Pillar stability detection method and device based on distributed optical fiber sensor

Abstract

The application provides a kind of based on distributed optical fiber sensor's pillar stability detection method and device, related to mine engineering safety detection technical field.The method comprises: obtaining the surrounding rock environment parameters and stress working condition parameters of target pillar, and according to determining stress working condition parameters and surrounding rock environment parameters, determine the optical fiber sensor layout material selection strategy of target pillar;Combining optical fiber sensor layout strategy, the multi-dimensional distributed optical fiber sensor layout is carried out to target pillar, so that the distributed optical fiber sensor forms a multi-dimensional detection network along different directions and different regions of target pillar, obtains the measuring point data collected by distributed optical fiber sensor in multi-dimensional detection network, and according to measuring point data, constructs the multi-dimensional strain nephogram of target pillar, according to the multi-dimensional strain nephogram of target pillar, determines the stability detection result of target pillar.The application aims to improve the problem that the existing method cannot accurately predict the asymmetric damage of the pillar.

Description

Technical Field

[0001] This application relates to the field of mine engineering safety detection technology, and in particular to a method and device for detecting the stability of mine pillars based on distributed optical fiber sensors. Background Technology

[0002] As underground mineral resource mining becomes deeper and more complex, the stability of pillars, as key load-bearing structures in underground mining areas, directly affects mining safety and continuous production capacity. Under high stress, strong disturbances, and multi-field coupling environments, pillars are prone to localized damage, plastic deformation, or shear failure. Instability can lead to mining area collapse, roadway deformation, equipment damage, and even endanger the safety of underground personnel. Therefore, stability testing of pillars and identification of early signs of instability are crucial technical requirements for mine safety monitoring and risk warning.

[0003] In existing technologies, resistance strain gauges, vibrating wire strain gauges, and linear displacement gauges can be used for local strain or displacement detection, but these point-based detection methods are difficult to fully cover the spatial state of the mine pillar.

[0004] However, due to the significant non-uniformity of stress and deformation in the pillar, if sensors are not deployed in key areas, local anomalies may not be detected in time, thus making it impossible to accurately predict the asymmetric failure of the pillar. Summary of the Invention

[0005] The embodiments disclosed in this application provide a method and apparatus for detecting the stability of a mine pillar based on a distributed optical fiber sensor, which can improve the problem that existing methods cannot accurately predict the asymmetric failure of the mine pillar.

[0006] The embodiments of this application adopt the following technical solutions: Firstly, a method for detecting the stability of a mine pillar based on a distributed optical fiber sensor is provided, the method comprising: Obtain the surrounding rock environment parameters and stress condition parameters of the target ore pillar, and determine the material selection strategy for the fiber optic sensor deployment of the target ore pillar based on the determined stress condition parameters and surrounding rock environment parameters. Combining fiber optic sensor deployment strategies, multi-dimensional distributed fiber optic sensors are deployed on the target ore pillar to form a multi-dimensional detection network along different directions and regions of the target ore pillar. Acquire measurement point data collected by distributed fiber optic sensors in a multidimensional detection network, and reconstruct the full tensor strain field distribution on the surface of the target ore pillar based on the measurement point data; Based on the full tensor strain field distribution results, the stability test results of the target pillar are determined; The multidimensional detection network includes a first detection network, a second detection network, and a third detection network. A multidimensional distributed fiber optic sensor deployment strategy is used to arrange the target ore pillar, enabling the distributed fiber optic sensors to form a multidimensional detection network along different directions and regions of the target ore pillar, including: Distributed fiber optic sensors are spirally and evenly spaced along the surface of the target pillar to obtain the first detection network; Distributed fiber optic sensors are deployed at equal intervals around the stress-bearing cross section of the target pillar to obtain a second detection network; Distributed fiber optic sensors are arranged at equal intervals along the surface axis of the target pillar to obtain a third detection network; The full tensor strain field distribution on the surface of the target ore pillar was reconstructed based on the measurement data, including: The measurement point data corresponding to different deployment paths in the multidimensional detection network are uniformly preprocessed to obtain the basic strain dataset for strain field reconstruction. Based on the cross-sectional dimensions and spatial geometric relationships of the target pillar, the basic strain dataset is transformed into a two-dimensional unfolded coordinate system on the surface of the target pillar, and periodic expansion and interpolation calculations are performed to obtain the two-dimensional strain field distribution data on the surface of the target pillar. Based on the two-dimensional strain field distribution data, a three-dimensional surface is mapped, and the maximum principal strain, minimum principal strain, and principal strain direction are calculated by combining strain information in different directions, so as to obtain the full tensor strain field distribution result of the target pillar surface.

[0007] In one feasible implementation of the first aspect, a material selection strategy for the fiber optic sensor deployment of the target pillar is determined based on the determined stress condition parameters and surrounding rock environment parameters, including: When the stress condition parameters and / or surrounding rock environment parameters characterize the corresponding deployment area of ​​the target pillar to meet the anti-disturbance adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be an acrylic coating. When the stress conditions and / or surrounding rock environment parameters characterize the deployment area of ​​the target pillar to meet the high-sensitivity transmission adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be polyimide coating.

[0008] In one feasible implementation of the first aspect, the measurement data includes: strain value, height coordinates, and helix angle.

[0009] In one feasible implementation of the first aspect, the stability test results of the target pillar are determined based on the full tensor strain field distribution results, including: Determine the circumferential strain, axial strain, and maximum shear strain of the target pillar, and determine the spatial distribution characteristics of the corresponding abnormal strain region; The equivalent volume strain of the target pillar is calculated based on the circumferential strain and axial strain. When the equivalent volume strain changes from a compression state to an expansion state and the discrete characteristics of the circumferential strain gradient meet the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion spalling. Based on the spatial connectivity of the maximum shear strain and the geometric evolution characteristics of the high shear strain concentration area, when the high shear strain concentration area extends along the preset shear direction and meets the preset shear instability identification conditions, it is determined that the target pillar has the risk of shear zone evolution instability.

[0010] In one feasible implementation of the first aspect, when a high shear strain concentration region extends along a preset shear direction and meets preset shear instability identification conditions, it is determined that the target pillar has a risk of shear zone evolution and instability, including: The band length and bandwidth of the high shear strain concentration region are calculated, and the shear band localization factor is determined based on the ratio of band length to bandwidth. Based on the temporal variation characteristics of the shear band localization factor, determine whether the shear band is in a state of rapid localization evolution; When the localization factor of the shear zone meets the preset growth condition and a connecting path is formed in the high shear strain concentration area that runs through the upper and lower ends of the target pillar, it is determined that the target pillar has an overall shear slip instability risk.

[0011] In one feasible implementation of the first aspect, the step of performing three-dimensional surface mapping based on the two-dimensional strain field distribution data, and calculating the maximum principal strain, minimum principal strain, and their principal strain directions in combination with strain information in different directions to obtain the full tensor strain field distribution result of the target pillar surface includes: In the two-dimensional unfolded coordinate system on the surface of the target pillar, the axial strain, circumferential strain and helical strain corresponding to each spatial position are determined; The in-plane shear strain on the surface of the target pillar is determined based on the axial strain, the circumferential strain, the helical strain, and the corresponding helical angle. Based on the axial strain, the circumferential strain, and the in-plane shear strain, the maximum principal strain, the minimum principal strain, and the direction of the principal strain on the surface of the target pillar are determined and mapped onto the surface of the target pillar to obtain the full tensor strain field distribution result.

