A high-precision displacement measurement method and system for a mine roof

Abstract

The present application relates to the technical field of mine roof monitoring, and particularly relates to a high-precision displacement measurement method and system for a mine roof, which solves the technical problem of insufficient measurement reliability and precision in the prior art. The method comprises: collecting displacement data and installation angle data of a plurality of monitoring points in the mine roof; performing angle correction on the displacement data of each monitoring point according to the installation angle data to obtain corrected displacement data; determining the instantaneous displacement of each monitoring point at each time according to the corrected displacement data of the plurality of monitoring points; performing collaborative analysis on the instantaneous displacement of each monitoring point at each time that is greater than a preset displacement threshold, to determine a collaborative performance value of the instantaneous displacement corresponding monitoring point at the corresponding time; and filtering vibration interference from the corrected displacement data of the plurality of monitoring points according to the collaborative performance value, to obtain true displacement data.

Description

Technical Field

[0001] This invention relates to the field of mine roof monitoring technology, specifically to a high-precision method and system for measuring the displacement of mine roof. Background Technology

[0002] The mine roof is the upper rock structure of mine roadways and stopes, and its stability directly determines the safety of underground operations. During mining, the roof is affected by multiple factors such as the release of mining stress, changes in geological structure, and changes in support load, making it prone to deformation phenomena such as subsidence, delamination, and collapse. If the roof displacement cannot be accurately measured in a timely manner, it may be impossible to provide timely warning of roof collapse accidents, resulting in roadway blockage and casualties. With the increase of mining depth, high ground pressure causes the roof to exhibit large deformation and plastic failure characteristics that are difficult to support, which places higher demands on the accuracy of roof displacement measurement.

[0003] Existing methods for measuring roof displacement in mines mainly include potentiometer-based sensor measurement and laser ranging measurement. The potentiometer-based sensor method converts mechanical displacement into a change in resistance by moving a sliding contact along a resistance wire, thus outputting a voltage signal. The laser ranging method emits a laser beam to a roof target and calculates the distance change using the reflection time. However, these existing methods are easily affected by the complex underground environment. The potentiometer-based sensor method is susceptible to resistance corrosion due to the humid environment, and the laser beam path of the laser ranging method is easily blocked by high concentrations of dust. Therefore, these methods suffer from insufficient reliability and accuracy in complex underground environments, making it difficult to meet the high-precision measurement requirements of mine roof displacement and limiting the effectiveness of underground operational safety assurance. Summary of the Invention

[0004] To address the technical problems of insufficient reliability and accuracy in existing measurement technologies, the present invention aims to provide a high-precision method and system for measuring the displacement of mine roofs. The specific technical solution adopted is as follows:

[0005] This application provides a high-precision method for measuring the displacement of mine roof, including:

[0006] Displacement and installation angle data of multiple monitoring points in the mine roof are collected; the monitoring points include shallow base points and deep base points, and there is a corresponding relationship between the shallow base points and the deep base points are located at a greater depth than the corresponding shallow base points; the displacement data includes the displacement of the monitoring points at each time point recorded in time sequence.

[0007] The displacement data of each monitoring point is corrected by performing angle correction on the installation angle data to obtain the corrected displacement data; the corrected displacement data is the displacement data after angle conversion from the installation angle data.

[0008] The instantaneous displacement of each monitoring point at each time moment is determined based on the corrected displacement data of multiple monitoring points; the instantaneous displacement is the difference between the displacement at the corresponding time moment and the average displacement.

[0009] For each monitoring point, the instantaneous displacements exceeding a preset displacement threshold at each time point are analyzed collaboratively to determine the collaborative performance value of the monitoring point at the corresponding time point; the collaborative performance value is used to characterize the degree of collaboration of vibration interference.

[0010] Vibration data segments are selected from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and vibration interference is filtered out from the vibration data segments to obtain the true displacement data.

[0011] In one possible implementation, the method includes:

[0012] The installation angle of each monitoring point is obtained from the installation angle data; the installation angle is used to characterize the angle between the inclination of the monitoring point and the vertical direction of the Earth's center.

[0013] For each monitoring point, based on the installation angle and displacement data corresponding to the monitoring point, the tilt displacement is converted into vertical displacement using trigonometric functions to generate corrected displacement data.

[0014] In one possible implementation, the method includes:

[0015] For the target monitoring point and target time corresponding to the instantaneous displacement that is greater than the preset displacement threshold, the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time are obtained; the displacement change is the difference between the displacement of the monitoring point at the target time and the displacement at the previous time.

[0016] The collaborative performance value of the target monitoring point at the target time is calculated based on the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time.

[0017] In one possible implementation, the method includes:

[0018] Vibration data segments are determined based on corrected displacement data where the collaborative performance value is greater than a preset performance value threshold. The vibration data segments include shallow base point vibration data segments and deep base point vibration data segments. The shallow base point vibration data segments consist of corrected displacement data where the collaborative performance value is greater than a preset performance value threshold in the shallow base points, and the deep base point vibration data segments consist of corrected displacement data where the collaborative performance value is greater than a preset performance value threshold in the deep base points.

[0019] Vibration interference filtering was performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to obtain the true displacement data.

[0020] In one possible implementation, the method includes:

[0021] Data fitting was performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to determine the average data curve of the shallow base point vibration data segment and the average data curve of the deep base point vibration data segment.

[0022] For the vibration data segments at shallow and deep base points respectively, the corresponding average data curves are used as the desired signals. An adaptive filtering algorithm is then used to perform vibration filtering on the vibration data segments to obtain the actual displacement data.

[0023] In one possible implementation, the method further includes:

[0024] For the actual displacement data of each monitoring point, a stable data segment within a preset time period before the vibration data segment is obtained from the actual displacement data of the monitoring point, and the actual displacement data is corrected by nonlinear fitting based on the stable data segment.

[0025] In one possible implementation, the method further includes:

[0026] The inter-story displacement difference between each shallow base point and its corresponding deep base point is determined based on the actual displacement data, and the shallow layer activity coefficient is determined based on the inter-story displacement difference between each shallow base point and its corresponding deep base point. The inter-story displacement difference is used to characterize the relative displacement between the shallow base point and its corresponding deep base point, and the shallow layer activity coefficient is used to characterize the deformation activity of the shallow top plate.

[0027] Risk warnings are issued based on interlayer displacement differences and shallow layer activity coefficients.

