Micro-seismic monitoring and early warning system for rockburst in tunnel / hole operation period

Abstract

The invention discloses a micro-seismic monitoring and early warning system for tunnel / hole operation period rockburst, and relates to the technical field of rockburst micro-seismic monitoring. The sensors are installed in a left-right hole cross distribution mode, it is ensured that micro-seismic signals can be effectively collected during tunnel operation, it is ensured that the monitoring ranges of all monitoring sections are not overlapped through sensor grouping with cross numbers and adjacent numbers, and the accuracy of seismic source positioning is improved through signal cross verification of the multiple sensors; the method comprises the following steps: extracting spectrum characteristic parameters of microseismic signals through Fourier transform, time-frequency analysis and other methods, carrying out microseismic active intensity analysis on the spectrum characteristic parameters to obtain an active intensity index of a monitoring area, and carrying out distance removal on the active intensity index to obtain a seismic source activity index of each monitoring area; according to the seismic source activity index development trend of the microseismic event of each monitoring area, analysis is carried out to judge the rockburst risk of each monitoring area, a risk early warning value is obtained, risk early warning or encryption processing is automatically triggered according to the risk early warning value, and the safety and stability of tunnel operation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rockburst microseismic monitoring, and in particular to a microseismic monitoring and early warning system for rockburst during tunnel / hole operation. Background Art

[0002] With the continuous deepening of underground engineering and the long-term effect of regional stress, the intensity of the accumulated stress inside the rock mass is strengthened after the completion of the tunnel lining, and its ability to bear stress is gradually enhanced, resulting in the damage of the original geological defect position having a time effect, that is, the position that may be damaged during the construction period is delayed to the operation period. This result will cause fatal harm to the running trains or cars, and this phenomenon has begun to appear on plateau railways, but so far no case of early warning of rock bursts through microseismic monitoring during operation has been reported, and it is still in a blank stage; for this reason, it is urgent to establish a microseismic system operation method suitable for rock burst monitoring during operation. Summary of the invention

[0003] Based on this, it is necessary to provide a microseismic monitoring and early warning system for rock bursts during tunnel / hole operation in response to the problems mentioned in the above background technology.

[0004] The object of the present invention can be achieved by the following technical solutions: a microseismic monitoring and early warning system for rock burst during tunnel / hole operation period, the system comprising a deployment acquisition module, a memory, a microseismic monitoring module and a risk early warning module;

[0005] The collection module is installed by cross-distributing the sensors in the left and right holes, and the sensors are numbered; the sensors are segmented according to their numbers to form several monitoring sections, each of which contains three monitoring areas, and the source location is determined according to the numbers and quantity of the sensors;

[0006] The memory is connected to each sensor in communication to collect and store microseismic events and their corresponding microseismic signals;

[0007] The microseismic monitoring module performs microseismic activity intensity analysis based on the microseismic events in each monitoring area and their corresponding microseismic signals to obtain the activity intensity index of the monitoring area, and then de-distances the activity intensity index according to the distance between each sensor and the center point of the monitoring area to obtain the source activity index of each monitoring area; analyzes the development trend of the source activity index of the microseismic events in each monitoring area to determine the rock burst risk of each monitoring area, obtains the risk warning value, and sends it to the risk warning module;

[0008] The risk warning module performs risk warning processing based on the received risk warning value, specifically:

[0009] The risk warning values ​​of the three monitoring areas of each monitoring section are retrieved and compared with the set warning interval. If the risk warning value of any monitoring area is greater than the upper limit of the set warning interval, the risk warning is triggered; if the risk warning values ​​of the three monitoring areas are all less than the lower limit of the set warning interval, no operation is required; in other cases, the monitoring section is recorded as an encrypted section, and the encrypted section is encrypted by the sensor. The specific encryption process is as follows:

[0010] The risk warning values ​​of the three monitoring areas of the encrypted segment are retrieved, and the average is calculated to obtain the risk average; the product obtained by multiplying the risk average by the set encryption conversion coefficient is rounded to obtain the encrypted quantity, and the encrypted quantity is output; thus, the encrypted quantity of each encryption segment can be obtained.

[0011] In some embodiments, sensors are arranged crosswise in the left and right holes, and the monitoring sections are formed by segmentation as follows:

[0012] The sensors are installed in a cross-distribution manner in the left and right holes, and the sensors are cross-numbered one by one, so that each sensor corresponds to a position and number; the specific numbering sequence is: the first sensor in the left hole is numbered 1, the first sensor in the right hole is numbered 2, the second sensor in the left hole is numbered 3, and so on. The numbering of all sensors is recorded as n, n = 1, 2, 3...N, N is a positive integer, N represents the total number of sensors, and n represents the number of any one of the sensors;

[0013] Three sensors with adjacent numbers are grouped together, and the corresponding monitoring range is a monitoring segment. Specifically, there is only one intersection sensor between two adjacent groups of sensors. Each monitoring segment is marked as m, and specifically m = 1, 2, 3...M, where M is a positive integer, M represents the total number of monitoring segments, and m represents the number of any monitoring segment.