[0012] In a feasible implementation of the first aspect, determining that the target pillar has a risk of radial expansion spalling when the equivalent volume strain transitions from a compressive state to an expansion state and the circumferential strain gradient discrete characteristics satisfy a preset spalling identification condition includes: Extract the circumferential strain and axial strain corresponding to at least one target horizontal section of the target pillar, and determine the equivalent volumetric strain of the target horizontal section based on the circumferential strain and the axial strain; Based on the circumferential strain distribution along the target horizontal cross section, the discrete characteristics of the circumferential strain gradient are determined; When the equivalent volume strain changes from negative to positive and the discrete characteristics of the circumferential strain gradient satisfy the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion spalling.

[0013] Secondly, a pillar stability detection device based on a distributed optical fiber sensor is provided, the device comprising: The first acquisition module is used to acquire the surrounding rock environment parameters and stress condition parameters of the target pillar, and to determine the fiber optic sensor deployment material selection strategy for the target pillar based on the determined stress condition parameters and surrounding rock environment parameters. The deployment module is used to deploy multi-dimensional distributed optical fiber sensors to the target ore pillar in combination with the optical fiber sensor deployment strategy, so that the distributed optical fiber sensors form a multi-dimensional detection network along different directions and different areas of the target ore pillar. The second acquisition module is used to acquire the measurement point data collected by the distributed optical fiber sensors in the multidimensional detection network, and reconstruct the full tensor strain field distribution result of the target ore pillar surface based on the measurement point data. The detection module is used to determine the stability test results of the target pillar based on the full tensor strain field distribution results.

[0014] Thirdly, an electronic device is provided, comprising: a memory and at least one processor. The memory is communicatively connected to the processor. The memory is used to store computer program code, which includes computer instructions. When the processor executes the computer instructions, it causes the electronic device to perform a method as described in the first aspect and any possible implementation thereof.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions. When these computer instructions are executed by a processor, they are used to implement the method as described in the first aspect and any possible implementation thereof.

[0016] Fifthly, embodiments of this application provide a computer program product that, when running on a computer / executed by the computer's processor, implements the method described in the first aspect and any possible design thereof. The computer may be the pillar stability detection device based on distributed optical fiber sensors described in the second aspect and any possible implementation thereof.

[0017] The pillar stability detection method based on distributed optical fiber sensors provided in this application adaptively determines an optical fiber sensor deployment strategy that matches the target pillar monitoring scenario by combining surrounding rock environmental parameters and stress condition parameters. Based on the deployment strategy, a multi-dimensional detection network is constructed on the surface of the target pillar to obtain strain monitoring data in different directions and regions of the target pillar. Furthermore, the multi-dimensional strain field distribution result on the surface of the target pillar is reconstructed based on the strain monitoring data, thereby realizing the transformation from single-point, unidirectional strain perception to multi-dimensional strain state characterization of the entire pillar surface. Finally, the stability state of the target pillar is determined based on the multi-dimensional strain field distribution result, which can more effectively identify the local damage characteristics and overall instability evolution trend of the target pillar, thereby improving the comprehensiveness, accuracy, and early warning reliability of pillar stability detection. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the steps of a method for detecting the stability of a mine pillar based on a distributed optical fiber sensor, as provided in this application embodiment; Figure 2 A schematic diagram illustrating the deployment of a distributed optical fiber sensor provided in an embodiment of this application; Figure 3 A block diagram of a pillar stability detection device based on a distributed optical fiber sensor provided in this application embodiment; Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions in some embodiments of this application will be clearly and completely described below with reference to the figures. Obviously, the embodiments described in the specification are only some embodiments of this application, and not all embodiments. Based on the embodiments provided in this application, all other embodiments obtained by those skilled in the art are within the scope of protection of this application.

[0020] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as open-ended and encompassing, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "exemplary," or "some examples," etc., are intended to indicate that a particular parameter, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this application. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0021] As underground mineral resource development progresses towards deeper, larger-scale, and more complex geological conditions, the geostress environment faced by underground mining engineering is becoming increasingly severe. Under deep mining conditions, the stress level of the original rock is high, and the surrounding rock structure is more complex due to factors such as geological structure, mining disturbance, and mining sequence. Roadways, stopes, and underground load-bearing structures are in a high-stress, strong-disturbance, and multi-field coupling environment for extended periods. Especially in mining processes such as room-and-pillar, stope, and open-cut mining, pillars typically serve as key load-bearing structures in underground stopes, supporting overlying strata, isolating goaf areas, maintaining roadway stability, and ensuring the safety of the stope structure. The stability of pillars directly affects the overall safety and continuous production capacity of underground stopes. Once a pillar suffers localized damage, accumulated plastic deformation, spalling, shear failure, or even overall instability, it can easily trigger safety accidents such as stope collapse, roof instability, roadway deformation, and equipment damage, and in severe cases, may even endanger the personal safety of underground workers. Therefore, conducting stability testing on mine pillars and promptly identifying early signs of pillar instability are important technical requirements for mine safety monitoring and disaster early warning.

[0022] From the perspective of rock mechanics, pillar instability is usually not sudden but rather involves a gradual evolution process. When a pillar is subjected to long-term high stress or mining disturbance, stress concentration, fracture propagation, increased local deformation, and damage accumulation gradually occur inside and on its surface, further manifesting as abnormal strain, intensified deformation, or abrupt displacement in localized areas. As the damage evolves, the pillar may gradually develop from localized instability to overall instability. Therefore, before macroscopic failure occurs, continuous monitoring of the strain, displacement, and other mechanical response information on the pillar's surface or in localized areas helps to detect abnormal trends in advance, thus providing a basis for pillar stability assessment and risk warning. In other words, the key to pillar stability monitoring lies in obtaining monitoring information that characterizes the pillar's stress and deformation states as promptly and accurately as possible, and identifying whether the pillar has entered an abnormal evolution stage based on this information.

[0023] In one feasible implementation of the related technology, sensors such as resistance strain gauges, vibrating wire strain gauges, or linear displacement gauges can be used for detection. Resistance strain gauges are typically attached to the surface of the pillar or the structure being measured to acquire strain changes at local locations. Vibrating wire strain gauges are generally installed at preset detection points to detect stress or strain changes at specific locations. Linear displacement gauges are mostly used to measure the relative displacement change between two preset locations, thereby reflecting the local deformation of the pillar or surrounding rock. By pre-setting several detection points on the surface, perimeter, or relevant parts of the pillar, and deploying the aforementioned sensors at the corresponding detection points, strain, displacement, or deformation information at local locations of the pillar can be acquired to a certain extent, thereby assisting in determining whether there are any abnormal changes in the pillar.

[0024] However, the aforementioned detection methods, such as resistance strain gauges, vibrating wire strain gauges, or linear displacement gauges, are essentially discrete point-based detection methods. That is, these methods rely on deploying points at a limited number of preset locations, with each sensor only reflecting the state changes at its own location or in a localized area. If the detection points are not deployed in the actual area where the anomaly occurs, even if significant damage has already occurred in a localized part of the pillar, the relevant sensors may fail to react in time, resulting in missed anomaly information. Furthermore, since a pillar is a load-bearing structure with a certain spatial scale, its surface often exhibits differences in stress and deformation at different locations, heights, and circumferential regions. Traditional point-based detection methods typically only acquire single-point data from a few discrete locations, making it difficult to continuously reflect the spatial deformation distribution of the entire pillar surface. For example, when a pillar experiences localized strain concentration in a certain sidewall region, or when a continuously expanding damage zone appears within a certain height range, relying solely on a small number of discrete detection points often fails to accurately characterize the extent, direction of development, and evolution trend of the anomaly. In other words, while traditional point-based detection methods can reflect changes in local locations, they are insufficient to form a comprehensive understanding of the overall stability of the pillar and cannot accurately reflect the complex destructive evolution process on the pillar surface.

