Electrical method roof damage monitoring inversion imaging method based on optical fiber strain

Abstract

The invention discloses an electrical method roof damage monitoring inversion imaging method based on optical fiber strain, and the method comprises the steps: arranging electrode sensors and optical fiber sensors in an exploration hole at the same time, obtaining the apparent resistivity data in a target monitoring area through the electrode sensors, and obtaining the strain data of each electrode sensor and surrounding rock in real time through the optical fiber sensors; the coupling quality of each electrode sensor and the rock mass is evaluated in combination with a set threshold value, data weight factors of each electrode sensor are obtained according to evaluation results, so that a data weighting matrix of all apparent resistivity is obtained through combination, and the apparent resistivity is obtained through self-adaptive dynamic adjustment of the data weighting matrix in electrical method inversion. The influence of unreliable data caused by poor electrode coupling on an inversion imaging result is reduced, and finally the accuracy and the reliability of an electrical method inversion result are effectively improved. According to the method, the interference influence of electrical method monitoring under complex working conditions can be effectively compensated, and powerful data support is provided for accurate monitoring and imaging of roof damage of the stope face.

Description

Technical Field

[0001] The invention belongs to the technical field of underground engineering monitoring, and in particular is an inversion imaging method for monitoring roof damage by electrical method based on optical fiber strain. Background Art

[0002] During mining, real-time monitoring of roof damage is crucial to production safety and efficient resource mining. Currently, monitoring usually relies on the deployment of sensors in exploration holes. Electrical electrodes are widely used to monitor changes in electrical parameters of the roof, but during the mining process, the exploration holes are affected by the development of the "two zones" (i.e., collapse zones and fracture zones) of the roof, which may cause hole wall ruptures or even collapse, reducing the electrode coupling quality inside the exploration holes, thereby affecting the accuracy of monitoring data and causing electrical inversion imaging results to not converge or be distorted. With its high sensitivity and anti-interference ability, optical fiber sensors can monitor the changes in pressure and strain in the exploration holes in real time, and then analyze the development of the "two zones" of the roof. However, its monitoring range is limited to the exploration holes, and it is difficult to fully reflect the overall changes in the roof.

[0003] Although electrical and optical fiber technologies each have significant advantages, existing research has mostly focused on single applications or joint interpretation of collaborative monitoring data. Existing studies have shown that there is a certain relationship between electrical excitation current and rock strain, but the electrode coupling situation has not been effectively combined with strain data to improve the accuracy of electrical inversion, and the reliability of electrical monitoring data is largely affected by the quality of electrode coupling.

