Laboratory fault monitoring system

Abstract

The invention discloses a laboratory fault monitoring system which can effectively simulate nucleation, fracture and friction behaviors of natural earthquakes and continuously monitor stress, strain and displacement space-time distribution rules of a laboratory fault contact surface. The system comprises a fault model, an optical fiber sensor unit, a data acquisition and processing unit and a control and monitoring unit, and can further improve the precision of laboratory fault monitoring. Through arrangement of the optical fiber sensors, the high spatial resolution and sensitivity requirements which are difficult to meet by a traditional experimental observation system are solved, automatic processing and model analysis of experimental data are realized in combination with data acquisition and machine learning, and the accuracy and efficiency of data analysis are improved by adopting an intelligent algorithm. According to the invention, an existing laboratory fault monitoring system is further supplemented, the precision level of laboratory seismic research can be improved, and powerful support is provided for research of physical mechanisms of natural earthquakes.

Description

Technical Field

[0001] The invention belongs to the intersecting field of earthquake mechanics, rock tribology and optical fiber sensing technology, and relates to a laboratory fault monitoring system. Background Art

[0002] Laboratory seismic research refers to artificially and controllably generating a series of earthquakes similar to natural earthquakes in the laboratory, and directly observing the source process through certain observation methods, abstracting the complex fault plane in the crust into a friction contact surface formed by two mutually compressed blocks. Laboratory seismic research provides a unique perspective for understanding the nucleation, rupture and friction behavior of natural earthquakes, but traditional laboratory seismic research still has the following shortcomings:

[0003] 1. The monitoring technology is not accurate and real-time enough. Traditional sensing technologies (such as resistance strain gauges, mechanical displacement sensors, etc.) have limited performance in high-precision experiments and are difficult to meet the requirements for capturing subtle changes. Some experiments require real-time acquisition and processing of large-scale data, but the processing speed of the acquisition equipment often cannot keep up, resulting in lags. Most experiments require simultaneous monitoring of stress, displacement, temperature, vibration and other parameters, but traditional equipment is difficult to integrate multiple sensing functions.

[0004] 2. Complex equipment layout and poor flexibility. Traditional sensors and data acquisition equipment rely on complex wired connections, which are cumbersome to install and have poor adaptability, especially in large-scale experiments; some sensors are easily damaged under high pressure, high temperature or strong chemical environments, resulting in increased equipment loss.

[0005] 3. Limited data processing capabilities. As the number of sensors increases, the amount of data collected increases exponentially, but the storage, processing and analysis capabilities of existing systems have failed to keep up with development needs; traditional data processing methods mainly rely on rule-based algorithms, which have limited ability to capture and understand complex nonlinear phenomena, making it difficult to achieve intelligent analysis and prediction.

[0006] Based on the above technical background, there is an urgent need for a laboratory fault detection system that can achieve high accuracy, good flexibility, and strong data processing capabilities to improve the accuracy level of laboratory earthquake research and provide strong support for studying the nucleation, rupture, and friction behavior of natural earthquakes. Summary of the invention

[0007] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0008] Therefore, the purpose of the present invention is to provide a laboratory fault monitoring system to solve the problems of limited accuracy, complex equipment layout, poor data processing capability, etc. in existing fault experiments.

[0009] In order to achieve the above object, the present invention adopts the following technical solution:

[0010] The present invention provides a laboratory fault monitoring system, comprising:

[0011] A fault model, comprising a first sub-model and a second sub-model, wherein the first sub-model and the second sub-model use the same right-angled triangle plate, and the inclined surfaces of the first sub-model and the second sub-model are attached to each other to form a laboratory fault at the attached position;

[0012] A loading device is arranged around the fault model to realize biaxial loading of the fault model to simulate the occurrence of an earthquake;

[0013] An optical fiber sensor unit, comprising at least one continuous optical fiber sensor arranged near the surface of the laboratory fault, so as to realize continuous acquisition of corresponding physical parameter signals at the laboratory fault;

[0014] A data acquisition and processing unit, including a data acquisition device and a data processing module, monitors the physical parameters of the laboratory earthquake fault in real time based on the physical parameter signals acquired by the optical fiber sensor unit;

[0015] The control and monitoring unit is connected with the loading device and the data acquisition and processing unit to facilitate the control of the stability of the experiment and the observation and analysis of the experimental results.

[0016] In some embodiments, the first sub-model and the second sub-model are made of the same material, and an acrylic material having a wave velocity close to that of an actual rock formation is selected.

[0017] In some embodiments, the slope of each sub-model is a rough surface formed by abrasive particles ejected by 0.2Mpa-0.8Mpa high-pressure gas through sandblasting to impact, cut and erode the originally smooth slope of each sub-model, thereby simulating the rough fault surface morphology.