[0025] In summary, discrete-point detection methods in related technologies struggle to achieve continuous coverage of the entire pillar area, easily creating blind spots and failing to fully reflect the overall deformation and failure evolution process of the pillar, resulting in low accuracy in stability assessment and reliability in early warning. To address the problems existing in the aforementioned related technologies, this application provides a method for detecting the stability of a mine pillar based on distributed optical fiber sensors. By combining the surrounding rock environment parameters and stress condition parameters of the target mine pillar to determine the optical fiber sensor deployment strategy, and acquiring multi-directional measurement point data on the surface of the target mine pillar based on a multi-dimensional detection network, the full tensor strain field distribution of the target mine pillar surface is reconstructed. Furthermore, based on the full tensor strain field distribution, the local spalling risk and overall shear instability risk of the target mine pillar are identified, thereby improving the comprehensiveness, accuracy, and reliability of the mine pillar stability detection and early warning.

[0026] The pillar stability detection method based on distributed optical fiber sensors provided in this application can be applied to underground mine engineering safety monitoring scenarios. It is understood that the implementing entity of this method can be one or more of the following: a pillar stability detection system, a distributed optical fiber detection device, a mine safety monitoring platform, an edge computing device, a server, and a terminal device.

[0027] In some embodiments, the executing entity may include a processor and a memory, the memory storing computer program instructions. When the processor executes the computer program instructions, it performs the various steps of the mine pillar stability detection method based on distributed optical fiber sensors provided in this application embodiment. Furthermore, the executing entity may also be communicatively connected to a display device, an alarm device, a mine dispatching system, or a remote monitoring platform to realize the display of detection results, alarms for abnormal states, and coordinated safety dispatching.

[0028] Figure 1 This is a flowchart illustrating a method for detecting the stability of a mine pillar based on a distributed optical fiber sensor, provided in an embodiment of this application. The method can include two stages: the first stage is the matching process between the vehicle and the field-end sensing device; the second stage is the interaction between the vehicle and the field-end sensing device to trigger a risk detection mode. The matching process between the vehicle and the field-end sensing device will be described first. For example, please refer to... Figure 1 As shown, the method for detecting the stability of a mine pillar based on a distributed optical fiber sensor may include steps S101 to S104: S101: Obtain the surrounding rock environment parameters and stress condition parameters of the target pillar, and determine the material selection strategy for the fiber optic sensor deployment of the target pillar based on the determined stress condition parameters and surrounding rock environment parameters.

[0029] Target pillars can be naturally preserved pillars or functional pillars reserved according to mining design. In practical applications, target pillars can be key load-bearing structural units that require stability testing, stress evolution testing, crack propagation testing, deformation response testing, or disaster early warning testing.

[0030] Before conducting fiber optic sensing detection on the target pillar, the appropriate fiber optic sensor material can be pre-selected based on the geological environment characteristics and load-bearing response characteristics of the target pillar. This ensures that the fiber optic sensors deployed subsequently can balance structural adaptability, signal transmission stability, and long-term service reliability in complex mining environments.

[0031] For example, some target pillars are located in areas affected by strong mining, blasting disturbance, or high-fracture development, where external mechanical disturbances are strong, requiring sensors to have better damage resistance and environmental tolerance. On the other hand, some target pillars are located in stress concentration areas, microcrack initiation sensitive areas, or key detection areas that require high-precision capture of early micro-deformations, requiring sensors to have better strain coupling capabilities and higher response sensitivity with the pillar medium.

[0032] Therefore, in this embodiment, a fixed material fiber optic sensor is not used for all target pillars. Instead, by acquiring and analyzing the surrounding rock environment parameters and stress conditions of the target pillars, a differentiated fiber optic sensor deployment material selection strategy is formed for different deployment areas.

[0033] Surrounding rock environmental parameters can be used to characterize the physical environment, structural integrity, and media interaction conditions of the surrounding rock around a target pillar. These parameters may include, but are not limited to: rock type, lithology, integrity level, degree of joint and fracture development, fracture aperture, water content, seepage intensity, humidity, temperature, distribution of corrosive media, rock roughness, weathering degree, porosity, extent of local loosening zones, and surface adhesion conditions. These parameters reflect the influence of the area surrounding the target pillar on the fiber optic sensor coating, encapsulation layer, and bonding interface. For example, when the surrounding rock environment experiences strong humid heat fluctuations, seepage erosion, dust scouring, blasting vibration propagation, or fracture displacement, the sensor material needs to be more resistant to disturbances, peeling, and environmental changes.

[0034] Stress condition parameters can be used to characterize the bearing state, stress evolution, and deformation response characteristics of a target pillar during the current or expected monitoring period. These parameters may include, but are not limited to: axial stress, lateral stress, principal stress distribution, stress concentration factor, loading rate, unloading rate, periodic disturbance frequency, mining disturbance intensity, blasting influence intensity, pillar compression deformation, shear deformation trend, bending deformation trend, local strain gradient, crack propagation trend, creep characteristics, and stability risk level.

[0035] The specific steps for determining the fiber optic sensor deployment material selection strategy for the target ore pillar may include: S1011: Under the condition that the stress condition parameters and / or surrounding rock environment parameters characterize the corresponding deployment area of ​​the target pillar meet the anti-disturbance adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be an acrylic coating.

[0036] Disturbance resistance adaptation conditions can be used to characterize the deployment area corresponding to the target pillar. It is more suitable for scenarios that prioritize the mechanical protection capability, interface buffer capability, and environmental tolerance capability of the sensor.

[0037] As an example, when the target pillar is located in an area with strong mining disturbance, near the path of blasting impact, in an area with obvious rock fissure activity, in an area with local rockfall risk, in an area with obvious damp heat fluctuations, or in an area with a strong risk of external mechanical impact, if materials that overemphasize high strain transfer efficiency are still preferred, it may lead to problems such as coating damage, bonding interface instability, increased signal drift, or reduced lifespan of the sensor during long-term service.

[0038] Therefore, in such scenarios, acrylic coated optical fibers with good flexibility, buffering and environmental adaptability can be given priority as the deployment material to improve the deployment tolerance and continuous working stability of sensors in complex mining environments.

[0039] S1012: Under the condition that the stress condition parameters and / or surrounding rock environment parameters characterize the deployment area corresponding to the target pillar meet the high sensitivity transmission adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be polyimide coating.

[0040] Sensitive transmission adaptation conditions can be used to characterize scenarios where the corresponding deployment area of ​​the target pillar is more suitable for prioritizing strain transmission efficiency, micro-deformation response capability, and detection accuracy. For example, when the target pillar is located in a stress concentration zone, a microcrack initiation zone, an early identification zone of stability degradation, or a critical detection zone requiring high-precision tracking of subtle strain evolution, the detection target is usually not just to identify whether large deformations have occurred, but to capture as early as possible the subtle strain changes, crack initiation precursors, or stress redistribution trends inside or on the surface of the pillar. In this case, using materials that are more biased towards buffer protection may, to some extent, weaken the effective transmission of subtle deformations of the pillar body to the fiber optic sensor, thereby affecting the capture effect of precursor information.

[0041] Therefore, in such scenarios, polyimide-coated optical fibers with better strain coupling characteristics and higher transmission sensitivity can be selected as the deployment material to improve the ability to sense small strains, local stress concentrations and early damage evolution.

[0042] The method provided in this application embodiment can adaptively match high-sensitivity deployment materials according to the sensitive transmission adaptation conditions of the deployment area corresponding to the target pillar, so as to enhance the effective transmission and perception of micro-strain information, thereby improving the accuracy and reliability of early anomaly identification and early warning of pillar stability.

[0043] S102: Combine fiber optic sensor deployment strategy to deploy multi-dimensional distributed fiber optic sensors on the target ore pillar so that the distributed fiber optic sensors form a multi-dimensional detection network along different directions and different areas of the target ore pillar.