[0014] In the same group of sensors within a certain monitoring section, sensor n in the middle position is taken as the center, and each monitoring area 50m away from sensor n is selected as a monitoring area n; the monitoring area n-1 is the edge of the monitoring area n starting from the n-1 sensor, and similarly, the monitoring area n+1 is the edge of the monitoring area n starting from the n+1 sensor. In this way, each monitoring section can be divided into three monitoring areas. The source position can be determined based on the microseismic signals received in each monitoring area.

[0015] In some embodiments, the specific method of determining the earthquake source location based on the sensor number and quantity is:

[0016] There is a group of sensors (n-1, n and n+1) in the monitoring section. If microseismic signals are received from sensors n-1 and n, the source location is judged to be in the monitoring area n-1; if microseismic signals are received from sensors n and n+1, the source location is judged to be in the monitoring area n+1; if microseismic signals are received from sensors n-1, n and n+1, the source location is judged to be in the monitoring area n; thus, the source location can be judged according to the received microseismic signals and recorded as Lmn.

[0017] In some embodiments, the specific process of microseismic activity intensity analysis is:

[0018] Perform Fourier transform on the microseismic signal, convert the signal from time domain to frequency domain, and use time-frequency analysis method to extract spectrum characteristic parameters. Specific spectrum characteristic parameters include bandwidth, peak frequency, and signal duration.

[0019] The envelope of the microseismic signal is extracted and the amplitude jump value is obtained by using derivative and calculus calculation and analysis;

[0020] The bandwidth K, peak frequency P, duration T and amplitude jump value △A are normalized and their values ​​are taken. The values ​​are analyzed and calculated by formula to obtain the activity intensity index KP of the microseismic signal. The specific calculation formula is:

[0021]

[0022] β1, β2, β3, and β4 are respectively set weight constants, and their specific values ​​are set by those skilled in the art according to actual needs.

[0023] In some embodiments, the de-distance method is:

[0024] The minimum circumscribed rectangle is used to find the center point of each monitoring area, the distance between each sensor and the center point is calculated, and then the active intensity index is divided by the distance to obtain a unitless intensity index. The mean of each intensity index in each monitoring area is calculated to obtain the source activity value; thus, the source activity value of each microseismic event in each monitoring area can be obtained and recorded as KPj, where j = 1, 2, 3...J, J is a positive integer, J represents the total number of microseismic events, and j represents any microseismic event in the monitoring area.

[0025] In some embodiments, the envelope of the microseismic signal is extracted and analyzed by using derivatives and calculus calculations as follows:

[0026] The microseismic signal F(t) is extracted and the envelope is recorded as |F Hilbert(t)|, the specific envelope is the complex signal of F(t) after Hilbert transform, "| |" represents the modulo operation, where t is the time dimension;

[0027] The amplitude change of the microseismic signal is described by calculating the instantaneous change rate of the envelope. The specific amplitude change rate is approximated by the derivative of the envelope. The specific derivative formula is:

[0028]

[0029] Where △A(t) represents the rate of change of amplitude at the time dimension t;

[0030] According to the amplitude change rate △A(t) of each unit time dimension, the overall change degree of the microseismic signal is calculated by calculus to obtain the amplitude jump value △A. The specific calculation formula is:

[0031]

[0032] Where T represents the total duration of the microseismic signal, and the amplitude jump value △A represents the total amount of change in the microseismic signal during this period of time.

[0033] In some embodiments, the method of analyzing the development trend of the source activity index of microseismic events in each monitoring area is as follows:

[0034] A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the source activity value as the vertical coordinate. The source activity value of each microseismic event in the monitoring area is input into the coordinate according to its corresponding time, and the position of the source activity value in the coordinate axis is recorded as the activity point. The line segments are used to connect the activity points in turn to obtain a line graph of the change of the source activity index.