[0028] In one possible implementation, the method includes:

[0029] For each shallow base point, calculate the first inter-layer displacement difference between the shallow base point and the corresponding deep base point, and the second inter-layer displacement difference between the shallow base point and the core deep base point; the core deep base point is the deep base point with the smallest average displacement among all deep base points.

[0030] The inter-story displacement difference between the shallow base point and the corresponding deep base point is determined based on the first inter-story displacement difference and the second inter-story displacement difference.

[0031] The shallow activity coefficient is calculated based on the mean and standard deviation of the interlayer displacement difference between each shallow base point and its corresponding deep base point; the shallow activity coefficient is positively correlated with the mean and standard deviation, respectively.

[0032] In one possible implementation, the method includes:

[0033] When the inter-layer displacement difference of all shallow base points is less than the inter-layer displacement difference threshold, and the shallow activity coefficient is less than the shallow activity coefficient threshold, the warning level is determined to be the first warning level.

[0034] When there is a shallow base point where the inter-layer displacement difference is greater than or equal to the inter-layer displacement difference threshold, and the shallow activity coefficient is less than the shallow activity coefficient threshold, the warning level is determined to be the second warning level.

[0035] When the inter-layer displacement difference of all shallow base points is less than the inter-layer displacement difference threshold, and the shallow activity coefficient is greater than or equal to the shallow activity coefficient threshold, the warning level is determined to be the second warning level.

[0036] When there is a shallow base point with an inter-layer displacement difference greater than or equal to the inter-layer displacement difference threshold, and the shallow layer activity coefficient is greater than or equal to the shallow layer activity coefficient threshold, the warning level is determined to be the third warning level.

[0037] This application provides a high-precision measurement system for the displacement of mine roof, including:

[0038] The data acquisition unit is used to collect displacement data and installation angle data of multiple monitoring points in the mine roof; the monitoring points include shallow base points and deep base points, and there is a corresponding relationship between the shallow base points and the deep base points are located at a greater depth than the corresponding shallow base points; the displacement data includes the displacement of the monitoring points at each time point recorded in time sequence.

[0039] An angle correction unit is used to correct the displacement data of each monitoring point based on the installation angle data to obtain corrected displacement data; the corrected displacement data is the displacement data after angle conversion from the installation angle data.

[0040] The vibration filtering unit is used to determine the instantaneous displacement of each monitoring point at each time moment based on the corrected displacement data of multiple monitoring points; to perform collaborative analysis on the instantaneous displacements of each monitoring point at each time moment that are greater than a preset displacement threshold, and to determine the collaborative performance value of the monitoring point at the corresponding time moment; to filter vibration data segments from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and to filter the vibration data segments for vibration interference to obtain the true displacement data; the instantaneous displacement is the difference between the displacement at the corresponding time moment and the average displacement; the collaborative performance value is used to characterize the degree of collaboration of vibration interference.

[0041] The present invention has the following beneficial effects:

[0042] In view of the technical problems of insufficient reliability and accuracy of existing measurement technologies, this application provides a high-precision measurement method and system for the displacement of mine roof. This application can collect displacement data and installation angle data of shallow and corresponding deep benchmarks at various locations on the mine roof, achieving comprehensive acquisition of displacement and installation angle of rock strata at different depths of the mine roof. This provides a data foundation for subsequent correction and filtering. Then, based on the installation angle data, the displacement data of each monitoring point is calibrated to obtain calibrated displacement data. Finally, based on the calibrated displacement data of multiple monitoring points, the instantaneous displacement of each monitoring point at each moment is determined. The instantaneous displacement exceeding a preset displacement threshold is analyzed collaboratively to determine the collaborative performance value of the corresponding monitoring point at the corresponding time. Through collaborative analysis, vibration interference and true deformation are distinguished, avoiding misjudgment based on data from a single monitoring point. Thus, this application can filter vibration data segments from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and filter vibration interference from the vibration data segments to effectively eliminate false displacement data and retain true surrounding rock deformation information. This solves the problem of measurement data distortion caused by underground vibration, realizes high-precision measurement of mine roof displacement, and further improves the reliability and accuracy of displacement measurement in complex underground environments. Attached Figure Description

[0043] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a system architecture diagram of a high-precision displacement measurement system for mine roof provided in one embodiment of the present invention;

[0045] Figure 2 A system architecture diagram of a mining area communication network system provided in one embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of a mine roof provided in one embodiment of the present invention;

[0047] Figure 4 This is one of the flowcharts illustrating a high-precision method for measuring the displacement of a mine roof according to an embodiment of the present invention.

[0048] Figure 5 This is a second flowchart illustrating a high-precision method for measuring the displacement of a mine roof, provided in one embodiment of the present invention.

[0049] Figure 6 This is a third flowchart illustrating a high-precision method for measuring the displacement of a mine roof, provided in one embodiment of the present invention.

[0050] Figure 7 This is a fourth flowchart illustrating a high-precision method for measuring the displacement of a mine roof, as provided in one embodiment of the present invention.

[0051] Figure 8 This is the fifth flowchart illustrating a high-precision method for measuring the displacement of a mine roof, as provided in one embodiment of the present invention. Detailed Implementation

[0052] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a high-precision method and system for measuring the displacement of mine roof according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0054] In view of the technical problems of insufficient reliability and accuracy of existing measurement technologies, this application provides a high-precision measurement method and system for the displacement of mine roof. This application can collect displacement data and installation angle data of shallow and corresponding deep benchmarks at various locations on the mine roof, achieving comprehensive acquisition of displacement and installation angle of rock strata at different depths of the mine roof. This provides a data foundation for subsequent correction and filtering. Then, based on the installation angle data, the displacement data of each monitoring point is calibrated to obtain calibrated displacement data. Finally, based on the calibrated displacement data of multiple monitoring points, the instantaneous displacement of each monitoring point at each moment is determined. The instantaneous displacement exceeding a preset displacement threshold is analyzed collaboratively to determine the collaborative performance value of the corresponding monitoring point at the corresponding time. Through collaborative analysis, vibration interference and true deformation are distinguished, avoiding misjudgment based on data from a single monitoring point. Thus, this application can filter vibration data segments from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and filter vibration interference from the vibration data segments to effectively eliminate false displacement data and retain true surrounding rock deformation information. This solves the problem of measurement data distortion caused by underground vibration, realizes high-precision measurement of mine roof displacement, and further improves the reliability and accuracy of displacement measurement in complex underground environments.

[0055] The following description, in conjunction with the accompanying drawings, details the specific scheme of a high-precision measurement method and system for the displacement of mine roof provided by the present invention.