[0018] In some embodiments, before the inclined surfaces of the first sub-model and the second sub-model are attached to each other, a high-pressure airflow of 0.3 Mpa-1 Mpa is used to clean the rough surface to remove residual particles.

[0019] In some embodiments, each corner of the fault model is chamfered to reduce stress concentration at the end.

[0020] In some embodiments, the loading device includes a main structure, which is a U-shaped integral casting frame. Servo cylinders and servo control valves supported on corresponding side walls of the main structure are respectively provided around the fault model, and are equipped with corresponding digital closed-loop servo controllers, load sensors and displacement sensors. A loading plate is fixed to the end of the piston rod of each servo cylinder. During the loading process, the loading plate contacts the corresponding side of the fault model. The digital closed-loop servo controller, the load sensor and the displacement sensor are connected to the control and monitoring unit.

[0021] In some embodiments, the optical fiber sensor uses an optical fiber Bragg grating sensor or a distributed optical fiber sensor to obtain any one or more of the strain signal, stress signal and displacement signal at the laboratory fault in real time.

[0022] In some embodiments, the data collector is a multi-channel data collector for collecting signals from the optical fiber sensor, and the collected signals include any one or more of strain signals, stress signals, and displacement signals at the laboratory fault.

[0023] In some embodiments, the data processing module combines machine learning algorithms and numerical models to automatically process and analyze the signals collected by the data collector to accurately monitor the displacement, strain and stress at the laboratory fault;

[0024] With respect to the displacement signal, the data processing module performs correction and smoothing processing on the displacement signal, and improves the accuracy of displacement measurement in combination with a regression model;

[0025] For the strain signal, the data processing module reconstructs the global strain field of the laboratory fault and optimizes the global strain field data analysis by combining multi-point sensor data with a deep neural network;

[0026] With respect to the stress signal, the data processing module solves the inverse problem of the finite element model of the fault model and the collected stress signal, and uses machine learning to inversely infer the stress distribution of the laboratory fault.

[0027] In some embodiments, the control and monitoring unit includes a control module and a monitoring platform connected to each other, wherein the control module is used to control the loading device and data acquisition to ensure the stability and repeatability of the experiment; and the monitoring platform provides real-time monitoring and data display functions of the experimental process.

[0028] The laboratory fault monitoring system provided by the embodiment of the present invention has the following characteristics and beneficial effects:

[0029] 1) Through the deployment of optical fiber sensors, the high spatial resolution and sensitivity requirements that are difficult to achieve with traditional experimental observation systems can be met.

[0030] 2) Combine multi-channel data acquisition and machine learning technology to achieve automated processing and model analysis of experimental data.

[0031] 3) Use intelligent algorithms to improve the accuracy and efficiency of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a laboratory fault monitoring system provided by an embodiment of the present invention;

[0033] Numbers in the figure: 1—first sub-model; 2—second sub-model; 3—loading device; 4—optical fiber sensor. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. The following scheme is only used as an explanation of the inventive concept, and the specific scheme is not limited thereto. In addition, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, rather than the entire process.

[0035] On the contrary, the present application covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present application as defined by the claims. Further, in order to make the public have a better understanding of the present application, some specific details are described in detail in the detailed description of the present application below. Those skilled in the art can fully understand the present application without the description of these details.

[0036] See also Figure 1 , an embodiment of the present invention provides a laboratory fault monitoring system, the system mainly includes:

[0037] The fault model includes a first sub-model 1 and a second sub-model 2. The first sub-model 1 and the second sub-model 2 use the same right-angled triangle plate, and the inclined surfaces of the first sub-model 1 and the second sub-model 2 are attached to each other to form a laboratory fault at the attachment point.

[0038] The loading device 3 is arranged around the fault model to realize biaxial loading of the fault model and simulate the occurrence of an earthquake;

[0039] The optical fiber sensor unit comprises at least one optical fiber sensor 4 arranged near the surface of the laboratory fault, and is used to realize continuous acquisition of corresponding physical parameter signals at the laboratory fault;

[0040] A data acquisition and processing unit, including a data acquisition device and a data processing module, monitors the physical parameters of the laboratory earthquake fault in real time based on the physical parameter signals acquired by the optical fiber sensor unit;

[0041] The control and monitoring unit is connected with the loading device 3 and the data acquisition and processing unit to facilitate the control of the stability of the experiment and the observation and analysis of the experimental results.

[0042] In some embodiments, the fault model is a rectangular plate structure formed by splicing a first sub-model 1 and a second sub-model 2. The two sub-models have exactly the same shape and size, and the laboratory fault formed between the first sub-model 1 and the second sub-model 2 is located exactly on a diagonal line of the fault model.

