Multi-parameter synchronous sensing method based on multi-core distributed optical fiber

Abstract

The application relates to the technical field of geotechnical engineering safety monitoring and engineering testing, and provides a multi-parameter synchronous sensing method based on a multi-core distributed optical fiber, which comprises the following steps: drilling a cylindrical monitoring drill hole in a to-be-monitored area affected by mining; implanting a flexible cylindrical sensor into the monitoring drill hole; arranging a coupling consolidation layer between the flexible cylindrical sensor and the hole wall of the monitoring drill hole; connecting the end of the multi-core distributed optical fiber to a multi-protocol distributed optical fiber demodulation system, collecting initial reference data as a relative zero point reference; collecting continuous Brillouin frequency shift data of stress sensing cores and continuous vibration data of microseismic sensing cores in a mining process, and extracting the Brillouin frequency shift variation and the vibration data variation of the continuous Brillouin frequency shift data and the continuous vibration data relative to the relative zero point reference; and based on the Brillouin frequency shift variation and the vibration data variation, continuously mining stress and microseismic multi-parameter data of the whole monitoring drill hole are obtained through calculation.

Description

Technical Field

[0001] This application relates to the field of geotechnical engineering safety monitoring and engineering testing technology, specifically to a multi-parameter synchronous sensing method based on multi-core distributed optical fiber. Background Technology

[0002] In geotechnical engineering projects such as deep mining, tunnel excavation, and dam foundation disturbance, mining activities trigger continuous dynamic evolution of the surrounding rock stress field. Accurate monitoring of mining stress is a core technology for ensuring the stability of engineering structures and the safety of construction and operation. Currently, the industry still relies primarily on traditional point-based monitoring equipment such as hollow inclusion stress gauges and oil bladder stress gauges for mining stress measurement. These monitoring methods have significant technical limitations in practical engineering applications and are difficult to adapt to the full-cycle monitoring needs under complex mining environments.

[0003] Traditional point-based stress monitoring equipment can only collect stress data at discrete points, failing to cover the stress field across the entire structural area of ​​the monitoring region. During the continuous dynamic migration of mining-induced stress with engineering activities, this discrete monitoring model easily misses key nodes of local stress concentration and dynamic stress abrupt changes, failing to fully capture the spatial evolution of the surrounding rock stress field under the influence of mining. Furthermore, the deployment cost of a single point-based monitoring device is high, and the number of devices that can be deployed on-site is extremely limited. It can only interpolate the overall stress field distribution through data from a small number of discrete points, unable to form a continuous, high-density stress distribution characterization within the monitoring area, making it difficult to support refined surrounding rock stability analysis and engineering safety assessment.

[0004] Furthermore, in deep geotechnical engineering, large-scale water conservancy projects, and complex underground spatial structures, the incubation and occurrence of disasters are often accompanied by the intense coupling and evolution of multiple physical fields, such as stress concentration leading to deformation, temperature changes causing thermal stress, and microfracture propagation generating high-frequency micro-vibrations. Therefore, achieving simultaneous monitoring of multiple parameters such as temperature, strain, stress, and vibration is a prerequisite for accurate disaster early warning. However, existing multi-parameter fiber optic monitoring technologies generally have serious shortcomings: conventional distributed optical fibers are sensitive to both strain and temperature simultaneously, making them prone to false alarms; at the same time, the slow creep of the rock mass (static strain) and the vibration generated by microfractures (dynamic strain) are superimposed on each other in terms of physical signals, making it difficult for existing technologies to achieve high-precision temperature-variable decoupling and dynamic-static separation in a single optical fiber or simple bundle.

[0005] Furthermore, traditional point stress gauges are poorly adapted to the harsh environments of mining operations. Complex conditions such as high stress, strong disturbance, and damp corrosion in deep surrounding rock can easily cause damage and failure of a single monitoring device. The failure of a single device will directly lead to the loss of data at the corresponding monitoring location, which will not only disrupt the integrity of the monitoring sequence, but also significantly increase the operation and maintenance costs of the monitoring system and the risk to data reliability. Summary of the Invention

[0006] This application provides a multi-parameter synchronous sensing method based on multi-core distributed optical fiber, which is used to solve the problems of insufficient coverage of single-parameter monitoring of mining stress and cross-sensitivity and signal coupling in the existing technology, so as to realize the co-source, synchronous and continuous sensing of three-dimensional mining stress and vibration.

[0007] According to an embodiment of the first aspect of this application, a multi-parameter synchronous sensing method based on multi-core distributed optical fiber is provided. The multi-parameter synchronous sensing method includes the following steps: Drill cylindrical monitoring boreholes in the monitoring area affected by mining activities; A flexible cylindrical sensor is implanted into the monitoring borehole. The sensor substrate of the flexible cylindrical sensor contains a multi-core distributed optical fiber. The multi-core distributed optical fiber includes a central fiber core located on the central axis of the sensor substrate and multiple peripheral fiber cores distributed around the central axis. The peripheral fiber cores include stress-sensing fiber cores and micro-vibration-sensing fiber cores. The central fiber core and all peripheral fiber cores extend along the axial direction of the sensor substrate and are parallel to each other. A coupling consolidation layer is provided between the flexible cylindrical sensor and the borehole wall, forming a consolidated coupling body between the flexible cylindrical sensor and the surrounding rock of the monitoring borehole. The end of the multi-core distributed optical fiber is connected to a multi-protocol distributed optical fiber demodulation system integrating Brillouin optical time-domain analysis and distributed acoustic sensing. At the initial moment before the arrival of the disturbance, the initial reference data of the central fiber core and all peripheral fiber cores are collected as a relative zero-point reference. During the mining process, continuous Brillouin frequency shift data of the stress-sensing fiber core and continuous vibration data of the microseismic sensing fiber core are collected, and the changes in Brillouin frequency shift and vibration data relative to the relative zero-point reference are extracted. Based on the aforementioned Brillouin frequency shift and vibration data changes, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area are calculated through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model.

[0008] According to one embodiment of this application, drilling a cylindrical monitoring borehole in the monitoring area affected by mining activities includes: According to the preset monitoring plan, monitoring boreholes are drilled in the top, bottom, side or target monitoring body of the surrounding rock in the area to be monitored, along the vertical, horizontal or inclined direction. After the monitoring borehole is completed, high-pressure air or clean water is used to remove rock powder and loose debris from the borehole. The inner diameter of the monitoring borehole is 5mm to 20mm larger than the outer diameter of the sensor, and the depth of the monitoring borehole covers the mining impact range of the area to be monitored.