[0056] Please see Figure 1 The diagram shows a system architecture diagram of a high-precision displacement measurement system for mine roof provided in an embodiment of the present invention. The high-precision displacement measurement system 10 for mine roof includes: a data acquisition unit 11, an angle correction unit 12, and a vibration filtering unit 13.

[0057] For example, the high-precision displacement measurement system 10 for mine roofs can be applied to, for example... Figure 2 In the mining area communication network system shown, the data acquisition unit 11 transmits data to the surface mining area network via the underground roof monitoring network, while the angle correction unit 12 and the vibration filtering unit 13 acquire and process data from the surface mining area network. The underground roof monitoring network consists of a communication master station, monitoring area communication substations, and communication cables.

[0058] The underground roof monitoring network can adopt a two-level isolated 485 bus configuration. The communication master station connects to the monitoring area communication substations via the lower bus, with a maximum of 16 monitoring area communication substations. Each monitoring area communication substation can undertake different monitoring functions. Typically, one monitoring area communication substation is responsible for monitoring one mining face and retreat roadway. Within the monitoring area, the bus connects to pressure transmitters and separation bus sensors. Each monitoring area communication substation can collect data from up to 256 pressure transmitters or separation bus sensors to meet the ground pressure monitoring needs of large mines with multiple mining areas. Different types of data can use a unified encoding, distinguishing parameter types through identifiers in the communication protocol. The underground communication master station can connect to the surface monitoring server via telephone lines, single-mode fiber optic cables, or an Ethernet ring network.

[0059] In some embodiments, the data acquisition unit 11 is used to acquire displacement data and installation angle data of multiple monitoring points in the mine roof.

[0060] The monitoring points include shallow and deep baselines, with a corresponding relationship between them. For example, one shallow baseline can correspond to one deep baseline, meaning a deep baseline can be deployed at a greater depth than the location of each shallow baseline. Alternatively, multiple shallow baselines can correspond to one deep baseline, meaning a deep baseline is deployed every few shallow baselines. The depth of the installation location of a deep baseline is greater than the depth of the installation location of its corresponding shallow baseline. Displacement data includes the displacement of the monitoring points at various times, recorded sequentially.

[0061] For example, the data acquisition unit 11 may include a mine displacement sensor (with a built-in angle sensor), an explosion-proof and intrinsically safe uninterruptible power supply, and other equipment. This application allows for the deployment of separation measurement points starting 30 meters from the cut-off point, with one sensor installed every 50 meters. The sensors are installed using ф28mm drilling, with the drilling depth in the top plate not exceeding 10 meters and an allowable drilling inclination angle of +30 degrees.

[0062] Among them, combined Figure 3 For mine roof support, the recommended installation depth for shallow foundation points is 2.2m (anchored within the effective range of the anchor bolt support, reflecting the uniformity of deformation within the support layer), and the recommended installation depth for deep foundation points is 8.5m (anchored in undisturbed deep rock strata, reflecting the stability of deep rock strata). One deep foundation point should be installed for every 1-5 shallow foundation points. The sensor data acquisition frequency is set to 1Hz, and data transmission is conducted wirelessly to reduce the cost of underground cable laying and maintenance, while also avoiding data transmission interference caused by environmental factors.

[0063] Angle correction unit 12 is used to correct the displacement data of each monitoring point according to the installation angle data to obtain corrected displacement data.

[0064] The corrected displacement data is the displacement data after angle conversion from the installation angle data.

[0065] For example, the angle correction unit 12 can be integrated into the communication master station or the survey area communication substation. By receiving the installation angle data transmitted by the data acquisition unit 11, it performs targeted correction on the original displacement data of each monitoring point. Since the displacement data may have lateral deviations due to differences in drilling inclination angles during sensor installation, the angle correction unit 12 uses a specific algorithm to convert the displacement data in the tilt direction into displacement data in the vertical direction, ensuring the comparability of displacement data from different monitoring points and laying the foundation for subsequent vibration filtering and displacement analysis.

[0066] The vibration filtering unit 13 is used to determine the instantaneous displacement of each monitoring point at each time based on the corrected displacement data of multiple monitoring points, to perform collaborative analysis on the instantaneous displacements of each monitoring point at each time that are greater than a preset displacement threshold, to determine the collaborative performance value of the monitoring point corresponding to the instantaneous displacement, to filter vibration data segments from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and to filter vibration interference from the vibration data segments to obtain the true displacement data.

[0067] Among them, the instantaneous displacement is the difference between the displacement at the corresponding moment and the average displacement, and the cooperative performance value is used to characterize the degree of cooperation of vibration disturbance.

[0068] For example, the vibration filtering unit 13 has a built-in data processing chip that can efficiently process time-series displacement data from multiple monitoring points. Instantaneous or periodic vibrations can occur during underground blasting, mine car passage, and fan start-up and shutdown, causing the displacement sensor to output false displacement peaks. The vibration filtering unit 13 analyzes the synergy of the multi-base-point displacement data to accurately distinguish between vibration interference and actual surrounding rock deformation, eliminating false data, retaining true displacement information, and improving the reliability of the measurement data.

[0069] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0070] Please see Figure 4 The diagram illustrates a flowchart of a high-precision method for measuring the displacement of a mine roof according to an embodiment of the present invention. The method includes the following steps:

[0071] Step 401: Collect displacement data and installation angle data of multiple monitoring points in the mine roof.

[0072] The monitoring points include shallow base points and deep base points. There is a corresponding relationship between shallow base points and deep base points. The depth of the installation position of the deep base point is greater than the depth of the installation position of the corresponding shallow base point. The displacement data includes the displacement of the monitoring points at each time point recorded in time sequence.

[0073] In some embodiments, the layout of monitoring points can be combined with the distribution of the mining face and the mining roadway. Shallow benchmarks are anchored within the effective range of the anchor bolt support (usually 2-3m) to reflect the uniformity of deformation within the support layer, while deep benchmarks are anchored in the deep, undisturbed rock strata (usually 8-10m) to reflect the stability of the deep rock strata. Displacement data is collected using mining displacement sensors, and installation angle data is obtained through the angle sensors built into the sensors. The installation of the sensors must meet the preset requirements for borehole depth, spacing, and inclination angle to ensure the effectiveness of data acquisition.

[0074] For example, the sensor acquisition frequency is set to 1Hz, and the time-series displacement data is stored in the order of timestamps to facilitate subsequent data synchronization processing.