[0035] Two adjacent activity points constitute an activity line segment, and thus several activity line segments can be cut out from the line graph of the change of the source activity index. The mean of the activity mean is calculated by calculating the mean of the source activity index corresponding to the activity points at both ends of each activity line segment. The slope of each active line segment is calculated by data fitting and recorded as

[0036] The activity mean of each activity line segment in the line graph of earthquake source activity index change is and slope Perform formula calculation and analysis to obtain the risk warning value S R isk, the specific calculation formula is:

[0037]

[0038] δ1, δ2, and δ3 are respectively set weight constants, and their specific values ​​are set by those skilled in the art according to actual needs.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. Sensors are installed in a cross-distributed manner in the left and right tunnels to ensure that microseismic signals can be effectively collected during tunnel operation without damaging the original secondary lining structure; each sensor has a unique position and number, and the cross-numbered and adjacent numbered sensors are grouped to ensure that the monitoring ranges of each monitoring section do not overlap; in a quiet operating environment, sensors can better receive microseismic signals, and use the signals of multiple sensors for cross-verification to improve the accuracy of earthquake source positioning, providing accurate data support for subsequent risk assessment and processing;

[0041] 2. The frequency spectrum characteristic parameters of microseismic signals are extracted through Fourier transform, time-frequency analysis and other methods, and the microseismic activity intensity is analyzed to obtain the activity intensity index of the monitoring area. Then, the activity intensity index is de-distanced according to the distance between each sensor and the center point of the monitoring area to obtain the source activity index of each monitoring area. The development trend of the source activity index of microseismic events in each monitoring area is analyzed to determine the rock burst risk of each monitoring area, and the risk warning value is obtained, which can effectively quantify the energy concentration of microseismic signals and the intensity of source activity. It not only improves the accuracy of monitoring, but also can timely discover potential risks in tunnels, thereby providing reliable data support for the prevention, control and management of tunnel risks;

[0042] 3. By receiving the risk warning value of each monitoring area and combining it with the set risk range, the potential rock burst risk of microseismic events can be monitored and warned in real time, and risk warning or encrypted processing can be automatically triggered; according to different risk warning values, the number of sensors in the encrypted section can be adjusted to ensure more intensive monitoring in areas with higher risks; an automated risk handling process can be implemented to quickly respond to potential rock burst risks and improve the safety and stability of tunnel operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the conventional technology, the drawings required for use in the embodiments or the conventional technology descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 It is a principle block diagram of the present invention;

[0045] Figure 2 This is a schematic diagram of the sensor layout of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0047] Embodiment 1:

[0048] like Figure 1 As shown, a microseismic monitoring and early warning system for rock burst during tunnel / hole operation period, the system comprises: a memory, a layout acquisition module and a microseismic monitoring module;

[0049] The acquisition module is installed by cross-distributing sensors in the left and right tunnels (the sensors are installed by surface rivets. The tunnel is relatively quiet during operation, so the microseismic signals can be better collected. The original secondary lining is not damaged, and the signal collection can be completed well). The sensors are cross-numbered one by one, so that each sensor corresponds to a position and number; the specific numbering sequence is: the first sensor in the left tunnel is numbered 1, the first sensor in the right tunnel is numbered 2, the second sensor in the left tunnel is numbered 3, and so on. The numbering of all sensors is recorded as n, n = 1, 2, 3...N, N is a positive integer, N represents the total number of sensors, n It represents the number of any one of the sensors; three sensors with adjacent numbers (n-1, n and n+1) are grouped as a group, and the corresponding monitoring range is a monitoring segment. There is only one intersection sensor between two specific adjacent groups of sensors. For example, there are three adjacent sensor groups (n-3, n-2 and n-1), (n-1, n and n+1) and (n+1, n+2 and n+3); it can be seen that the monitoring ranges of the monitoring segments do not overlap; each monitoring segment is marked as m, specifically m=1,2,3...M, M is a positive integer, M represents the total number of monitoring segments, and m represents the number of any one of the monitoring segments;

[0050] In the same group of sensors in a certain monitoring section, sensor n in the middle is taken as the center, and each monitoring area 50m away from sensor n is selected as a monitoring area n; the area from sensor n-1 to the edge of monitoring area n is monitoring area n-1, and similarly, the area from sensor n+1 to the edge of monitoring area n is monitoring area n+1; thus, each monitoring section can be divided into three monitoring areas; the source position can be determined based on the microseismic signals received in each monitoring area; the specific determination method is as follows:

[0051] Taking a certain monitoring section as an example, there is a group of sensors (n-1, n and n+1) in the monitoring section. If the microseismic signals from sensors n-1 and n are received, the source position is judged to be in the monitoring area n-1; if the microseismic signals from sensors n and n+1 are received, the source position is judged to be in the monitoring area n+1; if the microseismic signals from sensors n-1, n and n+1 are received, the source position is judged to be in the monitoring area n; thus, the source position can be judged according to the received microseismic signals and recorded as Lmn; this method is very reasonable in the microseismic detection in the tunnel during the operation period, and the accuracy of the source location can be improved by cross-validation of the signals of multiple sensors;

