In-situ test system and method for engineering properties of a tectonic mélange

Abstract

The present invention discloses an in-situ test system and method for the engineering properties of tectonic mélange, including a microseismic acquisition mechanism and a processing controller. The microseismic acquisition mechanism is composed of multiple microseismic acquisition components, which are arranged in a specific array. The microseismic acquisition component includes a microseismic fixed conduction unit and multiple microseismic wave acquisition units. The fixed conduction unit is well coupled with the rock mass surface, and the acquisition units are arranged on the conduction unit or the rock mass of the tectonic mélange to be tested, and are used to collect ambient microseismic signals. The processing controller is connected to multiple microseismic wave acquisition units through a wireless network, sends acquisition instructions, receives data, and gives the in-situ measurement results of the engineering properties of the rock mass according to the collected microseismic signals. The method of the present invention performs time-frequency coherence analysis on the collected ambient microseismic data, extracts the dispersion energy spectrum diagram, and combines the convolutional neural network algorithm to perform intelligent quantitative evaluation on the engineering properties of the tectonic mélange.

Description

Technical Field

[0001] The present invention relates to the technical field of geotechnical engineering investigation, and more specifically, to an in-situ test system and method for the engineering properties of tectonic mélange. Background Art

[0002] Due to the special formation process of tectonic mélange rock mass, its internal structure and composition are complex. Different rock mass structures or different lithologic combinations will result in different engineering mechanical properties of the rock mass. Moreover, tectonic mélange is extremely easy to break, making it difficult to collect complete rock samples. And conventional small-size rock sample tests cannot represent the properties of large-size rock masses. In addition, it is difficult to simulate the true stress conditions where the rock mass is located, which directly increases the difficulty of studying the mechanical properties of tectonic mélange rock mass by means of laboratory tests.

[0003] At present, most of the existing testing technologies for the engineering properties of tectonic mélange rock mass are small-size rock block tests in the laboratory, which cannot simulate the in-situ stress environment. For example, the invention patent CN116907995A discloses a testing system and method for detecting the multi-field coupling mechanical properties of tectonic mélange. The testing system includes a multi-field applying device and a deformation testing device. The multi-field applying device includes a pressure regulating component, a temperature regulating component and an osmotic pressure regulating component. The deformation testing device includes a conventional triaxial compression deformation device, a true triaxial compression deformation device and a triaxial shear deformation device. The conventional triaxial compression deformation device, the true triaxial compression deformation device and the triaxial shear deformation device all include a pressure head and a detection component. The true triaxial compression deformation device and the triaxial shear deformation device include a fixture. The true triaxial compression deformation device applies compressive stress to the tectonic mélange sample, and the triaxial shear deformation device applies shear stress to the tectonic mélange sample. However, large-scale plate load tests and large-scale direct shear in-situ tests in the field are extremely costly in terms of human and material resources, complex to operate, and difficult to achieve large-scale and rapid investigation.

[0004] Therefore, how to design an in-situ test system that can perform in-situ tests on the rock mass in a large range of tectonic mélange areas is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] Aiming at the defects existing in the prior art, the present invention provides an in-situ test system and method for the engineering properties of tectonic mélange. It can quickly perform in-situ tests on the engineering properties of the rock mass in a large range of tectonic mélange areas and accurately quantify and describe the distribution of the mechanical properties of the tectonic mélange rock mass.

[0006] In a first aspect, the present invention provides an in-situ test system for the engineering properties of tectonic mélange, including a microseismic acquisition mechanism and a processing controller;

[0007] The microseismic acquisition mechanism includes a plurality of microseismic acquisition components arranged in an array. Each microseismic acquisition component includes a microseismic fixed conduction unit and a plurality of microseismic wave acquisition units. The microseismic fixed conduction unit is fixedly coupled to the surface of the tectonic melange rock mass. The microseismic wave acquisition units are arranged on the microseismic fixed conduction unit or the tectonic melange rock mass and are used to collect ambient microseismic signals.

[0008] The processing controller is signal-connected to the plurality of microseismic wave acquisition units, and is used to send acquisition instructions to the microseismic wave acquisition units and give in-situ measurement results of the engineering properties of the tectonic melange rock mass according to the ambient microseismic signals collected by the microseismic wave acquisition units.

[0009] Further, the microseismic wave acquisition unit includes a microseismic wave electromagnetic sensor, a microseismic signal preprocessing module, a high-precision AD analog-to-digital conversion module, a GPS real-time clock positioning module, and a wireless data transmission module. The output end of the microseismic wave electromagnetic sensor is connected to the input end of the microseismic signal preprocessing module. The output end of the microseismic signal preprocessing module is connected to the analog-to-digital conversion module. The analog-to-digital conversion module is connected to the wireless data transmission module. The wireless data transmission module transmits the collected microseismic signals to the processing controller through wide-area WiFi wireless communication technology. The GPS real-time clock positioning module performs positioning and timing functions for each microseismic acquisition unit. After the microseismic acquisition unit is started, the GPS time of each microseismic acquisition unit is synchronized in real time and command synchronization for sending and receiving is performed.