[0075] Step 402: Correct the displacement data of each monitoring point according to the installation angle data to obtain the corrected displacement data.

[0076] The corrected displacement data is the displacement data after angle conversion from the installation angle data.

[0077] It should be noted that since tilt angle deviations are unavoidable during drilling and installation, the difference in tilt angles at different monitoring points will cause deviations when the original displacement data is directly compared. Therefore, angle correction is needed to eliminate this error.

[0078] In some embodiments, angle correction refers to converting displacement data in the tilt direction into displacement data in the vertical direction, ensuring that the displacement data of all monitoring points are analyzed based on the same reference (vertical direction).

[0079] In one possible implementation, this application can obtain the installation angle of each monitoring point from the installation angle data. Then, for each monitoring point, based on the installation angle and displacement data corresponding to the monitoring point, the tilt displacement is converted into vertical displacement through trigonometric functions to generate correction displacement data.

[0080] The installation angle is used to characterize the angle between the tilt of the monitoring point and the vertical direction of the Earth's center. This angle directly reflects the degree of tilt of the sensor installation. The larger the angle value, the higher the proportion of lateral deviation in the original displacement data.

[0081] For example, the corrected displacement data is calculated using the following formula:

[0082]

[0083] in, This is the corrected displacement. This is the displacement before correction. The installation angle is used. The displacement before correction is the displacement in the tilt direction, and its projection component in the vertical direction is the effective displacement that truly reflects the settlement of the top plate. This application uses the installation angle... The cosine value can be used to strip away lateral deviations and extract the effective displacement in the vertical direction, thereby achieving angle correction.

[0084] Step 403: Determine the instantaneous displacement of each monitoring point at each moment based on the corrected displacement data of multiple monitoring points.

[0085] The instantaneous displacement is the difference between the displacement at the corresponding moment and the mean displacement.

[0086] In some embodiments, for the time-series corrected displacement data of each monitoring point, this application can first calculate the average displacement at each moment in the time-series corrected displacement data, and then subtract the average displacement from the corrected displacement at each moment to obtain the instantaneous displacement. The instantaneous displacement can reflect the fluctuation of the displacement data at a single moment relative to the average level, which is convenient for identifying abnormal fluctuations.

[0087] Step 404: Perform collaborative analysis on the instantaneous displacements of each monitoring point at each time point that are greater than the preset displacement threshold, and determine the collaborative performance value of the monitoring point at the corresponding time point for the instantaneous displacement.

[0088] Among them, the cooperative performance value is used to characterize the degree of cooperativeness of vibration disturbance.

[0089] For example, the instantaneous displacement of the monitoring point at each moment usually follows a normal distribution. Therefore, this application can determine the preset displacement threshold through the 3σ principle, that is, the preset displacement threshold is set to 3σ (σ is the standard deviation of the instantaneous displacement of the monitoring point). When the instantaneous displacement at a certain moment exceeds 3σ, it is considered that there may be vibration interference at that moment. This application can trigger collaborative analysis and further determine whether the abnormal fluctuation is vibration interference or real surrounding rock deformation through the collaborative characteristics of displacement data from multiple monitoring points.

[0090] In one possible implementation, this application can obtain the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time for the target monitoring point and the target time corresponding to the instantaneous displacement greater than a preset displacement threshold. Then, the collaborative performance value of the target monitoring point at the target time is calculated based on the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time.

[0091] The displacement change is the difference between the displacement of the monitoring point at the target time and the displacement at the previous time. For example, this application can use the target monitoring point as the center and determine the monitoring points of the same type within a preset radius (i.e., if the target monitoring point is a shallow base point, then the adjacent monitoring points are also shallow base points) as the adjacent monitoring points of the target monitoring point. The preset radius can be determined according to the distribution density and distribution area of ​​the downhole monitoring points.

[0092] For example, taking the target monitoring point as the deep baseline, the collaborative performance value satisfies the following formula:

[0093]

[0094] in, As a deep base point The collaborative performance value at the target time. As a deep base point And the standard deviation of the displacement changes of multiple adjacent monitoring points at the target time. As a deep base point And the standard deviation of the instantaneous displacement of multiple adjacent monitoring points at the target time.

[0095] Taking the target monitoring point as a shallow baseline as an example, the collaborative performance value satisfies the following formula:

[0096]

[0097] in, shallow base point The collaborative performance value at the target time. shallow base point And the standard deviation of the displacement changes of multiple adjacent monitoring points at the target time. shallow base point And the standard deviation of the instantaneous displacement of multiple adjacent monitoring points at the target time.

[0098] It should be noted that the smaller the standard deviation of the displacement change, the more consistent the displacement change rate of the target monitoring point and its adjacent monitoring points. The smaller the standard deviation of the instantaneous displacement, the more consistent the instantaneous displacement of the target monitoring point and its adjacent monitoring points. The larger the cooperative performance value, the higher the degree of cooperation in displacement fluctuation, and the more likely it is to be vibration interference.

[0099] Step 405: Based on the collaborative performance value, select vibration data segments from the corrected displacement data of multiple monitoring points, and filter the vibration data segments for vibration interference to obtain the true displacement data.

[0100] It should be noted that various vibration sources exist in the underground environment, such as blasting, mine car passage, and ventilation fan start-up and shutdown. These vibrations can cause false displacement peaks to be output by displacement sensors, which, if not filtered, will affect the accuracy of displacement measurements. Furthermore, even with single-point data filtering, there is still a possibility of mistakenly identifying actual support layer slippage as vibration. Therefore, this application implements multi-base-point linkage filtering based on corrected displacement data from multiple monitoring points, accurately distinguishing vibration interference from actual surrounding rock deformation through displacement synchronization verification at different base points.

[0101] The essence of mine vibration interference is a systemic physical impact, and its core difference from actual surrounding rock deformation lies in the synchronicity and stratification of displacement. When vibration causes changes in the data of displacement sensors, due to the systemic physical impact of vibration, all monitoring points will experience instantaneous jumps synchronously. However, different vibration situations will manifest differently at different depths of reference points. For example, blasting will be reflected at reference points at different depths, while vibrations caused by small vibrations such as the start-up and shutdown of ventilation fans will not be reflected at deep reference points.

[0102] In addition, since vibration can cause jumps in displacement data, and considering the data synchronization of each monitoring point, the displacement difference between different monitoring points will also have similar changing patterns. However, the actual deformation is a trend change in the displacement difference, and the changes at different monitoring points are different.