[0052] like Figure 2 As shown, the schematic diagram of the specific sensor installation position is as follows: the first sensor is installed 10 meters away from the left tunnel entrance, and then the next sensor is installed every 500 meters in the left tunnel. A total of 16 sensors can be installed in the left tunnel. The right tunnel is also installed with 16 sensors, and each sensor is installed in the middle of the two sensors in the left tunnel, that is, the axial distance between the left tunnel sensor and the front and rear sensors is 250 meters. This installation ensures that at least each microseismic signal can be received by at least two sensors, and the microseismic signal can be well received in a quiet environment during operation (compared to the construction period when the construction disturbance noise is large and the noise is high, and the operation period is relatively quiet), and compared with a single sensor, the threshold is increased to a certain extent, and a certain amount of noise can be screened out;

[0053] Micro-fractures will occur at the location where a microseismic event occurs, which is a potential rock burst risk area. Determining its location is an important part of risk prevention and control. According to the sensor layout, there will be at least 2 to 3 microseismic waveform-triggered sensors. According to the sensor trigger number and number, the risk area can be preliminarily determined. When the microseismic event falls within area 1, sensors 2 and 3 will receive the signal. If the microseismic event is within area 2, sensors 1 and 2 will receive the signal. If the microseismic event falls within area 3, sensors 1, 2, and 3 can all receive the signal.

[0054] It should be noted that compared with tunnel excavation during the construction period, the probability of rock burst during tunnel operation will be greatly reduced. In addition, the support strength will increase after the addition of the second lining to the original rock, further prolonging the development and occurrence time of rock burst. For this reason, the sensor layout does not need to be as dense as during the construction period. It is only necessary to detect it in time when it begins to have a rock burst trend. Traffic tunnels are generally double-track tunnels, and there will be a cross passage connecting the two tunnels at an axial distance of 50-100 meters. We describe the two tunnels as "left and right tunnels". The all-fiber microseismic monitoring system can connect up to 32 sensors, and the monitoring distance of each sensor can reach 300 meters. In addition, the all-fiber microseismic monitoring system transmits signals through optical fibers, with low loss, and can transmit signals over long distances. This effect far exceeds the monitoring effect of piezoelectric sensors and is more suitable for monitoring during the operation period.

[0055] The storage device communicates with each deployed sensor (specific sensors include all-fiber microseismic sensors) to collect microseismic signals from each monitoring section, analyzes the signals to determine the location of the earthquake source Lmn, and saves the signals together with the corresponding microseismic signals, thus ensuring data traceability and subsequent analysis requirements;

[0056] Sensors are installed in a cross-distributed manner in the left and right tunnels to ensure that microseismic signals can be effectively collected during tunnel operation without damaging the original secondary lining structure; each sensor has a unique position and number, and the cross-numbering and adjacent numbered sensor grouping ensure that the monitoring ranges of each monitoring section do not overlap; in a quiet operating environment, the sensors can better receive microseismic signals and use signal cross-verification from multiple sensors to improve the accuracy of earthquake source positioning, providing accurate data support for subsequent risk assessment and processing.

[0057] The microseismic monitoring module identifies and analyzes the time-frequency characteristics of microseismic signals to determine whether there are potential risks. Specifically:

[0058] The microseismic signal is transformed by Fourier transform, and the signal is converted from the time domain to the frequency domain. The spectrum characteristic parameters are extracted by using time-frequency analysis methods (specifically short-time Fourier transform, wavelet transform and Hilbert-Huang transform, etc.). The specific spectrum characteristic parameters include bandwidth (bandwidth refers to the frequency range occupied by the signal in the frequency domain, that is, the difference from the lowest to the highest frequency in the signal spectrum), peak frequency, and signal duration, which are respectively recorded as K, P and T; thus, the spectrum characteristic parameters of the microseismic signal at each source position Lmn can be obtained; it should be noted that rockburst signals usually have a higher bandwidth. The larger the bandwidth of the microseismic signal, the more complex, violent and energy-concentrated the microseismic signal is, and the greater the rockburst risk in the monitoring area; the larger the peak frequency, the greater the possibility of strong source activity, and the greater the rockburst risk in the monitoring area; the longer the signal duration, the more continuous the source activity is, and the greater the rockburst risk in the monitoring area;

[0059] The microseismic signal F(t) is subjected to envelope extraction to obtain the envelope (i.e., instantaneous amplitude) and is recorded as |F Hilbert (t)|, the specific envelope is the complex signal of F(t) after Hilbert transform, "| |" represents the modulo operation, where t is the time dimension;