[0009] According to one embodiment of this application, prior to implanting the flexible cylindrical sensor into the monitoring borehole, the method further includes: A flexible cylindrical substrate adapted to the monitoring borehole was selected as the sensor substrate, and the substrate material has deformation synergy that matches the surrounding rock to be monitored. The multi-core distributed optical fiber is extended along the axial direction of the sensor substrate and arranged parallel to each other. The multi-core distributed optical fiber is then integrated with the sensor substrate through injection molding. The ends of the stress-sensing fiber core group and the micro-vibration-sensing fiber core group are respectively led out through a multi-core fiber optic splitter. The two ends of the sensor substrate are sealed and waterproofed to form a multi-core fiber optic sensing probe with multi-parameter global sensing capability.

[0010] According to one embodiment of this application, the deployment structure of the multi-core distributed optical fiber includes: A multi-core distributed optical fiber consists of one central core and at least three peripheral cores; The peripheral fiber cores are distributed at equal angular intervals along the circumference with the central fiber core as the center, and the axes of both the central fiber core and the peripheral fiber cores are parallel to the axis of the sensor substrate.

[0011] According to one embodiment of this application, the multi-core distributed optical fiber adopts a seven-core structure with one central core and six peripheral cores arranged in parallel; wherein, the central core and three peripheral cores forming a 120° angle with each other on the circumference form a stress sensing channel, and the remaining three peripheral cores forming a 120° angle with each other form a micro-vibration sensing channel.

[0012] According to one embodiment of this application, the step of connecting the end of the multi-core distributed optical fiber to a multi-protocol distributed optical fiber demodulation system integrating Brillouin optical time-domain analysis and distributed acoustic sensing, and collecting initial reference data of the central fiber core and all peripheral fiber cores as a relative zero-point reference at the initial moment before the arrival of a disturbance, includes: Set the spatial sampling interval, acquisition frequency, and measurement range parameters for the multi-protocol distributed optical fiber demodulation system; Throughout the entire mining process, Brillouin frequency shift data of all measuring points on the stress-sensing fiber core were simultaneously acquired using the Brillouin optical time-domain analysis module, and continuous vibration data of all measuring points on the micro-vibration sensing fiber core were simultaneously acquired using the distributed acoustic sensing module. Stable multi-parameter data before and after mining were recorded to obtain a multi-parameter continuous dataset covering the entire sensor domain.

[0013] According to one embodiment of this application, before calculating the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area based on the aforementioned Brillouin frequency shift variation and vibration data variation, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model, the method further includes: Using the Brillouin frequency shift data of the central fiber core as a reference, the interference of ambient temperature fluctuations and the overall axial tension of the surrounding rock on the strain data is eliminated; Based on the linear relationship between Brillouin frequency shift and strain, the local strain distribution of each stress-sensing fiber core along the axial direction of the sensor substrate is calculated; Based on the local strain distribution and spatial arrangement of each stress-sensing fiber core, an apparent curvature vector is constructed, and the local curvature and bending direction angle of each measuring point are calculated. Background noise filtering is performed on the continuous vibration data of the microseismic sensing fiber core to extract the effective microseismic signal.

[0014] According to one embodiment of this application, after calculating the local curvature and bending direction angle of each measuring point, the method further includes: Calculate the local deflection of the corresponding measuring point based on the bending direction angle of each measuring point; We introduce the Frenet-Serret differential equation system and construct a kinematic space orthogonal frame composed of tangent vector, principal normal vector and binormal vector; Using the borehole anchor point as the spatial integration reference point, continuous integration is performed along the axial direction of the sensor substrate to reconstruct the three-dimensional absolute coordinate trajectory of the borehole at the corresponding sampling time.

[0015] According to one embodiment of this application, based on the aforementioned Brillouin frequency shift variation and vibration data variation, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area are calculated through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model, including: Based on the reconstructed three-dimensional absolute coordinate trajectory, the radial displacement distribution increments on each cross section along the depth of the monitored borehole are extracted; Based on the preset layout orientation of the stress-sensing fiber core, extract the dynamic aperture relative deformation of at least three cross sections with a specific included angle. By combining the elastic modulus and Poisson's ratio parameters of the surrounding rock to be monitored, the relative deformation of the borehole diameter is substituted into the stress concentration formula at the borehole edge. By solving the multivariate simultaneous equations, the three-dimensional mining stress additional field components and principal stress increment values ​​of each measuring point are obtained. Based on continuous vibration data from the microseismic sensing fiber core, the three-dimensional coordinates of the source and the rupture energy parameters of the rock mass microseismic event were calculated using a three-component array polarization analysis and spatial grid search algorithm.

[0016] According to one embodiment of this application, after calculating the three-dimensional mining stress additional field components, principal stress increment values, and microseismic parameters of each measuring point, the method further includes: The three-dimensional mining stress parameters and microseismic parameters obtained from each measuring point are correlated one by one with the three-dimensional spatial absolute coordinates of the corresponding measuring point to generate a continuous mining stress and microseismic multi-parameter data set for monitoring the entire borehole area. Based on the multi-parameter data set, an axial continuous mining stress profile curve, a three-dimensional spatial mining stress cloud map, and a microseismic event distribution map of the monitoring borehole are generated; the profile curve, cloud map, and distribution map are used for stability analysis, safety assessment, and multi-physics field collaborative disaster early warning of mining projects.

[0017] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects: This application's multi-parameter synchronous sensing method based on multi-core distributed optical fiber utilizes a flexible cylindrical sensor with integrated multi-core distributed optical fiber. Through continuous optical fibers, it achieves synchronous acquisition of Brillouin frequency shift data from the stress-sensing fiber core and vibration data from the microseismic-sensing fiber core. Then, through three-dimensional spatial morphology reconstruction, a borehole deformation mechanical model, and a microseismic location algorithm, it calculates continuous mining stress and microseismic multi-parameter data. Leveraging the spatial multiplexing characteristics of multi-core optical fiber, a dual-modal sensing system coupling quasi-static stress sensing and high-frequency microseismic sensing is constructed, achieving co-source, synchronous, and full-domain measurement of mining stress and microseismic activity. It eliminates the need for separate stress gauges and microseismic detectors; a multi-parameter four-dimensional spatiotemporal sensing system can be established using only a single multi-core distributed optical fiber. This directly demodulates and monitors synchronous multi-parameter data across the entire borehole area, solving problems such as spatial mismatch, disparate sources of multi-parameter data, weak anti-interference capability, and susceptibility to damage inherent in traditional monitoring methods. This application breaks through the traditional split-type single-parameter monitoring mode, realizing the synchronous perception of mining stress and microseismic activity across the entire borehole. It not only fundamentally solves the core pain points of traditional monitoring, such as large coordinate errors, asynchronous data, and low survival rate in harsh environments, but also achieves a fundamental upgrade in geotechnical engineering monitoring from split-type single-parameter measurement to synchronous measurement of multiple parameters across the entire borehole, providing accurate, real-time, and comprehensive data support for early warning of dynamic disasters in mining engineering.