[0103] Therefore, this application can distinguish between vibration interference and actual surrounding rock deformation based on the coordinated characteristics of displacement and displacement difference at multiple monitoring points at multiple locations and depths, thereby eliminating false data and retaining true displacement information.

[0104] In some embodiments, this application may employ least mean square adaptive filtering algorithms, Kalman filtering algorithms, etc., for vibration interference filtering. These algorithms are adaptable to non-periodic vibration scenarios underground. During the filtering process, this application may use the corrected displacement data of the vibration data segment as the input signal, and use the algorithm to separate the vibration interference components (such as the instantaneous impact displacement generated by blasting and the periodic fluctuation displacement generated by mine car passage) and the real surrounding rock deformation components (such as the linear displacement of the roof slowly sinking and the step-like displacement of rock strata delamination). Finally, the vibration interference components are removed, and the real surrounding rock deformation components are retained to form the real displacement data.

[0105] Furthermore, this application can also smoothly connect the filtered real displacement data with the non-vibration data segments before and after the vibration data segment (such as using linear interpolation to supplement the trend data that may be missing during the filtering process), to avoid the trend break of the displacement data caused by the filtering operation, and to ensure that the real displacement data can fully reflect the continuous deformation process of the top plate, providing a continuous and reliable data foundation for subsequent inter-story displacement difference calculation and risk warning.

[0106] Based on the above technical solution, this application can collect displacement data and installation angle data of shallow and corresponding deep base points at various locations on the mine roof, achieving comprehensive collection of displacement and installation angle of rock strata at different depths in the mine roof. This provides a data foundation for subsequent correction and filtering. Then, the displacement data of each monitoring point is calibrated based on the installation angle data to obtain calibrated displacement data. Furthermore, the instantaneous displacement of each monitoring point at various times is determined based on the calibrated displacement data from multiple monitoring points. Finally, the instantaneous displacements of each monitoring point at various times that exceed a preset displacement threshold are processed... By analyzing the data, the collaborative performance value of the monitoring point corresponding to the instantaneous displacement is determined at the corresponding moment. Through collaborative analysis, vibration interference and real deformation are distinguished, avoiding misjudgment based on data from a single monitoring point. Thus, this application can filter vibration data segments from the corrected displacement data of multiple monitoring points based on the collaborative performance value, and filter vibration interference from the vibration data segments to effectively eliminate false displacement data and retain real surrounding rock deformation information. This solves the problem of measurement data distortion caused by underground vibration, realizes high-precision measurement of mine roof displacement, and further improves the reliability and accuracy of displacement measurement in complex underground environments.

[0107] As one possible embodiment of this application, combined with Figure 4 ,like Figure 5 As shown, step 405 above can be achieved through the following steps:

[0108] Step 501: Determine the vibration data segment based on the corrected displacement data whose collaborative performance value is greater than the preset performance value threshold.

[0109] The vibration data segment includes a shallow base point vibration data segment and a deep base point vibration data segment. The shallow base point vibration data segment consists of corrected displacement data where the co-performance value of the shallow base point is greater than a preset performance value threshold, and the deep base point vibration data segment consists of corrected displacement data where the co-performance value of the deep base point is greater than a preset performance value threshold.

[0110] In some embodiments, the preset performance value threshold of the collaborative performance value can be set in combination with the actual characteristics of downhole vibration, and is usually set to 0.7 (this threshold is calibrated through a large amount of downhole measurement data. When the collaborative performance value is greater than 0.7, the displacement fluctuation of the monitoring point is likely caused by vibration interference).

[0111] This application can, when screening vibration data segments, take the target time as the origin, trace back to the starting time when the collaborative performance value first exceeds the preset performance value threshold, and extend backward to the ending time when the collaborative performance value falls back below the preset performance value threshold, thereby forming a complete vibration data segment and avoiding the omission of data in the beginning or end stages of vibration interference.

[0112] Step 502: Perform vibration interference filtering on the shallow base point vibration data segment and the deep base point vibration data segment respectively to obtain the true displacement data.

[0113] In one possible implementation, this application can perform data fitting on the shallow base point vibration data segment and the deep base point vibration data segment respectively to determine the average data curve of the shallow base point vibration data segment and the average data curve of the deep base point vibration data segment. Then, for the shallow base point vibration data segment and the deep base point vibration data segment respectively, the corresponding average data curve is used as the desired signal, and vibration filtering is performed on the vibration data segment through an adaptive filtering algorithm to obtain the real displacement data.

[0114] For example, this application can obtain the average data curve of the vibration data segment by calculating the average value point by point: For the shallow base point vibration data segment, the average value of the corrected displacement data of all shallow base points at each time moment is taken, and the average displacement values ​​at each time moment are connected in chronological order to form the average data curve of the shallow base point vibration data segment. The method for obtaining the average data curve of the deep base point vibration data segment is similar and will not be described again. The average data curve can reflect the overall characteristics of the vibration disturbance.

[0115] For example, the adaptive filtering algorithm can employ the least mean square algorithm, which features strong real-time performance and low computational cost, making it suitable for filtering data related to non-periodic vibrations in mines. Taking the average data curve of a shallow base point vibration data segment as an example, this application uses the average data curve of the shallow base point as the desired signal and the corrected displacement data of each shallow base point as the input signal. The least mean square algorithm separates the average data curve of the shallow base point into vibration components and true displacement data, which are the true surrounding rock deformation displacement data.

[0116] Based on the above technical solution, this application can determine the vibration data segment based on the corrected displacement data with a collaborative performance value greater than the preset performance value threshold, thereby accurately screening the vibration data segment and avoiding invalid processing of non-vibration data. Then, vibration interference filtering is performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to obtain the real displacement data, further improving the extraction accuracy of the real displacement data and ensuring that the measurement results can accurately reflect the actual deformation of the top plate.

[0117] It should be noted that, in order to retain as much of the real data as possible at each base point while filtering vibration, this application has implemented vibration feature extraction and vibration elimination based on vibration data segments through the above embodiments. Since the real displacement data may still have residual filtering delay after separating vibration components through adaptive filtering, resulting in trend deviation, this application can also combine the historical trends of each base point and ensure the integrity of the real deformation trend through nonlinear fitting, avoiding the problem of real trend lag caused by moving average filtering.

[0118] As one possible embodiment of this application, combined with Figure 5 ,like Figure 6 As shown, the method also includes the following steps:

[0119] Step 601: For the actual displacement data of each monitoring point, obtain the stable data segment within the preset time period before the vibration data segment from the actual displacement data of the monitoring point, and perform nonlinear fitting correction on the actual displacement data based on the stable data segment.