[0010] Further, the high-precision AD analog-to-digital conversion module includes a preamplifier, a signal attenuator, a bandpass filter, a programmable gain amplifier, and an analog-to-digital converter, and sequentially performs amplification processing, filtering processing, and analog-to-digital conversion processing on the collected microseismic signals to obtain a set of processed ambient microseismic signals, which are transmitted to the processing controller by the wireless data transmission module.

[0011] Further, the microseismic fixed conduction unit includes a conduction member and a plurality of fixing members. The plurality of fixing members are fixed on the same side wall of the conduction member and are used to be fixed to the surface of the tectonic melange rock mass. The fixing member includes three locking screws with anti-rotation functions, and the locking holes are uniformly arranged on the surface of the conduction member at an angle of 120° with the center.

[0012] Further, the array formed by arranging the plurality of microseismic acquisition components is a circular array, a semi-circular array, a linear multi-station array, or a double-station array.

[0013] In another aspect, a method for in-situ testing of the engineering properties of a tectonic melange uses the in-situ testing system for the engineering properties of a tectonic melange as described above. The method for in-situ testing of the engineering properties of a tectonic melange includes:

[0014] According to the type and size of the tectonic mélange rock mass to be tested, determine the microseismic acquisition components and corresponding array parameters in the microseismic acquisition mechanism; according to the determined microseismic acquisition components and array parameters, set the microseismic acquisition mechanism on the tectonic mélange rock mass to be tested; the processing controller sends an acquisition instruction to the microseismic acquisition mechanism, and based on the ambient microseismic signals collected by the microseismic wave acquisition unit, gives the in-situ measurement results of the engineering properties of the tectonic mélange rock mass, including:

[0015] Preprocess the ambient microseismic signals within a preset acquisition period to obtain several microseismic data segments of the same time length; the selected time length of the microseismic data should ensure that the overlap rate of each channel of data is ≥ 50%.

[0016] Perform normalization processing on all microseismic data segments in the frequency domain or time domain;

[0017] Calculate the correlation of all normalized microseismic data segments to obtain a microseismic data correlation set; analyze and process the microseismic data cross-correlation set to obtain the phase velocity distribution map of the mélange rock mass;

[0018] Based on a pre-constructed rock mass engineering property identification model, identify the phase velocity distribution map of the tectonic mélange rock mass to obtain the engineering property parameter data of the tectonic mélange rock mass.

[0019] Furthermore, analyze and process the microseismic data cross-correlation set to obtain the phase velocity distribution map of the tectonic mélange rock mass, including:

[0020] 1) Using the spatial autocorrelation method, the spatial autocorrelation calculation formula for the original microseismic trace data set is:

[0021]

[0022] where r xy (f,θ) is the spatial covariance function, which is used to calculate the autocorrelation relationship of the waveforms with frequency f observed at the microseismic stations at positions x and y; the seismic interferometry cross-correlation calculation formula:

[0023]

[0024] G x,y (τ) is the cross-correlation relationship of the microseismic waveforms observed at the microseismic stations at positions x and y, and τ is the time difference between the waveforms received by the two stations; based on the processed dispersion energy spectrum diagram, use the Bessel function to fit the spatial autocorrelation coefficient or pick up the peak values of the interference energy spectra at each frequency to extract the dispersion curve;

[0025] 2) Conduct cross-correlation ensemble phase velocity analysis of microseismic data using seismic interferometry. Represent the microseismic real signal as a complex signal through Hilbert transform, and at the same time use the phase cross-correlation technique to analyze the phase coherence of each pair of microseismic data sets, obtaining the phase coherence set c(t) of microseismic data in the time domain;

[0026]

[0027] J is the number of channels of the microseismic acquisition unit, Φ j (t) is the instantaneous phase of the Jth channel, and v is the measured sensitivity; then perform time-frequency domain phase weighted superposition analysis on the microseismic data phase coherence set using inverse continuous wavelet transform and S transform,

[0028] S pws (τ,f) = c(τ,f)S ls (τ,f)

[0029] Obtain the microseismic data phase coherence set S pws (τ,f) in the time-frequency domain. S ls (τ,f) is the linear S transform set of all microseismic trace data; then find the maximum amplitude represented by the microseismic data in the time-frequency domain to extract the microseismic frequency-phase velocity distribution map. Perform iterative processing on the created dispersion image to give the processed dispersion curve.