[0004] Therefore, how to provide a new method to obtain the strain information at the electrode in real time, dynamically evaluate the electrode coupling quality, and then adjust the data weighting matrix in the electrical inversion process, and ultimately improve the reliability and stability of the inversion results, is the research direction required by the present invention. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, the present invention provides an electrical method for roof damage monitoring inversion imaging based on optical fiber strain, which obtains the strain information at the electrode in real time through optical fiber, dynamically evaluates the electrode coupling quality, and then adjusts the data weighting matrix in the electrical inversion process, thereby ultimately improving the reliability and stability of the inversion results, and providing strong data support for the accurate imaging of roof damage under complex working conditions.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: an inversion imaging method for roof damage monitoring based on optical fiber strain electrical method, the specific steps are: A. Laying out electrode sensors and optical fiber sensors: Before mining at the coal seam working face, an exploration hole is drilled obliquely upward from the coal seam working face, and multiple electrode sensors and optical fiber sensors are laid out in the hole. Multiple electrode sensors are connected to the electrical method instrument outside the exploration hole, and the coupling quality of each electrode sensor and the rock mass is ensured, so as to monitor the damage of the roof rock mass in real time; the optical fiber sensor is laid out along the axis of the exploration hole, and each electrode sensor is in close contact with the optical fiber sensor at different positions, and the optical fiber sensor is connected to the optical fiber demodulator outside the exploration hole, so as to monitor the deformation of the roof rock mass at each electrode sensor position; then multiple detection time points are pre-set during the mining process; B. Obtaining the initial state data of the rock mass: Before mining the coal seam working face, first start the electrical method instrument to control each electrode sensor to conduct an electrical method detection on the roof rock mass to obtain the apparent resistivity background value, and at the same time start the optical fiber demodulator to control the optical fiber sensor to conduct an optical fiber strain measurement on the roof rock mass to obtain the strain background value at each electrode sensor before mining; C. Collect rock mass data during mining: Start mining on the working face. When the first detection time point is reached during the mining process, start the electrical method instrument and the optical fiber demodulator at the same time to respectively obtain the apparent resistivity data collected at the detection time point and the strain data at each electrode sensor; then, subtract the strain data currently collected at each electrode sensor from the strain background value at each electrode sensor in step B and take the absolute value to obtain the strain difference at each electrode sensor at the detection time point; D. Determine the coupling quality between each electrode sensor and the rock mass during mining: Set the threshold of strain difference and the maximum allowable strain difference ; If the strain difference at a certain electrode sensor is less than or equal to the strain difference threshold , it is judged that the electrode sensor is well coupled with the rock mass; if the strain difference at a certain electrode sensor is greater than the strain difference threshold And less than the maximum allowable strain difference , it is judged that the electrode sensor is poorly coupled with the rock mass; if the strain difference at a certain electrode sensor is greater than or equal to the maximum allowable strain difference , it is determined that the electrode sensor is completely failed; according to the above standard, the strain difference at each electrode sensor in step C is analyzed, and the data weight factor of each electrode sensor at this detection time point is determined by the following formula: in is the strain difference threshold; is the maximum allowable strain difference; is the data weight factor of electrode sensor i; is the strain difference of electrode sensor i; E. Apparent resistivity inversion: Use the data weight factors of each electrode sensor in step D Calculate the data weight factor of each apparent resistivity data at this detection time point in step C Since each apparent resistivity data is related to four electrodes (i.e., power supply electrodes A and B, and measurement electrodes M and N), the weight factor of each apparent resistivity data is calculated according to the following formula: is the data weight factor of the measuring electrode N; The data weight factors of all apparent resistivity data at the detection time point are calculated by the above formula and combined into a data weight matrix Wd for electrical inversion. The data weight matrix Wd is a diagonal matrix, and its diagonal elements are the data weight factors of each apparent resistivity data. The specific form is as follows: Where N is the total number of apparent resistivity data; Then the above data weighted matrix is ​​applied to the objective function of electrical inversion, the data is weighted optimized and solved, and the weighted least squares method is used for inversion to adjust the reliability of apparent resistivity data and improve the stability of electrical inversion. The specific formula is as follows: in The apparent resistivity prediction data calculated by the inversion model m; is the regularization parameter; is the model weighting matrix; is the reference model; Finally, the top plate imaging obtained by electrical inversion at the time of this detection was obtained; F. Continuously monitor the roof damage: During the mining process of the working face, repeat steps C to E every time a detection time point is reached, so as to obtain the roof imaging obtained by electrical inversion at each detection time point, and continuously monitor the roof damage during the mining process.

[0007] Furthermore, in step A, multiple electrode sensors are arranged at equal intervals in the exploration hole, the distance between two adjacent electrode sensors is 1 m, and the optical fiber sensors at different positions are closely contacted with each electrode sensor using tape to ensure that the strain data collected by the optical fiber sensor can truly reflect the coupling status of the electrodes.

[0008] Furthermore, in step A, the angle between the exploration hole and the mining direction is 30° to 45°; the length of the exploration hole is 100 meters, and the diameter of the borehole is 100 mm; after the electrode sensors and optical fiber sensors are laid out, the exploration hole is grouted with bentonite slurry to ensure that each electrode sensor and optical fiber sensor is well coupled with the rock mass of the hole wall.

[0009] Furthermore, in step A, each electrode sensor after deployment is numbered in sequence from the deepest part of the exploration hole to the outside, and the position corresponding to each electrode sensor number is calibrated in the optical fiber strain curve collected by the optical fiber sensor according to the position of each electrode sensor, so as to be used for the subsequent collection of strain data at each electrode sensor.

[0010] Furthermore, the electrical detection in steps B and C adopts the Wenner running electrode method.

