Coal rock dynamic disaster monitoring and early warning system and method

Abstract

The invention discloses a coal rock dynamic disaster monitoring and early warning system, which comprises a distributed sound wave monitoring system, and is characterized in that the distributed sound wave monitoring system is communicated with mining armored optical cables, and the mining armored optical cables are distributed in a plurality of detection areas; the distributed sound wave monitoring system is connected with the Socket server, and the Socket server is connected with the Web server and the alarm unit. The coal rock dynamic disaster monitoring and early warning method comprises the following steps: carrying out initialization setting on the coal rock dynamic disaster monitoring and early warning system; an optical signal is sent to the mining armored optical cable; collecting detection area information and processing and extracting coal rock dynamic disaster characteristic mode components; and comparing the coal rock dynamic disaster characteristic mode component with a preset condition, and if the preset condition is satisfied, outputting an alarm signal. According to the coal rock dynamic disaster monitoring and early warning system and method, sound wave signals of coal rock dynamic disasters can be collected in a high-precision and sensitive mode, the accuracy and the real-time performance of data collection are ensured, and the timeliness and the reliability of early warning are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine safety monitoring, relates to a coal and rock dynamic disaster monitoring and early warning system, and also relates to a coal and rock dynamic disaster monitoring and early warning system and method. Background Art

[0002] Nowadays, the complexity and depth of coal mining continue to increase, resulting in an increasing frequency, intensity, and damage degree of coal and rock dynamic disasters. Coal and rock dynamic disasters mainly include coal and gas outbursts, rock bursts, and roof accidents, etc. These disasters pose a major threat to mine safety. Although certain progress has been made in existing dynamic disaster monitoring and control technologies, these disasters still occur from time to time, bringing severe challenges to the safe production of mines. Coal and rock dynamic disasters not only directly threaten the lives of miners but also have a great negative impact on the production efficiency and economic benefits of mines. Therefore, how to effectively monitor and early warn coal and rock dynamic disasters has become a key issue in mine safety management.

[0003] Currently, the technologies applicable to mine dynamic disaster monitoring are mainly divided into the following three categories: 1. Manual monitoring: This method mainly relies on manual observation and data recording, with disadvantages such as long cycle, slow response, and limited coverage. It is difficult to capture the early signals of disasters in a timely and accurate manner, lacking real-time performance and early warning capabilities. 2. "Point" monitoring: Represented by coal and rock stress monitoring. Commonly used instruments are mostly contact sensors, mainly used to reflect the stress distribution and structural conditions around coal and rock masses, and it is difficult to early warn the deformation and fracture processes of coal and rock masses. In addition, contact sensors have high coupling requirements for coal and rock masses, and the contact quality between the sensor and coal and rock directly affects the monitoring effect. Therefore, they have limited effects in the monitoring and early warning of dynamic disasters. 3. "Regional" monitoring, mainly including electromagnetic radiation method, acoustic emission method, microseismic method, etc. Although the acoustic emission method and microseismic method can monitor the deformation and fracture processes of coal and rock masses, these methods rely on a large number of sensors and data acquisition devices, with high maintenance costs, and are easily interfered by environmental factors, making it difficult to achieve all-round and distributed monitoring of large-scale areas. In addition, the probes of the acoustic emission and microseismic methods need to be well coupled with coal and rock masses and are easily interfered by surrounding noises, thus affecting the monitoring accuracy and resulting in large errors. The electromagnetic radiation method can dynamically monitor the occurrence process of coal and rock dynamic disasters such as coal and gas outbursts and rock bursts by monitoring the electromagnetic radiation signals and their variation laws when coal and rock masses are loaded. However, the monitoring of the electromagnetic radiation method has multi-solution problems and is prone to false alarms or missed alarms.

[0004] With the continuous increase in the depth of coal mining, the complexity, suddenness, and diversity of dynamic disasters such as rock bursts have become increasingly prominent. Traditional monitoring technologies are faced with a series of problems such as "difficulty in accurately locating the disaster-causing source and unsatisfactory early warning effects". Therefore, it is urgent to improve the monitoring, prediction, and early warning levels of dynamic disasters to minimize the risks and impacts of disasters.

[0005] In summary, the existing technology has problems that traditional coal and rock dynamic disaster monitoring technologies are difficult to accurately locate the disaster-causing source and have unsatisfactory early warning effects. Summary of the Invention

[0006] The purpose of the present invention is to provide a coal and rock dynamic disaster monitoring and early warning system, which solves the problems in the existing technology that coal and rock dynamic disaster monitoring technologies are difficult to accurately locate the disaster-causing source and have unsatisfactory early warning effects.

[0007] Another purpose of the present invention is to provide a coal and rock dynamic disaster monitoring and early warning method.

[0008] The technical solution adopted by the present invention is that a coal and rock dynamic disaster monitoring and early warning system includes a distributed acoustic wave monitoring system. The distributed acoustic wave monitoring system is connected to a mining armored optical cable, and the mining armored optical cable is distributed in several detection areas; the distributed acoustic wave monitoring system is connected to a Socket server, and the Socket server is respectively connected to a Web server and an alarm unit.

[0009] The characteristics of the present invention also lie in: The distributed acoustic wave monitoring system includes a distributed fiber optic acoustic sensing system. The distributed fiber optic acoustic sensing system is respectively connected to a measurement and control and signal processing system and a mining armored optical cable, and the measurement and control and signal processing system is connected to the Socket server.