[0030] Superimpose the dispersion maps created by each microseismic data segment onto the entire microseismic record according to the time average function. Calculate the phase velocity value distribution at different positions of the rock mass based on the fact that different frequency dispersion waves in the microseismic wave reflect the situation at a depth of 1 / 2 to 1 / 3 of the wavelength of the dispersion wave, and then inversely obtain the phase velocity distribution map of the tectonic mélange rock mass varying with depth.

[0031] Furthermore, the construction of the mélange engineering property identification model includes:

[0032] Obtain historical environmental microseismic data and the corresponding tectonic mélange rock mass type and engineering property parameter data; obtain the tectonic mélange rock mass data with known engineering property parameters of 4 types, namely "soft matrix wrapping hard rock block type, hard and soft interbedded mixing type, tectonic fracture mixing type, hard and soft contact mixing type", as the training set. This training set contains a large number of "characteristic microseismic data set-phase velocity distribution value-engineering property parameter" data samples of tectonic mélange rock masses of these 4 types;

[0033] Based on the historical environmental microseismic data and the tectonic mélange rock mass engineering property parameter data, use the convolutional neural network algorithm for training until convergence to give the corresponding engineering property identification model.

[0034] The in-situ test system and method for the engineering properties of tectonic mélange provided by the present invention have at least the following beneficial effects:

[0035] (1) It can conduct in-situ tests on the engineering properties of tectonic mélange rock masses, quickly obtain the engineering properties of large-scale tectonic mélange rock masses, solve the problems of difficult acquisition of test samples, poor representativeness of small-scale tests, and difficulty in reflecting the true strength properties of tectonic mélange rock masses, and provide reliable strength parameters for evaluating the mechanical behavior of tectonic mélange.

[0036] (2) The device of the present invention has a simple and reasonable structure, and uses a microseismic fixed conduction unit to detect the engineering properties of tectonic mélange rock masses in the horizontal direction.

[0037] (3) The present invention combines the spatial autocorrelation method, seismic interferometry, and time-frequency domain phase weighted stacking method to extract dispersion curves, which can be applied to simple two-station or linear multi-station microseismic observation systems. Moreover, performing cross-correlation calculations can greatly increase the size of the tested tectonic mélange rock mass, and the inversion combines a convolutional neural network algorithm to intelligently and quantitatively evaluate the engineering properties of tectonic mélange rock masses. Description of the Drawings

[0038] Figure 1 It is a schematic diagram of the layout of a wireless array type microseismic acquisition station sequence in a tectonic mélange area:

[0039] Figure 1 (a) is a schematic diagram of the in-situ test of the engineering properties of the rock mass in the horizontal direction of the tunnel face in a tectonic mélange area, Figure 1 (b) is a schematic diagram of the in-situ test of the engineering properties of the rock mass in the vertical direction in a tectonic mélange area;

[0040] Figure 2 It is a schematic diagram of a microseismic acquisition station and a microseismic fixed conduction component;

[0041] Figure 3 It is the overall framework of the microseismic in-situ test method for the engineering properties of the rock mass in the tectonic mélange zone.

[0042] In the figure: 1 - Wireless array microseismic acquisition station sequence, 1.1 - High-sensitivity microseismic wave electromagnetic sensor, 1.2 - 24-bit high-precision analog-to-digital conversion module (1.2.1 - Preamplifier, 1.2.2 - Signal attenuator, 1.2.3 - Band filter, 1.2.4 - Programmable amplifier, 1.2.5 - Analog-to-digital converter), 1.3 - Wide-area WiFi wireless data transmission module, 1.4 - GPS real-time clock positioning module, 2 - Microseismic fixed conduction component (2.1 - Fixed part, 2.2 - Conduction part), 3 - On-site control host (3.1 - Central processor, 3.2 - Data display module, 3.3 - Data storage module, 3.4 - Control module), 4 - Microseismic dispersion curve extraction module (4.1 - Microseismic raw data filtering, 4.2 - Time-domain and frequency-domain normalization processing, 4.3 - Dispersion curve extraction, 4.4 - Iterative calculation, 4.5 - Frequency-domain inversion), 5 - Tunnel face of tectonic melange rock mass. Specific implementation mode

[0043] In order to better understand the above technical solution, the following will combine the accompanying drawings of the specification and specific implementation modes to make a detailed description of the above technical solution. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "the" and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0045] The present invention includes a microseismic acquisition mechanism and a processing controller;

[0046] The microseismic acquisition mechanism includes a plurality of microseismic acquisition components arranged in an array. The microseismic acquisition component includes a microseismic fixed conduction unit and a plurality of microseismic wave acquisition units. The microseismic fixed conduction unit is fixed to the surface of the tectonic melange rock mass, and the microseismic wave acquisition unit is arranged on the microseismic fixed conduction unit or the tectonic melange rock mass for collecting ambient microseismic signals;

[0047] The processing controller is signal-connected to the plurality of microseismic wave acquisition units, and is used to send acquisition instructions to the microseismic wave acquisition units and give in-situ measurement results of the engineering characteristics of the tectonic melange rock mass according to the ambient microseismic signals collected by the microseismic wave acquisition units.