[0060] The amplitude change of the microseismic signal is described by calculating the instantaneous change rate of the envelope. The specific amplitude change rate is approximated by the derivative of the envelope. The specific derivative formula is:

[0061]

[0062] Where △A(t) represents the rate of change of amplitude at the time dimension t;

[0063] According to the amplitude change rate △A(t) of each unit time dimension, the overall change degree of the microseismic signal is calculated by calculus to obtain the amplitude jump value △A. The specific calculation formula is:

[0064]

[0065] Where T represents the total duration of the microseismic signal, and the amplitude jump value △A represents the total amount of change of the microseismic signal during this period of time, which is used to describe the degree of drastic change of the microseismic signal. The larger it is, the greater the rock burst risk in the monitoring area.

[0066] The bandwidth K, peak frequency P, duration T and amplitude jump value △A are normalized and their values ​​are taken. The values ​​are analyzed and calculated by formula to obtain the activity intensity index KP of the microseismic signal. The specific calculation formula is:

[0067]

[0068] β1, β2, β3, and β4 are respectively set weight constants, and their specific values ​​are set by those skilled in the art according to actual needs;

[0069] Thus, the activity intensity index of the microseismic signal received in each monitoring area can be obtained, and the center point of each monitoring area can be found by using the minimum bounding rectangle (MBR), and the distance between each sensor and the center point is calculated. Then, the activity intensity index is divided by the distance to obtain a unitless intensity index, which effectively removes the influence caused by the different distances between the sensor and the source, and can more accurately measure and evaluate the intensity of the source activity in the monitoring area, which helps to improve the accuracy of the monitoring results; the mean of each intensity index in each monitoring area is calculated to obtain the source activity value; thus, the source activity value of each microseismic event in each monitoring area can be obtained, and it is recorded as KPj, where j = 1, 2, 3...J, J is a positive integer, J represents the total number of microseismic events, and j represents any microseismic event in the monitoring area;

[0070] A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the source activity value as the vertical coordinate. The source activity value of each microseismic event in the monitoring area is input into the coordinate according to its corresponding time, and the position of the source activity value in the coordinate axis is recorded as the activity point. The activity points are connected in sequence by line segments to obtain a line graph of the change of the source activity index; two adjacent activity points constitute an activity line segment, so that several activity line segments can be cut out from the line graph of the change of the source activity index, and the source activity index corresponding to the activity points at both ends of each activity line segment is averaged to obtain the activity mean, which is recorded as The slope of each active line segment is calculated by data fitting and recorded as It should be noted that when the slope is greater than zero and the larger the slope is, the more the earthquake source activity index in the monitoring area is increasing, and the faster the increase is; when the slope is less than zero and the smaller the slope is, the more the earthquake source activity index in the monitoring area is decreasing, and the faster the decrease is.

[0071] The activity mean of each activity line segment in the line graph of earthquake source activity index change is and slope Perform formula calculation and analysis to obtain the risk warning value S R isk, the specific calculation formula is:

[0072]

[0073] δ1, δ2, and δ3 are respectively set weight constants, and their specific values ​​are set by personnel in this field according to actual needs; it can be seen from the formula that when the slope is greater than zero, the greater the slope, the greater the risk warning value; when the slope is less than zero, the smaller the slope, the smaller the risk warning value; when the activity mean is greater, the greater the risk warning value; thus, the risk warning value of each monitoring area can be obtained and sent to the risk warning module;

[0074] The frequency spectrum characteristic parameters of microseismic signals are extracted through Fourier transform, time-frequency analysis and other methods, and the microseismic activity intensity is analyzed to obtain the activity intensity index of the monitoring area. The activity intensity index is then de-distanced according to the distance between each sensor and the center point of the monitoring area to obtain the source activity index of each monitoring area. The development trend of the source activity index of microseismic events in each monitoring area is analyzed to judge the rock burst risk of each monitoring area, and the risk warning value is obtained, which can effectively quantify the energy concentration of microseismic signals and the intensity of source activity. It not only improves the accuracy of monitoring, but also can timely discover potential risks in tunnels, thereby providing reliable data support for tunnel risk prevention and control and management.