[0018] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the continuous sampling stress measurement method based on multi-core distributed optical fiber provided in this application.

[0021] Figure 2 This is a schematic diagram of the state of the cylindrical sensor provided in this application implanted in the monitoring borehole (the monitoring borehole is mainly horizontal, but the actual monitoring borehole can also be vertical).

[0022] Figure 3 This is a schematic diagram of the cylindrical sensor with distributed optical fiber provided in this application (solid lines indicate the original positions of the cylindrical sensor and the seven fiber cores, and dashed lines indicate the positions of the cylindrical sensor and the seven fiber cores after being subjected to mining pressure).

[0023] Figure 4 This is a connection diagram of the multi-protocol distributed optical fiber demodulation system provided in this application.

[0024] Figure label: 1. Cylindrical sensor; 11. Central fiber core; 12. Peripheral fiber core; 121. Stress-sensing fiber core; 122. Micro-vibration-sensing fiber core; 2. Coupling consolidation layer; 3. Surrounding rock; 31. Monitoring borehole; 4. Multi-protocol distributed fiber optic demodulation system; 41. BOTDA host or OFDR host; 42. DAS host; 5. Multi-core fiber optic splitter; 6. Multi-physics field coupled early warning data terminal. Detailed Implementation

[0025] The embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but should not be used to limit the scope of this application.

[0026] In the description of the embodiments of this application, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application. In addition, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0027] In the description of the embodiments of this application, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application based on the specific circumstances.

[0028] In the embodiments of this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0029] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0030] According to an embodiment of the first aspect of this application, a multi-parameter synchronous sensing method based on multi-core distributed optical fiber is provided, such as... Figure 1As shown, this method innovatively reuses the internal core array structure of multi-core optical fibers and constructs a dual-modal sensing channel through a spatial multiplexing strategy, achieving integrated monitoring of mining-induced stress field evolution and microseismic activity in the same hole, location, and source. The monitoring system based on this method includes a multi-core optical fiber aperture deformation sensing probe (i.e., cylindrical sensor 1), a multi-core optical fiber splitter 5, a multi-protocol distributed optical fiber demodulation system 4 integrating Brillouin optical time-domain analysis (BOTDA host or OFDR host 41) and distributed acoustic sensing (DAS host 42), and a multi-physics coupled early warning data terminal 6. The sensing probe is a flexible, expandable cylinder, with multi-core optical fibers embedded inside in a geometric trajectory arranged parallel to straight lines at specific angles along the circumference. The probe is pushed into the monitoring deep hole along its entire length and permanently coupled to the borehole wall through high-strength grouting.

[0031] The specific implementation steps of this method are as follows: Drill cylindrical monitoring boreholes 31 in the area to be monitored due to mining impact; (e.g., ...) Figure 2 As shown, a flexible cylindrical sensor 1 is implanted into a monitoring borehole 31. The sensor substrate of the flexible cylindrical sensor 1 contains a multi-core distributed optical fiber. This multi-core distributed optical fiber includes a central fiber core 11 located on the central axis of the sensor substrate and multiple peripheral fiber cores 12 distributed around the central axis. The peripheral fiber cores 12 include stress-sensing fiber cores 121 and micro-vibration-sensing fiber cores 122. The central fiber core 11 and all peripheral fiber cores 12 extend axially along the sensor substrate and are parallel to each other. A coupling consolidation layer 2 is provided between the flexible cylindrical sensor 1 and the borehole wall of the monitoring borehole 31, forming a consolidation coupling body between the flexible cylindrical sensor 1 and the surrounding rock 3 of the monitoring borehole 31. The ends of the multi-core distributed optical fiber are connected to an integrated Brillouin optical fiber. The multi-protocol distributed optical fiber demodulation system 4, which combines time-domain analysis and distributed acoustic sensing, collects initial reference data of the central fiber core 11 and all peripheral fiber cores 12 as a relative zero-point reference at the initial moment before the arrival of mining disturbance. It also collects continuous Brillouin frequency shift data of stress-sensing fiber core 121 and continuous vibration data of microseismic sensing fiber core 122 during mining, and extracts the changes in Brillouin frequency shift and vibration data relative to the relative zero-point reference. Based on the above changes in Brillouin frequency shift and vibration data, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, it calculates the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole 31 through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model.

[0032] By integrating a multi-core distributed optical fiber within a flexible cylindrical sensor 1, the traditional separate stress monitoring and microseismic monitoring are transformed into a single-sensor, full-domain multi-parameter synchronous sensing system. The monitoring borehole 31 provides the sensor with a close-fitting installation space with the surrounding rock 3. The coupling consolidation layer 2 eliminates the interface gap between the sensor and the surrounding rock 3, ensuring lossless transmission of stress and vibration signals from the surrounding rock 3 to the sensing unit. A multi-protocol distributed optical fiber demodulation system 4 synchronously acquires Brillouin frequency shift and vibration signals across the entire optical fiber. Utilizing the spatial multiplexing characteristics of the multi-core optical fiber, it simultaneously acquires stress signals reflecting quasi-static three-dimensional deformation of the borehole and microseismic signals reflecting dynamic rock fracture on the same physical carrier, completely eliminating the spatial coordinate matching error present in traditional dual-system monitoring. Ultimately, it achieves synchronous calculation of mining-induced stress and microseismic multi-parameters across the entire borehole range, providing accurate, consistent, and comprehensive data support for stability analysis and multi-physics collaborative disaster early warning in mining projects.