[0043] Optionally, the first sub-model 1 and the second sub-model 2 both use isosceles right-angled triangle plates, the right-angled side length of each sub-model is about 50 cm, and the thickness of each sub-model is about 2 cm.

[0044] In some embodiments, the first sub-model 1 and the second sub-model 2 are made of the same material, and an acrylic material having a wave velocity close to that of an actual rock formation is selected. In addition, the acrylic material is easy to process and can better simulate the properties of an actual earthquake fault.

[0045] Furthermore, the inclined surfaces of each sub-model are formed by sandblasting with high-speed abrasive particles ejected through 0.2Mpa-0.8Mpa high-pressure gas to impact, cut and erode the originally smooth inclined surfaces on each sub-model to form a rough surface, thereby simulating the rough fault surface morphology to achieve roughness processing.

[0046] Furthermore, after the roughness of the fault surface is processed, a high-pressure airflow of 0.3Mpa-1Mpa is used to clean the fault surface to remove the residual particles on the fault surface.

[0047] Furthermore, the four top corners of the fault model are chamfered to reduce stress concentration at the ends.

[0048] In some embodiments, the loading device 3 includes a main structure, which is a U-shaped integral casting frame, the inner side wall of the main structure does not contact the outer side wall of the fault model, and the fault model is surrounded by ( Figure 1The upper, lower, left and right sides are shown in the figure. Each of the servo cylinders and servo control valves supported on the corresponding side walls of the main structure is provided with a corresponding digital closed-loop servo controller, a high-precision load sensor and a high-precision displacement sensor. A loading plate is fixed to the piston rod end of each servo cylinder. The loading plate contacts the corresponding side of the fault model during loading. The digital closed-loop servo controller, the high-precision load sensor and the high-precision displacement sensor are connected to the control module in the control and monitoring unit. When applying pressure load to the fault model, the control module is operated to load the horizontal and vertical forces to the preset load value at the same time, and then the horizontal pressure is kept unchanged, and the vertical direction is switched to displacement control. The loading speed is 1μm / s. The high-precision sensor measures and feeds back the current load or displacement. The digital closed-loop servo controller performs double closed-loop PID calculation, outputs control signals, drives the servo cylinder control valve, and realizes high-precision displacement control and load control of the servo cylinder.

[0049] In some embodiments, the optical fiber sensor 4 in the optical fiber sensor unit is arranged along the surface and / or near the laboratory fault formed between the two sub-models, and the direction of the optical fiber sensor 4 is parallel to the direction of the laboratory fault. The layout position and density of the optical fiber sensor 4 can be set according to the experimental requirements. The optical fiber sensor 4 can adopt a commercially available fiber Bragg grating sensor or a distributed optical fiber sensor to obtain any one or more physical quantity signals of strain, stress, displacement, etc. at the laboratory fault in real time. The optical fiber sensor 4 includes an optical fiber strain sensor, a stress sensor, and a displacement sensor, which can record the strain, stress, and displacement changes of the laboratory fault in real time during the slip process, with high sensitivity and a resolution of up to micrometer level.

[0050] In a specific embodiment of the present application, an optical fiber sensor 4 is arranged on the surface of the laboratory fault and on both sides thereof, that is, a total of three optical fiber sensors are arranged, and the distance between the optical fiber sensors on both sides and the center of the laboratory fault is about 2 mm. The three optical fiber sensors are used to measure strain, stress and displacement respectively.

[0051] In some embodiments, when the optical fiber sensor unit contains multiple optical fiber sensors 4, the data acquisition unit in the data acquisition and processing unit adopts a multi-channel data acquisition unit for collecting signals from multiple optical fiber sensors, and the collected signals include physical quantities such as strain, displacement and stress of the laboratory fault. The data processing module accurately monitors displacement, strain and stress by combining machine learning algorithms and numerical models. First, the displacement signal obtained by the optical fiber sensor is corrected and smoothed, and the accuracy of displacement measurement is improved by combining the regression model. Strain monitoring reconstructs the global strain field of the laboratory fault and optimizes the global strain field data analysis by combining multi-point sensor data with a deep neural network. Stress monitoring solves the inverse problem of the finite element model of the fault model and the collected stress signal data, and uses machine learning to invert and infer the stress distribution of the laboratory fault. The data processing module of this embodiment can provide the changing characteristics of displacement, strain and stress in real time and accurately under complex working conditions, and supports efficient analysis and prediction of experimental data.

