A Stress-Displacement-Based Intelligent Early Warning Method for Roof Disasters

Abstract

This invention discloses a stress-displacement intelligent early warning method for roof disasters, relating to the field of coal mine engineering safety and support technology. The method includes: first, establishing stress-time and displacement-time databases based on the relationship between stress and time in roof delamination and the relationship between displacement and time in roof delamination, with four early warning modules set up in each database; then, collecting stress-time and displacement-time data in real time using sensors and transmitting the collected data to corresponding data processors; after processing the data by the data processors, uploading it to the stress-time and displacement-time databases, dynamically matching it with the four early warning modules in each database, and then generating an early warning signal for issuance. This invention follows the principle of stress-displacement synchronization, significantly improving the accuracy of early warning through dual monitoring methods and comprehensive monitoring of roof delamination stress and displacement.

Description

Technical Field

[0001] This invention relates to the field of coal mine engineering safety and support technology, specifically to an intelligent early warning method for roof disasters based on stress-displacement. Background Technology

[0002] In coal mining, the stability of the tunnel roof is crucial for safe production. As stress redistributes in the surrounding rock, localized delamination and deformation of the roof can occur, potentially leading to roof collapse and other safety accidents. Currently, anchor bolt (cable) support is primarily used to ensure roof stability, and most existing monitoring methods rely on a single parameter—either the stress state of the anchor bolts (cables) or roof deformation. After obtaining the monitoring data, the lack of appropriate judgment criteria hinders its effective utilization. Therefore, it is necessary to establish a corresponding early warning model to perform real-time matching and analysis of the collected data, accurately determine the roof's condition, capture multi-level changes in the roof, and provide precise early warnings before delamination develops and anchoring instability occurs.

[0003] Application No. 201911170436.4 discloses a monitoring and early warning system and method for rockburst disasters in deep well soft coal mines. The system uses a stress sensor to detect borehole pressure and a displacement sensor to detect displacement values ​​generated during roadway wall deformation. It also includes three stress warning signals (first green, first yellow, and first red) and two preset warning pressure values ​​(first and second warning pressure values), as well as three displacement warning signals (second green, second yellow, and second red) and two preset warning pressure values ​​(first and second warning pressure values). The stress warning indicators issue corresponding stress warnings based on the displacement values, thus enabling early warning issuance based on comprehensive data of borehole pressure and roadway deformation.

[0004] The aforementioned existing technologies achieve early warning through monitoring pressure and displacement values. However, their early warning methods emphasize threshold-based warnings based on pressure values ​​and do not explicitly point out the relationship between stress and displacement changes. In reality, displacement and stress can change synchronously. For example, under specific geological conditions (such as soft rock tunnels, deep mining environments, and localized stress relief zones), the stress and displacement of the coal mine roof can exhibit synchronous changes. Specifically, when the stress on the roof strata reaches a certain level, stress redistribution and deformation response occur almost simultaneously. Therefore, existing prediction methods are not feasible for situations where stress and displacement change synchronously, and their prediction accuracy needs further improvement. Summary of the Invention

[0005] The purpose of this invention is to provide a "stress-displacement" intelligent early warning method for roof disasters. This method follows the principle of "stress-displacement" synchronization and significantly improves the accuracy of early warning by comprehensively monitoring the delamination stress and displacement of the roof through dual monitoring methods.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solution: a “stress-displacement” roof disaster intelligent early warning method, including the following steps: (1) establish a stress-time database and a displacement-time database respectively by using the relationship between stress and time of roof delamination and the relationship between displacement and time of roof delamination.

[0007] (2) The stress-time and displacement-time data are collected in real time by sensors, and the collected data is transmitted to the corresponding data processor.

[0008] (3) Four early warning modules are set in the stress-time database, namely stress stability module, stress slow development module, stress delamination development module and stress delamination instability module. The stress stability module means that the anchoring force does not change with time. The stress slow development module means that the anchoring force increases slowly with time. The stress delamination development module means that the anchoring force increases in a jump. The stress delamination instability module means that the anchoring force decreases sharply.