[0120] In some embodiments, the preset time period can be composed of the time corresponding to 10 consecutive data points before the vibration data segment. For example, based on the acquisition frequency of 1Hz, it corresponds to the corrected displacement data of the first 10 seconds of the vibration data segment. The displacement data within this preset time period is not affected by vibration and can be regarded as a stable data segment.

[0121] First, this application can calculate the average instantaneous displacement and the average displacement change at each moment in the stable data segment. Then, using the average instantaneous displacement as the starting coordinate and the average displacement change as the slope, a theoretical trend data curve is generated. Simultaneously, nonlinear fitting is performed on the actual displacement data through polynomial regression to obtain the actual trend data curve. In this way, this application can calculate the difference between the theoretical trend data curve and the actual trend data curve at each moment, obtaining the trend compensation amount at each moment. Finally, the displacement at each moment in the actual displacement data is added to the corresponding trend compensation amount, thereby completing the nonlinear fitting correction.

[0122] Based on the above technical solution, this application can generate a theoretical trend curve from the stable data segment before vibration, and perform nonlinear fitting correction on the real displacement data, thereby eliminating the trend deviation caused by the filtering delay, avoiding the problem of real trend lag caused by moving average filtering, ensuring that the real displacement data can completely retain the real deformation trend such as the slow sinking of the top plate and delamination, and further improving the accuracy and completeness of displacement measurement.

[0123] Furthermore, after determining the actual displacement data, this application can further conduct risk warnings based on the actual displacement data.

[0124] As one possible embodiment of this application, combined with Figure 4 ,like Figure 7 As shown, the method also includes the following steps:

[0125] Step 701: Determine the inter-layer displacement difference between each shallow base point and its corresponding deep base point based on the actual displacement data, and determine the shallow layer activity coefficient based on the inter-layer displacement difference between each shallow base point and its corresponding deep base point.

[0126] Interlayer displacement difference is used to characterize the relative displacement between shallow base points and corresponding deep base points, reflecting the relative deformation degree of shallow rock layers relative to deep stable rock layers. The shallow activity coefficient is used to characterize the deformation activity of the shallow top plate.

[0127] The actual displacement data is obtained through the angle correction (eliminating system errors caused by sensor installation tilt) and vibration interference filtering (removing false displacement data caused by vibrations such as underground blasting and mine car passage) processes described in the above scheme, which can ensure that the basic data used to calculate the interlayer displacement difference is accurate and reliable.

[0128] The greater the difference in interlayer displacement, the greater the difference between the subsidence of the shallow rock layer where the shallow foundation point is located and the subsidence of the deep rock layer where the deep foundation point is located. In other words, there is a tendency for delamination between the shallow and deep layers, and the corresponding risk around the monitoring point is greater. The smaller the difference in interlayer displacement, the more synchronous the deformation of the shallow and deep rock layers or the deformation of the shallow layer is less than that of the deep layer. At this time, the corresponding rock layer is usually in a stable state, and the corresponding risk around the monitoring point is smaller.

[0129] The shallow activity coefficient is calculated based on the interlayer displacement difference between each shallow base point and its corresponding deep base point. It can reflect the overall condition of the rock strata. The larger the shallow activity coefficient, the worse the overall stability of the current rock strata. Conversely, the smaller the shallow activity coefficient, the better the overall stability of the current rock strata.

[0130] Step 702: Conduct risk warning based on interlayer displacement difference and shallow layer activity coefficient.

[0131] It should be noted that the inter-layer displacement difference obtained in the above scheme can reflect the risk at a single point, while the shallow activity coefficient can reflect the overall risk. Therefore, this application can achieve multi-dimensional risk warning for both single points and the overall situation by combining the inter-layer displacement difference and the shallow activity coefficient.

[0132] In some embodiments, this application may determine the threshold based on interlayer displacement difference and shallow layer activity coefficient, respectively.

[0133] When the inter-story displacement difference of all shallow base points is less than the inter-story displacement difference threshold and the shallow activity coefficient is less than the shallow activity coefficient threshold, the warning level is determined to be the first warning level. This indicates that the shallow top plate deformation is stable and continuous monitoring is sufficient. For example, the first warning level can be 0.

[0134] When there is a shallow base point where the inter-layer displacement difference is greater than or equal to the inter-layer displacement difference threshold, and the shallow activity coefficient is less than the shallow activity coefficient threshold, the warning level is determined to be the second warning level. This indicates that the local shallow deformation exceeds the limit and local support monitoring needs to be strengthened. For example, the second warning level can be 1.

[0135] When the inter-story displacement difference of all shallow foundation points is less than the inter-story displacement difference threshold, and the shallow activity coefficient is greater than or equal to the shallow activity coefficient threshold, the warning level is determined to be the second warning level. This indicates that the overall shallow deformation is active and the support condition needs to be fully investigated.

[0136] When there are shallow base points with inter-layer displacement differences greater than or equal to the inter-layer displacement difference threshold, and the shallow layer activity coefficient is greater than or equal to the shallow layer activity coefficient threshold, the warning level is determined to be the third warning level. This indicates that the local area exceeds the limit and the overall area is active. It is necessary to organize the evacuation of personnel immediately and implement reinforcement measures. For example, the third warning level can be 2.

[0137] For example, the multi-level early warning mechanism is shown in Table 1 below:

[0138]

[0139] in, shallow base point Inter-story displacement difference, This represents the shallow layer activity coefficient. The inter-layer displacement difference threshold represents the critical risk value for shallow deformation at the monitoring point, and is typically taken as 80% of the maximum allowable deformation in the design. The threshold for the shallow activity coefficient can be determined based on historical monitoring data of the mine. According to the shallow activity coefficient data of the past three complete mining cycles of the mine when the shallow roof was in a stable state (no need for support and reinforcement, no record of deformation exceeding the limit), the maximum value of the shallow activity coefficient during the stable period is obtained. Considering the increased deformation risk that may be caused by the increase in mining depth and changes in geological conditions, a safety margin of 20% is reserved and calculated, for example, it can be 0.9.