[0033] The aforementioned multi-parameter synchronous sensing method breaks through the traditional single-parameter monitoring mode of multiple devices being deployed separately. It requires only one drilling operation and one probe implantation to simultaneously complete macroscopic mechanical stress monitoring and microscopic rock mass fracture acoustic monitoring throughout the entire borehole using a single multi-core optical fiber, significantly reducing the workload and hardware costs of mine disaster monitoring. Simultaneously, the all-fiber passive detection structure gives the probe inherent explosion-proof characteristics, and the probe's external flexible material coating can withstand the large deformation and compression of the borehole wall in front of mining operations while also sensitively transmitting high-frequency vibration sound waves, greatly extending the monitoring lifespan under extreme working conditions.

[0034] According to one embodiment of this application, a cylindrical monitoring borehole 31 is drilled in the area to be monitored by mining, including: drilling the monitoring borehole 31 in the top plate, bottom plate, sidewall or target monitoring body of the surrounding rock 3 in the area to be monitored in a vertical, horizontal or inclined direction according to a preset monitoring plan; after the monitoring borehole 31 is drilled, rock powder and loose debris in the borehole are removed by high pressure air or clean water; wherein, the inner diameter of the monitoring borehole 31 is 5mm to 20mm larger than the outer diameter of the sensor, and the depth of the monitoring borehole 31 covers the mining impact range of the area to be monitored.

[0035] The aforementioned drilling process for monitoring borehole 31 provides installation space for multi-parameter synchronous sensing sensors that conforms to industry standards. The option of multiple locations and directions allows for adaptation to the monitoring needs of different parts of the surrounding rock 3: vertical boreholes are used for monitoring the top and bottom plates, horizontal boreholes for monitoring the ribs or sidewalls, and inclined boreholes for specific stress field analysis. Hole cleaning eliminates the adverse effects of debris inside the borehole on subsequent coupling effects. The parameter design of the inner diameter and depth ensures both smooth sensor implantation and provides uniform filling space for the coupling consolidation layer 2, guaranteeing the uniformity and accuracy of stress and vibration signal transmission.

[0036] In some embodiments, before drilling the monitoring borehole 31, the inner diameter, depth, orientation, and layout points of the monitoring borehole 31 are determined according to a preset monitoring plan. The borehole opening position is marked, and matching drilling tools are selected to carry out the drilling operation. After the hole cleaning operation is completed, the integrity of the borehole wall and the axial deviation of the monitoring borehole 31 are checked to ensure that there are no problems such as borehole collapse or diameter reduction, and that the axial deviation meets the sensor installation requirements. The actual depth and inner diameter of the monitoring borehole 31 are verified to ensure that the drilling parameters are completely matched with the size of the flexible cylindrical sensor 1 and the monitoring requirements.

[0037] According to one embodiment of this application, before implanting the flexible cylindrical sensor 1 into the monitoring borehole 31, the method further includes: selecting a flexible cylindrical substrate adapted to the monitoring borehole 31 as the sensor substrate, wherein the substrate material has deformation compatibility matching the surrounding rock 3 to be monitored; extending multi-core distributed optical fibers along the axial direction of the sensor substrate and arranging them parallel to each other, and integrating the multi-core distributed optical fibers with the sensor substrate through an injection molding process; leading out the ends of the stress sensing fiber core group and the micro-vibration sensing fiber core group respectively through the multi-core optical fiber splitter 5; and sealing and waterproofing both ends of the sensor substrate to form a multi-core optical fiber sensing probe with multi-parameter global sensing capability.

[0038] The sensor prefabrication process is the core foundation for achieving synchronous sensing of multiple parameters. A flexible cylindrical substrate adapted to the monitoring borehole 31 provides a stable deployment carrier for the multi-core distributed optical fiber. Simultaneously, through a material design coordinated with rock deformation, it ensures that the sensor can undergo large deformations synchronously with the surrounding rock 3 without being damaged. The injection molding process tightly integrates the multi-core distributed optical fiber with the sensor substrate, eliminating relative slippage between the fiber and the substrate and ensuring accurate transmission of strain and vibration signals. Figure 4 As shown, the multi-core fiber optic splitter 5 separates different functional fiber cores within the same multi-core fiber and leads them out to their respective demodulation modules (e.g., connecting the end of the stress-sensing fiber core 121 to the Brillouin optical time-domain analysis module, and connecting the end of the micro-vibration-sensing fiber core 121 to the distributed acoustic sensing module), thus realizing a space-division multiplexing optical path architecture. Sealed and waterproof encapsulation protects the fiber optic connectors from corrosion in the humid underground environment, improving the long-term reliability of the sensors. It should be noted that... Figure 4 The "11+121" indicates that one of the four optical fibers is the central fiber core, and the other three are stress-sensing fiber cores. Figure 4 The number "41" in the code can be either a BOTDA host or an OFDR host.

[0039] In some embodiments, the sensor substrate is made of polyurethane material, with a substrate diameter 5-20 mm smaller than the inner diameter of the monitoring borehole 31, and a length adapted to the depth of the monitoring borehole 31. During injection molding, the injection pressure and temperature are controlled to ensure that the multi-core distributed optical fiber remains straight and parallel inside the sensor substrate, without bending or twisting. The sensor ends are encapsulated with stainless steel sealing connectors, the inside of which is filled with waterproof sealant, and the outer layer is wrapped with a glass fiber reinforcement layer to improve the sensor's impact and tensile strength. For long-distance monitoring needs, multiple multi-core fiber optic sensing probes can be connected in series via low-loss optical fiber fusion splicing, with the splice encapsulated in a stainless steel sealing protective sleeve to form a long-distance multi-parameter monitoring network.

[0040] According to one embodiment of this application, such as Figure 3 As shown, the multi-core distributed optical fiber layout structure includes: the multi-core distributed optical fiber includes a central fiber core 11 and at least three peripheral fiber cores 12; the peripheral fiber cores 12 are distributed at equal angular intervals along the circumference with the central fiber core 11 as the center, and the axes of the central fiber core 11 and the peripheral fiber cores 12 are parallel to the axis of the sensor substrate.

[0041] Multiple independent fiber cores form the core carrier for constructing a dual-modal, multi-parameter sensing system. The central fiber core 11, located on the central axis of the sensor substrate, is unaffected by bending strain and can serve as a reference for temperature and axial tensile force compensation. The peripheral fiber cores 12 are distributed at equal angular intervals along the circumference and are functionally grouped to undertake stress sensing and microseismic sensing tasks, providing multiple sets of independent basic data for three-dimensional spatial morphology reconstruction and microseismic source localization.