[0009] The displacement-time database contains four early warning modules: an overall stability module, a delamination development module one, a delamination development module two, and a delamination instability module. The overall stability module refers to a displacement deformation that does not change over time. The delamination development module one refers to a displacement deformation that increases slowly and then tends to stabilize. The delamination development module two refers to a displacement deformation that increases abruptly. The delamination instability module refers to a displacement deformation that increases exponentially.

[0010] (4) After the data is processed by the data processor, it is uploaded to the stress-time database and the displacement-time database, dynamically matched with the four early warning modules in each database, and then transformed into an early warning signal for early warning.

[0011] In the above-mentioned "stress-displacement" roof disaster intelligent early warning method, in step (2), the sensor is installed on the anchor bolt or anchor cable, and the anchor bolt or anchor cable is arranged in the roof of the roadway; the sensor includes a stress sensor and a displacement sensor, stress-time data is collected in real time through the stress sensor, and displacement-time data is collected in real time through the displacement sensor.

[0012] In the above-mentioned "stress-displacement" roof disaster intelligent early warning method, in step (2), boreholes are arranged in the roof rock layer of the roadway, and the anchor rods or anchor cables are installed in the boreholes. The stress sensor is fixed at the end of the anchor rods or anchor cables.

[0013] In the above-mentioned "stress-displacement" roof disaster intelligent early warning method, in step (3), the early warning signal is converted into an early warning signal and issued through the early warning release terminal.

[0014] In the above-mentioned "stress-displacement" roof disaster intelligent early warning method, in step (3), the stress stability module indicates that the roof rock layer is stable; the stress slow development module indicates that the roof rock layer support system has begun to be stressed and needs to be monitored and observed; the stress delamination development module indicates that the roof rock layer structure has changed drastically and there are hidden dangers; the stress delamination instability module indicates that the support system has failed and the danger level is high.

[0015] In the above-mentioned "stress-displacement" roof disaster intelligent early warning method, in step (3), the overall stability module indicates that the roof rock layer has not undergone obvious delamination; the delamination development module indicates that the rock layer has slight deformation, but is in a controllable state; the delamination development module indicates that the delamination is developing rapidly and the risk of instability is increasing; the delamination instability module indicates that the rock layer instability trend is intensifying and the risk of collapse is high.

[0016] Compared with the prior art, the present invention brings the following beneficial technical effects: (1) By comprehensively monitoring the delamination stress and displacement of the top plate, a comprehensive analysis of the support system and the state of the rock strata is realized, which makes up for the limitations of traditional single monitoring methods and significantly improves the accuracy of early warning.

[0017] (2) This method divides the monitoring results into eight detailed situations, which can more accurately determine the state of the roof and predict the trend and risk of roof deformation and instability.

[0018] (3) This method can flexibly adjust the monitoring strategy and mode threshold according to changes in geological conditions, and is applicable to various environments such as soft rock, hard rock and deep mining.

[0019] (4) This invention provides a scientific basis for mine management personnel to make decisions, reduces casualties and equipment damage caused by accidents such as collapses, and thus ensures safe production in the mine. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the layout for roof delamination disaster under stress-time monitoring.

[0021] Figure 2 The figures are graphical analysis diagrams for four early warning modules, where (a) is the graphical analysis diagram for the stress stability module; (b) is the graphical analysis diagram for the slow stress development module; (c) is the graphical analysis diagram for the stress delamination development module; and (d) is the graphical analysis diagram for the stress delamination instability module.

[0022] Figure 3 Schematic diagram of the layout for roof delamination disaster under displacement-time monitoring.

[0023] Figure 4 The following are graphical analysis diagrams of four early warning modules: (a) is the graphical analysis diagram of the overall stability module; (b) is the graphical analysis diagram of the first delamination development module; (c) is the graphical analysis diagram of the second delamination development module; and (d) is the graphical analysis diagram of the delamination instability module.