[0140] Based on the above technical solution, this application can determine the inter-layer displacement difference between each shallow foundation point and its corresponding deep foundation point based on real displacement data, and determine the shallow layer activity coefficient based on the inter-layer displacement difference between each shallow foundation point and its corresponding deep foundation point. Risk warning is then conducted based on the inter-layer displacement difference and the shallow layer activity coefficient. Specifically, the single-point warning value identifies local over-limit risks in advance, while the overall warning value identifies the overall instability trend of the region. Thus, this application can establish a multi-dimensional risk warning mechanism for both single points and the overall situation based on the inter-layer displacement difference and the shallow layer activity coefficient, avoiding false alarms due to accidental fluctuations at single points or missed reports of overall regional deformation, effectively reducing the risk of roof collapse accidents.

[0141] As one possible embodiment of this application, combined with Figure 7 ,like Figure 8 As shown, step 701 above can be achieved through the following steps:

[0142] Step 801: For each shallow base point, calculate the first interlayer displacement difference between the shallow base point and the corresponding deep base point, and the second interlayer displacement difference between the shallow base point and the core deep base point.

[0143] Among them, the core deep base point is the deep base point with the smallest average displacement among all deep base points.

[0144] For example, the first-layer displacement difference between a shallow base point and its corresponding deep base point satisfies the following formula:

[0145]

[0146] in, shallow base point With corresponding deep base points The first inter-story displacement difference shallow base point The displacement, For the corresponding deep base point The amount of displacement.

[0147] The second-layer displacement difference between the shallow foundation point and the core deep foundation point satisfies the following formula:

[0148]

[0149] in, shallow base point With core foundation The second inter-story displacement difference, shallow base point The displacement, As the core foundation The displacement of the core deep base point. The core deep base point is the deep base point with the smallest average displacement within a preset time period (e.g., 24 hours) among all deep base points. The displacement of the core deep base point is the most stable and can be used as a global benchmark to improve the reliability of inter-layer displacement difference calculation.

[0150] Step 802: Determine the inter-layer displacement difference between the shallow base point and the corresponding deep base point based on the first inter-layer displacement difference and the second inter-layer displacement difference.

[0151] For example, the inter-story drift difference satisfies the following formula:

[0152]

[0153] in, shallow base point Compared to the corresponding deep base point Inter-story displacement difference, shallow base point With corresponding deep base points The first inter-layer displacement difference reflects the local relative displacement between the shallow base point and its directly corresponding deep base point. shallow base point With core foundation The second interlayer displacement difference reflects the relative displacement between the shallow benchmark and the global stability benchmark. Averaging these two values ​​integrates the characteristics of both the local and global benchmarks, reducing the impact of local biases in a single benchmark. A larger interlayer displacement difference indicates a greater displacement of the shallow benchmark relative to the deeper stable rock layers, and more significant shallow deformation at that benchmark, providing a basis for subsequent risk assessment of local deformation.

[0154] Step 803: Calculate the shallow activity coefficient based on the mean and standard deviation of the interlayer displacement difference between each shallow base point and its corresponding deep base point.

[0155] Among them, the shallow activity coefficient is positively correlated with the mean and standard deviation, respectively.

[0156] For example, the shallow activity coefficient satisfies the following formula:

[0157]

[0158] in, This represents the shallow layer activity coefficient. The standard deviation of the inter-story displacement difference for all shallow foundation points. This represents the average inter-story displacement difference for all shallow foundation points. This is a normalization function (e.g., maximum-minimum normalization) used to normalize the shallow activity coefficients to between 0 and 1. The larger the value, the more uncoordinated the interlayer displacements of the shallow base points relative to the deep base points, and the more active the shallow layer displacements. The larger the value, the greater the displacement of the shallow base point relative to the deep base point, the greater the interlayer displacement, and the greater the corresponding shallow activity coefficient.

[0159] Based on the above technical solution, this application can calculate the inter-layer displacement difference of each shallow base point corresponding to the deep base point and the core deep base point, thereby integrating the characteristics of local and global stability benchmarks and improving the accuracy of local deformation assessment. In addition, the shallow active coefficient quantifies the overall deformation degree and coordination of the shallow top plate through the mean and standard deviation, providing an intuitive and quantifiable indicator for risk warning.

[0160] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0161] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A high-precision method for measuring the displacement of mine roof, characterized in that, include: Displacement data and installation angle data of multiple monitoring points in the mine roof are collected; the monitoring points include shallow base points and deep base points, and there is a corresponding relationship between the shallow base points and the deep base points. The depth of the installation position of the deep base point is greater than the depth of the installation position of the corresponding shallow base point; the displacement data includes the displacement of the monitoring points at each time point recorded in time sequence. The displacement data of each monitoring point is corrected by performing angle correction on the installation angle data to obtain corrected displacement data; the corrected displacement data is the displacement data after angle conversion from the installation angle data. The instantaneous displacement of each monitoring point at each time moment is determined based on the corrected displacement data of the multiple monitoring points; the instantaneous displacement is the difference between the corrected displacement at the corresponding time moment and the mean of the corrected displacement. For each monitoring point, the instantaneous displacements at each time point that are greater than a preset displacement threshold are analyzed collaboratively to determine the collaborative performance value of the monitoring point at the corresponding time point; the collaborative performance value is used to characterize the degree of collaboration of vibration interference. Based on the collaborative performance value, vibration data segments are selected from the corrected displacement data of the multiple monitoring points, and vibration interference is filtered out from the vibration data segments to obtain the true displacement data. Specifically, the displacement data of each monitoring point is corrected based on the installation angle data to obtain corrected displacement data, including: The installation angle of each monitoring point is obtained from the installation angle data; the installation angle is used to characterize the angle between the inclination angle of the monitoring point and the vertical direction of the Earth's center. For each monitoring point, based on the installation angle and displacement data corresponding to the monitoring point, the tilt displacement is converted into vertical displacement using trigonometric functions to generate the correction displacement data; Specifically, for each monitoring point, the instantaneous displacements exceeding a preset displacement threshold at each time moment are analyzed collaboratively to determine the collaborative performance value of the monitoring point at the corresponding time moment, including: For a target monitoring point and a target time corresponding to an instantaneous displacement greater than a preset displacement threshold, the instantaneous displacement and displacement change of the target monitoring point and a plurality of adjacent monitoring points at the target time are obtained; the displacement change is the difference between the displacement of the monitoring point at the target time and the displacement at the previous time. The collaborative performance value of the target monitoring point at the target time is calculated based on the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time.

