All-fiber micro-seismic monitoring device and monitoring method

Abstract

The invention relates to the technical field of optical fiber micro-seismic monitoring, in particular to an all-optical fiber micro-seismic monitoring device and a monitoring method. According to the method, the geological survey data and the geological state of the tunnel engineering are obtained, the geological evaluation result is obtained, the sensor installation analysis is performed according to the geological evaluation result to obtain the sensor installation strategy, then the sensor installation calibration is performed based on the sensor installation strategy, and the tunnel detection data are acquired through the sensor. The multi-source information data of tunnel construction is obtained, and the multi-source information data and the tunnel detection data are comprehensively analyzed to obtain the micro-seismic monitoring state, so that the monitoring position can be adjusted by changing the sensor mounting mode under the condition that the monitoring equipment algorithm and the mounting space cannot be changed, errors caused by mounting position limitation are reduced, and the monitoring accuracy is improved. And early warning of a rockburst fine control position is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of optical fiber microseismic monitoring, and in particular to an all-optical fiber microseismic monitoring device and a monitoring method. Background Art

[0002] Microseismic monitoring, as a three-dimensional rock damage monitoring technology, has been recognized as one of the reliable means of rock burst warning. The spatial distribution of microseismicity has an obvious correspondence with the location of rock burst or stress concentration area. The all-fiber microseismic monitoring device uses fiber-optic microseismic sensors, which have the characteristics of anti-electromagnetic interference and can work stably in complex electromagnetic environments, thus improving the reliability of monitoring. It uses optical fiber as a signal transmission medium, has the advantages of high bandwidth and low loss, and can transmit data quickly and stably.

[0003] Currently, microseismic monitoring captures microseismic signals by installing microseismic sensors in tunnels. However, due to the limitations on the installation position of microseismic monitoring sensors in tunnels and the accuracy differences of different monitoring equipment, certain errors are inevitable when locating the location of rock ruptures through microseismic monitoring, which is very unfavorable for the refined spatial position warning of rock bursts. Summary of the invention

[0004] The present invention provides an all-optical fiber microseismic monitoring device and a monitoring method, which are used to solve the above-mentioned technical problems.

[0005] A first aspect of the present invention provides an all-fiber microseismic monitoring method, comprising the following steps:

[0006] Step 1: Obtain geological survey data and geological status of the tunnel project and obtain geological assessment results; obtain geological survey data of the monitored area including geological structure, rock properties and fault distribution through geological survey, obtain stress state through comprehensive analysis of geological structure, rock properties and fault distribution, and obtain geological assessment results based on geological status.

[0007] As a further improvement of the present invention, a comprehensive analysis is conducted on the geological structure, rock formation properties and fault distribution, and the specific analysis method is as follows:

[0008] The geological structure includes crust thickness and coordinate information; multiple unit monitoring sections are set in the monitoring area, the crust thickness is divided into multiple thickness intervals, each thickness interval corresponds to a crust fluctuation value, and the crust thickness corresponding to each current unit monitoring section is matched with multiple thickness intervals to obtain the crust fluctuation value corresponding to each unit monitoring section; the tectonic activity belt information in the database is obtained, the tectonic activity belt information is identified to obtain the coordinate information of each seismic belt, the coordinate information corresponding to the tunnel project is matched with the coordinate information of each seismic belt to obtain the adjacent seismic belt, the coordinate information of the adjacent seismic belt and the tunnel project is calculated to obtain the interval distance, the interval distance is divided into multiple interval distance intervals, each interval distance interval corresponds to a distance influence index, the current interval distance is matched with multiple interval distance intervals to obtain the corresponding distance influence index, the earthquake probability and magnitude intensity corresponding to the adjacent seismic belt are obtained, the distance influence index, the earthquake probability and the magnitude intensity are multiplied to calculate the tectonic belt influence value, and recorded as gzd.