[0011] Furthermore, the threshold value and the maximum allowable strain difference of the strain difference in step D are obtained in the following manner: first, the top rock mass of the required monitoring working face is sampled, and the samples are subjected to strain experiments in the laboratory, so as to calibrate the threshold value and the maximum allowable strain difference corresponding to this detection.

[0012] Compared with the prior art, the present invention drills an upward oblique exploration hole in the mining face, arranges electrode sensors and optical fiber sensors in the exploration hole at the same time, uses electrode sensors to obtain apparent resistivity data in the target monitoring area, uses optical fiber sensors to obtain strain data of each electrode sensor and surrounding rock in real time, and evaluates the coupling quality of each electrode sensor and rock mass in combination with a set threshold value, obtains the data weight factor of each electrode sensor according to the evaluation result, and thus obtains the data weight matrix Wd of all apparent resistivities by combination, and introduces the data weight matrix in electrical inversion, and evaluates the coupling quality of each electrode sensor and updates the data weight matrix Wd at each detection time point, and adjusts the data weight matrix in electrical inversion by adaptive dynamic adjustment to reduce the unreliable data caused by poor electrode coupling that affects the inversion imaging results, so as to achieve electrical high-resolution imaging of roof damage; and finally effectively improves the accuracy and reliability of electrical inversion results. The method can effectively compensate for the interference effect of electrical monitoring under complex working conditions, and provide strong data support for the accurate monitoring and imaging of roof damage in mining faces. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the overall process of the present invention; Figure 2 It is a schematic diagram of the layout of the electrode sensor and the optical fiber sensor in the present invention. DETAILED DESCRIPTION

[0014] The present invention will be further described below.

[0015] like Figure 1 As shown, the specific steps of the present invention are: A. Laying out electrode sensors and optical fiber sensors: Figure 2 As shown, before mining is carried out at the coal seam working face, an exploration hole is drilled obliquely upward from the coal seam working face, and multiple electrode sensors and optical fiber sensors are arranged in the hole. The multiple electrode sensors are all connected to the electrical instrument outside the exploration hole, and the coupling quality of each electrode sensor and the rock mass is ensured, so as to monitor the damage of the roof rock mass in real time; the distance between two adjacent electrode sensors is 1m, and the optical fiber sensors at different positions are closely contacted with each electrode sensor with tape, so as to ensure that the strain data collected by the optical fiber sensor can truly reflect the coupling condition of the electrode. The optical fiber sensor is arranged along the axis of the exploration hole, and each electrode sensor is in close contact with the optical fiber sensor at different positions. The optical fiber sensor is connected to the optical fiber demodulator outside the exploration hole to monitor the deformation of the roof rock mass at each electrode sensor position; the angle between the exploration hole and the mining direction is 30° to 45°; the length of the exploration hole is 100 meters, and the diameter of the borehole is 100 mm; the exploration hole is grouted with bentonite slurry after the electrode sensor and the optical fiber sensor are arranged to ensure that each electrode sensor and the optical fiber sensor are well coupled with the rock mass of the hole wall; the electrode sensors after arrangement are numbered from the inside to the outside from the deepest part of the exploration hole, and the position corresponding to the number of each electrode sensor is calibrated in the optical fiber strain curve collected by the optical fiber sensor according to the position of each electrode sensor, which is used for the subsequent collection of strain data at each electrode sensor. Then, multiple detection time points in the mining process are pre-set.