[0052] In some embodiments, the control and monitoring unit includes a control module and a monitoring platform connected to each other, which is convenient for controlling the stability of the experiment, observing and analyzing the experimental results; wherein the control module is connected to the loading device 3 and the data acquisition and processing unit, and is used to control the loading device 3 and data acquisition to ensure the stability and repeatability of the experiment. Specifically, the control module is connected to the digital closed-loop servo controller, the high-precision load sensor and the high-precision displacement sensor in the loading device 3. The monitoring platform provides real-time monitoring and data display functions of the experimental process, and can display the change curves of stress, strain, displacement and other data, and realize the monitoring of the spatiotemporal continuous change law of the stress field, strain field and displacement field of the fault contact surface, which is convenient for the analysis of subsequent experimental data.

[0053] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "install", "connect", "connect", and "set" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0054] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the description of the present application, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0055] Although embodiments of the present disclosure have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents.

Claims

1. A laboratory fault monitoring system, characterized in that: include: A fault model, comprising a first sub-model and a second sub-model, wherein the first sub-model and the second sub-model use the same right-angled triangle plate, and the inclined surfaces of the first sub-model and the second sub-model are attached to each other to form a laboratory fault at the attached position; A loading device is arranged around the fault model to realize biaxial loading of the fault model to simulate the occurrence of an earthquake; An optical fiber sensor unit, comprising at least one continuous optical fiber sensor arranged near the surface of the laboratory fault, so as to realize continuous acquisition of corresponding physical parameter signals at the laboratory fault; A data acquisition and processing unit, including a data acquisition device and a data processing module, monitors the physical parameters of the laboratory earthquake fault in real time based on the physical parameter signals acquired by the optical fiber sensor unit; The control and monitoring unit is connected with the loading device and the data acquisition and processing unit to facilitate the control of the stability of the experiment and the observation and analysis of the experimental results.

2. The laboratory fault monitoring system according to claim 1, characterized in that: The first sub-model and the second sub-model are made of the same material, an acrylic material having a wave velocity close to that of an actual rock formation.

3. The laboratory fault monitoring system according to claim 1, characterized in that: The inclined surface of each sub-model is a rough surface formed by abrasive particles ejected by 0.2Mpa-0.8Mpa high-pressure gas through sandblasting to impact, cut and erode the originally smooth inclined surface on each sub-model, thereby simulating the rough fault surface morphology.

4. The laboratory fault monitoring system according to claim 3, characterized in that: Before the inclined surfaces of the first sub-model and the second sub-model are attached to each other, the rough surface is cleaned with a high-pressure airflow of 0.3 Mpa-1 Mpa to remove residual particles.

5. The laboratory fault monitoring system according to claim 1, characterized in that: Each corner of the fault model is chamfered to reduce stress concentration at the end.

6. The laboratory fault monitoring system according to claim 1, characterized in that: The loading device includes a main structure, which is a U-shaped integral casting frame. Servo cylinders and servo control valves supported on the corresponding side walls of the main structure are respectively arranged around the fault model, and are equipped with corresponding digital closed-loop servo controllers, load sensors and displacement sensors. A loading plate is fixed to the end of the piston rod of each servo cylinder. During the loading process, the loading plate contacts the corresponding side of the fault model. The digital closed-loop servo controller, the load sensor and the displacement sensor are connected to the control and monitoring unit.

7. The laboratory fault monitoring system according to claim 1, characterized in that: The optical fiber sensor adopts an optical fiber Bragg grating sensor or a distributed optical fiber sensor, and is used to obtain any one or more of the strain signal, stress signal and displacement signal at the laboratory fault in real time.

8. The laboratory fault monitoring system according to claim 1, characterized in that: The data collector is a multi-channel data collector for collecting signals from the optical fiber sensor, and the collected signals include any one or more of the strain signal, stress signal and displacement signal at the laboratory fault.

9. The laboratory fault monitoring system according to claim 8, characterized in that: The data processing module combines machine learning algorithms and numerical models to automatically process and analyze the signals collected by the data collector to accurately monitor the displacement, strain and stress at the laboratory fault; With respect to the displacement signal, the data processing module performs correction and smoothing processing on the displacement signal, and improves the accuracy of displacement measurement in combination with a regression model; For the strain signal, the data processing module reconstructs the global strain field of the laboratory fault and optimizes the global strain field data analysis by combining multi-point sensor data with a deep neural network; With respect to the stress signal, the data processing module solves the inverse problem of the finite element model of the fault model and the collected stress signal, and uses machine learning to inversely infer the stress distribution of the laboratory fault.

10. The laboratory fault monitoring system according to claim 1, characterized in that: The control and monitoring unit includes a control module and a monitoring platform connected to each other. The control module is used to control the loading device and data acquisition to ensure the stability and repeatability of the experiment; the monitoring platform provides real-time monitoring and data display functions of the experimental process.

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