[0009] The rock type and rock strength corresponding to each unit monitoring section are obtained by identifying the properties of the rock formation; the rock type includes stable rock and soft rock; stable rock includes but is not limited to quartzite, basalt, granite, and quartz porphyry; soft rock includes but is not limited to soft shale, very soft limestone, chalk, rock salt, and gypsum; the rock type is recorded as YS, and the rock type corresponding to each unit monitoring section is identified. When the rock type corresponding to the unit monitoring section is stable rock, YS=0; when the rock type corresponding to the unit monitoring section is soft rock, YS=1; the rock strength corresponding to the stable rock is obtained and marked as the rock strength reference value. When the rock strength corresponding to the unit monitoring section is less than the rock strength reference value, the corresponding rock strength is subtracted from the rock strength reference value to obtain the strength influence difference, which is recorded as QD.

[0010] The activity records corresponding to each fault are obtained by identifying the fault distribution. The number of activities within the unit analysis time corresponding to each fault is obtained according to the activity records corresponding to each fault. The activity probability is calculated by ratioing the number of activities to the unit analysis time, and the pre-set activity probability threshold is obtained. When the activity probability corresponding to the fault is greater than the activity probability threshold, the activity impact value is calculated by subtracting the activity probability threshold and recorded as hdz.

[0011] The structural belt impact value, intensity impact difference value and activity impact value are normalized and their values ​​are taken. The formula is used The geological influence value DZ is calculated; among them, N1, N2 and N3 are preset weight factors, and their values ​​are 0.571, 0.237 and 0.399 respectively; e is a natural constant, and its value is about 2.71828; when the geological influence value is less than the set stability threshold, the corresponding geological state is generated as the key monitoring section.

[0012] Step 2: Analyze the sensor installation through the geological assessment results to obtain the sensor installation strategy; identify the geological assessment data to obtain the geological status corresponding to each unit monitoring section. When the geological status corresponds to the key monitoring section, the corresponding sensor installation strategy is generated as dense installation. The installation method includes but is not limited to drilling and surface installation of sensors at different depths at the positions of the tunnel vault, waist and shoulder.

[0013] Step 3: Perform sensor installation calibration based on the sensor installation strategy, and obtain tunnel detection data through sensor collection.

[0014] Step 4: Acquire multi-source information data of tunnel construction, and conduct comprehensive analysis on the multi-source information data and tunnel detection data to obtain microseismic monitoring status, which is specifically: obtain multi-source data by analyzing the multi-source information data, and obtain monitoring status information by analyzing the multi-source data and tunnel detection data.

[0015] As a further improvement of the present invention, the multi-source information data is analyzed, and the specific analysis method is as follows:

[0016] The sound data and tunnel construction records are obtained by identifying multi-source information data; the sound data includes key sound data and noise data, and the noise data includes but is not limited to the operation of construction equipment, human activities, and the sensor's own noise; the voiceprint features corresponding to each noise data are obtained, and each sound data is matched with the voiceprint features corresponding to the noise data to obtain the corresponding current noise data, and the number of current noise data is counted to obtain the current noise number, and a pre-set noise number threshold is obtained. If the current noise number is greater than the noise number threshold, the current noise number and the noise number threshold are subtracted to obtain the noise impact amount.

[0017] Tunnel construction data is identified to obtain tunnel image data and construction material information; a pre-set standard image of tunnel construction is obtained, and the tunnel image data is overlapped and compared with the standard image to obtain a construction error value. When the construction error value is greater than a set upper limit value, the part of the construction error value greater than the set upper limit value is marked as a construction impact value, and construction impact values ​​corresponding to tunnel image data corresponding to multiple unit monitoring sections are obtained, and multiple construction impact values ​​are calculated to obtain an average value and the value is marked as a construction impact mean value; construction material information is identified to obtain the material stiffness corresponding to the construction material, and a pre-set stiffness requirement interval is obtained, and the material stiffness corresponding to the construction material is matched with the stiffness requirement interval. When the material stiffness is less than the stiffness requirement interval, the corresponding material stiffness is marked as a material impact value.