[0016] B. Obtaining the initial state data of the rock mass: Before mining the coal seam working face, first start the electrical method instrument to use the Wenner running electrode method to control each electrode sensor to conduct an electrical method detection of the roof rock mass to obtain the apparent resistivity background value, and at the same time start the optical fiber demodulator to control the optical fiber sensor to conduct an optical fiber strain measurement of the roof rock mass to obtain the strain background value at each electrode sensor before mining; C. Collect rock mass data during mining: Start mining on the working face. When the first detection time point is reached during the mining process, start the electrical method instrument and the optical fiber demodulator at the same time to respectively obtain the apparent resistivity data collected at the detection time point and the strain data at each electrode sensor; then, subtract the strain data currently collected at each electrode sensor from the strain background value at each electrode sensor in step B and take the absolute value to obtain the strain difference at each electrode sensor at the detection time point; D. Determine the coupling quality between each electrode sensor and the rock mass during mining: Set the threshold of strain difference and the maximum allowable strain difference The specific acquisition process is: first sample the roof rock mass of the required monitoring working face, and conduct strain experiments on the samples in the laboratory, so as to calibrate the threshold and maximum allowable strain difference of the strain difference corresponding to this detection. If the strain difference at a certain electrode sensor is less than or equal to the strain difference threshold , then it is judged that the electrode sensor is well coupled with the rock mass, and the data weight factor is 1; if the strain difference at a certain electrode sensor is greater than the strain difference threshold And less than the maximum allowable strain difference , it is judged that the electrode sensor is poorly coupled with the rock mass; if the strain difference at a certain electrode sensor is greater than or equal to the maximum allowable strain difference , it is judged that the electrode sensor is completely failed, and the data weight factor is 0; according to the above standard, the strain difference at each electrode sensor in step C is analyzed, and the data weight factor of each electrode sensor at this detection time point is determined by the following formula: in is the strain difference threshold; is the maximum allowable strain difference; is the data weight factor of electrode sensor i; is the strain difference of electrode sensor i; E. Apparent resistivity inversion: Use the data weight factors of each electrode sensor in step D Calculate the data weight factor of each apparent resistivity data at this detection time point in step C Since each apparent resistivity data is related to four electrodes (i.e., power supply electrodes A and B, and measurement electrodes M and N), the weight factor of each apparent resistivity data is calculated according to the following formula: is the data weight factor of the measuring electrode N; The data weight factors of all apparent resistivity data at the detection time point are calculated by the above formula and combined into a data weight matrix Wd for electrical inversion. The data weight matrix Wd is a diagonal matrix, and its diagonal elements are the data weight factors of each apparent resistivity data. The specific form is as follows: Where N is the total number of apparent resistivity data; Then the above data weighted matrix is ​​applied to the objective function of electrical inversion, the data is weighted optimized and solved, and the weighted least squares method is used for inversion to adjust the reliability of apparent resistivity data and improve the stability of electrical inversion. The specific formula is as follows: in The apparent resistivity prediction data calculated by the inversion model m; is the regularization parameter; is the model weighting matrix; is the reference model; Finally, the top plate imaging obtained by electrical inversion at the time of this detection was obtained; F. Continuously monitor the roof damage: During the mining process of the working face, repeat steps C to E every time a detection time point is reached, so as to obtain the roof imaging obtained by electrical inversion at each detection time point, and continuously monitor the roof damage during the mining process.