[0044] After determining the material selection strategy for the fiber optic sensor deployment corresponding to the target pillar, a multi-dimensional distributed fiber optic sensor deployment can be implemented by combining the geometric characteristics, stress transmission path characteristics, potential failure modes, and detection targets of the target pillar. This multi-dimensional distributed fiber optic sensor deployment can be understood as not simply linearly deploying sensors along a single direction or in a single region, but rather collaboratively deploying distributed fiber optic sensors along multiple dimensions, including the circumferential, axial, spiral paths, and key stress sections of the target pillar. This allows strain responses in different directions, layers, and regions to be simultaneously sensed, thereby constructing a multi-dimensional detection network covering the surface and key stress areas of the target pillar.

[0045] The specific steps for forming a multidimensional detection network may include: S1021: Distributed fiber optic sensors are spirally and evenly spaced along the surface of the target pillar to obtain the first detection network.

[0046] Distributed fiber optic sensors are spirally and evenly spaced along the surface of the target ore pillar. This allows one or more optical fibers to continuously cover different height and circumferential positions along the outer perimeter of the pillar in a spiral winding manner, forming a composite detection path with both axial and circumferential coverage capabilities. "Equally spaced" can mean that the spacing between adjacent spiral coils along the height direction is basically the same, or that the spiral pitch of the optical fibers along the target ore pillar surface meets a preset spacing requirement, ensuring relatively uniform coverage density across different height areas of the target ore pillar. The first detection network formed in this way can be used to characterize the continuous variation of surface strain of the target ore pillar in the height-circumferential coupling direction.

[0047] S1022: Distributed fiber optic sensors are deployed at equal intervals along the stress-bearing cross section of the target pillar to obtain a second detection network.

[0048] Distributed fiber optic sensors are deployed at equal intervals around the stress-bearing cross-section of the target pillar, forming a circumferentially closed or nearly closed circumferential detection path at key load-bearing sections, stress concentration sections, potential failure sections, or preset detection sections of the target pillar. The stress-bearing cross-section can be a section where stress redistribution is significant during actual load-bearing, or a key detection layer determined based on mining design, geological conditions, numerical simulation results, or historical detection experience.

[0049] By deploying distributed fiber optic sensors circumferentially along the stress-bearing cross-section, the circumferential strain distribution of the target pillar on that cross-section can be reflected more directly. This allows for the identification of whether the stress on the cross-section is uniform, whether there is localized stress concentration, whether elliptic deformation of the cross-section occurs, and whether a concentrated area of ​​circumferential cracks or signs of local instability have formed. The evenly spaced deployment refers to deploying the sensors at preset angular intervals along the circumference or approximately circumference of the stress-bearing cross-section, ensuring good comparability and balanced sampling of strain information from different locations on the cross-section. The second detection network formed in this way can detect the circumferential strain distribution of the key stress-bearing cross-sections of the target pillar.

[0050] S1023: Distributed fiber optic sensors are arranged at equal intervals along the surface axis of the target pillar to obtain a third detection network.

[0051] By arranging distributed fiber optic sensors at equal intervals along the axial direction of the target pillar surface, the distributed fiber optic sensors can be continuously extended along the height direction or the main load-bearing direction of the target pillar to form a longitudinal detection path that can reflect the axial load transmission path and the deformation evolution law in the height direction of the pillar.

[0052] Compared to helical deployment, which emphasizes height-circumferential composite coverage, axial deployment prioritizes continuous strain tracking of the target pillar along the main load-bearing direction. Therefore, it is more suitable for detecting the response characteristics of the pillar during overall compression, local buckling, delamination deformation, longitudinal fracture propagation, and stress redistribution along the height direction. The third detection network formed in this way can be used to detect the overall load-bearing path and longitudinal evolution of the target pillar. Specifically, equidistant deployment refers to multiple axially deployed distributed optical fibers distributed at preset angles or arc lengths along the circumference of the target pillar, allowing for synchronous acquisition of axial strain responses at different circumferential positions. This third detection network can then be used for continuous strain tracking along the main load-bearing direction.

[0053] The method provided in this application constructs a multi-dimensional distributed optical fiber sensor network on the surface of the target pillar, arranged in a helical, circumferential, and axial manner. This upgrades the traditional discrete strain detection method, which targets local measuring points or a single direction, to a continuous, multi-directional strain sensing method covering the entire surface of the target pillar, thereby expanding from point detection to surface detection. Furthermore, based on the strain monitoring data acquired by the multi-dimensional detection network in different regions and directions of the target pillar, the multi-dimensional strain field on the surface of the target pillar is reconstructed and mapped. This transforms the originally dispersed linear strain information into a continuous field distribution result characterizing the overall stress state, local deformation characteristics, and damage evolution trend of the target pillar, further enhancing the transformation from surface detection to a volumetric state representation reflecting the overall stress and instability evolution of the pillar. Therefore, this method overcomes the limitations of existing technologies that rely on only a few measuring points or unidirectional monitoring data, making it difficult to comprehensively reflect the complex stress state and progressive failure process of the pillar. It improves the overall integrity, continuity, accuracy, and instability early warning capability of pillar stability detection.

[0054] As an example, a schematic diagram of the deployment of a multidimensional detection network can be shown as follows: Figure 2 As shown, 201 is a distributed optical fiber sensor in the first detection network, 202 is a distributed optical fiber sensor in the second detection network, and 203 is a distributed optical fiber sensor in the third detection network.

[0055] S103: Acquire the measurement point data collected by the distributed optical fiber sensors in the multidimensional detection network, and reconstruct the full tensor strain field distribution on the surface of the target ore pillar based on the measurement point data.

[0056] After deploying multi-dimensional distributed fiber optic sensors on the target pillar, a multi-dimensional detection network can continuously collect multi-directional strain response information on the pillar's surface. Since the distributed fiber optic sensors deployed in different directions correspond to linear strain measurements in different directions, the multi-directional strain state of the target pillar's surface can be jointly reconstructed based on the measurement point data corresponding to each deployment path. This yields a full tensor strain field distribution that reflects the stress and deformation characteristics of the target pillar's surface. Compared to detection methods that rely solely on linear strain data from a single path, this step, by fusing measurement point data from different directions and regions, can not only characterize the axial and circumferential deformation of the target pillar's surface but also further calculate in-plane shear deformation and principal strain distribution. This facilitates more accurate identification of early signs of instability such as local crack propagation, spalling, and shear slip.

[0057] In some embodiments, the measurement point data may include: strain value, height coordinates, and helix angle. The strain value characterizes the magnitude of the strain response at the corresponding measurement point location; the height coordinates characterize the position of the corresponding measurement point in the axial direction of the target pillar; and the helix angle characterizes the relative angular position of the corresponding measurement point in the circumferential direction of the target pillar, which is particularly suitable for surface continuous measurement point data obtained by a helical layout path.

[0058] In some embodiments, for the measurement point data corresponding to the axial and circumferential layout paths, the circumferential or axial position parameters of each measurement point on the surface of the target pillar can be obtained by combining the pre-set layout start position, the cross-sectional size parameters of the target pillar, and the geometric rules of the layout path, so as to achieve a unified spatial expression of the measurement point data under different layout paths.

[0059] The specific steps for constructing the full tensor strain field distribution of the target ore pillar can include: S1031: Perform unified preprocessing on the measurement point data corresponding to different deployment paths in the multidimensional detection network to obtain the basic strain dataset for strain field reconstruction.

[0060] Since the measurement point data come from the first detection network, the second detection network, and the third detection network, and the layout paths and spatial representation methods of the different detection networks are different, the measurement point data can be preprocessed and spatially analyzed in a unified manner before constructing the full tensor strain field of the target ore pillar.

[0061] Specifically, the raw measurement point data collected by each detection network can be processed separately for time synchronization, outlier removal, noise filtering, drift compensation, and missing value repair to reduce the impact of environmental disturbances, signal attenuation, and local sampling anomalies on the accuracy of subsequent strain field reconstruction.