[0048] Such as Figure 1 And 2As shown in the figure, in this embodiment, the test system mainly includes: a wireless array microseismic acquisition station sequence 1, a microseismic fixed conduction component 2, a field control host 3, and a microseismic dispersion curve extraction module 4. The field control host 3 uses a secondary wireless network to send commands and perform real-time data transmission to the wireless array microseismic acquisition station sequence 1, and preprocesses and displays the acquired microseismic data in real time. The structure of the microseismic fixed conduction component 2 is as shown in the appendix Figure 2 As shown, this device is mainly composed of a fixing part 2.1 and a conduction part 2.2. When horizontal detection is required in a tectonic melange area, the fixing part 2.1 can be used to fix the microseismic station on the surface of the tectonic melange rock mass, and a specific array can be arranged according to the detection accuracy requirements and on-site conditions. At the same time, it is connected to the conduction part 2.2 to transmit the weak vibration signals received on the rock mass surface to the microseismic station without loss. The arrays that can be used include circular arrays, semi-circular arrays, linear multi-station or double-station arrays, etc.

[0049] The wireless array microseismic acquisition station sequence 1 mainly includes a high-sensitivity microseismic wave electromagnetic sensor 1.1, a high-precision analog-to-digital conversion module 1.2, a wide-area WiFi wireless data transmission module 1.3, and a GPS real-time clock positioning module 1.4. The high-sensitivity microseismic wave sensor 1.1 is designed with a low-frequency integration network structure, which can greatly improve the quality of the acquired signals in the low-frequency band. The overall microseismic data acquisition system uses a low-power and high-performance vibration signal acquisition chip, which has an integrated low-noise programmable gain amplifier and a dual-channel input multiplexer, and the power consumption is less than 25 mW. The high-sensitivity microseismic wave electromagnetic sensor 1.1 outputs signals to the access end of the high-precision analog-to-digital conversion module 1.2, and the microseismic signals are amplified and filtered in the high-precision analog-to-digital conversion module 1.2. The communication end of the microseismic acquisition station performs time synchronization through a primary wireless network. After obtaining the microseismic information, it is stored and displayed on the control host through a secondary wireless network. The clock error of the GPS real-time clock positioning module 1.4 does not exceed 1 ns, which is used to synchronize the acquisition data and receive commands.

[0050] In this embodiment, the seismic source used is the ambient microseismic signal, without the need for traditional shot-point seismic sources or spark seismic sources, with high safety and strong applicability. The data observation time is usually about 30 minutes, and it is specifically judged according to the convergence of the dispersion energy spectrum diagram.

[0051] In each station of the wireless array microseismic acquisition station sequence 1 described above, weak vibration signals on the rock mass surface are synchronously acquired. In addition, an external seismic source with a fixed frequency can also be applied to improve the quality of microseismic data. The frequency of the acquired signals can be in the range of 0.2 - 100 Hz. Subsequently, the acquired microseismic signals are converted into electrical signals through a voltage displacement transducer, and the electrical signals are processed through a preamplifier 1.2.1, a signal attenuator 1.2.2, a bandpass filter 1.2.3, and a programmable amplifier 1.2.4. Then, the electrical signals are converted into digital signals through an analog-to-digital converter 1.2.5, and finally, the data is transmitted to the on-site control host 3 through a wide-area WiFi wireless data transmission module for storage and further analysis.

[0052] Based on the ambient microseismic signals obtained by the microseismic wave acquisition unit, in-situ measurement results of the engineering properties of the tectonic mélange rock mass are given, including:

[0053] Preprocess the ambient microseismic signals within a preset acquisition period to obtain several microseismic data segments of the same time length; the selected time length of the microseismic data should ensure that the overlap rate of each channel of data is ≥ 50%.