[0042] According to one embodiment of this application, such as Figure 3 As shown, the multi-core distributed optical fiber adopts a seven-core structure with one central fiber core 11 and six peripheral fiber cores 12 arranged in parallel. Among them, the central fiber core 11 and the three peripheral fiber cores 12 at a 120° angle to each other on the circumference form a stress sensing channel, and the remaining three peripheral fiber cores 12 at a 120° angle to each other form a micro-seismic sensing channel.

[0043] The spatial multiplexing strategy of the seven-core structure is one of the core innovations of this application. The four fiber cores of the stress sensing channel are used to collect quasi-static strain data and invert the three-dimensional dynamic stress field. The three fiber cores of the microseismic sensing channel are distributed in an equilateral triangle in cross-section, which is equivalent to a three-component virtual detector array continuously distributed in the hole. By comparing the acoustic wave phase difference and arrival time difference sensed by the three fiber cores in the same cross-section, the inversion accuracy of the microseismic source azimuth can be greatly improved and common-mode background noise interference can be effectively suppressed.

[0044] In some implementations, the multi-core distributed optical fiber is a single-mode optical fiber that simultaneously supports Brillouin scattering and Rayleigh scattering. The Brillouin frequency shift has a stable linear relationship with strain, the Rayleigh scattering phase is highly sensitive to high-frequency vibrations, and the strain sensitivity is calibrated and fixed, supporting long-distance signal transmission over kilometers without attenuation, thus meeting the requirements for long-distance multi-parameter monitoring.

[0045] According to one embodiment of this application, the end of a multi-core distributed optical fiber is connected to a multi-protocol distributed optical fiber demodulation system 4 integrating Brillouin optical time-domain analysis and distributed acoustic sensing. At the initial moment before the arrival of the mining disturbance, the initial reference data of the central fiber core 11 and all peripheral fiber cores 12 are collected as a relative zero-point reference, including: setting the spatial sampling interval, acquisition frequency and measurement range parameters of the multi-protocol distributed optical fiber demodulation system 4; during the entire mining activity, the Brillouin frequency shift data of all measuring points on the stress sensing fiber core 121 are synchronously collected through the Brillouin optical time-domain analysis module, and the continuous vibration data of all measuring points on the micro-vibration sensing fiber core 122 are synchronously collected through the distributed acoustic sensing module, and the stable multi-parameter data before and after the mining are recorded to obtain a multi-parameter continuous dataset covering the entire sensor domain.

[0046] The integrated multi-protocol distributed fiber optic demodulation system is the core equipment for achieving synchronous acquisition of multiple parameters. The parameter setting process can be matched to the dynamic characteristics of the sampling activities, allowing the acquisition accuracy and sampling frequency to adapt to the monitoring needs of different parameters. The Brillouin optical time-domain analysis module performs polling scans of the entire aperture Brillouin frequency shift distribution using a low-frequency sampling period to acquire accumulated spatial strain data; the distributed acoustic sensing module continuously monitors the phase deflection of the coherent Rayleigh scattering signal along the entire probe length using a high-frequency sampling rate at the kilohertz level to acquire transient high-frequency strain rate sequences. The two sets of data are timestamped using a unified timing clock, ensuring precise synchronization of measurement data for various parameters in the time dimension, providing a time-synchronized and spatially continuous fundamental data source for subsequent multi-parameter calculations and spatiotemporal fusion.

[0047] In some implementations, before setting the acquisition parameters, the first and last ends of the stress-sensing fiber core group and the microseismic-sensing fiber core group are connected to the corresponding acquisition channels of the multi-protocol distributed optical fiber demodulation system 4 to complete the optical path connection and optical transmission performance verification. Before officially starting mining-induced monitoring, various initial optical fiber data are collected when the rock mass is undisturbed, serving as the initial reference values ​​for subsequent multi-parameter calculations. During data acquisition, the integrity of each channel's data is verified in real time, and invalid data with abnormal jumps is removed to ensure the validity of the multi-parameter dataset. The acquired Brillouin frequency shift data and continuous vibration data can also be timestamped using a unified timing clock.

[0048] According to one embodiment of this application, before calculating the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole 31 based on the aforementioned Brillouin frequency shift change and vibration data change, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, and through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model, the method further includes: using the Brillouin frequency shift data of the central fiber core 11 as a reference, eliminating the interference of ambient temperature fluctuations and the overall axial tension of the surrounding rock 3 on the strain data; calculating the local strain distribution of each stress-sensing fiber core 121 along the sensor matrix axis based on the linear relationship between Brillouin frequency shift and strain; constructing an apparent curvature vector based on the local strain distribution and spatial layout of each stress-sensing fiber core 121, and calculating the local curvature and bending direction angle of each measuring point; and performing background noise filtering on the continuous vibration data of the microseismic sensing fiber core 122 to extract the effective microseismic signal.

[0049] This process is a fundamental preprocessing step for achieving accurate multi-parameter calculations. The central fiber core 11 is unaffected by bending strain; its Brillouin frequency shift is solely caused by ambient temperature and overall axial tension. Therefore, it can serve as a benchmark to eliminate interference from these two factors on the strain data. It also features built-in global temperature compensation, eliminating temperature drift interference in complex environments. Based on the linear relationship between Brillouin frequency shift and strain, the Brillouin frequency shift changes of each stress-sensing fiber core 121 are converted into local strain data. Based on the local strain data of each stress-sensing fiber core 121 and its spatial position on the cross-section, an apparent curvature vector is constructed, thereby calculating the local curvature and bending direction angle at any position along the fiber. Simultaneously, bandpass filtering and background noise suppression are applied to the raw vibration data collected by the microseismic sensing fiber core 122 to remove environmental interference signals and extract the effective microseismic signals generated by microfractures in the rock mass.

[0050] In some implementations, the linear relationship between Brillouin frequency shift and strain is as follows: in The local strain of the i-th stress-sensing fiber core 121 at axial position s. Let be the Brillouin frequency shift change of the i-th stress-sensing fiber core 121 at axial position s. This represents the sensitivity coefficient of the fiber optic Brillouin frequency shift to mechanical strain, which is obtained through fiber optic factory calibration or laboratory material tensile testing. This represents the initial reference Brillouin frequency under the initial strain-free state and the current reference temperature.