[0062] After data preprocessing, the geometric dimensions of the target pillar and the layout rules of each detection network can be combined to perform unified spatial positioning of the measuring points along different paths. For example, for measuring points laid out along the axial direction of the target pillar, their axial position can be directly determined based on the cumulative distance of the measuring point along the fiber optic path, and their spatial position can be determined by combining the preset circumferential layout position; for measuring points laid out circumferentially along the target pillar, their circumferential angle position can be determined based on the mapping relationship between the circumferential path length and the perimeter of the target pillar cross-section, and their spatial position can be determined by combining the corresponding layout height; for measuring points laid out along the spiral path of the target pillar, their position parameters in the axial and circumferential directions can be jointly solved based on the cumulative length of the measuring point along the fiber optic path, the spiral pitch, and the layout spiral angle.

[0063] After the above processing, measurement point data from different detection networks can be uniformly converted into a basic strain dataset under the same coordinate description framework. In some embodiments, each data item in the basic strain dataset may include: measurement point identifier, timestamp, strain value, axial coordinate z, circumferential coordinate θ, and deployment direction identifier. The deployment direction identifier can be used to distinguish whether the strain value corresponding to the measurement point belongs to axial linear strain, circumferential linear strain, or helical linear strain, so as to facilitate subsequent multi-directional strain field fitting and tensor solution.

[0064] S1032: Based on the cross-sectional dimensions and spatial geometric relationships of the target pillar, the basic strain dataset is transformed into a two-dimensional unfolded coordinate system on the surface of the target pillar, and periodic expansion and interpolation calculations are performed to obtain the two-dimensional strain field distribution data on the surface of the target pillar.

[0065] Since the target pillar can usually be approximated as a columnar bearing structure, its surface spatial morphology can be modeled by a cylindrical or approximately cylindrical surface. Therefore, the three-dimensional curved surface of the target pillar can be unfolded into a two-dimensional plane to facilitate unified interpolation of multi-source measurement data and reconstruction of the continuous strain field.

[0066] Specifically, based on the cross-sectional dimensions (e.g., radius, diameter, or equivalent radius) and circumferential length relationship of the target pillar, the circumferential coordinates θ on the surface of the target pillar can be converted into circumferential unfolded coordinates s in the unfolded coordinate system, where the circumferential unfolded coordinates s can satisfy the correspondence with the circumferential angle θ.

[0067] For example, when the target pillar is approximately cylindrical, it can be transformed using the formula s = R·θ, where R represents the equivalent radius of the target pillar and θ represents the circumferential angular position of the measuring point. Thus, all measuring points can be uniformly mapped to a two-dimensional unfolded coordinate system (s, z), where s represents the circumferential unfolded position of the target pillar surface and z represents the axial height position of the target pillar.

[0068] Considering the natural periodicity of the target pillar's circumferential direction—that is, the spatial position returns to the same location when the circumferential angle changes from 0° to 360°—the data at the circumferential expansion boundary in the two-dimensional unfolded coordinate system exhibits a continuous relationship. To avoid boundary breaks, edge distortions, or pseudo-abrupt changes during interpolation or fitting, the basic strain dataset can be periodically expanded. Specifically, the measurement data of points close to the starting and ending boundaries of the circumferential expansion coordinates can be periodically replicated and extended to adjacent virtual regions, ensuring that the two-dimensional interpolation calculation maintains continuity and smoothness in the boundary region.

[0069] After coordinate transformation and period expansion, two-dimensional continuous field interpolation or fitting reconstruction can be performed on the measurement point data corresponding to different directional deployment paths. For example, two-dimensional distribution fields of axial strain, circumferential strain, and helical strain can be constructed separately. In some embodiments, inverse distance weighted interpolation, bilinear interpolation, bicubic interpolation, radial basis function interpolation, kriging interpolation, spline surface fitting, or least squares surface fitting can be used to process the discrete measurement point data into a continuous form, thereby obtaining the continuous strain field distribution data of the target pillar surface in a two-dimensional unfolded coordinate system.

[0070] Furthermore, to improve the spatial correspondence accuracy between strain fields in different directions, a unified meshing rule can be adopted for the strain fields in each direction. For example, a regular mesh can be constructed on the two-dimensional unfolded plane (s,z), discretizing the surface of the target ore pillar into multiple spatial mesh points (i,j), and calculating the corresponding axial strain, circumferential strain, and helical strain at each mesh point. This yields multi-directional two-dimensional strain field distribution data corresponding to each other under the same spatial mesh, providing a foundation for subsequent full tensor strain field solutions.

[0071] S1033: Based on the two-dimensional strain field distribution data, perform three-dimensional surface mapping, and combine the strain information in different directions to calculate the maximum principal strain, minimum principal strain and their principal strain directions, to obtain the full tensor strain field distribution results of the target pillar surface.

[0072] After obtaining the two-dimensional axial strain distribution field, the two-dimensional circumferential strain distribution field, and the two-dimensional helical strain distribution field on the surface of the target pillar, the in-plane shear strain and principal strain information on the surface of the target pillar can be further calculated based on the geometric relationship between strains in different directions, thereby completing the reconstruction from one-dimensional linear strain to the full tensor strain field.

[0073] Specifically, at any spatial grid point (i,j) in the two-dimensional unfolded plane (s,z), the axial strain ε corresponding to that grid point can be extracted. z Circumferential strain ε θ and the strain ε in the helical direction α Wherein, axial strain ε z It can originate from the strain field corresponding to the axially arranged path. Circumferential strain ε θ It can originate from the strain field corresponding to the circumferential layout path. The strain ε in the helical direction... α It can originate from the strain field corresponding to the spiral arrangement path. Since the strain in the spiral direction is essentially a linear strain along the spiral path, and its direction has an angular relationship with the axial and circumferential directions, a coupling equation between the three can be established based on the strain coordinate transformation relationship in elasticity.

[0074] In some embodiments, the in-plane shear strain can be solved based on the following strain coordinate transformation formula: ; Where γ zθ This represents the in-plane shear strain on the surface of the target pillar within the axial-circumferential plane. Given ε... αθ ε z ε θ Given the helix angle α, the in-plane shear strain γ at the corresponding spatial grid point can be obtained by simultaneously solving the equations. zθ Therefore, the continuous in-plane shear strain field can be calculated point by point across the entire two-dimensional unfolded plane.

[0075] In obtaining ε αθ ε z ε θ and in-plane shear strain γ zθ Next, a two-dimensional plane strain tensor of the target pillar surface can be constructed, and the corresponding principal strain parameters can be solved. Specifically, based on the principle of plane strain analysis, the maximum principal strain ε1, the minimum principal strain ε2, and the principal strain direction angle at each spatial grid point can be calculated. The maximum principal strain can be used to characterize the strongest tensile or compressive tendency of the target pillar surface in a local region; the minimum principal strain can be used to characterize the principal deformation tendency in the direction orthogonal to the maximum principal strain; and the principal strain direction angle can be used to characterize the dominant direction of local crack initiation, propagation, or shear slip.

[0076] In some embodiments, the maximum shear strain γ can be further calculated based on the principal strain information. max This is used for subsequent shear band identification and evolution analysis.

[0077] For example, the magnitude of the maximum shear strain can be determined based on the difference between the maximum and minimum principal strains, thereby obtaining a highly sensitive identification parameter that reflects the degree of local shear concentration. After completing the tensor calculations described above, the strain parameter results in the two-dimensional unfolded plane can be inversely mapped back to the three-dimensional surface coordinate space of the target pillar to generate the full tensor strain field distribution results on the surface of the target pillar.

[0078] In some embodiments, the full tensor strain field distribution result may include at least one or more of the following: axial strain field, circumferential strain field, in-plane shear strain field, maximum principal strain field, minimum principal strain field, principal strain direction field, and maximum shear strain field.