[0018] A right-angled trapezoid is constructed with the material impact value and the construction impact value as the upper and lower bases of the right-angled trapezoid. The length of the right-angled waist of the right-angled trapezoid is equal to the value of the noise impact amount. The area of ​​the right-angled trapezoid is calculated and the value of the area is marked as the multi-source impact value.

[0019] As a further improvement of the present invention, the multi-source data and tunnel detection data are analyzed, and the specific analysis method is as follows:

[0020] Frequency characteristics, signal strength data and sensor status data are obtained by identifying tunnel detection data; standard frequency characteristics corresponding to microseismicity are extracted from the database, and the frequency characteristics corresponding to the tunnel detection data of each sensor are matched with the standard frequency characteristics to obtain the microseismic frequency characteristics, and the frequency characteristics of multiple unit detection times corresponding to each sensor are obtained. The number of microseismic frequency characteristics is counted and recorded as the microseismic frequency number, and the microseismic occurrence frequency is calculated by ratio of the microseismic frequency number to the detection time.

[0021] The signal strength data corresponding to the microseismic frequency characteristics are obtained, and the microseismic energy values ​​corresponding to each microseismic frequency characteristic are obtained through the signal strength data. The microseismic energy values ​​are divided into multiple energy value intervals, each energy value interval corresponds to a microseismic impact value, and the microseismic energy values ​​corresponding to each microseismic frequency characteristic are matched with multiple energy value intervals to obtain the corresponding microseismic impact value.

[0022] The sensor status data is identified to obtain the calibration status and power status; the corresponding calibration cycle and current use date are obtained according to the calibration status of each sensor, the most recent calibration date of each sensor is obtained, the difference between the most recent calibration date and the current use date is calculated to obtain the corresponding current use time, the healthy use time of each sensor is obtained through the calibration cycle, the current use time of each sensor is compared with the corresponding healthy use time, if the current use time is longer than the healthy use time, the portion of the current use time of each sensor that exceeds the healthy use time is recorded as the time impact value; the corresponding power supply voltage value is obtained according to the power status of each sensor, a pre-set voltage reference value is obtained, and the difference between the power supply voltage value and the voltage reference value is calculated to obtain the voltage difference value; a circle is constructed with the value of the time impact value as the radius, another circle is constructed with any point of the side length of the circle as the center and the value of the voltage difference as the radius, and then a closed figure is formed by the two circles, the area of ​​the closed figure is calculated and the value of the area is recorded as the sensor status value.

[0023] The microseismic frequency, microseismic impact value and sensor state value are normalized and their values ​​are taken. The formula is used to The monitoring status value JC is calculated; among them, DY, CG, wzp and wzy represent the multi-source influence value, sensor status value, microseismic occurrence frequency and microseismic influence value, respectively; ΔDY and ΔCG represent the multi-source influence allowable value and sensor status allowable value, respectively; b1, b2, b3 and b4 are preset weight factors, with values ​​of 1.33, 1.71, 2.16 and 1.98, respectively; when the monitoring status value is greater than the set threshold, the corresponding microseismic monitoring status generated is monitoring anomaly.

[0024] Step 5: Generate monitoring warning information according to the microseismic monitoring status. The monitoring warning information includes but is not limited to abnormal microseismic data, abnormal sensor status, and sensor installation adjustment information.

[0025] A second aspect of the present invention provides an all-fiber microseismic monitoring device, comprising: a sensing detection component, a fiber-optic microseismic monitoring host, a signal transmission component and an edge computing host;

[0026] The sensing detection component is used to sense tiny vibration signals generated by micro-fractures in the rock mass and convert them into optical or electrical signals.

[0027] The optical fiber microseismic monitoring host is used to receive the signal from the sensing detection component and process it to highlight the characteristics of the microseismic signal, and to control and manage the microseismic monitoring.