[0054] Normalize all microseismic data segments in the frequency domain or time domain. Calculate the correlation of all normalized microseismic data segments to obtain a microseismic data correlation set; analyze and process the microseismic data cross-correlation set, including:

[0055] 1) Using the spatial autocorrelation method, the original microseismic trace set data spatial autocorrelation calculation formula is:

[0056]

[0057] where r xy (f,θ) is the spatial covariance function, used to calculate the autocorrelation relationship of waveforms with frequency f observed at microseismic stations at positions x and y; the seismic interference cross-correlation calculation formula:

[0058]

[0059] G x,y (τ) is the cross-correlation relationship of microseismic waveforms observed at microseismic stations at positions x and y, and τ is the time difference between the waveforms received by the two stations; based on the processed dispersion energy spectrum diagram, use the Bessel function to fit the spatial autocorrelation coefficient or pick the peak values of the interference energy spectrum at each frequency to extract the dispersion curve;

[0060] 2) Use the seismic interference method to perform phase velocity analysis on the microseismic data cross-correlation set. Represent the microseismic real signal as a complex signal through the Hilbert transform, and at the same time use the phase cross-correlation technology to analyze the phase coherence of each pair of microseismic data sets to obtain the phase coherence set c(t) of the microseismic data in the time domain;

[0061]

[0062] J is the number of channels of the microseismic acquisition unit, and Φ j (t) is the instantaneous phase of the Jth channel, and v is the measured sensitivity; then, the continuous wavelet inverse transform and the S transform are used for time-frequency domain phase weighted superposition analysis and processing of the microseismic data phase coherence set.

[0063] S pws (τ,f) = c(τ,f)S ls (τ,f)

[0064] The time-frequency domain microseismic data phase coherence set S pws (τ,f) is obtained, and S ls (τ,f) is the linear S transform set of all microseismic trace data; then, the maximum amplitude represented by the time-frequency domain microseismic data is found to extract the microseismic frequency-phase velocity distribution map. The created dispersion image is iteratively processed to give the processed dispersion curve.

[0065] The dispersion maps created from each microseismic data segment are superimposed onto the entire microseismic record according to the time averaging function. According to the fact that different frequency dispersion waves in the microseismic wave reflect the situation at a depth of 1 / 2 to 1 / 3 of the wavelength of the dispersion wave, the phase velocity value distribution at different positions of the rock mass is calculated, and then the phase velocity distribution map of the tectonic mélange rock mass changing with depth is inversely obtained.

[0066] Establishing the identification model for the engineering characteristics of the described mélange rock includes: obtaining historical environmental microseismic data and the corresponding tectonic mélange rock mass type and engineering characteristic parameter data; obtaining the data of tectonic mélange rock masses with known engineering characteristic parameters of 4 types, namely "soft matrix wrapping hard rock block type, hard and soft interbedded mixing type, tectonic fracture mixing type, hard and soft contact mixing type", as the training set, and this training set contains a large number of data samples of "characteristic microseismic data set - phase velocity distribution value - engineering characteristic parameters" of tectonic mélange rock masses of these 4 types.

[0067] Based on the historical environmental microseismic data and the engineering characteristic parameter data, the convolutional neural network algorithm is trained until convergence to give the engineering characteristic identification model.

[0068] The basic principle of the present invention is to utilize the characteristics of the frequency amplitude change and action duration shown by microseismic signals when passing through rock and soil masses with different engineering geological characteristics to perform rapid large-scale in-situ engineering characteristic tests on the rock mass in the tectonic mélange area. This patent also designs a good conduction structure at the lower part of the microseismic station to solve the problem of difficult horizontal direction testing of the engineering characteristics of tectonic mélange rock masses in tunnel or slope engineering.

[0069] The microseismic dispersion curve extraction module 4 mainly includes the following steps:

[0070] 1) Divide the collected microseismic data into several microseismic data segments of equal length, and the selected time length of the microseismic data is determined according to the quality of the collected data;

[0071] 2) Screen out the microseismic segments that can reflect the engineering characteristics of the rock mass in front of the tunnel face of the tectonic mélange, and perform normalization processing on the selected microseismic data segments in the frequency domain or time domain;

[0072] 3) Calculate the correlation of the microseismic trace data segments in 2), and establish a new coherence set of double or multi-trace microseismic data;

[0073] 4) Subsequently, perform phase velocity analysis on the new set through spatial autocorrelation method, seismic interferometry and time-frequency domain phase weighted stacking method, and create a dispersion image. Reduce the error through iterative calculation, and then extract the microseismic dispersion curve. Obtain the phase velocity distribution map of the tectonic mélange rock mass through frequency domain inversion;

[0074] 5) Establish a rich and accurate "microseismic data - engineering characteristic parameter data of tectonic mélange rock mass" sample library. For tunnel or slope projects in the complex geological environment of tectonic mélange areas, select known borehole data to simulate observation samples, establish a sample library through a large number of numerical simulation tests, and construct an identification model for engineering characteristic parameters of microseismic detection of tectonic mélange rock mass using convolutional neural network algorithm. Input a large amount of microseismic data to be analyzed into the identification model to obtain the distribution of engineering mechanical properties of the tectonic mélange rock mass.