[0024] Figure 5 This is a schematic diagram of an intelligent early warning method for roof delamination disasters.

[0025] In the diagram: 1-Stress sensor; 2-Borehole; 3-Roof strata; 4-Coal seam; 5-Roadway; 6-Anchor bolt; 7-Four early warning modules in the stress-time database; 71-Stress stability module; 72-Slow stress development module; 73-Stress delamination development module; 74-Stress delamination instability module; 8-Deep anchoring point of displacement sensor; 9-Four early warning modules in the displacement-time database; 91-Overall stability module; 92-Delamination development module one; 93-Delamination development module two; 94-Delamination instability module; 10-Shallow anchoring point of displacement sensor; 11-Displacement sensor; 12-Stress-time database and displacement-time database; 13-Early warning release terminal. Detailed Implementation

[0026] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0027] In the description of this application, the words "one," "two," etc., are used only to distinguish different objects and do not limit the quantity or order of execution, nor do they imply that they must be different. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0028] The technical solution of this application will be further described in detail below with reference to the accompanying drawings.

[0029] The main technical concept of this application is as follows: After processing the data collected by stress sensor 1 and displacement sensor 11, the data is input into four early warning modules 7 in the stress-time database and four early warning modules 9 in the displacement-time database for dynamic matching. This is to monitor stress-time and displacement-time synchronously, which is different from the sequential monitoring method in the prior art. By analyzing the judgment and graphics of the four early warning modules, the stability state of the roof, the delamination development process and the instability situation can be identified.

[0030] Combination Figures 1-5 As shown, the present invention provides an intelligent early warning method for roof disaster based on stress-displacement, comprising the following steps:

[0031] Step 1: Set up stress sensor 1 and displacement sensor 11. Figure 1 The diagram shows roadway 5, coal seam 4, and roof rock stratum 3. A borehole 2 is arranged in the roof rock stratum 3 of roadway 5, and an anchor bolt 6 is installed in the borehole 2. A stress sensor 1 is fixed to the end of the anchor bolt 6 to collect stress data in real time.

[0032] A deep anchor point 8 for a displacement sensor is installed at a deep position in borehole 2, and a shallow anchor point 10 for a displacement sensor is installed at a shallow position in borehole 2. The displacement sensor 11 is then fixed outside borehole 2 to collect displacement data in real time.

[0033] The second step is to construct a stress-time database and a displacement-time database 12. The corresponding databases are established through eight early warning modules based on the stress-time and displacement-time relationships. Stress-time and displacement-time data are collected in real time by stress sensor 1 and displacement sensor 11 and uploaded to the data processor. The uploaded data is dynamically matched in the eight early warning modules to determine the state of the top plate and make an evaluation. Finally, the early warning signal is issued using the early warning release terminal 13.

[0034] The eight early warning modules mentioned above specifically include four stress-time modules and four displacement-time modules, as detailed below. Figure 2 As shown, the stress-time database includes four early warning modules 7: stress stability module 71, slow stress development module 72, stress delamination development module 73, and stress delamination instability module 74. Stress stability module 71 indicates a constant stress value, represented by a horizontal straight line in the graph, signifying that the top rock stratum 3 is stable and without risk. Slow stress development module 72 indicates a gradual increase in stress from a constant state, represented by a horizontal straight line followed by a sloping upward line in the graph, indicating that the rock support system is beginning to bear stress and requires enhanced monitoring and observation. Stress delamination development module 73 indicates a sudden increase in stress, represented by a jump in the straight line, indicating drastic changes in the rock structure and potential safety hazards. Stress delamination instability module 74 indicates a precipitous drop in stress, represented by a sudden drop in the straight line, indicating that the support system has failed and a collapse may be imminent, representing the highest level of danger.