[0010] The distributed fiber optic acoustic sensing system includes an optical pulse generation module. The optical pulse generation module is respectively connected to an optical quantity detection module and a mining armored optical cable through a circulator; the optical pulse generation module and the optical quantity detection module are respectively connected to the measurement and control and signal processing system.

[0011] The optical pulse generation module includes a narrow linewidth laser. The narrow linewidth laser is connected to an optical fiber coupler, and the optical fiber coupler is respectively connected to an acousto-optic modulator and an optical quantity detection module. The acousto-optic modulator is respectively connected to the measurement and control and signal processing system and an erbium-doped fiber amplifier, and the erbium-doped fiber amplifier is connected to the circulator.

[0012] The optical quantity detection module includes a polarization diversity receiver. The polarization diversity receiver is respectively connected to the optical fiber coupler and the circulator, and the polarization diversity receiver is respectively connected to the measurement and control and signal processing system through a first balanced photodetector and a second balanced photodetector.

[0013] The signal processing system includes a data processing system, which is connected to an FPGA module. The FPGA module is respectively connected to an ADC module and a DAC module. The DAC module is connected to an acousto-optic modulator through a radio frequency amplifier, and the ADC module is respectively connected to a polarization diversity receiver through a first balanced photodetector and a second balanced photodetector.

[0014] Another technical solution adopted by the present invention is a method for monitoring and warning of coal and rock dynamic disasters, including the following steps: Step 1, perform initialization settings on the monitoring and warning system for coal and rock dynamic disasters; The initialization settings include device self-check and parameter configuration; Step 2, send an optical signal to the mining armored optical cable through a distributed acoustic wave monitoring system; Step 3, collect information on the detection area and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 4, compare the characteristic mode components of coal and rock dynamic disasters with preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2.

[0015] The characteristics of another technical solution of the present invention also lie in: Step 2 includes: The narrow-linewidth laser generated by a narrow-linewidth laser generator is modulated by an acousto-optic modulator to form a linearly chirped optical pulse, and then enhanced by an erbium-doped fiber amplifier and injected into the mining armored optical cable.

[0016] Step 3 includes: Step 3.1, obtain the Rayleigh scattering signal and the interference signal of the local narrow-linewidth laser in the detection area through a distributed fiber optic acoustic sensing system, convert the interference signal into an electrical signal and send it to the FPGA module; Step 3.2, the FPGA module performs rotational vector averaging and phase difference operation on the data stream converted by the ADC module to detect the differential phase information at each position of the optical cable in real time; Step 3.3, the data processing system processes the data stream processed by the FPGA module using the MEEMD analysis method to extract the characteristic mode components of coal and rock dynamic disasters with relatively large changes in differential phase.

[0017] Step 4 includes: Step 4.1, compare the characteristic mode components of coal and rock dynamic disasters with a set threshold. If the characteristic mode components of coal and rock dynamic disasters are greater than the set threshold, output a primary warning signal and go to Step 4.2; if the characteristic mode components of coal and rock dynamic disasters are less than the set threshold, go to Step 2; Step 4.2: Compare the duration of the coal and rock dynamic disaster characteristic mode component with the preset time value. If the duration of the coal and rock dynamic disaster characteristic mode component is greater than the preset time value, output a medium-level warning signal and execute Step 4.3; if the duration of the coal and rock dynamic disaster characteristic mode component is less than the preset time value, execute Step Two. Step 4.3: Determine the specific location of the coal and rock dynamic disaster characteristic mode component through the multi-point time difference positioning method. If the coal and rock dynamic disaster characteristic mode component continuously appears at the same location, output a high-level warning; if the coal and rock dynamic disaster characteristic mode component does not continuously appear at the same location, execute Step Two.

[0018] The beneficial effects of the present invention are as follows: 1. High monitoring accuracy and sensitivity. The present invention adopts the distributed acoustic wave sensing technology, which can collect the acoustic wave signals of coal and rock dynamic disasters with high precision and sensitivity, ensuring the accuracy and real-time nature of data collection, and significantly improving the timeliness and reliability of early warning.

[0019] 2. Full-coverage spatial monitoring. Through the distributed sensing system arranged along the optical fiber, full coverage of the detection area is achieved, enabling continuous monitoring of a large-scale mine area and overcoming the defect of limited monitoring range of traditional point sensors.

[0020] 3. Dynamic continuous monitoring and big data support. The system supports continuous dynamic monitoring in terms of time, can collect a large amount of data in real time, provides rich data support for in-depth analysis and disaster trend prediction in the later stage, and enhances the ability to predict disasters.

[0021] 4. Precise positioning and scientific decision-making support. The system can accurately locate the possible positions of dynamic disasters, provide a scientific basis for disaster prevention and treatment, help relevant personnel respond quickly, and effectively reduce disaster risks.

[0022] 5. Accurate early warning. Through the multi-level early warning mechanism, the system can effectively reduce the false alarm rate, improve the accuracy of early warning, ensure the reliability of early warning information, and provide scientific and effective support for disaster prevention and treatment. Description of the Drawings

[0023] Figure 1 is a schematic structural diagram of the coal and rock dynamic disaster monitoring and early warning system of the present invention; Figure 2 is a schematic structural diagram of the distributed acoustic wave monitoring system in the present invention.