[0075] Implementation Case 1: Linear Multi-station Array

[0076] Select a large tectonic mélange mining area with different rock types and structures, and its stability and engineering characteristics need to be evaluated;

[0077] According to the geological map and rock distribution of the mining area, determine the layout of the microseismic acquisition components. Adopt a linear multi-station array and arrange it along the main geological fault line of the mining area. Each microseismic acquisition component includes a microseismic fixed conduction unit and a microseismic wave acquisition unit. The fixed conduction unit is coupled with the rock mass surface through a fixing piece.

[0078] Start the processing controller, send acquisition instructions to all microseismic wave acquisition units. The microseismic wave acquisition units collect ambient microseismic signals, perform signal processing through the analog-to-digital conversion module, and then perform time synchronization through the GPS module.

[0079] Normalize the collected microseismic signals in the frequency domain or time domain, perform cross-correlation calculations, and use the time-frequency domain phase-weighted superposition algorithm to analyze the cross-correlation set of microseismic data to obtain the phase velocity distribution map of the tectonic mélange rock mass. Then, use a pre-trained engineering property identification model to identify the phase velocity distribution map and obtain the engineering property parameters of the tectonic mélange rock mass.

[0080] Implementation Case 2: Circular Array

[0081] In a tunnel engineering area with complex geology, it is necessary to evaluate the engineering properties of the rock mass around the tunnel to ensure construction safety. The system is deployed at the entrance and exit of the tunnel, as well as at the center point of the tunnel. Microseismic acquisition components are deployed to form a circular array. The microseismic fixed conduction unit is fixed on the tunnel wall, and the microseismic wave acquisition unit is installed on the fixed conduction unit or directly contacts the rock mass surface. The processing controller is started to send synchronous acquisition instructions to all microseismic wave acquisition units. The microseismic wave acquisition units collect the microseismic signals around the tunnel, and perform signal preprocessing and time synchronization. Data analysis normalizes and cross-correlates the collected microseismic signals to obtain the phase velocity distribution map of the rock mass around the tunnel. Then, use the engineering property identification model to identify the phase velocity distribution map and obtain the engineering property parameters of the rock mass.

[0082] As Figure 3 shown, the rock mass characteristic analysis identifies different lithologies and rock mass structures, including hardness and combination characteristics, as well as the geometric characteristics of the rock mass. These characteristics are crucial for understanding the heterogeneity of the tectonic mélange rock mass. The microseismic signal acquisition system uses highly sensitive microseismic wave electromagnetic sensors to capture microseismic signals, which reflect the dynamic characteristics of the rock mass. Signal preprocessing includes preamplifiers, signal attenuators, band filters, etc., for the preliminary processing of signals. Programmable amplifiers and analog-to-digital converters further process the signals to prepare for high-precision analysis. During analog-to-digital conversion, the high-precision A / D analog-to-digital conversion module converts the analog signal into a digital signal.

[0083] GPS time synchronization ensures the time accuracy of data acquisition. The on-site control host and the central processor are used for real-time monitoring and control of the test process. The data storage and data display module are responsible for saving and presenting the test results. Microseismic dispersion curve extraction includes raw data filtering and dispersion curve extraction. Through normalization processing in the time domain and frequency domain, it prepares for subsequent analysis. Implementation Case 3: Microseismic Monitoring of a Tunnel Crossing a Tectonic Mélange Rock Mass

[0084] In a large infrastructure project, it is necessary to cross a tectonic mélange rock mass with a complex geological structure to build a tunnel. To ensure construction safety and engineering quality, it is necessary to conduct real-time monitoring and evaluation of the engineering properties of the rock mass.

[0085] Implementation Steps:

[0086] Carry out geological surveys to identify the lithology, rock mass structure, hardness and geometric characteristics along the tunnel path. In the tunnel construction area, according to the results of the geological survey, arrange a highly sensitive microseismic wave electromagnetic sensor array, and adopt a linear multi-station array layout.

[0087] Signal acquisition and preprocessing:

[0088] Start the microseismic signal acquisition system, preprocess the signals through a preamplifier, signal attenuator and bandpass filter. Use GPS for time synchronization in data synchronization and transmission to ensure the accuracy of data acquisition. Transmit the preprocessed signals to the central processing unit through a wide-area WiFi wireless network.

[0089] Data processing and analysis:

[0090] On the central processing unit, use an analog-to-digital converter to convert the analog signals into digital signals, further filter and normalize the digital signals, extract the dispersion curve using the microseismic dispersion curve extraction module, and perform iterative processing. Apply seismic interferometry technology to perform frequency-domain inversion and spatial autocorrelation analysis to improve the accuracy of data interpretation. Based on historical data and a trained convolutional neural network algorithm, construct an engineering property recognition model, and use this model to identify the phase velocity distribution map to obtain the engineering property parameters of the tectonic mélange rock mass.