2. The high-precision measurement method for the displacement of mine roof according to claim 1, characterized in that, Based on the collaborative performance value, vibration data segments are selected from the corrected displacement data of the multiple monitoring points, and vibration interference is filtered out from the vibration data segments to obtain the true displacement data, including: Vibration data segments are determined based on corrected displacement data where the collaborative performance value is greater than a preset performance value threshold. The vibration data segments include shallow base point vibration data segments and deep base point vibration data segments. The shallow base point vibration data segments consist of corrected displacement data where the collaborative performance value is greater than a preset performance value threshold in shallow base points, and the deep base point vibration data segments consist of corrected displacement data where the collaborative performance value is greater than a preset performance value threshold in deep base points. Vibration interference filtering was performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to obtain the true displacement data.

3. The high-precision measurement method for the displacement of mine roof according to claim 2, characterized in that, Vibration interference filtering was performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to obtain the true displacement data, including: Data fitting was performed on the shallow base point vibration data segment and the deep base point vibration data segment respectively to determine the average data curve of the shallow base point vibration data segment and the average data curve of the deep base point vibration data segment. For the shallow base point vibration data segment and the deep base point vibration data segment respectively, the corresponding average data curve is used as the desired signal, and the vibration data segment is subjected to vibration filtering through an adaptive filtering algorithm to obtain the real displacement data.

4. The high-precision measurement method for the displacement of mine roof according to claim 2, characterized in that, The method further includes: For the actual displacement data of each monitoring point, a stable data segment within a preset time period before the vibration data segment is obtained from the actual displacement data of the monitoring point, and the actual displacement data is corrected by nonlinear fitting based on the stable data segment.

5. The high-precision measurement method for the displacement of mine roof according to claim 1, characterized in that, The method further includes: The inter-layer displacement difference between each shallow base point and its corresponding deep base point is determined based on the actual displacement data, and the shallow layer activity coefficient is determined based on the inter-layer displacement difference between each shallow base point and its corresponding deep base point; the inter-layer displacement difference is used to characterize the relative displacement between the shallow base point and its corresponding deep base point, and the shallow layer activity coefficient is used to characterize the deformation activity of the shallow top plate. Risk warnings are issued based on the interlayer displacement difference and the shallow layer activity coefficient.

6. The high-precision measurement method for the displacement of mine roof according to claim 5, characterized in that, Based on the actual displacement data, the inter-layer displacement difference between each shallow base point and its corresponding deep base point is determined, and the shallow layer activity coefficient is determined based on the inter-layer displacement difference between each shallow base point and its corresponding deep base point, including: For each shallow base point, calculate the first interlayer displacement difference between the shallow base point and the corresponding deep base point, and the second interlayer displacement difference between the shallow base point and the core deep base point; the core deep base point is the deep base point with the smallest average displacement among all deep base points. The inter-layer displacement difference between the shallow base point and the corresponding deep base point is determined based on the first inter-layer displacement difference and the second inter-layer displacement difference; The shallow activity coefficient is calculated based on the mean and standard deviation of the interlayer displacement difference between each shallow base point and its corresponding deep base point; the shallow activity coefficient is positively correlated with the mean and standard deviation, respectively.

7. The high-precision measurement method for the displacement of mine roof according to claim 5, characterized in that, The risk warning based on the interlayer displacement difference and the shallow layer activity coefficient includes: When the inter-layer displacement difference of all shallow base points is less than the inter-layer displacement difference threshold, and the shallow layer activity coefficient is less than the shallow layer activity coefficient threshold, the warning level is determined to be the first warning level. When there is a shallow base point where the inter-layer displacement difference is greater than or equal to the inter-layer displacement difference threshold, and the shallow layer activity coefficient is less than the shallow layer activity coefficient threshold, the warning level is determined to be the second warning level. When the inter-layer displacement difference of all shallow base points is less than the inter-layer displacement difference threshold, and the shallow activity coefficient is greater than or equal to the shallow activity coefficient threshold, the warning level is determined to be the second warning level. When there is a shallow base point where the inter-layer displacement difference is greater than or equal to the inter-layer displacement difference threshold, and the shallow layer activity coefficient is greater than or equal to the shallow layer activity coefficient threshold, the warning level is determined to be the third warning level.

8. A high-precision measurement system for the displacement of mine roof, characterized in that, include: The data acquisition unit is used to collect displacement data and installation angle data of multiple monitoring points in the mine roof; the monitoring points include shallow base points and deep base points, and there is a corresponding relationship between the shallow base points and the deep base points. The depth of the installation position of the deep base point is greater than the depth of the installation position of the corresponding shallow base point; the displacement data includes the displacement of the monitoring points at each time point recorded in time sequence. An angle correction unit is used to correct the displacement data of each monitoring point according to the installation angle data to obtain corrected displacement data; the corrected displacement data is displacement data after angle conversion through the installation angle data. A vibration filtering unit is used to determine the instantaneous displacement of each monitoring point at each time moment based on the corrected displacement data of the multiple monitoring points; to perform collaborative analysis on the instantaneous displacements of each monitoring point at each time moment that are greater than a preset displacement threshold, and to determine the collaborative performance value of the monitoring point corresponding to the instantaneous displacement at the corresponding time moment; to filter vibration data segments from the corrected displacement data of the multiple monitoring points based on the collaborative performance value, and to perform vibration interference filtering on the vibration data segments to obtain the true displacement data; the instantaneous displacement is the difference between the corrected displacement at the corresponding time moment and the mean of the corrected displacement; the collaborative performance value is used to characterize the degree of collaboration of vibration interference. Specifically, the displacement data of each monitoring point is corrected based on the installation angle data to obtain corrected displacement data, including: The installation angle of each monitoring point is obtained from the installation angle data; the installation angle is used to characterize the angle between the inclination angle of the monitoring point and the vertical direction of the Earth's center. For each monitoring point, based on the installation angle and displacement data corresponding to the monitoring point, the tilt displacement is converted into vertical displacement using trigonometric functions to generate the correction displacement data; Specifically, for each monitoring point, the instantaneous displacements exceeding a preset displacement threshold at each time moment are analyzed collaboratively to determine the collaborative performance value of the monitoring point at the corresponding time moment, including: For a target monitoring point and a target time corresponding to an instantaneous displacement greater than a preset displacement threshold, the instantaneous displacement and displacement change of the target monitoring point and a plurality of adjacent monitoring points at the target time are obtained; the displacement change is the difference between the displacement of the monitoring point at the target time and the displacement at the previous time. The collaborative performance value of the target monitoring point at the target time is calculated based on the instantaneous displacement and displacement change of the target monitoring point and multiple adjacent monitoring points at the target time.

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