[0024] In the figure, 1. Distributed acoustic wave monitoring system; 1-1. Measurement and control and signal processing system; 1-1-1. ADC module; 1-1-2. FPGA module; 1-1-3. Data processing system; 1-1-4. DAC module; 1-1-5. RF amplifier; 1-2, Distributed fiber optic acoustic sensing system; 1-2-1, Narrow linewidth laser; 1-2-2, Fiber optic coupler; 1-2-3, Acousto-optic modulator; 1-2-4, Erbium-doped fiber amplifier; 1-2-5, Circulator; 1-2-6, Polarization diversity receiver; 1-2-7, First balanced photodetector; 1-2-8, Second balanced photodetector; 2, Mine armored optical cable; 3-1, Socket server; 3-2, Web server; 3-3, Alarm unit; 4, Detection area. Specific implementation mode

[0025] The present invention will be described in detail below with reference to the accompanying drawings and specific implementation modes.

[0026] The coal and rock dynamic disaster monitoring and early warning system includes a distributed acoustic wave monitoring system 1. The distributed acoustic wave monitoring system 1 is connected to the mine armored optical cable 2, and the mine armored optical cable 2 is distributed in a number of detection areas 4. The distributed acoustic wave monitoring system 1 is connected to the Socket server 3-1, and the Socket server 3-1 is respectively connected to the Web server 3-2 and the alarm unit 3-3.

[0027] The distributed acoustic wave monitoring system 1 includes a distributed fiber optic acoustic sensing system 1-2. The distributed fiber optic acoustic sensing system 1-2 is respectively connected to the measurement and control and signal processing system 1-1 and the mine armored optical cable 2, and the measurement and control and signal processing system 1-1 is connected to the Socket server 3-1.

[0028] The distributed fiber optic acoustic sensing system 1-2 includes an optical pulse generation module. The optical pulse generation module is respectively connected to the optical quantity detection module and the mine armored optical cable 2 through the circulator 1-2-5. The optical pulse generation module and the optical quantity detection module are respectively connected to the measurement and control and signal processing system 1-1. The optical pulse generation module includes a narrow linewidth laser 1-2-1. The narrow linewidth laser 1-2-1 is connected to the fiber optic coupler 1-2-2. The fiber optic coupler 1-2-2 is respectively connected to the acousto-optic modulator 1-2-3 and the optical quantity detection module. The acousto-optic modulator 1-2-3 is respectively connected to the measurement and control and signal processing system 1-1 and the erbium-doped fiber amplifier 1-2-4. The erbium-doped fiber amplifier 1-2-4 is connected to the circulator 1-2-5. The optical quantity detection module includes a polarization diversity receiver 1-2-6. The polarization diversity receiver 1-2-6 is respectively connected to the fiber optic coupler 1-2-2 and the circulator 1-2-5. The polarization diversity receiver 1-2-6 is respectively connected to the measurement and control and signal processing system 1-1 through the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8.

[0029] The signal processing system 1-1 includes a data processing system 1-1-3. The data processing system 1-1-3 is connected to the FPGA module 1-1-2. The FPGA module 1-1-2 is respectively connected to the ADC module 1-1-1 and the DAC module 1-1-4. The DAC module 1-1-4 is connected to the acousto-optic modulator 1-2-3 through the radio frequency amplifier 1-1-5. The ADC module 1-1-1 is respectively connected to the polarization diversity receiver 1-2-6 through the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8.

[0030] A monitoring and early warning method for coal and rock dynamic disasters includes the following steps: Step 1: Initialize the monitoring and early warning system for coal and rock dynamic disasters; The initialization settings include device self-check and parameter configuration; Step 2: Send an optical signal to the mining armored optical cable 2 through the distributed acoustic wave monitoring system 1; The narrow linewidth laser generated by the narrow linewidth laser 1-2-1 is modulated by the acousto-optic modulator 1-2-2 to form a linearly chirped optical pulse, and then enhanced by the erbium-doped fiber amplifier 1-2-4 and injected into the mining armored optical cable 2; Step 3: Collect the information of the detection area 4 and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 3.1: Obtain the Rayleigh scattering signal and the interference signal of the local narrow linewidth laser in the detection area 4 through the distributed fiber optic acoustic sensing system 1-2, convert the interference signal into an electrical signal and send it to the FPGA module 1-1-2; Step 3.2: The FPGA module 1-1-2 performs rotational vector averaging and phase difference operation on the data stream converted by the ADC module 1-1-1, and then real-time detects the differential phase information at each position of the optical cable; Step 3.3: The data processing system 1-1-3 processes the data stream processed by the FPGA module 1-1-2 using the MEEMD analysis method, and then extracts the characteristic mode components of coal and rock dynamic disasters with large changes in differential phase; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2; Step 4.1: Compare the characteristic mode components of coal and rock dynamic disasters with the set threshold. If the characteristic mode components of coal and rock dynamic disasters are greater than the set threshold, output a primary early warning signal and go to Step 4.2; if the characteristic mode components of coal and rock dynamic disasters are less than the set threshold, go to Step 2; Step 4.2: Compare the duration of the coal and rock dynamic disaster characteristic mode component with the preset time value. If the duration of the coal and rock dynamic disaster characteristic mode component is greater than the preset time value, output a medium-level warning signal and execute Step 4.3; if the duration of the coal and rock dynamic disaster characteristic mode component is less than the preset time value, execute Step Two. Step 4.3: Determine the specific location of the coal and rock dynamic disaster characteristic mode component through the multi-point time difference positioning method. If the coal and rock dynamic disaster characteristic mode component continuously appears at the same location, output a high-level warning; if the coal and rock dynamic disaster characteristic mode component does not continuously appear at the same location, execute Step Two.