[0091] Tectonic mélange tunnel face:

[0092] Each station in the wireless array type microseismic acquisition station sequence 1 synchronously acquires the weak vibration signals on the rock mass surface. In addition, an external seismic source with a fixed frequency can also be applied to improve the quality of microseismic data. The frequency of the acquired signals can be in the range of 0.2 - 100 Hz. Subsequently, convert the acquired microseismic signals into electrical signals through a voltage-displacement transducer. The electrical signals are preprocessed through a preamplifier 1.2.1, signal attenuator 1.2.2, bandpass filter 1.2.3 and programmable amplifier 1.2.4, and then converted into digital signals through an analog-to-digital converter 1.2.5. Finally, the data is transmitted to the on-site control host 3 through a wide-area WiFi wireless data transmission module for storage and further analysis.

[0093] When using the spatial autocorrelation method for testing, its effective test length is 10 times the length of the microseismic station array, that is, the array length needs to be greater than 1 / 10 of the size of the tectonic mélange rock mass, and the microseismic station spacing dx needs to be less than half the wavelength of the acquired microseismic signals. When using the seismic interferometry method for testing, its effective test length is 1 / 2 of the wavelength of the acquired microseismic signals, and the microseismic station spacing dx can be flexibly selected according to the site conditions. The number of stations can be determined by the ratio of the rock mass size to the station spacing.

[0094] The microseismic in-situ test technical solution for constructing the engineering characteristics of the rock mass in the mélange zone provided by this implementation case can timely and accurately obtain the changes in the engineering characteristics of the tectonic mélange rock mass, provide wave velocity data for dividing the lithological changes and the distribution range of rock masses with poor mechanical properties, and provide technical support for the active prevention and control of geological disasters in tunnel or artificial slope engineering construction in the tectonic mélange area.

[0095] The implementation of this invention is convenient. The use of wide-area WIFI wireless data transmission technology reduces the topographical and environmental limitations caused by communication cables. The design of this invention uses the spatial autocorrelation method and the seismic interferometry method to extract the dispersion curve, which is applicable to simple double-station or linear multi-station microseismic observation systems. Moreover, the use of the seismic interferometry method greatly increases the size of the tested tectonic mélange rock mass, and the inversion combines the convolutional neural network algorithm to intelligently quantify and evaluate the engineering characteristics of the tectonic mélange rock mass.

[0096] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present invention. Obviously, those skilled in the art can make various changes and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. An in-situ test system for the engineering properties of tectonic mélange, characterized in that, It includes a microseismic acquisition mechanism and a processing controller; the microseismic acquisition mechanism includes a plurality of microseismic acquisition components arranged in an array, and each microseismic acquisition component includes a microseismic fixed conduction unit and a plurality of microseismic wave acquisition units. The microseismic fixed conduction unit is fixedly coupled to the surface of the tectonic mélange rock mass, and the microseismic wave acquisition units are arranged on the microseismic fixed conduction unit or the tectonic mélange rock mass for acquiring ambient microseismic signals; the processing controller is signal-connected to the plurality of microseismic wave acquisition units for sending acquisition instructions to the microseismic wave acquisition units and giving in-situ measurement results of the engineering characteristics of the tectonic mélange rock mass according to the ambient microseismic signals acquired by the microseismic wave acquisition units. Analyze and process the cross-correlation set of microseismic data to obtain the phase velocity distribution map of the tectonic mélange rock mass, including: 1) Using the spatial autocorrelation method, the spatial autocorrelation calculation formula for the original microseismic trace data set is: Among them, rxy(f,θ) is the spatial covariance function used to calculate the autocorrelation relationship of the waveforms with frequency f observed at the microseismic stations at positions x and y; the cross-correlation calculation formula for seismic interferometry: Gx,y(τ) is the cross-correlation relationship of the microseismic waveforms observed at the microseismic stations at positions x and y, and τ is the time difference between the waveforms received by the two stations; based on the processed dispersion energy spectrum diagram, use the Bessel function to fit the spatial autocorrelation coefficient or pick up the peak values of the interference energy spectra at each frequency to extract the dispersion curve. 2) Use the seismic interferometry method to perform phase velocity analysis on the cross-correlation set of microseismic data. Represent the microseismic real signal as a complex signal through Hilbert transform, and at the same time use the phase cross-correlation technology to analyze the phase coherence of each pair of microseismic data sets to obtain the phase coherence set c(t) of the microseismic data in the time domain. J is the number of channels of the microseismic acquisition unit, Φj(t) is the instantaneous phase of the Jth channel, and v is the measurement sensitivity; then perform time-frequency domain phase weighted superposition analysis and processing on the microseismic data phase coherence set using the inverse continuous wavelet transform and S transform. Obtain the phase coherence set of microseismic data in the time-frequency domain It is the linear S-transform set of all microseismic trace gather data; then find the maximum amplitude represented by the microseismic data in the time-frequency domain to extract the microseismic frequency-phase velocity distribution diagram, perform iterative processing on the created dispersion image, and give the processed dispersion curve; For the dispersion spectrograms created by each microseismic data segment, superimpose each segmented spectrogram onto the entire microseismic record according to the time average function. Calculate the phase velocity value distribution at different positions of the rock mass according to the fact that different frequency dispersion waves in the microseismic wave reflect the situation at a depth of 1 / 2 to 1 / 3 of the wavelength of the dispersion wave, and then inversely obtain the phase velocity distribution map of the tectonic mélange rock mass varying with depth.