[0075] The risk warning module performs risk processing based on the risk warning values ​​received for each monitoring area, specifically:

[0076] The risk warning values ​​of the three monitoring areas of each monitoring section are retrieved and compared with the set warning interval. If the risk warning value of any monitoring area is greater than the upper limit of the set warning interval, the risk warning is triggered. It should be noted that when the risk warning is usually triggered, the staff will suspend operations such as peers, multi-party detection, and fixed-point stress removal. If the risk warning values ​​of the three monitoring areas are all less than the lower limit of the set warning interval, it means that the rockburst risk is very small and can be ignored, and no operation is required. In other cases, the monitoring section is recorded as an encrypted section, and the encrypted section is subjected to sensor encryption processing. The specific encryption processing is as follows:

[0077] The risk warning values ​​of the three monitoring areas of the encrypted section are retrieved, and the average is calculated to obtain the risk average; the product obtained by multiplying the risk average by the set encryption conversion coefficient is rounded to obtain the encrypted quantity, and the encrypted quantity is output; thus, the encrypted quantity of each encrypted section can be obtained, and the staff can timely encrypt the sensors of the encrypted section according to the encrypted quantity, so as to achieve more accurate rock burst risk monitoring of the encrypted section;

[0078] By receiving the risk warning values ​​of each monitoring area and combining them with the set risk range, the potential rock burst risk of microseismic events can be monitored and warned in real time, which can automatically trigger risk warnings or encrypted processing; according to different risk warning values, the number of sensors in the encrypted section can be adjusted to ensure more intensive monitoring in higher-risk areas; an automated risk processing process can be implemented to quickly respond to potential rock burst risks and improve the safety and stability of tunnel operations.

[0079] Embodiment 2: The collection module is also used to deploy sensors in a single-line tunnel. The specific deployment method is as follows:

[0080] For single-line tunnels, a linear distribution method is adopted. The first sensor is installed 10m away from the entrance side, and then the next sensor is installed at a fixed length interval (the fixed length here is set according to actual needs, usually 100 to 300 meters, depending on the tunnel length and monitoring accuracy requirements). This installation can also ensure that each microseismic signal is received by at least two sensors. The sensor is installed on the surface of the secondary lining through expansion screws, and is preferably installed at the arch top position. If the arch top position is inconvenient to install, it can be installed at the spandrel position. When selecting the spandrels on both sides of the tunnel, it is necessary to judge based on the geological conditions of the surrounding rock mass exposed during the construction period, and try to install it on the side with more exposed cracks, or on the side perpendicular to the main stress direction;

[0081] The sensors in the single-line tunnel are numbered one by one as n, n = 1, 2, 3 ... N, N is a positive integer, N represents the total number of sensors, n represents the number of any sensor; the area composed of two adjacent sensors is recorded as a monitoring area and is recorded as

[0082] If the monitoring area Two adjacent sensors receive microseismic signals and calculate the arrival time difference between the two adjacent microseismic signals. If the arrival time difference is less than the set difference, the earthquake source is located in the monitoring area. The specific arrival time difference calculation formula is: Where Un and Un+1 are the times when the microseismic signal arrives at sensor n and sensor n+1 respectively;

[0083] If the arrival time difference is greater than or equal to the set difference, it means that the earthquake source is not in the current monitoring area, but closer to one of the sensors. Then, sensor encryption processing is required to accurately locate the monitoring area. The specific encryption processing process is as follows:

[0084] The sensor with an earlier arrival time is selected as the target sensor from two adjacent sensors. It is necessary to indicate that the earthquake source is closer to the target sensor. The target sensor is taken as the center point, and sensors are installed at a certain distance on both sides. The specific number is set by engineers in this field. It can be seen from the installation of sensors that the target sensor is taken as the center point, and the two adjacent monitoring areas involving the target sensor are subjected to sensor encryption processing to determine the area where the earthquake source is located.

[0085] Thus, the earthquake source location can be determined, and the microseismic signals detected in each monitoring area are sent to the microseismic monitoring module; it should be noted that there are at least 2 microseismic signals in each monitoring area;

[0086] The microseismic monitoring module identifies and analyzes the time-frequency characteristics of the microseismic signals in each monitoring area to obtain the risk warning value of each monitoring area, and sends it to the risk warning module;

[0087] The risk warning module is also used to process the risk warning values ​​of each monitoring section of the single-line tunnel, specifically:

[0088] The monitoring area The risk warning value is compared with the set warning interval. If the risk warning value is greater than the upper limit of the set warning interval, the risk warning is triggered; if the risk warning value of the monitoring area is less than the lower limit of the set warning interval, it means that the rock burst risk is very small and can be ignored, and no operation is required; if the risk warning value is within the set warning interval, the monitoring area is recorded as an encrypted area, and the encrypted area is encrypted by sensors. The specific encryption processing is as follows:

[0089] Retrieve the risk warning value of the encrypted area, multiply it by the set encryption conversion coefficient, round the product to get the encrypted number, and output the encrypted number; thereby, the encrypted number of each encrypted area can be obtained, and the staff can promptly perform encryption processing on the sensors of the encrypted section according to the encrypted number, so as to achieve more accurate rock burst risk monitoring of the encrypted section.