[0031] A large number of on-site monitoring data and indoor simulation experiments show that the coal and rock dynamic disaster usually releases a large amount of elastic energy during the process from the deformation to the instability and failure of the coal and rock mass, accompanied by the generation of high-energy and low-frequency seismic sources, which usually manifest as low-frequency sound waves or infrasound waves. The distributed acoustic sensing technology (DAS) used in the present invention monitors the propagation of sound waves and infrasound waves along the optical fiber sensor, and has the advantages of corrosion resistance, high temperature resistance, high pressure resistance, and anti-electromagnetic interference. Compared with the traditional monitoring technology, the distributed acoustic sensing technology can realize continuous monitoring of a large area, has the advantages of high sensitivity and strong real-time performance, and is suitable for the monitoring and early warning of coal and rock dynamic disasters. The present invention accurately locates and warns of coal and rock dynamic disasters by non-contact, distributed, high-density, and real-time monitoring of the anomalies of temperature, low-frequency sound waves, and infrasound waves during the process from the deformation to the instability and failure of the coal and rock mass, so as to improve the monitoring, prediction, and early warning levels of dynamic disasters and minimize the risk and impact of disasters.

[0032] In the present invention, a mine armored optical cable 2 is arranged in the roadway of the coal mine heading face and the fully mechanized mining face. The distributed acoustic monitoring system 1 obtains the temperature, low-frequency sound wave, and infrasound wave data in each detection area in real time through the mine armored optical cable 2 and transmits them to the socket server 3-1. The socket server 3-1 analyzes whether there are abnormal characteristics in the monitoring data, locates the abnormal characteristic position, and determines whether the alarm condition is satisfied; the Web server 3-2 is connected to the socket server 3-1 to display information such as the data processing result, abnormal warning signal, abnormal position, or alarm signal; after receiving the alarm signal through the communication network, the alarm unit 3-3 issues an audible, visual, and vibration alarm.

[0033] The distributed optical fiber acoustic monitoring system 1 includes a distributed optical fiber acoustic sensing system 1-2 and a measurement and control and signal processing system 1-1.

[0034] The distributed fiber optic acoustic sensing system 1-2 is the core part of the distributed fiber optic acoustic wave monitoring system 1, responsible for detecting acoustic signals. Its main components include: an optical pulse generation module, an optical quantity detection module, and a circulator 1-2-5, etc. The optical pulse generation module includes a narrow linewidth laser 1-2-1, an optical fiber coupler 1-2-2, an acousto-optic modulator 1-2-3, an erbium-doped fiber amplifier 1-2-4, etc. The optical quantity detection module includes a polarization diversity receiver 1-2-6 and a balanced photodetector, etc.

[0035] The narrow linewidth laser 1-2-1 is used to emit a narrow linewidth laser with high stability as the light source of the sensing system. Its output end is connected to the input end of the optical fiber coupler 1-2-2 to ensure the efficient transmission of the optical signal. The optical fiber coupler 1-2-2 divides the optical signal emitted by the narrow linewidth laser 1-2-1 into two paths: the first output end is connected to the first input end of the optical quantity detection module to detect the intensity change of the optical signal; the second output end is connected to the first input end of the acousto-optic modulator 1-2-3 to modulate the laser emitted by the narrow linewidth laser 1-2-1 to form a linear swept-frequency optical pulse, which is output to the erbium-doped fiber amplifier 1-2-4. The acousto-optic modulator 1-2-3 uses a radio frequency signal to modulate the narrow linewidth laser emitted by the narrow linewidth laser 1-2-1 to form a linear swept-frequency optical pulse, which is used to modulate the light emitted by the laser into a linear swept-frequency optical pulse signal through gating and output to the erbium-doped fiber amplifier 1-2-4. The erbium-doped fiber amplifier 1-2-4 enhances the optical pulse power output by the acousto-optic modulator and injects it into the mining armored optical cable 2 through the circulator 1-2-5.

[0036] The fiber optic circulator 1-2-5 is used to separate the transmitted optical signal and the received reflected signal. Transmitting end: The high-power optical pulse output by the erbium-doped fiber amplifier 1-2-4 in the optical pulse generation module enters through the first port of the circulator and is output from the second port and transmitted to the mining armored optical cable 2; Receiving end: The reflected signal returned from the mining armored optical cable 2 enters through the second port of the circulator 1-2-4 and is output from the third port and transmitted to the polarization diversity receiver 1-2-6 of the optical quantity detection module.

[0037] The mixed optical signal of the local optical pulse and the reflected light output by the fiber optic coupler 1-2-2 enters the polarization diversity receiver 1-2-6. The polarization diversity receiver 1-2-6 decomposes the mixed optical signal into two orthogonal polarization components, a horizontal polarization component and a vertical polarization component. The two decomposed polarization components are respectively adjusted in phase by an optical phase retarder to ensure the stability of the subsequent interference signal. The two polarization components after phase adjustment are respectively interfered with a reference optical signal, and the interfered optical signals are respectively transmitted to the input ends of the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8. The balanced photodetector converts the received interference optical signal into an electrical signal and outputs it to the input end of the ADC module in the measurement and control and signal processing system 1-1 through a coaxial cable.