[0028] The signal transmission component is used as a data transmission channel between the sensing detection component, the optical fiber microseismic monitoring host and the edge computing host.

[0029] The edge computing host makes intelligent warnings and decisions based on the analysis results, and independently controls and manages the monitoring system in the event of a communication interruption with the central server or cloud.

[0030] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0031] The present invention obtains geological survey data and geological status of tunnel engineering and obtains geological assessment results, and performs sensor installation analysis based on the geological assessment results to obtain a sensor installation strategy, then performs sensor installation calibration based on the sensor installation strategy, obtains tunnel detection data through sensor collection, and obtains multi-source information data of tunnel construction, and performs comprehensive analysis on the multi-source information data and tunnel detection data to obtain microseismic monitoring status. Therefore, under the condition that the monitoring equipment algorithm and installation space cannot be changed, the monitoring position can be adjusted by changing the sensor installation method, thereby reducing the error caused by the installation position limitation and facilitating early warning of the refined control position of the rockburst. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0033] Figure 1 is a flow chart of the method of the present invention;

[0034] Figure 2 The figure is a schematic diagram of an all-fiber microseismic monitoring device. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 In an embodiment of the present invention, an embodiment of an all-fiber microseismic monitoring method includes the following steps:

[0037] Step 1: Obtain geological survey data and geological status of the tunnel project and obtain geological assessment results; obtain geological survey data of the monitored area including geological structure, rock properties and fault distribution through geological survey, obtain stress state through comprehensive analysis of geological structure, rock properties and fault distribution, and obtain geological assessment results based on geological status.

[0038] A comprehensive analysis of geological structure, rock properties and fault distribution is conducted. The specific analysis method is as follows:

[0039] The geological structure includes crust thickness and coordinate information; multiple unit monitoring sections are set in the monitoring area, the crust thickness is divided into multiple thickness intervals, each thickness interval corresponds to a crust fluctuation value, and the crust thickness corresponding to each current unit monitoring section is matched with multiple thickness intervals to obtain the crust fluctuation value corresponding to each unit monitoring section; the tectonic activity belt information in the database is obtained, the tectonic activity belt information is identified to obtain the coordinate information of each seismic belt, the coordinate information corresponding to the tunnel project is matched with the coordinate information of each seismic belt to obtain the adjacent seismic belt, the coordinate information of the adjacent seismic belt and the tunnel project is calculated to obtain the interval distance, the interval distance is divided into multiple interval distance intervals, each interval distance interval corresponds to a distance influence index, the current interval distance is matched with multiple interval distance intervals to obtain the corresponding distance influence index, the earthquake probability and magnitude intensity corresponding to the adjacent seismic belt are obtained, and the distance influence index, the earthquake probability and the magnitude intensity are multiplied to obtain the tectonic belt influence value.

[0040] The rock type and rock strength corresponding to each unit monitoring section are obtained by identifying the properties of the rock formation; the rock type includes stable rock and soft rock; stable rock includes but is not limited to quartzite, basalt, granite, and quartz porphyry; soft rock includes but is not limited to soft shale, very soft limestone, chalk, rock salt, and gypsum; the rock type is recorded as YS, and the rock type corresponding to each unit monitoring section is identified. When the rock type corresponding to the unit monitoring section is stable rock, YS=0; when the rock type corresponding to the unit monitoring section is soft rock, YS=1; the rock strength corresponding to the stable rock is obtained and marked as the rock strength reference value. When the rock strength corresponding to the unit monitoring section is less than the rock strength reference value, the corresponding rock strength is calculated by difference with the rock strength reference value to obtain the strength influence difference.

[0041] The activity records corresponding to each fault are obtained by identifying the fault distribution. The number of activities within the unit analysis time corresponding to each fault is obtained according to the activity records corresponding to each fault. The activity probability is calculated by ratioing the number of activities to the unit analysis time. The pre-set activity probability threshold is obtained. When the activity probability corresponding to the fault is greater than the activity probability threshold, the activity impact value is calculated by subtracting the activity probability threshold from the activity probability threshold.