[0051] According to one embodiment of this application, after calculating the local curvature and bending direction angle of each measuring point, the method further includes: calculating the local deflection of the corresponding measuring point based on the bending direction angle of each measuring point; introducing the Frenet-Serret differential equation system to construct a follower space orthogonal frame composed of tangent vector, principal normal vector and secondary normal vector; taking the borehole anchor point of the monitoring borehole 31 as the spatial integration reference point, continuously integrating along the axial direction of the sensor substrate to reconstruct the three-dimensional spatial absolute coordinate trajectory of the monitoring borehole 31 at the corresponding sampling time.

[0052] This process is the core step in reconstructing the three-dimensional spatial morphology. Based on differentiating the bending direction angle with respect to the axial position at each measuring point, the local deflection is obtained. The Frenet-Serret differential equations of spatial analytic geometry are introduced to construct a spatial moving frame composed of tangent vectors, principal normal vectors, and secondary normal vectors. Substituting the extracted curvature and deflection into this equation system, the coordinates of the borehole reference point are set. Through continuous spatial integration along the arc length, the absolute coordinate trajectories (x(s), y(s), z(s)) of the optical fiber and borehole wall in three-dimensional space during the mining process are reconstructed. Combining the data from each sampling time point, a four-dimensional continuous evolution model of the borehole morphology is generated as the mining progresses. This model can intuitively recreate the overall subsidence, delamination, and fault slippage processes of the roof and floor as the working face advances.

[0053] According to one embodiment of this application, based on the aforementioned Brillouin frequency shift variation and vibration data variation, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole 31 are calculated through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model. This includes: extracting the radial displacement distribution increment on each cross section of the monitoring borehole 31 along the depth based on the reconstructed three-dimensional spatial absolute coordinate trajectory; extracting at least three dynamic borehole relative deformations at specific angles on each cross section according to the preset layout orientation of the stress sensing fiber core 121; substituting the borehole relative deformations into the borehole edge stress concentration formula by combining the elastic modulus and Poisson's ratio parameters of the surrounding rock 3 to be monitored, and solving the multivariate simultaneous equations to obtain the three-dimensional mining stress additional field components and principal stress increment values ​​at each measuring point; and using the continuous vibration data of the microseismic sensing fiber core 122, calculating the source three-dimensional coordinates and fracture energy parameters of the rock mass microseismic using three-component array polarization analysis and spatial grid search algorithm.

[0054] This process is the core step in achieving accurate multi-parameter calculations, and it consists of two parallel branches: mining-induced stress inversion and microseismic source location. The mining-induced stress inversion branch extracts the radial displacement distribution increments at each depth cross-section from the reconstructed three-dimensional absolute coordinate trajectory, thereby obtaining the relative deformation of the borehole diameter in multiple directions. These borehole diameter deformations are substituted into the stress concentration formula at the borehole edge in elasticity to establish a system of multivariate simultaneous equations. Solving this system yields the three-dimensional mining-induced stress additional field components and principal stress increments at that cross-section, including the maximum principal stress increment, minimum principal stress increment, and their principal stress azimuths. By traversing the borehole longitudinally and combining the solution with a time series, a four-dimensional cloud map of the continuous distribution of mining-induced stress along the entire length of the borehole is finally obtained, enabling the visualization and tracking of the leading influence range of mining-induced stress and the forward shift of stress peak values.

[0055] Microseismic source location branch: Utilizing a long-short-term window ratio algorithm, the arrival times of sudden microseismic waves along the probe's path are acquired in real time. Taking advantage of the physical characteristic of the three fiber cores of the microseismic sensing channel being arranged in a 120° array on the probe's cross-section, these three fiber cores are equivalent to a continuously distributed three-component virtual geophone within the aperture. The extremely small high-frequency phase difference and arrival time difference of the seismic wave from the same microseismic event propagating to these three outer fiber cores over 12 hours are extracted. Combined with the P-wave and S-wave velocity models of the rock mass propagation medium, seismic wave polarization analysis is performed to solve for the three-dimensional spatial direction vector of the seismic wave. Then, combining the travel time difference of different monitoring points along the longitudinal direction of the fiber, a spatial grid search positioning algorithm is used to accurately calculate the absolute coordinates and microseismic energy of the rock mass micro-fracture source that triggered the microseismic event in three-dimensional space.

[0056] In some implementations, the elastic modulus and Poisson's ratio of the rock mass can be obtained through laboratory confining pressure grading tests on rock samples from the same batch collected on-site. The calculated three-dimensional mining-induced stress values ​​and microseismic parameters can comprehensively reflect the stress state and fracture activity characteristics of the surrounding rock 3.

[0057] According to one embodiment of this application, after calculating the three-dimensional mining stress additional field components, principal stress increment values, and microseismic parameters of each measuring point, the method further includes: associating the three-dimensional mining stress parameters and microseismic parameters calculated at each measuring point with the three-dimensional spatial absolute coordinates of the corresponding measuring point to generate a continuous mining stress and microseismic multi-parameter data set for the entire monitoring borehole 31; based on the multi-parameter data set, generating the axial continuous mining stress profile curve, three-dimensional spatial mining stress cloud map, and microseismic event distribution map of the monitoring borehole 31; the profile curve, cloud map, and distribution map are used for stability analysis, safety assessment, and multi-physics field collaborative disaster early warning of mining projects.

[0058] Because the stress sensing channel and the microseismic sensing channel are strictly fixed on the same spatial scale of the same optical fiber, the system directly eliminates the three-dimensional coordinate registration error required by traditional dual-system monitoring. The one-to-one correlation between multi-parameter data and absolute coordinates in three-dimensional space allows each set of data to accurately correspond to the actual physical location of the monitoring area, forming a complete set of continuous multi-parameter data. The early warning data terminal projects the high-gradient anomaly area of ​​mining-induced stress concentration peak, dense microseismic event area, and high-energy fracture point onto a unified full-size three-dimensional geological digital model of coal and rock mass. Based on the rock mechanics fracture criteria, it analyzes the pre- and post-constitutive relationships between the microseismic cluster occurrence area and the spatiotemporal evolution of the stress field. When a high-stress concentration core area is identified and accompanied by microseismic frequency and energy index crossing the set nonlinear growth critical threshold, a high-risk early warning signal for deep geodynamic disasters is automatically triggered, and the precise three-dimensional boundary range of the disaster-prone area is output.