[0038] The measurement and control and signal processing system 1-1 is the control and data processing center of the distributed fiber optic acoustic wave monitoring system 1, responsible for signal acquisition, processing, analysis and output. Its main modules include: a data processing system 1-1-3 composed of a GPU and a CPU, a measurement and control core unit FPGA (Field Programmable Gate Array) module 1-1-2 and an ADC (Analog / Digital Conversion) module 1-1-1 and a DAC (Digital / Analog Conversion) module 1-1-4 connected in parallel with it. The FPGA module 1-1-2 generates a digital sweep pulse, the DAC module 1-1-4 converts the digital signal into an analog signal, the radio frequency amplifier 1-1-5 amplifies the analog signal, and the amplified analog signal is sent into the acousto-optic modulator 1-2-3 through a coaxial cable. The input end of the ADC module 1-1-1 is connected to the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8 in the optical quantity detection module of the distributed fiber optic acoustic sensing system 1-2 through a coaxial cable, and is used to collect the electrical signals output by the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8. By processing the electrical signals output by the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8, the intensity, phase and polarization state information of the reflected optical signal can be extracted.

[0039] The coal and rock dynamic disaster monitoring and early warning method realizes the early warning of coal and rock dynamic disasters by collecting and analyzing acoustic wave data in real time, thereby improving the safety production level of coal mines. After the coal and rock dynamic disaster monitoring and early warning system is started, initialization settings are performed such as equipment self-check and parameter configuration, including calibration of distributed acoustic wave sensing equipment, division of detection areas, and configuration of early warning parameters.

[0040] When collecting data, first modulate the narrow-linewidth laser to form a linearly swept optical pulse. After further enhancing the optical power through an erbium-doped fiber amplifier 1-2-4, it is injected into the mining armored optical cable 2. The backscattered Rayleigh signal generated during transmission in the underground coal mine detection area interferes with the local narrow-linewidth laser, and the optical signal after interference is converted into an electrical signal. The rotational vector averaging algorithm is used for processing to eliminate the influence of coherent fading noise, and then phase space difference operation is performed to eliminate the influence of the light source phase noise, obtaining the differential phase information.

[0041] In order to obtain the Rayleigh scattering signals at each position of the optical fiber in the detection area 4 in real time, the FPGA module 1-1-2 performs rotational vector averaging and phase difference operation on the data stream converted by the ADC module 1-1-1 to detect the differential phase information at each position of the optical cable in real time. When analyzing the monitoring data, the data processing system 1-1-3 analyzes the acoustic wave data in real time and extracts the characteristic parameters of coal and rock dynamic disasters.

[0042] In order to further improve the detection accuracy and reduce the influence of environmental noise on the signal, the improved Multivariate Ensemble Empirical Mode Decomposition (MEEMD) is performed on the demodulated differential signal to extract the signal with a large change in differential phase and accurately locate the area where coal and rock dynamic disasters may occur. MEEMD does not require prior determination or forced given basis functions, but depends on the characteristics of the signal itself and decomposes adaptively. It has a good decomposition effect on intermittent signals. Its characteristics are: perform MEEMD on the demodulated differential signal. Each IMF (Intrinsic Mode Function, IMF) after decomposition represents a basic mode. Select the mode component representing the characteristics of coal and rock dynamic disasters and perform signal reconstruction to obtain the acoustic wave signal only containing coal and rock dynamic disasters.

[0043] When determining whether the characteristics of dynamic disasters exist, first compare the pattern components of the dynamic disaster characteristics with a preset threshold to determine whether the extracted dynamic disaster characteristics exist. If the characteristic component does not exceed the threshold, return to the data acquisition step; if a certain area of the characteristic component exceeds the threshold, that is, a coal and rock dynamic disaster may occur in this area, it is judged as a primary warning and enter the next judgment. The characteristic persistence judgment is to determine whether the extracted pattern components of the dynamic disaster characteristics continuously exist within a set time range. If the characteristics do not continuously exist, return to the data acquisition step; if the characteristics continuously exist, it is judged as an intermediate warning and enter the next judgment. The dynamic disaster characteristic positioning is to locate the continuously existing characteristics through the multi-point time difference positioning method to determine the specific location where a coal and rock dynamic disaster may occur. The characteristic position consistency judgment is to determine whether the continuously existing dynamic disaster characteristics appear at the same position. If the characteristics appear at different positions, return to the data acquisition step; if the characteristics continuously appear at the same position, it is judged as a high-level warning and trigger an alarm. When it is detected that the dynamic disaster characteristics continuously appear at the same position, the system issues a warning signal to prompt relevant personnel to take countermeasures.

[0044] Embodiment 1 This embodiment proposes a coal and rock dynamic disaster monitoring and warning system, as Figure 1 shown, including a distributed acoustic wave monitoring system 1, the distributed acoustic wave monitoring system 1 is connected to a mining armored optical cable 2, and the mining armored optical cable 2 is distributed in several detection areas 4; the distributed acoustic wave monitoring system 1 is connected to a Socket server 3-1, and the Socket server 3-1 is respectively connected to a Web server 3-2 and an alarm unit 3-3.

[0045] Embodiment 2 This embodiment proposes a coal and rock dynamic disaster monitoring and warning system, as Figure 1 shown, including a distributed acoustic wave monitoring system 1, the distributed acoustic wave monitoring system 1 is connected to a mining armored optical cable 2, and the mining armored optical cable 2 is distributed in several detection areas 4; the distributed acoustic wave monitoring system 1 is connected to a Socket server 3-1, and the Socket server 3-1 is respectively connected to a Web server 3-2 and an alarm unit 3-3. Combining Figure 2 shown, the distributed acoustic wave monitoring system 1 includes a distributed fiber optic acoustic sensing system 1-2, the distributed fiber optic acoustic sensing system 1-2 is respectively connected to a measurement and control and signal processing system 1-1 and a mining armored optical cable 2, and the measurement and control and signal processing system 1-1 is connected to the Socket server 3-1.