[0079] Furthermore, based on the aforementioned full tensor strain field, three-dimensional strain cloud maps, two-dimensional unfolded strain cloud maps, or time-series evolution cloud maps of the target ore pillar can be generated for subsequent stability state identification and instability early warning.

[0080] S104: Determine the stability test results of the target pillar based on the full tensor strain field distribution results.

[0081] After obtaining the full tensor strain field distribution results on the surface of the target pillar, the local damage risk and overall instability risk of the target pillar can be comprehensively identified based on the spatial distribution characteristics and temporal evolution of different types of strain parameters, thereby determining the stability test results of the target pillar.

[0082] It should be noted that a target pillar can refer to a columnar or near-columnar ore body structure in the vicinity of underground mining areas, roadways, or goafs, which serves to bear the pressure of overlying strata and maintain the stability of underground space. It can be a naturally preserved pillar or an artificially designed pillar. Because target pillars typically undergo a gradual failure process under long-term pressure, disturbance, and the coupling effect of surrounding rock, including local fracture initiation, surface spalling and expansion, and overall shear slip, multi-level identification of their stability based on the full tensor strain field is beneficial for improving the predictability and accuracy of pillar disaster early warning.

[0083] In some embodiments, the stability detection results may include at least one of the following: stable state, local damage warning state, spalling risk state, shear zone evolution risk state, and overall shear slip instability risk state. The specific steps for determining the stability detection results of the target pillar may include: S1041: Determine the circumferential strain, axial strain, and maximum shear strain of the target pillar, and determine the spatial distribution characteristics of the corresponding abnormal strain region; In some embodiments, the circumferential strain field, axial strain field, and maximum shear strain field of the target pillar surface can be extracted from the full tensor strain field distribution results, and local regions exceeding a preset anomaly threshold or exhibiting significant abrupt changes can be identified. Circumferential strain can reflect the expansion or contraction trend of the pillar surface along the circumferential direction; axial strain can reflect the deformation response of the pillar during axial compression, unloading, or local yielding; and maximum shear strain can reflect the degree of shear concentration in local regions of the pillar surface.

[0084] Furthermore, spatial clustering analysis, connected component identification, or boundary extraction can be performed on the abnormal strain regions to determine characteristic parameters such as area, length, width, circumferential distribution location, height distribution range, and spatial connectivity of the abnormal strain regions. This processing provides a foundation for subsequent identification of spalling risk and shear band evolution instability.

[0085] S1042: Calculate the equivalent volume strain of the target pillar based on the circumferential strain and axial strain. When the equivalent volume strain changes from a compression state to an expansion state and the discrete characteristics of the circumferential strain gradient meet the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion spalling. In some embodiments, the circumferential strain ε within the corresponding cross-sectional range can be extracted at one or more horizontal cross-sections of the target pillar. θ With axial strain ε z The equivalent volumetric strain ε was calculated based on circumferential strain and axial strain. v Among them, equivalent volumetric strain can be used to characterize the volumetric deformation trend of the local area on the surface of the pillar as it transforms from compaction and contraction to expansion and dilatation.

[0086] In one feasible implementation, the equivalent volumetric strain can be calculated as follows: ε v =ε+2ε θ , where, when ε v When ε is less than zero, it indicates that the surface region of the target pillar is in a state of volume compression. v When the value is greater than zero, it can indicate that the surface region of the target pillar has changed from a state of compression to expansion. Since the initiation, expansion and connection of microcracks on the surface of the pillar are often accompanied by a transition in volumetric strain from compaction to expansion, when the equivalent volumetric strain changes from negative to positive, it can be regarded as an important precursor feature of the connection of microcracks on the surface of the pillar.

[0087] Furthermore, to avoid misjudgments based solely on single-point strain inflection points, the spatial discrete characteristics of the circumferential strain gradient can be combined to jointly identify spalling risk. Specifically, the dispersion parameters of the circumferential strain gradient, such as the coefficient of variation, variance, standard deviation, coefficient of variation, or local range, can be calculated along the circumferential direction of the target pillar or within a local target area to reflect whether there is significant non-uniform concentration in the circumferential deformation of the pillar surface. Before asymmetric spalling occurs on the pillar surface, significant abrupt changes in circumferential strain and non-uniform expansion usually occur in local areas. Therefore, if the discrete characteristics of the circumferential strain gradient exceed the preset spalling identification threshold, it can be considered that there is a significant localized failure trend on the pillar surface.

[0088] Therefore, when the equivalent body strain changes from a compression state to an expansion state, and the discrete characteristics of the circumferential strain gradient meet the preset spalling identification conditions, it can be determined that micro-cracks have been connected on the surface of the target pillar and early signs of asymmetric spalling have appeared, thus confirming that the target pillar has a risk of radial expansion spalling.

[0089] In some embodiments, the risk status can be output as a local spalling warning to the mine safety monitoring platform to prompt response measures such as inspection, support or personnel evacuation to be taken in the working area around the target pillar.

[0090] S1043: Based on the spatial connectivity of the maximum shear strain and the geometric evolution characteristics of the high shear strain concentration area, when the high shear strain concentration area extends along the preset shear direction and meets the preset shear instability identification conditions, it is determined that the target pillar has the risk of shear zone evolution instability.

[0091] In some embodiments, high shear strain regions on the surface of a target pillar can be extracted based on the maximum shear strain field in the full tensor strain field distribution results to identify potential shear concentration zones or shear failure initiation zones. Specifically, a maximum shear strain threshold can be set, and spatial grid points exceeding the threshold can be divided into high shear strain candidate points. Then, adjacent candidate points can be spatially aggregated through connected component analysis, neighborhood clustering, or path tracing to form one or more high shear strain concentration regions.

[0092] Since the overall shear slip instability of the pillar is usually manifested as the high shear strain concentration area gradually penetrates along a specific shear direction and forms a narrow localized zone, the geometric morphology of the high shear strain concentration area and its evolution trend over time can be further analyzed.

[0093] In some embodiments, the preset shear direction can be a target direction determined based on the pillar's stress state, the orientation of the surrounding rock structural plane, the theoretical shear angle, or the empirical failure mode. When the high shear strain concentration area continues to extend along the preset shear direction and exhibits a trend of evolving from discrete patches to continuous narrow banded structures, it can be considered that the target pillar has obvious shear zone development characteristics.

[0094] In some embodiments, to improve the quantification and stability of the identification, shear instability identification conditions can be constructed by combining the geometric evolution characteristics of high shear strain concentration areas. For example, parameters such as band length, bandwidth, aspect ratio, penetration height, consistency of connecting path direction, end expansion rate, and localized growth rate of high shear strain concentration areas can be extracted. When the above parameters meet the preset shear instability identification conditions, it can be determined that the target pillar has a risk of shear zone evolution instability.

[0095] In one feasible implementation, when a high shear strain concentration region extends along a preset shear direction and meets preset shear instability identification conditions, it is determined that the target pillar has a risk of shear zone evolution and instability, including: The length and bandwidth of the high shear strain concentration area are calculated, and the shear zone localization factor is determined based on the ratio of the length to the bandwidth. Based on the temporal variation characteristics of the shear zone localization factor, it is determined whether the shear zone is in a state of rapid localization evolution. When the shear zone localization factor meets the preset growth conditions and the high shear strain concentration area forms a connecting path through the upper and lower ends of the target pillar, it is determined that the target pillar has an overall shear slip instability risk.

[0096] In some embodiments, the characteristic length along the extension direction of the high shear strain concentration region can be calculated as the band length L, based on the principal axis direction and boundary profile of the region, and its average width or equivalent width perpendicular to the extension direction can be calculated as the bandwidth W. Further, the shear band localization factor I can be determined based on the ratio of the band length L to the bandwidth W. The shear band localization factor can be used to characterize the degree to which the high shear strain region evolves from a dispersed state to a narrow, concentrated state. When the shear band localization factor continuously increases, it generally indicates that the deformation is gradually developing from planar diffusion to narrow band concentration.