[0035] The displacement-time database contains four early warning modules 9, including an overall stability module 91, a delamination development module one 92, a delamination development module two 93, and a delamination instability module 94. The overall stability module 91 shows that the displacement difference between deep and shallow anchor points remains constant, represented by a horizontal straight line in the graph, indicating that no significant delamination has occurred in the top stratum 3, and there is no danger. The delamination development module one 92 shows that the displacement difference between deep and shallow anchor points increases slightly and then stabilizes, indicating slight deformation of the stratum, but it is still under control and the danger level is low. The delamination development module two 93 shows a sudden increase in the displacement difference between deep and shallow anchor points, with the curve rising in a jump-like manner, indicating rapid delamination development, requiring attention, and increasing the risk of instability. The delamination instability module 94 shows an exponential increase in the displacement difference between deep and shallow anchor points, indicating an intensified trend of stratum instability and an extremely high risk of collapse.

[0036] The stress-time database contains four early warning modules 7, including stress stability module 71, slow stress development module 72, stress delamination development module 73, and stress delamination instability module 74. The determination method for each module is as follows.

[0037] Stress stabilization module 71: Stress change rate (ΔF / Δt) ≤ 0.05 kN / min.

[0038] Stress development module 72: 0.05MPa / min<ΔF / Δt≤0.2kN / min.

[0039] Stress delamination development module 73: 0.2kN / min < ΔF / Δt ≤ 0.5kN / min.

[0040] Stress delamination instability module 74: ΔF / Δt>0.5kN / min, or a significant decrease in stress value.

[0041] ΔF / Δt represents the change in anchoring force per unit time (i.e., Figure 2 (Slope of the middle curve).

[0042] The displacement-time database contains four early warning modules 9, including an overall stability module 91, a delamination development module one 92, a delamination development module two 93, and a delamination instability module 94. The determination method for each module is as follows.

[0043] Overall stabilization module 91: Displacement rate (ΔS / Δt) ≤ 0.01 mm / min.

[0044] Delamination development module 192: 0.01 mm / min < ΔS / Δt ≤ 0.1 mm / min.

[0045] Delamination development module 2 93: 0.1 mm / min < ΔS / Δt ≤ 3 mm / min.

[0046] Delamination instability module 94: ΔS / Δt>0.3mm / min.

[0047] ΔS / Δt represents the change in delamination displacement per unit time (i.e., Figure 4 (Slope of the middle curve).

[0048] Secondly, dynamic matching is performed, and "stress-displacement synchronous monitoring" is achieved based on real-time data acquisition, preprocessing, matching algorithms, and state judgment.

[0049] Dynamic matching identifies the condition of the roof by matching real-time data with the characteristic curves of modules in the stress-time and displacement-time databases. The specific process is as follows.

[0050] Data preprocessing: The collected stress and displacement data are normalized and averaged to eliminate noise interference.

[0051] Matching Algorithm: The Dynamic Time Warping (DTW) algorithm in the existing technology is used to match the real-time data curve with the feature curves of eight early warning modules and calculate the matching degree.

[0052] Status Determination: Based on the module with the highest matching degree, the current status of the roof is determined, and the result is verified in conjunction with quantitative standards. The specific steps are as follows: First, single-parameter judgment: Stress is matched with modules in the stress-time database, and displacement is matched with modules in the displacement-time database to obtain single-parameter matching results. Second, comprehensive judgment: The matching results of stress and displacement are comprehensively evaluated: If the matching states of the two are consistent, the current status is directly determined. If the two states are inconsistent, the state with the higher danger level is taken as the final result.

[0053] If the stress change rate matches the stress stability module 71 in the stress-time database, the stress state is stable; if the displacement rate matches the overall stability module 91 in the displacement-time database, the displacement state is stable; then, based on comprehensive judgment, the disaster type of the roof plate is stable.