[0046] Embodiment 3 This embodiment proposes a coal and rock dynamic disaster monitoring and warning system, as Figure 1As shown, it includes a distributed acoustic wave monitoring system 1. The distributed acoustic wave monitoring system 1 is connected to a mining armored optical cable 2, and the mining armored optical cable 2 is distributed in several detection areas 4. The distributed acoustic wave monitoring system 1 is connected to a Socket server 3-1, and the Socket server 3-1 is respectively connected to a Web server 3-2 and an alarm unit 3-3.

[0047] Combined with Figure 2 As shown, the distributed acoustic wave monitoring system 1 includes a distributed fiber optic acoustic sensing system 1-2. The distributed fiber optic acoustic sensing system 1-2 is respectively connected to a measurement and control and signal processing system 1-1 and a mining armored optical cable 2, and the measurement and control and signal processing system 1-1 is connected to the Socket server 3-1. The distributed fiber optic acoustic sensing system 1-2 includes an optical pulse generation module. The optical pulse generation module is respectively connected to an optical quantity detection module and a mining armored optical cable 2 through a circulator 1-2-5. The optical pulse generation module and the optical quantity detection module are respectively connected to the measurement and control and signal processing system 1-1. The optical pulse generation module includes a narrow linewidth laser 1-2-1. The narrow linewidth laser 1-2-1 is connected to an optical fiber coupler 1-2-2. The optical fiber coupler 1-2-2 is respectively connected to an acousto-optic modulator 1-2-3 and an optical quantity detection module. The acousto-optic modulator 1-2-3 is respectively connected to the measurement and control and signal processing system 1-1 and an erbium-doped fiber amplifier 1-2-4. The erbium-doped fiber amplifier 1-2-4 is connected to the circulator 1-2-5. The optical quantity detection module includes a polarization diversity receiver 1-2-6. The polarization diversity receiver 1-2-6 is respectively connected to the optical fiber coupler 1-2-2 and the circulator 1-2-5. The polarization diversity receiver 1-2-6 is respectively connected to the measurement and control and signal processing system 1-1 through a first balanced photodetector 1-2-7 and a second balanced photodetector 1-2-8.

[0048] Example 4 This example proposes a coal and rock dynamic disaster monitoring and early warning system. As Figure 1 shown, it includes a distributed acoustic wave monitoring system 1. The distributed acoustic wave monitoring system 1 is connected to a mining armored optical cable 2, and the mining armored optical cable 2 is distributed in several detection areas 4. The distributed acoustic wave monitoring system 1 is connected to a Socket server 3-1, and the Socket server 3-1 is respectively connected to a Web server 3-2 and an alarm unit 3-3. Combined with Figure 2As shown in the figure, the distributed acoustic wave monitoring system 1 includes a distributed fiber optic acoustic sensing system 1-2. The distributed fiber optic acoustic sensing system 1-2 is respectively connected to a measurement and control and signal processing system 1-1 and a mine armored optical cable 2. The measurement and control and signal processing system 1-1 is connected to a Socket server 3-1. The distributed fiber optic acoustic sensing system 1-2 includes an optical pulse generation module. The optical pulse generation module is respectively connected to an optical quantity detection module and a mine armored optical cable 2 through a circulator 1-2-5. The optical pulse generation module and the optical quantity detection module are respectively connected to the measurement and control and signal processing system 1-1. The optical pulse generation module includes a narrow linewidth laser 1-2-1. The narrow linewidth laser 1-2-1 is connected to an optical fiber coupler 1-2-2. The optical fiber coupler 1-2-2 is respectively connected to an acousto-optic modulator 1-2-3 and the optical quantity detection module. The acousto-optic modulator 1-2-3 is respectively connected to the measurement and control and signal processing system 1-1 and an erbium-doped fiber amplifier 1-2-4. The erbium-doped fiber amplifier 1-2-4 is connected to the circulator 1-2-5. The optical quantity detection module includes a polarization diversity receiver 1-2-6. The polarization diversity receiver 1-2-6 is respectively connected to the optical fiber coupler 1-2-2 and the circulator 1-2-5. The polarization diversity receiver 1-2-6 is respectively connected to the measurement and control and signal processing system 1-1 through a first balanced photodetector 1-2-7 and a second balanced photodetector 1-2-8. The signal processing system 1-1 includes a data processing system 1-1-3. The data processing system 1-1-3 is connected to an FPGA module 1-1-2. The FPGA module 1-1-2 is respectively connected to an ADC module 1-1-1 and a DAC module 1-1-4. The DAC module 1-1-4 is connected to the acousto-optic modulator 1-2-3 through a radio frequency amplifier 1-1-5. The ADC module 1-1-1 is respectively connected to the polarization diversity receiver 1-2-6 through the first balanced photodetector 1-2-7 and the second balanced photodetector 1-2-8.

[0049] Embodiment 5 This embodiment proposes a method for monitoring and warning coal and rock dynamic disasters, including the following steps: Step 1: Initialize the coal and rock dynamic disaster monitoring and warning system; The initialization settings include device self-check and parameter configuration; Step 2: Send an optical signal to the mine armored optical cable 2 through the distributed acoustic wave monitoring system 1; Step 3: Collect information on the detection area 4 and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output. If the preset conditions are not met, go to Step 2.