[0042] The structural belt impact value, intensity impact difference value and activity impact value are normalized and their values ​​are taken. The formula is used The geological influence value DZ is calculated; among them, gzd, QDA and hdz represent the tectonic belt influence value, intensity influence difference and activity influence value respectively; N1, N2 and N3 are all preset weight factors, with values ​​of 0.571, 0.237 and 0.399 respectively; e is a natural constant, with a value of approximately 2.71828; when the geological influence value is less than the set stability threshold, the corresponding geological state is generated as the key monitoring section.

[0043] Step 2: Analyze the sensor installation through the geological assessment results to obtain the sensor installation strategy; identify the geological assessment data to obtain the geological status corresponding to each unit monitoring section. When the geological status corresponds to the key monitoring section, the corresponding sensor installation strategy is generated as dense installation. The installation method includes but is not limited to drilling and surface installation of sensors at different depths at the positions of the tunnel vault, waist and shoulder.

[0044] Step 3: Perform sensor installation calibration based on the sensor installation strategy, and obtain tunnel detection data through sensor collection.

[0045] Step 4: Obtain multi-source information data of tunnel construction, and conduct comprehensive analysis of the multi-source information data and tunnel detection data to obtain the microseismic monitoring status.

[0046] Comprehensive analysis of multi-source information data and tunnel detection data:

[0047] The sound data and tunnel construction records are obtained by identifying multi-source information data; the sound data includes key sound data and noise data, and the noise data includes but is not limited to the operation of construction equipment, human activities, and the sensor's own noise; the voiceprint features corresponding to each noise data are obtained, and each sound data is matched with the voiceprint features corresponding to the noise data to obtain the corresponding current noise data, and the number of current noise data is counted to obtain the current noise number, and a pre-set noise number threshold is obtained. If the current noise number is greater than the noise number threshold, the current noise number and the noise number threshold are subtracted to obtain the noise impact amount.

[0048] Tunnel construction data is identified to obtain tunnel image data and construction material information; a pre-set standard image of tunnel construction is obtained, and the tunnel image data is overlapped and compared with the standard image to obtain a construction error value. When the construction error value is greater than a set upper limit value, the part of the construction error value greater than the set upper limit value is marked as a construction impact value, and construction impact values ​​corresponding to tunnel image data corresponding to multiple unit monitoring sections are obtained, and multiple construction impact values ​​are calculated to obtain an average value and the value is marked as a construction impact mean value; construction material information is identified to obtain the material stiffness corresponding to the construction material, and a pre-set stiffness requirement interval is obtained, and the material stiffness corresponding to the construction material is matched with the stiffness requirement interval. When the material stiffness is less than the stiffness requirement interval, the corresponding material stiffness is marked as a material impact value.

[0049] A right-angled trapezoid is constructed with the material impact value and the construction impact value as the upper and lower bases of the right-angled trapezoid. The length of the right-angled waist of the right-angled trapezoid is equal to the value of the noise impact amount. The area of ​​the right-angled trapezoid is calculated and the value of the area is marked as the multi-source impact value.

[0050] Frequency characteristics, signal strength data and sensor status data are obtained by identifying tunnel detection data; standard frequency characteristics corresponding to microseismicity are extracted from the database, and the frequency characteristics corresponding to the tunnel detection data of each sensor are matched with the standard frequency characteristics to obtain the microseismic frequency characteristics, and the frequency characteristics of multiple unit detection times corresponding to each sensor are obtained. The number of microseismic frequency characteristics is counted and recorded as the microseismic frequency number, and the microseismic occurrence frequency is calculated by ratio of the microseismic frequency number to the detection time.