[0054] If the stress change rate matches the stress stability module 71 in the stress-time database, the stress state is stable; if the displacement rate matches the delamination development module 92 in the displacement-time database, the displacement state is delamination development one; then, based on comprehensive judgment, the disaster type of the roof is delamination development one.

[0055] If the stress change rate matches the stress delamination instability module 74 in the stress-time database, the stress state is instability; if the displacement rate matches the delamination development module 92 in the displacement-time database, the displacement state is delamination development one; then, based on comprehensive judgment, the disaster type of the top plate is stress delamination instability.

[0056] In summary, this invention can simultaneously monitor stress-time and displacement-time, resulting in more accurate judgment results. Parts not mentioned in this invention can be achieved by referring to existing technologies.

[0057] Those skilled in the art should recognize that the above embodiments are only used to illustrate this application and are not intended to limit this application. Any appropriate changes and variations made to the above embodiments within the essential spirit and scope of this application fall within the scope of protection claimed in this application.

Claims

1. A method for intelligent early warning of roof disasters based on stress-displacement, characterized in that, Includes the following steps: (1) By establishing the stress-time database and displacement-time database respectively based on the relationship between stress and time of top plate delamination and the relationship between displacement and time of top plate delamination; (2) Real-time stress-time and displacement-time data are collected by sensors and the collected data are transmitted to the corresponding data processor. (3) Four early warning modules are set in the stress-time database, namely stress stability module, stress slow development module, stress delamination development module and stress delamination instability module. The stress stability module means that the anchoring force does not change with time, the stress slow development module means that the anchoring force increases slowly with time, the stress delamination development module means that the anchoring force increases in a jump, and the stress delamination instability module means that the anchoring force decreases sharply. The displacement-time database is equipped with four early warning modules: overall stability module, delamination development module one, delamination development module two, and delamination instability module. The overall stability module refers to the displacement deformation not changing with time. The delamination development module one refers to the displacement deformation increasing slowly and then stabilizing. The delamination development module two refers to the displacement deformation increasing abruptly. The delamination instability module refers to the displacement deformation increasing exponentially. (4) After the data is processed by the data processor, it is uploaded to the stress-time database and the displacement-time database, dynamically matched with the four early warning modules in each database, and then transformed into an early warning signal for early warning.

2. The "stress-displacement" roof disaster intelligent early warning method according to claim 1, characterized in that: In step (2), the sensor is installed on the anchor bolt or anchor cable, which is arranged in the roof of the roadway; the sensor includes a stress sensor and a displacement sensor, and the stress-time data is collected in real time by the stress sensor and the displacement-time data is collected in real time by the displacement sensor.

3. The "stress-displacement" roof disaster intelligent early warning method according to claim 2, characterized in that: In step (2), boreholes are arranged in the roof rock layer of the roadway, and the anchor bolts or anchor cables are installed in the boreholes. The stress sensor is fixed at the end of the anchor bolts or anchor cables.

4. The "stress-displacement" roof disaster intelligent early warning method according to claim 1, characterized in that: In step (3), the warning signal is converted into an early warning signal and issued through the early warning release terminal.

5. The "stress-displacement" roof disaster intelligent early warning method according to claim 1, characterized in that: In step (3), the stress stability module indicates that the roof rock layer is stable; the slow stress development module indicates that the roof rock layer support system has begun to be stressed and needs to be monitored and observed; the stress delamination development module indicates that the roof rock layer structure has changed drastically and there are hidden dangers; the stress delamination instability module indicates that the support system has failed and the danger level is high.

6. The "stress-displacement" roof disaster intelligent early warning method according to claim 1, characterized in that: In step (3), the overall stability module indicates that no obvious delamination has occurred in the top strata; the delamination development module one indicates that the strata have slight deformation, but are in a controllable state; the delamination development module two indicates that the delamination is developing rapidly and the risk of instability is increasing; the delamination instability module indicates that the trend of strata instability is intensifying and the risk of collapse is high.

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