[0090] The above formulas are all obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions.

[0091] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0092] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation, characterized in that: It includes the deployment of acquisition modules, storage devices, microseismic monitoring modules and risk warning modules; The collection module is installed by cross-distributing the sensors in the left and right holes, and the sensors are numbered; the sensors are segmented according to their numbers to form several monitoring sections, each of which contains three monitoring areas, and the source location is determined according to the numbers and quantity of the sensors; The memory is connected to each sensor in communication to collect and store microseismic events and their corresponding microseismic signals; The microseismic monitoring module performs microseismic activity intensity analysis based on the microseismic events in each monitoring area and their corresponding microseismic signals to obtain the activity intensity index of the monitoring area, and then de-distances the activity intensity index according to the distance between each sensor and the center point of the monitoring area to obtain the source activity index of each monitoring area; analyzes the development trend of the source activity index of the microseismic events in each monitoring area to determine the rock burst risk of each monitoring area, obtains the risk warning value, and sends it to the risk warning module; The risk warning module performs risk warning processing based on the received risk warning value, specifically: The risk warning values ​​of the three monitoring areas of each monitoring section are retrieved and compared with the set warning interval. If the risk warning value of any monitoring area is greater than the upper limit of the set warning interval, the risk warning is triggered; if the risk warning values ​​of the three monitoring areas are all less than the lower limit of the set warning interval, no operation is required; in other cases, the monitoring section is recorded as an encrypted section, and the encrypted section is encrypted by the sensor. The specific encryption process is as follows: The risk warning values ​​of the three monitoring areas of the encrypted segment are retrieved, and the average is calculated to obtain the risk average; the product obtained by multiplying the risk average by the set encryption conversion coefficient is rounded to obtain the encrypted quantity, and the encrypted quantity is output; thus, the encrypted quantity of each encryption segment can be obtained.

2. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation according to claim 1, characterized in that: Sensors are arranged crosswise in the left and right tunnels, and the monitoring sections are formed by segmentation: The sensors are installed in a cross-distribution manner in the left and right holes, and the sensors are cross-numbered one by one, so that each sensor corresponds to a position and number; the specific numbering sequence is: the first sensor in the left hole is numbered 1, the first sensor in the right hole is numbered 2, the second sensor in the left hole is numbered 3, and so on. The numbering of all sensors is recorded as n, n = 1, 2, 3...N, N is a positive integer, N represents the total number of sensors, and n represents the number of any one of the sensors; Three sensors with adjacent numbers are grouped together, and the corresponding monitoring range is a monitoring segment. Specifically, there is only one intersection sensor between two adjacent groups of sensors. Each monitoring segment is marked as m, and specifically m = 1, 2, 3...M, where M is a positive integer, M represents the total number of monitoring segments, and m represents the number of any monitoring segment. In the same group of sensors within a certain monitoring section, sensor n in the middle position is taken as the center, and each monitoring area 50m away from sensor n is selected as a monitoring area n; the monitoring area n-1 is the edge of the monitoring area n starting from the n-1 sensor, and similarly, the monitoring area n+1 is the edge of the monitoring area n starting from the n+1 sensor. In this way, each monitoring section can be divided into three monitoring areas. The source position can be determined based on the microseismic signals received in each monitoring area.

3. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation according to claim 2, characterized in that: The specific method of determining the earthquake source location based on the sensor number and quantity is as follows: There is a set of sensors (n-1, n and n+1) in the monitoring section. If microseismic signals from sensors n-1 and n are received, the source location is determined to be in the monitoring area n-1; If microseismic signals are received from sensors n and n+1, it is determined that the earthquake source is located in monitoring area n+1; If microseismic signals are received from sensors n-1, n and n+1, it is determined that the source location is in monitoring area n; thus, the source location can be determined based on the received microseismic signals and recorded as Lmn.

4. The microseismic monitoring and early warning system for rock burst during tunnel / hole operation period according to claim 1 is characterized in that: The specific process of microseismic activity intensity analysis is as follows: Perform Fourier transform on the microseismic signal, convert the signal from time domain to frequency domain, and use time-frequency analysis method to extract spectrum characteristic parameters. Specific spectrum characteristic parameters include bandwidth, peak frequency, and signal duration. The envelope of the microseismic signal is extracted and the amplitude jump value is obtained by using derivative and calculus calculation and analysis; The amplitude jump value, bandwidth, peak frequency, and signal duration are normalized and their values ​​are taken, and the values ​​are analyzed and calculated by formula to obtain the activity intensity index of the microseismic signal; thus, the activity intensity index of the microseismic signal received in each monitoring area can be obtained.

5. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation according to claim 4, characterized in that: The way to remove distance is: The minimum circumscribed rectangle is used to find the center point of each monitoring area, the distance between each sensor and the center point is calculated, and then the active intensity index is divided by the distance to obtain a unitless intensity index. The mean of each intensity index in each monitoring area is calculated to obtain the source activity value; thus, the source activity value of each microseismic event in each monitoring area can be obtained and recorded as KPj, where j = 1, 2, 3...J, J is a positive integer, J represents the total number of microseismic events, and j represents any microseismic event in the monitoring area.

6. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation according to claim 5, characterized in that: The method of extracting the envelope of microseismic signals and using derivatives and calculus to calculate and analyze is as follows: The microseismic signal F(t) is extracted and the envelope is recorded as |F Hilbert (t)|, the specific envelope is the complex signal of F(t) after Hilbert transform, "| |" represents the modulo operation, where t is the time dimension; The amplitude change of the microseismic signal is described by calculating the instantaneous change rate of the envelope. The specific amplitude change rate is approximated by the derivative of the envelope. The specific derivative formula is: Where △A(t) represents the rate of change of amplitude at the time dimension t; According to the amplitude change rate △A(t) of each unit time dimension, the overall change degree of the microseismic signal is calculated by calculus to obtain the amplitude jump value △A. The specific calculation formula is: Where T represents the total duration of the microseismic signal, and the amplitude jump value △A represents the total amount of change in the microseismic signal during this period of time.

7. A microseismic monitoring and early warning system for rock burst during tunnel / hole operation according to claim 6, characterized in that: The analysis method based on the development trend of the source activity index of microseismic events in each monitoring area is as follows: A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the source activity value as the vertical coordinate. The source activity value of each microseismic event in the monitoring area is input into the coordinate according to its corresponding time, and the position of the source activity value in the coordinate axis is recorded as the activity point. The line segments are used to connect the activity points in turn to obtain a line graph of the change of the source activity index. Two adjacent activity points constitute an activity line segment, and thus several activity line segments can be cut out from the line graph of the change of the source activity index. The activity mean is calculated by averaging the source activity indexes corresponding to the activity points at both ends of each activity line segment and recorded as The slope of each active line segment is calculated by data fitting and recorded as The activity mean of each activity line segment in the line graph of earthquake source activity index change is and slope Perform formula calculation and analysis to obtain the risk warning value S R isk, the specific calculation formula is: δ1, δ2, and δ3 are respectively set weight constants.

8. According to the microseismic monitoring and early warning system for rock burst during tunnel / hole operation period of claim 1, the deployment and collection module is also used to deploy sensors, collect microseismic signals and determine the source location of the single-line tunnel, specifically: For single-line tunnels, a linear distribution method is adopted. The first sensor is installed 10m away from the entrance, and then the next sensor is installed at a fixed length interval. The sensor is installed on the secondary lining surface through expansion screws. The sensors in the single-line tunnel are numbered one by one as n, n = 1, 2, 3 ... N, N is a positive integer, N represents the total number of sensors, n represents the number of any sensor; the area composed of two adjacent sensors is recorded as a monitoring area and is recorded as If the monitoring area Two adjacent sensors receive microseismic signals and calculate the arrival time difference between the two adjacent microseismic signals. If the arrival time difference is less than the set difference, it is determined that the earthquake source is located in the monitoring area. If the arrival time difference is greater than or equal to the set difference, the sensor needs to be encrypted to accurately locate the monitoring area. The specific encryption process is as follows: The sensor with an earlier arrival time is selected from two adjacent sensors as the target sensor. With the target sensor as the center point, sensors are installed at certain distances on both sides to further determine the monitoring area where the earthquake source is located.

9. According to the microseismic monitoring and early warning system for rock burst during tunnel / hole operation period of claim 7, the risk early warning module is also used to perform risk processing on the risk early warning value of each monitoring section of the single-line tunnel, specifically: The monitoring area The risk warning value is compared with the set warning interval. If the risk warning value is greater than the upper limit of the set warning interval, the risk warning is triggered; if the risk warning value is within the set warning interval, the monitoring area is recorded as an encrypted area, and the encrypted area is encrypted by sensors. The specific encryption processing is as follows: The risk warning value of the encrypted area is retrieved, and the product obtained by multiplying it by the set encryption conversion coefficient is rounded to obtain the encrypted quantity, and the encrypted quantity is output; thereby, the encrypted quantity of each encrypted area can be obtained.

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