[0051] The signal strength data corresponding to the microseismic frequency characteristics are obtained, and the microseismic energy values ​​corresponding to each microseismic frequency characteristic are obtained through the signal strength data. The microseismic energy values ​​are divided into multiple energy value intervals, each energy value interval corresponds to a microseismic impact value, and the microseismic energy values ​​corresponding to each microseismic frequency characteristic are matched with multiple energy value intervals to obtain the corresponding microseismic impact value.

[0052] The sensor status data is identified to obtain the calibration status and power status; the corresponding calibration cycle and current use date are obtained according to the calibration status of each sensor, the most recent calibration date of each sensor is obtained, the difference between the most recent calibration date and the current use date is calculated to obtain the corresponding current use time, the healthy use time of each sensor is obtained through the calibration cycle, the current use time of each sensor is compared with the corresponding healthy use time, if the current use time is longer than the healthy use time, the portion of the current use time of each sensor that exceeds the healthy use time is recorded as the time impact value; the corresponding power supply voltage value is obtained according to the power status of each sensor, a pre-set voltage reference value is obtained, and the difference between the power supply voltage value and the voltage reference value is calculated to obtain the voltage difference value; a circle is constructed with the value of the time impact value as the radius, another circle is constructed with any point of the side length of the circle as the center and the value of the voltage difference as the radius, and then a closed figure is formed by the two circles, the area of ​​the closed figure is calculated and the value of the area is recorded as the sensor status value.

[0053] The microseismic frequency, microseismic impact value and sensor state value are normalized and their values ​​are taken. The formula is used to The monitoring status value JC is calculated; among them, DY, CG, wzp and wzy represent the multi-source influence value, sensor status value, microseismic occurrence frequency and microseismic influence value, respectively; ΔDY and ΔCG represent the multi-source influence allowable value and sensor status allowable value, respectively; b1, b2, b3 and b4 are preset weight factors, with values ​​of 1.33, 1.71, 2.16 and 1.98, respectively; when the monitoring status value is greater than the set threshold, the corresponding microseismic monitoring status generated is monitoring anomaly.

[0054] Step 5: Generate monitoring warning information according to the microseismic monitoring status. The monitoring warning information includes but is not limited to abnormal microseismic data, abnormal sensor status, and sensor installation adjustment information.

[0055] The present invention also provides an all-fiber microseismic monitoring device, including a sensing detection component, a fiber-optic microseismic monitoring host, a signal transmission component and an edge computing host;

[0056] The sensing detection component senses tiny vibration signals generated by micro-cracks in the rock mass and converts them into optical or electrical signals.

[0057] The optical fiber microseismic monitoring host receives the signal of the sensing detection component and processes it to highlight the characteristics of the microseismic signal, and performs control and management of microseismic monitoring.

[0058] The signal transmission component serves as a data transmission channel between the sensing detection component, the optical fiber microseismic monitoring host and the edge computing host.

[0059] The edge computing host makes intelligent warnings and decisions based on the analysis results, and independently controls and manages the monitoring system in the event of communication interruptions to the central server or cloud.

[0060] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An all-fiber microseismic monitoring method, characterized in that: The steps include: Step 1: Obtain geological survey data and geological conditions of the tunnel project and obtain geological assessment results; Step 2: Perform sensor installation analysis based on geological assessment results to obtain sensor installation strategies; Step 3: Perform sensor installation calibration based on the sensor installation strategy, and obtain tunnel detection data through sensor collection; Step 4: Obtain multi-source information data of tunnel construction, and conduct comprehensive analysis on the multi-source information data and tunnel detection data to obtain microseismic monitoring status; Step 5: Generate monitoring warning information based on the microseismic monitoring status.

