition amplification circuit are further included. The output end of the photoelectric detector is connected with the first input end of the data processing module through the sound wave acquisition module amplification circuit. Each pressure sensor is connected with the second input end of the data processing module through the pressure acquisition amplification circuit.

7. A method for determining a position of a blockage in a pipe based on acoustic sensing, the method being based on the test device for determining a position of a blockage in a pipe based on acoustic sensing as defined in claim 6, characterized in that The data processing module determines the actual position of the simulated blocking pipe block by the following steps: Step 1: The sound wave acquisition control module extracts the sound wave frequency energy data and the sound pressure data in the sound wave signal, and transmits them to the controller through two SRAM interfaces respectively. Step 2: The controller uses the least square method to preprocess the sound wave frequency energy data, minimizes the historical weighted sum of the sound wave data, and obtains the preprocessed sound wave frequency energy data. Step 3: The controller decomposes the preprocessed sound wave frequency energy data to obtain multi-layer sound wave frequency energy data, calculates the power spectral density of the low-frequency approximation coefficient and the high-frequency detail coefficient of each layer of sound wave frequency energy data, and determines the energy peak value. Step 4: The controller determines the strain amplitude according to the sound pressure data, and determines the pipe deformation of the circulating filling pipeline at each position according to the strain amplitude. Step 5: The fluid velocity at each position is calculated according to the pressure detected by each pressure sensor, and the actual position of the simulated blocking block is determined according to the frequency energy data, the sound pressure data and the slurry flow.

8. The acoustic wave sensing based pipe blockage location determination method of claim 7, wherein, Step 3 Comprises the following sub-steps: Step 31: Based on the Parseval theorem, the power spectral density of the preprocessed sound wave frequency energy data is calculated using the following formula: Wherein, Z represents the characteristic impedance of the medium; P represents the sound pressure; P(t) represents the time domain signal of the sound wave signal; | P(f) | 2 represents the power spectral density; t represents time; Step 32, decompose the acoustic frequency energy data according to equal frequency band width or using wavelet base to obtain M layers of acoustic frequency energy data, denoted as [f low,i , f high,i ] f low,i acoustic band energy data representing low frequency approximation coefficients of the acoustic band energy data of the i-th layer; f high,i sonic frequency-division energy data representing high frequency detail coefficients of the i-th layer sonic frequency-division energy data; i represents the number of layers, i = 1, 2, …, M; Step 33: The power spectral density of the low-frequency approximation coefficient and the high-frequency detail coefficient of each layer of sound wave frequency energy data is calculated using the following formula, and then the energy peak value of each layer of sound wave frequency energy data is determined. where E i represents the power spectral density; Δf represents the frequency interval; f low denotes a low frequency approximation coefficient; f high represent high frequency detail coefficients.

9. The acoustic wave sensing based pipe blockage location determination method of claim 8, wherein, Step 4 comprises the following sub-steps: Step 41: The bulk modulus is calculated using the following formula: K = p c 2 Wherein, K represents the filling slurry bulk modulus; ρ represents the slurry density; c represents the sound wave velocity; Step 42: The strain amplitude ε is calculated using the following formula according to the amplitude P of the sound pressure: ε = P / pc 2 Step 43: The pipe deformation of the circulating filling pipeline at each position is calculated using the following formula: ε = ΔL / L Wherein, ΔL represents the pipe deformation; L represents the circumference of the inner wall of the circulating filling pipeline.

10. The method of claim 8, wherein, Step 5 comprises the following sub-steps: Step 51: The slurry flow rate v at each pressure sensor is calculated using the following formula: Wherein, p represents the slurry pressure, Pa; p represents the slurry density, kg / m 3 ; g represents the acceleration of gravity; C is a constant; z represents the liquid level height of the slurry in the circulating filling pipeline; Step 52, according to the frequency energy data, the weight coefficient of the pipe deformation amount, the weight coefficient of the slurry flow rate, the actual position of the simulated pipe blocking block is determined.

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