[0050] Embodiment 6 This embodiment proposes a method for monitoring and warning of coal and rock dynamic disasters, including the following steps: Step 1: Initialize the monitoring and warning system for coal and rock dynamic disasters; The initialization settings include device self-check and parameter configuration; Step 2: Send an optical signal to the mining armored optical cable 2 through the distributed acoustic wave monitoring system 1; The narrow-linewidth laser generated by the narrow-linewidth laser 1-2-1 is modulated by the acousto-optic modulator 1-2-2 to form a linearly chirped optical pulse, which is then enhanced by the erbium-doped fiber amplifier 1-2-4 and injected into the mining armored optical cable 2.

[0051] Step 3: Collect information on the detection area 4 and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2.

[0052] Embodiment 7 This embodiment proposes a method for monitoring and warning of coal and rock dynamic disasters, including the following steps: Step 1: Initialize the monitoring and warning system for coal and rock dynamic disasters; The initialization settings include device self-check and parameter configuration; Step 2: Send an optical signal to the mining armored optical cable 2 through the distributed acoustic wave monitoring system 1; Step 3: Collect information on the detection area 4 and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 3.1: Obtain the interference signal between the Rayleigh scattering signal in the detection area 4 and the local narrow-linewidth laser through the distributed fiber optic acoustic sensing system 1-2, convert the interference signal into an electrical signal, and send it to the FPGA module 1-1-2; Step 3.2: The FPGA module 1-1-2 performs rotational vector averaging and phase difference operation on the data stream converted by the ADC module 1-1-1 to detect the differential phase information at each position of the optical cable in real time; Step 3.3: The data processing system 1-1-3 processes the data stream processed by the FPGA module 1-1-2 using the MEEMD analysis method to extract the characteristic mode components of coal and rock dynamic disasters with relatively large changes in differential phase; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2.

[0053] Embodiment 8 This embodiment proposes a method for monitoring and warning of coal and rock dynamic disasters, including the following steps: Step 1: Initialize the coal and rock dynamic disaster monitoring and early warning system; The initialization settings include device self-check and parameter configuration; Step 2: Send optical signals to the mining armored optical cable 2 through the distributed acoustic wave monitoring system 1; Step 3: Collect information on the detection area 4 and use the MEEMD analysis method to process and extract the characteristic mode components of coal and rock dynamic disasters; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2; Step 4.1: Compare the characteristic mode components of coal and rock dynamic disasters with the set threshold. If the characteristic mode components of coal and rock dynamic disasters are greater than the set threshold, output a primary early warning signal and go to Step 4.2; if the characteristic mode components of coal and rock dynamic disasters are less than the set threshold, go to Step 2; Step 4.2: Compare the duration of the characteristic mode components of coal and rock dynamic disasters with the preset time value. If the duration of the characteristic mode components of coal and rock dynamic disasters is greater than the preset time value, output an intermediate early warning signal and go to Step 4.3; if the duration of the characteristic mode components of coal and rock dynamic disasters is less than the preset time value, go to Step 2; Step 4.3: Determine the specific location of the characteristic mode components of coal and rock dynamic disasters through the multi-point time difference positioning method. If the characteristic mode components of coal and rock dynamic disasters continuously appear at the same location, output a high-level early warning; if the characteristic mode components of coal and rock dynamic disasters do not continuously appear at the same location, go to Step 2.

[0054] The embodiment of the present invention is used in a large underground coal mine with an annual output of 8 million tons, and its mining depth is 600 meters. The average thickness of the coal seam is 2.5 meters, and the fully-mechanized mining technology of mining the whole seam at one time is adopted; the roof is hard sandstone with strong impact tendency. Select the return airway of a typical rock burst risk working face as the detection area, and the length of the roadway is 3000 meters. The monitoring plan is as follows: Two mining armored optical cables 2 are symmetrically arranged along the two sides of the roadway at an interval of 5.2 meters, and 1 optical fiber length calibration point is set every 50 meters. Install the distributed fiber optic acoustic wave monitoring system 1 in the ground monitoring room.

[0055] Installation of the server and the alarm unit: Install the server and the alarm unit 3-3 in the ground monitoring room.

[0056] Parameter configuration: The system sampling frequency is set to 4 kHz. There are 3 levels of early warning: the primary early warning is set as the strain change rate > 0.5 με / s, the intermediate early warning is set as the strain change rate > 1 με / s for 10 minutes continuously, and the high-level early warning is set as the strain change rate > 2 με / s for 20 minutes continuously at the same location.

[0057] Operation effect: The daily average data acquisition volume is about 800 GB, and the effective signal capture rate is 99.2%; 3 rock burst accidents have been successfully warned, with an average early warning time of 42 minutes, the highest warning accuracy rate of 97.6%, and a false alarm rate of 2.1%.

Claims

1. Coal and rock dynamic disaster monitoring and early warning system, characterized in that, It includes a distributed acoustic wave monitoring system (1), which is connected to a mining armored optical cable (2), and the mining armored optical cable (2) is distributed in a number of detection areas (4); the distributed acoustic wave monitoring system (1) is connected to a Socket server (3-1), and the Socket server (3-1) is respectively connected to a Web server (3-2) and an alarm unit (3-3).