2. The all-fiber microseismic monitoring method according to claim 1, characterized in that: The step of obtaining geological survey data and geological conditions of the tunnel project and obtaining geological assessment results specifically includes: obtaining geological survey data of the monitored area through geological survey, including geological structure, rock formation properties and fault distribution, performing comprehensive analysis on the geological structure, rock formation properties and fault distribution to obtain stress state, and obtaining geological assessment results based on the geological conditions; A comprehensive analysis of geological structure, rock properties and fault distribution is conducted. The specific analysis method is as follows: The geological structure includes crust thickness and coordinate information; multiple unit monitoring sections are set in the monitoring area, the crust thickness is divided into multiple thickness intervals, each thickness interval corresponds to a crust fluctuation value, and the crust thickness corresponding to each current unit monitoring section is matched with multiple thickness intervals to obtain the crust fluctuation value corresponding to each unit monitoring section; the tectonic activity belt information in the database is obtained, the tectonic activity belt information is identified to obtain the coordinate information of each seismic belt, the coordinate information corresponding to the tunnel project is matched with the coordinate information of each seismic belt to obtain the adjacent seismic belt, the coordinate information of the adjacent seismic belt and the tunnel project is calculated to obtain the interval distance, the interval distance is divided into multiple interval distance intervals, each interval distance interval corresponds to a distance influence index, the current interval distance is matched with multiple interval distance intervals to obtain the corresponding distance influence index, the earthquake probability and magnitude intensity corresponding to the adjacent seismic belt are obtained, and the distance influence index, the earthquake probability and the magnitude intensity are multiplied to obtain the tectonic belt influence value; The rock type and rock strength corresponding to each unit monitoring section are obtained by identifying the rock formation properties; rock types include stable rock and soft rock; the rock type is recorded as YS, and the rock type corresponding to each unit monitoring section is identified. When the rock type corresponding to the unit monitoring section is stable rock, YS=0; when the rock type corresponding to the unit monitoring section is soft rock, YS=1; Obtain the rock strength corresponding to the stable rock and mark it as the rock strength reference value. When the rock strength corresponding to the unit monitoring section is less than the rock strength reference value, calculate the difference between the corresponding rock strength and the rock strength reference value to obtain the strength impact difference. The activity records corresponding to each fault are obtained by identifying the distribution of faults. The number of activities within the unit analysis time of each fault is obtained according to the activity records corresponding to each fault. The activity probability is calculated by ratioing the number of activities to the unit analysis time, and a pre-set activity probability threshold is obtained. When the activity probability corresponding to the fault is greater than the activity probability threshold, the activity impact value is calculated by subtracting the activity probability threshold from the activity probability. The geological impact value is obtained by comprehensively analyzing the rock type, tectonic belt impact value, strength impact difference and activity impact value. When the geological impact value is less than the set stability threshold, the corresponding geological state is generated as the key monitoring section.

3. The all-fiber microseismic monitoring method according to claim 1, characterized in that: The sensor installation analysis based on the geological assessment results is used to obtain the sensor installation strategy, which is specifically: the geological state corresponding to each unit monitoring section is obtained by identifying the geological assessment data, and when the geological state corresponds to the key monitoring section, the corresponding sensor installation strategy is generated as dense installation.

4. The all-fiber microseismic monitoring method according to claim 1, characterized in that: The comprehensive analysis of the multi-source information data and the tunnel detection data is specifically: obtaining the multi-source data by analyzing the multi-source information data, and obtaining the monitoring status information by analyzing the multi-source data and the tunnel detection data; The multi-source information data is analyzed, specifically: sound data and tunnel construction records are obtained by identifying the multi-source information data; the sound data includes key sound data and noise data; the voiceprint features corresponding to each noise data are obtained, each sound data is matched with the voiceprint features corresponding to the noise data to obtain the corresponding current noise data, the number of current noise data is counted to obtain the current noise number, a preset noise number threshold is obtained, and if the current noise number is greater than the noise number threshold, the current noise number is calculated by difference with the noise number threshold to obtain the noise impact amount; Tunnel construction data is identified to obtain tunnel image data and construction material information; a preset standard image of tunnel construction is obtained, and the tunnel image data is overlapped and compared with the standard image to obtain a construction error value. When the construction error value is greater than a set upper limit value, the portion of the construction error value greater than the set upper limit value is marked as a construction impact value, and construction impact values ​​corresponding to tunnel image data corresponding to multiple unit monitoring sections are obtained, and multiple construction impact values ​​are calculated to obtain an average value and the value is marked as a construction impact mean value; construction material information is identified to obtain the material stiffness corresponding to the construction material, a preset stiffness requirement interval is obtained, and the material stiffness corresponding to the construction material is matched with the stiffness requirement interval. When the material stiffness is less than the stiffness requirement interval, the corresponding material stiffness is marked as a material impact value; A right-angled trapezoid is constructed with the material impact value and the construction impact value as the upper and lower bases of the right-angled trapezoid. The length of the right-angled waist of the right-angled trapezoid is equal to the value of the noise impact amount. The area of ​​the right-angled trapezoid is calculated and the value of the area is marked as the multi-source impact value.