[0097] In some embodiments, the shear band localization factor can be tracked over a continuous monitoring period, and its growth rate, growth acceleration, exponential fitting characteristics, or abrupt change characteristics can be analyzed. When the shear band localization factor rises rapidly in a short period of time, or when its growth trend meets a preset exponential growth condition, it can be determined that the high shear strain concentration region is undergoing a rapid localization evolution process.

[0098] In some embodiments, when the shear band localization factor reaches a preset threshold or its temporal change meets preset growth conditions (e.g., growth rate exceeds the threshold, growth acceleration exceeds the threshold, or the fitted curve exhibits exponential acceleration), the high shear strain region can be considered to possess significant elongated localization characteristics. Furthermore, the connectivity of the high shear strain concentration region within the three-dimensional surface space of the target pillar can be used to determine whether a continuous shear path has formed from the upper to the lower end of the target pillar. When the high shear strain concentration region forms a connecting path traversing the upper and lower surfaces of the target pillar, it indicates that the potential failure surface of the pillar has essentially formed, potentially inducing overall shear slip or through-hole instability.

[0099] Therefore, when the localization factor of the shear zone meets the preset growth conditions, and the high shear strain concentration area forms a connecting path through the upper and lower ends of the target pillar, it can be determined that the target pillar has an overall shear slip instability risk. In some embodiments, this risk status can be output as a red emergency warning or a high-level instability alarm, so that the mine safety management system can promptly implement measures such as stopping mining, evacuating personnel, reinforcing supports, or emergency response.

[0100] In one feasible implementation, a three-dimensional surface mapping is performed based on two-dimensional strain field distribution data, and the maximum principal strain, minimum principal strain, and their principal strain directions are calculated by combining strain information from different directions to obtain the full tensor strain field distribution result of the target pillar surface, including: In the two-dimensional unfolded coordinate system on the surface of the target pillar, determine the axial strain, circumferential strain and helical strain corresponding to each spatial position; The in-plane shear strain on the surface of the target pillar is determined based on the axial strain, circumferential strain, helical strain and corresponding helical angle. Based on axial strain, circumferential strain, and in-plane shear strain, the maximum principal strain, minimum principal strain, and principal strain direction of the target pillar surface are determined and mapped onto the target pillar surface to obtain the full tensor strain field distribution results.

[0101] In this embodiment, a correspondence can be established between each position point in the two-dimensional unfolded coordinate system and the actual spatial position on the surface of the target pillar. Based on the axial strain, circumferential strain, and helical strain, in-plane strain components at the corresponding positions are constructed. Subsequently, the helical strain is decomposed by combining the angle relationship between the helical direction and the axial direction to obtain the shear deformation components at each position. Further, a local strain tensor is constructed based on the strain components at each position, and the maximum principal strain, minimum principal strain, and principal strain direction are obtained by solving the principal strain. The solution results are then mapped back to the corresponding spatial position on the surface of the target pillar to form the full tensor strain field distribution result on the surface of the target pillar.

[0102] In one feasible implementation, when the equivalent volume strain transitions from a compressive state to an expansive state and the discrete characteristics of the circumferential strain gradient satisfy a preset spalling identification condition, it is determined that the target pillar has a risk of radial expansion spalling, including: Extract the circumferential strain and axial strain corresponding to at least one target horizontal section of the target pillar, and determine the equivalent volumetric strain of the target horizontal section based on the circumferential strain and axial strain; Based on the circumferential strain distribution along the target horizontal cross section, the discrete characteristics of the circumferential strain gradient are determined; When the equivalent body strain changes from negative to positive and the discrete characteristics of the circumferential strain gradient meet the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion and spalling.

[0103] In this embodiment, corresponding horizontal sections can be extracted at different heights of the target pillar, and circumferential strain data and corresponding axial strain data distributed along the circumference of each horizontal section can be obtained respectively. Subsequently, the equivalent volumetric strain is calculated based on the circumferential strain and axial strain at each circumferential position to characterize the volumetric strain state of the target pillar surface from compaction to expansion. Furthermore, the rate of change of the circumferential strain along the circumferential direction is statistically analyzed to extract gradient discrete features characterizing the degree of unevenness in circumferential distribution. When the equivalent volumetric strain is detected to change from a negative value to a positive value, and the gradient discrete features reach the preset spalling identification conditions, it is determined that there is a trend of microcrack penetration and asymmetric spalling evolution on the surface of the target pillar, and a radial expansion spalling risk warning result is output.

[0104] Figure 3 This is a block diagram of a mine pillar stability detection device based on a distributed optical fiber sensor, provided as an embodiment of this application. Figure 3 As shown, the pillar stability detection device 300 based on distributed optical fiber sensors includes: The first acquisition module 301 is used to acquire the surrounding rock environment parameters and stress condition parameters of the target pillar, and determine the fiber optic sensor deployment material selection strategy for the target pillar based on the determined stress condition parameters and surrounding rock environment parameters. The deployment module 302 is used to deploy multi-dimensional distributed optical fiber sensors to the target ore pillar in combination with the optical fiber sensor deployment strategy, so that the distributed optical fiber sensors form a multi-dimensional detection network along different directions and different areas of the target ore pillar. The second acquisition module 303 is used to acquire the measurement point data collected by the distributed optical fiber sensor in the multidimensional detection network, and reconstruct the full tensor strain field distribution result of the target ore pillar surface based on the measurement point data. The detection module 304 is used to determine the stability detection result of the target pillar based on the full tensor strain field distribution result.

[0105] The pillar stability detection device based on distributed optical fiber sensors provided in this application can execute the methods shown in the above-described method embodiments. Its implementation principle and beneficial effects can be found in the relevant descriptions in the method embodiments, and will not be repeated here. Furthermore, each module in the above-described pillar stability detection device based on distributed optical fiber sensors can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0106] In other embodiments, an electronic device is provided, which may be the mine pillar stability detection device based on distributed optical fiber sensors in the above method embodiments, used to execute the method steps performed by the terminal in the above method flow. The internal structure diagram of this electronic device can be as follows: Figure 4As shown, the device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for detecting the stability of a mine pillar based on a distributed fiber optic sensor. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the electronic device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the electronic device, or external keyboards, touchpads, or mice, etc.

[0107] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0108] In some embodiments, an electronic device includes a memory, a processor, and a communication interface. The communication interface is used to interact with other devices to send and receive data. For example, in this embodiment, the communication interface may specifically be used to store computer program code, which includes computer instructions. These computer instructions run in the electronic device to implement the method shown in the above-described method embodiments. For example, the memory may include high-speed random access memory (RAM), and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be a USB flash drive, portable hard drive, read-only memory, disk, or optical disk, etc.

[0109] The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a network processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The processor can also be other general-purpose processors. A general-purpose processor can be a microprocessor or any conventional processor.

[0110] Memory, communication interfaces, and processor communication connections. For example, memory and communication interfaces can connect to the processor via the system bus and communicate with each other. The system bus can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, an Industry Standard Architecture (ISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0111] Alternatively, the memory can be either standalone or integrated with the processor. When the memory is set up independently, it is connected to the processor via the system bus.

[0112] This application also provides a chip for executing instructions, which is used to execute the technical solution of the pillar stability detection method based on distributed optical fiber sensors in the above embodiments.

[0113] This application also provides a computer-readable storage medium storing computer instructions. When these computer instructions are executed by a processor, they are used to implement the technical solution of the pillar stability detection method based on a distributed optical fiber sensor provided in the above embodiments. Specifically, when the computer instructions are executed by a processor, the computer device can execute the technical solution of the pillar stability detection method based on a distributed optical fiber sensor provided in the above embodiments.