2. The coal and rock dynamic disaster monitoring and early warning system according to claim 1, characterized in that, The distributed acoustic wave monitoring system (1) includes a distributed fiber optic acoustic sensing system (1-2), and the distributed fiber optic acoustic sensing system (1-2) is respectively connected to a measurement and control and signal processing system (1-1) and a mining armored optical cable (2), and the measurement and control and signal processing system (1-1) is connected to the Socket server (3-1).

3. The coal and rock dynamic disaster monitoring and early warning system according to claim 2, characterized in that The distributed fiber optic acoustic sensing system (1-2) includes an optical pulse generation module, and the optical pulse generation module is respectively connected to an optical quantity detection module and a mining armored optical cable (2) through a circulator (1-2-5); the optical pulse generation module and the optical quantity detection module are respectively connected to the measurement and control and signal processing system (1-1).

4. The coal and rock dynamic disaster monitoring and early warning system according to claim 3, characterized in that, The optical pulse generation module includes a narrow linewidth laser (1-2-1), the narrow linewidth laser (1-2-1) is connected to an optical fiber coupler (1-2-2), the optical fiber coupler (1-2-2) is respectively connected to an acousto-optic modulator (1-2-3) and an optical quantity detection module, the acousto-optic modulator (1-2-3) is respectively connected to the measurement and control and signal processing system (1-1) and an erbium-doped fiber amplifier (1-2-4), and the erbium-doped fiber amplifier (1-2-4) is connected to the circulator (1-2-5).

5. The coal and rock dynamic disaster monitoring and early warning system according to claim 4, wherein, The optical quantity detection module includes a polarization diversity receiver (1-2-6), the polarization diversity receiver (1-2-6) is respectively connected to the optical fiber coupler (1-2-2) and the circulator (1-2-5), and the polarization diversity receiver (1-2-6) is respectively connected to the measurement and control and signal processing system (1-1) through a first balanced photodetector (1-2-7) and a second balanced photodetector (1-2-8).

6. The coal and rock dynamic disaster monitoring and early warning system according to claim 5, characterized in that, The signal processing system (1-1) includes a data processing system (1-1-3), the data processing system (1-1-3) is connected to an FPGA module (1-1-2), the FPGA module (1-1-2) is respectively connected to an ADC module (1-1-1) and a DAC module (1-1-4), the DAC module (1-1-4) is connected to the acousto-optic modulator (1-2-3) through a radio frequency amplifier (1-1-5), and the ADC module (1-1-1) is respectively connected to the polarization diversity receiver (1-2-6) through the first balanced photodetector (1-2-7) and the second balanced photodetector (1-2-8).

7. A method for monitoring and warning coal and rock dynamic disasters, characterized in that, It includes the following steps: Step 1: Perform initialization settings on the coal and rock dynamic disaster monitoring and early warning system; The initialization settings include equipment self-check and parameter configuration; Step 2: Send an optical signal to the mining armored optical cable (2) through the distributed acoustic wave monitoring system (1); Step 3: Collect information of the detection area (4) and process and extract the characteristic mode components of coal and rock dynamic disasters using the MEEMD analysis method; Step 4: Compare the characteristic mode components of coal and rock dynamic disasters with the preset conditions. If the preset conditions are met, an alarm signal is output; if the preset conditions are not met, go to Step 2.

8. The coal and rock dynamic disaster monitoring and early warning method according to claim 7, wherein, The said Step 2 includes: The narrow-linewidth laser generated by the narrow-linewidth laser (1-2-1) is modulated by the acousto-optic modulator (1-2-2) to form a linearly chirped optical pulse, and then enhanced by the erbium-doped fiber amplifier (1-2-4) and injected into the mining armored optical cable (2).

9. The coal and rock dynamic disaster monitoring and early warning method according to claim 7, characterized in that, The said Step 3 includes: Step 3.1: Obtain the Rayleigh scattering signal and the interference signal of the local narrow-linewidth laser within the detection area (4) through the distributed fiber optic acoustic sensing system (1-2), convert the interference signal into an electrical signal and send it to the FPGA module (1-1-2); Step 3.2: The FPGA module (1-1-2) performs rotational vector averaging and phase difference operation on the data stream converted by the ADC module (1-1-1) to detect the differential phase information at each position of the optical cable in real time; Step 3.3: The data processing system (1-1-3) processes the data stream processed by the FPGA module (1-1-2) using the MEEMD analysis method to extract the characteristic mode components of coal and rock dynamic disasters with relatively large changes in differential phase.

10. The coal and rock dynamic disaster monitoring and early warning method according to claim 7, characterized in that The said Step 4 includes: Step 4.1: Compare the characteristic mode components of coal and rock dynamic disasters with the set threshold. If the characteristic mode components of coal and rock dynamic disasters are greater than the set threshold, output a primary warning signal and go to Step 4.2; if the characteristic mode components of coal and rock dynamic disasters are less than the set threshold, go to Step 2; Step 4.2: Compare the duration of the characteristic mode components of coal and rock dynamic disasters with the preset time value. If the duration of the characteristic mode components of coal and rock dynamic disasters is greater than the preset time value, output an intermediate warning signal and go to Step 4.3; if the duration of the characteristic mode components of coal and rock dynamic disasters is less than the preset time value, go to Step 2; Step 4.3: Determine the specific position of the characteristic mode components of coal and rock dynamic disasters through the multi-point time difference positioning method. If the characteristic mode components of coal and rock dynamic disasters continuously appear at the same position, output a high-level warning; if the characteristic mode components of coal and rock dynamic disasters do not continuously appear at the same position, go to Step 2.

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