5. The all-fiber microseismic monitoring method according to claim 4, characterized in that: The analysis of multi-source data and tunnel detection data is specifically as follows: Frequency characteristics, signal strength data and sensor status data are obtained by identifying tunnel detection data; standard frequency characteristics corresponding to microseisms are extracted from the database, and each frequency characteristic corresponding to the tunnel detection data of each sensor is matched with the standard frequency characteristic to obtain the frequency characteristics of microseisms, and the frequency characteristics of multiple unit detection times corresponding to each sensor are obtained, and the number of microseismic frequency characteristics is counted and recorded as the number of microseismic frequencies, and the ratio of the number of microseismic frequencies to the detection time is calculated to obtain the frequency of microseismic occurrence; Acquire signal strength data corresponding to the microseismic frequency characteristics, obtain microseismic energy values ​​corresponding to each microseismic frequency characteristic through the signal strength data, divide the microseismic energy values ​​into multiple energy value intervals, each energy value interval corresponds to a microseismic impact value, match the microseismic energy values ​​corresponding to each microseismic frequency characteristic with the multiple energy value intervals to obtain the corresponding microseismic impact value; Identify the sensor status data to obtain the calibration status and power status; obtain the corresponding calibration cycle and current use date according to the calibration status of each sensor, obtain the most recent calibration date of each sensor, calculate the difference between the most recent calibration date and the current use date to obtain the corresponding current use time, obtain the healthy use time of each sensor through the calibration cycle, compare the current use time of each sensor with the corresponding healthy use time, if the current use time is longer than the healthy use time, record the portion of the current use time of each sensor that exceeds the healthy use time as the time impact value; according to the power status of each sensor Obtain the corresponding power supply voltage value, obtain a preset voltage reference value, and calculate the difference between the power supply voltage value and the voltage reference value to obtain the voltage difference value; construct a circle with the value of the duration impact value as the radius, construct another circle with any point of the side length of the circle as the center and the value of the voltage difference as the radius, and then form a closed figure with the two circles, calculate the area of ​​the closed figure and record the value of the area as the sensing state value; comprehensively analyze the multi-source impact value, microseismic occurrence frequency, microseismic impact value and sensing state value to obtain the monitoring state value; when the monitoring state value is greater than the set threshold, generate the corresponding microseismic monitoring state as monitoring anomaly.

6. An all-fiber microseismic monitoring device, characterized in that An all-fiber microseismic monitoring method as described in any one of claims 1 to 5, comprising a sensing detection component, a fiber-optic microseismic monitoring host, a signal transmission component and an edge computing host; The sensing detection component senses tiny vibration signals generated by micro-fractures in the rock mass and converts them into optical or electrical signals; The optical fiber microseismic monitoring host receives the signal of the sensing detection component and processes it to highlight the characteristics of the microseismic signal, and performs control and management of microseismic monitoring; The signal transmission component serves as a data transmission channel between the sensing detection component, the optical fiber microseismic monitoring host and the edge computing host; The edge computing host performs intelligent early warning and decision-making based on the analysis results, and independently controls and manages the monitoring system in the event of a central server or cloud communication interruption.

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