[0114] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, it can implement the technical solution of the pillar stability detection method based on distributed optical fiber sensors provided in the above embodiments.

[0115] The aforementioned computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), etc.

[0116] Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can take many forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). Computer-readable storage media may be any available medium accessible to general-purpose or special-purpose computers.

[0117] An exemplary computer-readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the computer-readable storage medium can also be a component of the processor. The processor and the computer-readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the computer-readable storage medium can exist as discrete components in an electronic control unit or main control device; this application does not limit this.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some parameters may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0119] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules in the formula can be selected to implement the solution of this embodiment according to actual needs.

[0120] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0121] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0122] It should be understood that the steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0123] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0124] The technical parameters in the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical parameters in the above embodiments are described. However, as long as these combinations of technical parameters do not contradict each other, they should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application's patent. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical parameters in the formula. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting the stability of a mine pillar based on a distributed optical fiber sensor, characterized in that, The method includes: Obtain the surrounding rock environment parameters and stress condition parameters of the target ore pillar, and determine the fiber optic sensor deployment material selection strategy for the target ore pillar based on the determined stress condition parameters and surrounding rock environment parameters. The fiber optic sensor deployment strategy is combined with the fiber optic sensor deployment strategy to deploy multi-dimensional distributed fiber optic sensors on the target ore pillar, so that the distributed fiber optic sensors form a multi-dimensional detection network along different directions and different areas of the target ore pillar. Acquire the measurement point data collected by the distributed optical fiber sensor in the multidimensional detection network, and reconstruct the full tensor strain field distribution result on the surface of the target ore pillar based on the measurement point data; Based on the full tensor strain field distribution results, the stability test results of the target pillar are determined; The multidimensional detection network includes a first detection network, a second detection network, and a third detection network; the multidimensional distributed fiber optic sensor deployment of the target ore pillar, combined with the fiber optic sensor deployment strategy, to form a multidimensional detection network along different directions and regions of the target ore pillar, includes: Distributed fiber optic sensors are spirally and evenly spaced along the surface of the target pillar to obtain the first detection network; Distributed fiber optic sensors are arranged at equal intervals around the stress section of the target pillar to obtain the second detection network; Distributed fiber optic sensors are arranged at equal intervals along the surface axis of the target pillar to obtain the third detection network; The process of reconstructing the full tensor strain field distribution on the surface of the target ore pillar based on the measured data includes: The measurement point data corresponding to different deployment paths in the multidimensional detection network are uniformly preprocessed to obtain a basic strain dataset for strain field reconstruction. Based on the cross-sectional dimensions and spatial geometric relationships of the target pillar, the basic strain dataset is transformed into a two-dimensional unfolded coordinate system on the surface of the target pillar, and periodic expansion and interpolation calculations are performed to obtain the two-dimensional strain field distribution data on the surface of the target pillar. Based on the two-dimensional strain field distribution data, a three-dimensional surface mapping is performed, and the maximum principal strain, minimum principal strain, and principal strain direction are calculated by combining strain information in different directions to obtain the full tensor strain field distribution result of the target pillar surface.

2. The method according to claim 1, characterized in that, The step of determining the fiber optic sensor deployment material selection strategy for the target pillar based on the determined stress condition parameters and surrounding rock environment parameters includes: When the stress condition parameters and / or surrounding rock environment parameters indicate that the deployment area corresponding to the target pillar meets the anti-disturbance adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be an acrylic coating. When the stress conditions and / or surrounding rock environment parameters indicate that the deployment area corresponding to the target pillar meets the high-sensitivity transmission adaptation conditions, the fiber optic sensor deployment material of the target pillar is determined to be polyimide coating.

3. The method according to claim 1, characterized in that, The measurement data includes: strain value, height coordinates, and helix angle.

4. The method according to claim 1, characterized in that, The determination of the stability test result of the target pillar based on the full tensor strain field distribution result includes: The circumferential strain, axial strain, and maximum shear strain of the target pillar are determined, and the spatial distribution characteristics of the corresponding abnormal strain region are determined. The equivalent volume strain of the target pillar is calculated based on the circumferential strain and the axial strain. When the equivalent volume strain changes from a compressed state to an expanded state and the discrete characteristics of the circumferential strain gradient meet the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion spalling. Based on the spatial connectivity of the maximum shear strain and the geometric evolution characteristics of the high shear strain concentration area, when the high shear strain concentration area extends along the preset shear direction and meets the preset shear instability identification conditions, it is determined that the target pillar has a risk of shear zone evolution instability.

5. The method according to claim 4, characterized in that, When the high shear strain concentration region extends along a preset shear direction and meets preset shear instability identification conditions, determining that the target pillar has a risk of shear zone evolution instability includes: The band length and bandwidth of the high shear strain concentration region are calculated, and the shear band localization factor is determined based on the ratio of the band length to the bandwidth. Based on the temporal variation characteristics of the shear band localization factor, determine whether the shear band is in a state of rapid localization evolution; When the localization factor of the shear zone meets the preset growth condition and the high shear strain concentration region forms a connecting path through the upper and lower ends of the target pillar, it is determined that the target pillar has an overall shear slip instability risk.

6. The method according to claim 4, characterized in that, The process of performing three-dimensional surface mapping based on the two-dimensional strain field distribution data, and calculating the maximum principal strain, minimum principal strain, and their principal strain directions in combination with strain information from different directions to obtain the full tensor strain field distribution result of the target pillar surface includes: In the two-dimensional unfolded coordinate system on the surface of the target pillar, the axial strain, circumferential strain and helical strain corresponding to each spatial position are determined; The in-plane shear strain on the surface of the target pillar is determined based on the axial strain, the circumferential strain, the helical strain, and the corresponding helical angle. Based on the axial strain, the circumferential strain, and the in-plane shear strain, the maximum principal strain, the minimum principal strain, and the direction of the principal strain on the surface of the target pillar are determined and mapped onto the surface of the target pillar to obtain the full tensor strain field distribution result.

7. The method according to claim 1, characterized in that, The step of determining that the target pillar has a risk of radial expansion and spalling when the equivalent volume strain transitions from a compressive state to an expansion state and the discrete characteristics of the circumferential strain gradient satisfy a preset spalling identification condition includes: Extract the circumferential strain and axial strain corresponding to at least one target horizontal section of the target pillar, and determine the equivalent volumetric strain of the target horizontal section based on the circumferential strain and the axial strain; Based on the circumferential strain distribution along the target horizontal cross section, the discrete characteristics of the circumferential strain gradient are determined; When the equivalent volume strain changes from negative to positive and the discrete characteristics of the circumferential strain gradient satisfy the preset spalling identification conditions, it is determined that the target pillar has a risk of radial expansion spalling.

8. A pillar stability detection device based on distributed optical fiber sensors, used to implement the method described in any one of claims 1-7, characterized in that, include: The first acquisition module is used to acquire the surrounding rock environment parameters and stress condition parameters of the target ore pillar, and determine the fiber optic sensor deployment material selection strategy for the target ore pillar based on the determined stress condition parameters and surrounding rock environment parameters. The deployment module is used to deploy multi-dimensional distributed optical fiber sensors to the target ore pillar in conjunction with the optical fiber sensor deployment strategy, so that the distributed optical fiber sensors form a multi-dimensional detection network along different directions and different areas of the target ore pillar. The second acquisition module is used to acquire the measurement point data collected by the distributed optical fiber sensor in the multidimensional detection network, and reconstruct the full tensor strain field distribution result of the target ore pillar surface based on the measurement point data. The detection module is used to determine the stability detection result of the target pillar based on the full tensor strain field distribution result.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on a computer / executed by the computer's processor, it implements the method as described in any one of claims 1-7.

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