2. The in-situ test system for engineering properties of tectonic mélange as described in claim 1, characterized in that The microseismic wave acquisition unit includes a microseismic wave electromagnetic sensor, a microseismic signal preprocessing module, a high-precision AD analog-to-digital conversion module, a GPS real-time clock positioning module, and a wireless data transmission module; the output end of the microseismic wave electromagnetic sensor is connected to the input end of the microseismic signal preprocessing module, the output end of the microseismic signal preprocessing module is connected to the analog-to-digital conversion module, the analog-to-digital conversion module is connected to the wireless data transmission module, and the wireless data transmission module transmits the acquired microseismic signals to the processing controller through wide-area WiFi wireless communication technology. The GPS real-time clock positioning module performs positioning and timing functions for each microseismic acquisition unit. After the microseismic acquisition unit is started, the GPS time of each microseismic acquisition unit is synchronized in real time and command synchronization for sending and receiving is performed.

3. The in-situ test system for engineering properties of tectonic mélange as described in claim 2, characterized in that, The high-precision AD analog-to-digital conversion module includes a preamplifier, a signal attenuator, a band-pass filter, a programmable gain amplifier, and an analog-to-digital converter. It sequentially performs amplification processing, filtering processing, and analog-to-digital conversion processing on the collected microseismic signals to obtain a set of processed ambient microseismic signals, which are then transmitted to the processing controller by the wireless data transmission module.

4. The in-situ test system for the engineering properties of the tectonic mélange as described in claim 1, wherein, The microseismic fixed conduction unit includes a conduction member and a plurality of fixing members. The plurality of fixing members are fixed on the same side wall of the conduction member and are used to fix to the surface of the tectonic melange rock mass. The fixing member includes three locking screws with anti-rotation functions, and the locking holes are evenly arranged on the surface of the conduction member at an angle of 120° with the center.

5. The in-situ test system for engineering properties of tectonic mélange according to claim 1, characterized in that The array formed by arranging multiple microseismic acquisition components is a circular array, a semi-circular array, a linear multi-station array, or a two-station array.

6. An in-situ test method for the engineering properties of tectonic mélange, characterized in that, Using the in-situ test system for the engineering properties of tectonic melange as described in any one of claims 1-5, the method for in-situ testing of the engineering properties of tectonic melange includes: According to the type and size of the tectonic melange rock mass to be tested, determine the microseismic acquisition components and the corresponding array parameters in the microseismic acquisition mechanism; according to the determined microseismic acquisition components and array parameters, set the microseismic acquisition mechanism on the tectonic melange rock mass to be tested; the processing controller sends an acquisition instruction to the microseismic acquisition mechanism, and based on the ambient microseismic signals collected by the microseismic wave acquisition unit, gives the in-situ measurement results of the engineering properties of the tectonic melange rock mass, including: Preprocess the ambient microseismic signals within the preset acquisition period to give several microseismic data segments of the same time length; the selected time length of the microseismic data should ensure that the overlap rate of each channel of data is ≥50%; Perform normalization processing on all microseismic data segments in the frequency domain or time domain; Perform correlation calculation on all normalized microseismic data segments to give a set of microseismic data correlations; analyze and process the set of microseismic data cross-correlations to obtain the phase velocity distribution map of the melange rock mass; Based on the pre-constructed rock mass engineering property identification model, identify the phase velocity distribution map of the tectonic melange rock mass to give the engineering property parameter data of the tectonic melange rock mass.

7. The in-situ test method for engineering properties of tectonic mélange according to claim 6, characterized in that Constructing the melange engineering property identification model includes: Obtain historical ambient microseismic data and the corresponding tectonic melange rock mass type and engineering property parameter data; obtain the data of tectonic melange rock masses with known engineering property parameters of the four types of "soft matrix wrapping hard rock block type, hard and soft intermingled type, tectonically fractured intermingled type, hard and soft contact intermingled type" as the training set, and this training set contains a large number of "characteristic microseismic data set - phase velocity distribution value - engineering property parameter" data samples of these four types of tectonic melange rock masses; Based on the historical ambient microseismic data and the engineering property parameter data of the tectonic melange rock mass, use the convolutional neural network algorithm for training until convergence to give the corresponding engineering property identification model.

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