[0017] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An inversion imaging method for roof damage monitoring based on optical fiber strain, characterized in that: The specific steps are: A. Laying out electrode sensors and optical fiber sensors: Before mining at the coal seam working face, an exploration hole is drilled obliquely upward from the coal seam working face, and multiple electrode sensors and optical fiber sensors are laid out in the hole. Multiple electrode sensors are connected to the electrical method instrument outside the exploration hole, and the coupling quality of each electrode sensor and the rock mass is ensured, so as to monitor the damage of the roof rock mass in real time; the optical fiber sensor is laid out along the axis of the exploration hole, and each electrode sensor is in close contact with the optical fiber sensor at different positions, and the optical fiber sensor is connected to the optical fiber demodulator outside the exploration hole, so as to monitor the deformation of the roof rock mass at each electrode sensor position; then multiple detection time points are pre-set during the mining process; B. Obtaining the initial state data of the rock mass: Before mining the coal seam working face, first start the electrical method instrument to control each electrode sensor to conduct an electrical method detection on the roof rock mass to obtain the apparent resistivity background value, and at the same time start the optical fiber demodulator to control the optical fiber sensor to conduct an optical fiber strain measurement on the roof rock mass to obtain the strain background value at each electrode sensor before mining; C. Collect rock mass data during mining: Start mining on the working face. When the first detection time point is reached during the mining process, start the electrical method instrument and the optical fiber demodulator at the same time to respectively obtain the apparent resistivity data collected at the detection time point and the strain data at each electrode sensor; then, subtract the strain data currently collected at each electrode sensor from the strain background value at each electrode sensor in step B and take the absolute value to obtain the strain difference at each electrode sensor at the detection time point; D. Determine the coupling quality between each electrode sensor and the rock mass during mining: Set the threshold of strain difference and the maximum allowable strain difference ; If the strain difference at a certain electrode sensor is less than or equal to the strain difference threshold , it is judged that the electrode sensor is well coupled with the rock mass; if the strain difference at a certain electrode sensor is greater than the strain difference threshold And less than the maximum allowable strain difference , it is judged that the electrode sensor is poorly coupled with the rock mass; if the strain difference at a certain electrode sensor is greater than or equal to the maximum allowable strain difference , it is determined that the electrode sensor is completely failed; according to the above standard, the strain difference at each electrode sensor in step C is analyzed, and the data weight factor of each electrode sensor at this detection time point is determined by the following formula: in is the strain difference threshold; is the maximum allowable strain difference; is the data weight factor of electrode sensor i; is the strain difference of electrode sensor i; E. Apparent resistivity inversion: Use the data weight factors of each electrode sensor in step D Calculate the data weight factor of each apparent resistivity data at this detection time point in step C Since each apparent resistivity data is related to four electrodes, the weight factor of each apparent resistivity data is calculated according to the following formula: The data weight factors of all apparent resistivity data at the detection time point are calculated by the above formula and combined into a data weight matrix Wd for electrical inversion. The data weight matrix Wd is a diagonal matrix, and its diagonal elements are the data weight factors of each apparent resistivity data. The specific form is as follows: Where N is the total number of apparent resistivity data; Then the above data weighted matrix is ​​applied to the objective function of electrical inversion, the data is weighted optimized and solved, and the weighted least squares method is used for inversion. The specific formula is as follows: in The apparent resistivity prediction data calculated by the inversion model m; is the regularization parameter; is the model weighting matrix; is the reference model; Finally, the top plate imaging obtained by electrical inversion at the time of this detection was obtained; F. Continuously monitor the roof damage: During the mining process of the working face, repeat steps C to E every time a detection time point is reached, so as to obtain the roof imaging obtained by electrical inversion at each detection time point, and continuously monitor the roof damage during the mining process.

2. According to the optical fiber strain-based electrical method for roof damage monitoring inversion imaging method of claim 1, it is characterized in that: In step A, multiple electrode sensors are arranged at equal intervals in the exploration hole, the distance between two adjacent electrode sensors is 1 m, and the optical fiber sensors at different positions are closely contacted with each electrode sensor using tape to ensure that the strain data collected by the optical fiber sensor can truly reflect the coupling status of the electrodes.

3. According to claim 1, the optical fiber strain-based electrical method for roof damage monitoring inversion imaging method is characterized in that: In step A, the angle between the exploration hole and the mining direction is 30° to 45°; the length of the exploration hole is 100 meters and the diameter of the borehole is 100 mm; after the electrode sensors and optical fiber sensors are laid out, the exploration hole is grouted with bentonite slurry to ensure that each electrode sensor and optical fiber sensor is well coupled with the rock mass of the hole wall.

4. According to claim 1, the optical fiber strain-based electrical method for roof damage monitoring inversion imaging method is characterized in that: In step A, the electrode sensors after deployment are numbered in sequence from the deepest part of the exploration hole to the outside, and the position corresponding to the number of each electrode sensor is calibrated in the optical fiber strain curve collected by the optical fiber sensor according to the position of each electrode sensor, so as to subsequently collect strain data at each electrode sensor.

5. According to claim 1, the optical fiber strain-based electrical method for roof damage monitoring inversion imaging method is characterized in that: The electrical detection in steps B and C adopts the Wenner running electrode method.

6. The inversion imaging method for roof damage monitoring based on optical fiber strain according to claim 1 is characterized in that: The threshold value and the maximum allowable strain difference of the strain difference in step D are obtained in the following manner: first, the top rock mass of the required monitoring working face is sampled, and the samples are subjected to strain experiments in the laboratory, so as to calibrate the threshold value and the maximum allowable strain difference of the strain difference corresponding to this detection.

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