[0059] In some implementations, before associating coordinates and multi-parameter data, the correspondence between the spatial coordinates of each measuring point and the actual engineering coordinates is clearly defined to ensure accurate matching between various data and the actual on-site locations. After generating the multi-parameter dataset, the integrity of the dataset is verified, and invalid data groups with duplicate coordinates or abnormal values ​​are removed. When generating various distribution maps and cloud maps, the locations and values ​​of stress concentration areas and areas prone to microseismic events are marked, providing intuitive key points for stability analysis and safety assessment of mining projects. The dataset can also generate visualization results such as principal stress direction distribution maps and microseismic energy cloud maps, intuitively presenting the coupling evolution laws of multi-physics fields over long distances.

[0060] The multi-parameter synchronous sensing method based on multi-core distributed optical fiber provided in this application has the following practical applications: First, the dual-mode in-situ monitoring channel zero-point calibration and background field initialization are performed. After the multi-core fiber optic sensing probe is implanted into the monitoring borehole and grouting consolidation is completed, and before the mining disturbance has affected the area, two demodulation modules are started simultaneously. The Brillouin optical time domain analysis module is used to scan and obtain the initial Brillouin frequency shift distribution of each fiber core of the stress sensing channel, and the relative zero stress reference of the coal and rock mass is calibrated. At the same time, the distributed acoustic sensing module is used to collect the background environmental noise signal, set the micro-seismic event trigger threshold, and establish the initial background field for micro-seismic waveform picking.

[0061] Then, multi-parameter cross-frequency domain time-series signal parallel acquisition and preprocessing are performed. As the working face continues to advance, the Brillouin optical time-domain analysis module polls and scans the Brillouin frequency shift of the entire hole at a low-frequency sampling period to obtain quasi-static strain accumulation data. The distributed acoustic sensing module continuously monitors the coherent Rayleigh scattering phase of the entire hole at a kilohertz-level high-frequency sampling rate to obtain transient high-frequency vibration data. The two sets of data are aligned with millisecond-level timestamps through a unified timing clock. Then, the Brillouin frequency shift data of the central fiber core is used as a reference to eliminate the interference of ambient temperature fluctuations and the overall axial tension of the surrounding rock on the strain data. Bandpass filtering and common-mode noise suppression are performed on the microseismic raw data to extract the effective signals generated by the microfractures of the rock mass.

[0062] Next, static three-dimensional mining stress full tensor inversion calculation is performed. Based on the linear relationship between Brillouin frequency shift and strain, the local strain along the axial direction of each stress-sensing fiber core is calculated. Based on the circumferential distribution coordinates of the three stress-sensing fiber cores, the apparent curvature vector is constructed. The local curvature and bending direction angle of each measuring point are calculated. After further obtaining the local deflection, the Frenet-Serret differential equation system is introduced to construct a follower orthogonal frame. The borehole anchor point is used as the spatial integration reference point and is continuously integrated along the fiber arc length to reconstruct the three-dimensional absolute coordinate trajectory of the borehole at the corresponding sampling time. Then, the relative deformation of the borehole diameter in three mutually 120° directions on the cross section at each depth is extracted. Combined with the rock elastic modulus and Poisson's ratio parameters measured in the laboratory, they are substituted into the borehole edge stress concentration formula to solve for the three-dimensional mining stress additional field components and principal stress increment values ​​of each measuring point, generating a four-dimensional evolution profile of mining stress continuously distributed along the borehole axis.

[0063] Subsequently, dynamic microseismic source parameter inversion was performed. The long-short time window ratio algorithm was used to pick up the first arrival time of the microseismic seismic waves to each microseismic sensing fiber core in real time. Taking advantage of the characteristic that the three microseismic sensing fiber cores are distributed in a 120° equilateral triangle on the cross section, they are equivalent to a three-component virtual geophone continuously distributed in the hole. The phase difference and arrival time difference of the same microseismic event on the three fiber cores were extracted. The polarization analysis was performed by combining the rock mass P-wave and S-wave velocity model to solve the three-dimensional spatial direction vector of the seismic wave. Then, combined with the seismic wave travel time difference of different monitoring points in the longitudinal direction of the optical fiber, the three-dimensional absolute coordinates and fracture energy parameters of the rock mass micro-fracture source were accurately calculated by the spatial grid search positioning algorithm.

[0064] Finally, the calculated three-dimensional mining stress parameters and microseismic parameters are correlated one-to-one with the three-dimensional spatial absolute coordinates of the corresponding measuring points to generate a multi-parameter fusion dataset. The high gradient anomaly area of ​​mining stress concentration peak, dense microseismic event area and high energy rupture point are projected into a unified three-dimensional geological digital model. The pre- and post-constitutive relationship between microseismic clusters and stress field evolution is analyzed. When a high-stress core area is identified and the microseismic frequency and energy index cross the preset nonlinear growth critical threshold, a high-risk early warning of deep geodynamic disasters is automatically triggered and the precise three-dimensional boundary range of the disaster-prone area is output.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate this application and are not intended to limit this application. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application and should be covered within the scope of the claims of this application.

Claims

1. A multi-parameter synchronous sensing method based on multi-core distributed optical fiber, characterized in that, Includes the following steps: Drill cylindrical monitoring boreholes in the monitoring area affected by mining activities; A flexible cylindrical sensor is implanted into the monitoring borehole. The sensor substrate of the flexible cylindrical sensor contains a multi-core distributed optical fiber. The multi-core distributed optical fiber includes a central fiber core located on the central axis of the sensor substrate and multiple peripheral fiber cores distributed around the central axis. The peripheral fiber cores include stress-sensing fiber cores and micro-vibration-sensing fiber cores. The central fiber core and all peripheral fiber cores extend along the axial direction of the sensor substrate and are parallel to each other. A coupling consolidation layer is provided between the flexible cylindrical sensor and the borehole wall, forming a consolidated coupling body between the flexible cylindrical sensor and the surrounding rock of the monitoring borehole. The end of the multi-core distributed optical fiber is connected to a multi-protocol distributed optical fiber demodulation system integrating Brillouin optical time-domain analysis and distributed acoustic sensing. At the initial moment before the arrival of the disturbance, the initial reference data of the central fiber core and all peripheral fiber cores are collected as a relative zero-point reference. During the mining process, continuous Brillouin frequency shift data of the stress-sensing fiber core and continuous vibration data of the microseismic sensing fiber core are collected, and the changes in Brillouin frequency shift and vibration data relative to the relative zero-point reference are extracted. Based on the aforementioned Brillouin frequency shift and vibration data changes, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area are calculated through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model.

2. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 1, characterized in that, Drilling cylindrical monitoring boreholes in the monitoring area affected by mining activities includes: According to the preset monitoring plan, monitoring boreholes are drilled in the top, bottom, side or target monitoring body of the surrounding rock in the area to be monitored, along the vertical, horizontal or inclined direction. After the monitoring borehole is completed, high-pressure air or clean water is used to remove rock powder and loose debris from the borehole. The inner diameter of the monitoring borehole is 5mm to 20mm larger than the outer diameter of the sensor, and the depth of the monitoring borehole covers the mining impact range of the area to be monitored.

3. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 1, characterized in that, Prior to implanting the flexible cylindrical sensor into the monitoring borehole, the method further includes: A flexible cylindrical substrate adapted to the monitoring borehole was selected as the sensor substrate, and the substrate material has deformation synergy that matches the surrounding rock to be monitored. The multi-core distributed optical fiber is extended along the axial direction of the sensor substrate and arranged parallel to each other. The multi-core distributed optical fiber is then integrated with the sensor substrate through injection molding. The ends of the stress-sensing fiber core group and the micro-vibration-sensing fiber core group are respectively led out through a multi-core fiber optic splitter. The two ends of the sensor substrate are sealed and waterproofed to form a multi-core fiber optic sensing probe with multi-parameter global sensing capability.

4. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 3, characterized in that, The deployment structure of the multi-core distributed optical fiber includes: A multi-core distributed optical fiber consists of one central core and at least three peripheral cores; The peripheral fiber cores are distributed at equal angular intervals along the circumference with the central fiber core as the center, and the axes of both the central fiber core and the peripheral fiber cores are parallel to the axis of the sensor substrate.

5. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 4, characterized in that, The multi-core distributed optical fiber adopts a seven-core structure with one central core and six peripheral cores arranged in parallel. Among them, the central core and three peripheral cores at a 120° angle to each other on the circumference form a stress sensing channel, and the remaining three peripheral cores at a 120° angle to each other form a micro-vibration sensing channel.

6. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 1, characterized in that, The step of connecting the end of the multi-core distributed optical fiber to a multi-protocol distributed optical fiber demodulation system integrating Brillouin optical time-domain analysis and distributed acoustic sensing, and collecting initial reference data of the central fiber core and all peripheral fiber cores as a relative zero-point reference at the initial moment before the arrival of the disturbance, includes: Set the spatial sampling interval, acquisition frequency, and measurement range parameters for the multi-protocol distributed optical fiber demodulation system; Throughout the entire mining process, Brillouin frequency shift data of all measuring points on the stress-sensing fiber core were simultaneously acquired using the Brillouin optical time-domain analysis module, and continuous vibration data of all measuring points on the micro-vibration sensing fiber core were simultaneously acquired using the distributed acoustic sensing module. Stable multi-parameter data before and after mining were recorded to obtain a multi-parameter continuous dataset covering the entire sensor domain.

7. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 6, characterized in that, Before calculating the continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area based on the aforementioned Brillouin frequency shift and vibration data changes, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model, the following steps are also included: Using the Brillouin frequency shift data of the central fiber core as a reference, the interference of ambient temperature fluctuations and the overall axial tension of the surrounding rock on the strain data is eliminated; Based on the linear relationship between Brillouin frequency shift and strain, the local strain distribution of each stress-sensing fiber core along the axial direction of the sensor substrate is calculated; Based on the local strain distribution and spatial arrangement of each stress-sensing fiber core, an apparent curvature vector is constructed, and the local curvature and bending direction angle of each measuring point are calculated. Background noise filtering is performed on the continuous vibration data of the microseismic sensing fiber core to extract the effective microseismic signal.

8. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 7, characterized in that, After calculating the local curvature and bending direction angle of each measuring point, the method further includes: Calculate the local deflection of the corresponding measuring point based on the bending direction angle of each measuring point; We introduce the Frenet-Serret differential equation system and construct a kinematic space orthogonal frame composed of tangent vector, principal normal vector and binormal vector; Using the borehole anchor point as the spatial integration reference point, continuous integration is performed along the axial direction of the sensor substrate to reconstruct the three-dimensional absolute coordinate trajectory of the borehole at the corresponding sampling time.

9. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 8, characterized in that, Based on the aforementioned Brillouin frequency shift and vibration data changes, combined with spatial analytical geometry theory and the elastic mechanical parameters of the rock mass, and through three-dimensional spatial morphology reconstruction and borehole deformation mechanical model, continuous mining stress and microseismic multi-parameter data of the entire monitoring borehole area are calculated, including: Based on the reconstructed three-dimensional absolute coordinate trajectory, the radial displacement distribution increments on each cross section along the depth of the monitored borehole are extracted; Based on the preset layout orientation of the stress-sensing fiber core, extract the dynamic aperture relative deformation of at least three cross sections with a specific included angle. By combining the elastic modulus and Poisson's ratio parameters of the surrounding rock to be monitored, the relative deformation of the borehole diameter is substituted into the stress concentration formula at the borehole edge. By solving the multivariate simultaneous equations, the three-dimensional mining stress additional field components and principal stress increment values ​​of each measuring point are obtained. Based on continuous vibration data from the microseismic sensing fiber core, the three-dimensional coordinates of the source and the rupture energy parameters of the rock mass microseismic event were calculated using a three-component array polarization analysis and spatial grid search algorithm.

10. The multi-parameter synchronous sensing method based on multi-core distributed optical fiber according to claim 9, characterized in that, After calculating the three-dimensional mining-induced stress additional field components, principal stress increments, and microseismic parameters for each measuring point, the method further includes: The three-dimensional mining stress parameters and microseismic parameters obtained from each measuring point are correlated one by one with the three-dimensional spatial absolute coordinates of the corresponding measuring point to generate a continuous mining stress and microseismic multi-parameter data set for monitoring the entire borehole area. Based on the multi-parameter data set, an axial continuous mining stress profile curve, a three-dimensional spatial mining stress cloud map, and a microseismic event distribution map of the monitoring borehole are generated; the profile curve, cloud map, and distribution map are used for stability analysis, safety assessment, and multi-physics field collaborative disaster early warning of mining projects.

Images