Method and system for early warning of abnormality in front based on seismic migration results

Abstract

The application discloses a front abnormality early warning method and system based on a tunneling seismic migration result, and the method comprises the following steps: acquiring a tunneling seismic signal corresponding to cutting at a set interval distance of each travel mileage in front of a tunneling head currently monitored by an observation system, and processing the tunneling seismic signal to obtain an abnormal interface of a front position corresponding to each set interval distance of a tunneling machine; extracting a midpoint of a tangent line segment of the abnormal interface of the front position corresponding to each set interval distance as an abnormal point in the abnormal interface to obtain all abnormal points extracted after multiple set interval distances; and performing cluster analysis on all the abnormal points, collecting the abnormal points in a set range according to a cluster radius, determining an abnormal area, and early warning; and the application can realize dynamic and real-time early warning in front of a tunneling roadway, and guide safe and efficient tunneling of a mine.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geological exploration, in particular to a front abnormality early warning method and system based on a while-excavating seismic migration result. BACKGROUND

[0002] Generally, a 30m excavation advance safety distance needs to be reserved during the roadway excavation process. The related geophysical and drilling methods are carried out for the reserved 30m excavation advance safety distance to ensure the safety of the rear excavation. The conventional seismic advance detection needs to stop the production work of the excavation face, arrange the observation system, drill holes, and set off the explosion, and the work is complicated, which seriously affects the excavation speed of the working face.

[0003] The while-excavating seismic advance detection method is a new type of mine roadway seismic advance detection method developed in recent years. This method uses the vibration generated by the power head of the excavator during the excavation process as the seismic source to detect the roadway in advance, thereby achieving the purpose of detecting while excavating.

[0004] The cutting of the power head of the excavator and the coal wall or rock wall will generate a large number of pseudo-random continuous seismic sources. Through the while-excavating seismic monitoring system arranged on the side of the roadway behind the head, continuous cutting vibration signals in the coal seam or rock stratum are received in real time. Combined with related superposition interference and other intelligent algorithms, the continuous vibration signals of the excavator are converted into pulse source signals. The reflection wave extraction and time-frequency polarization analysis based on the generalized S transform are used to speculate the abnormal geological interface changes in front, thereby achieving the purpose of dynamic advance detection of the structure in front of the excavation and in the working face. In the document "Intelligent Geological Support System for While-Mining and While-Excavating Seismic Monitoring in Coal Mines", No. 2022 / 11 of Intelligent Mine, Qiqi et al., the while-mining seismic monitoring technology and the while-excavating seismic monitoring technology are studied. Among them, the excavation refers to excavating and digging a roadway forward, which generally has a small working face and low efficiency, and the mining refers to arranging a mining working face in the middle of the excavated roadway to mine the coal seam backward. By arranging a sensor network in the roadway, continuous cutting vibration signals are received in real time and sent to the ground and the underground control center disk storage array for storage through the arranged optical fiber network. The while-excavating data processing system of the control center processes the real-time collected data to generate imaging results. This scheme only realizes online data collection while excavating.

[0005] The current tunneling seismic exploration scheme is to manually process the acquired data to obtain the abnormal position distribution within a certain range in front of the current tunneling machine after full-time data acquisition. The interval between data acquisition and abnormal position distribution acquisition is long, and the real-time warning requirements of tunneling and encountering geological anomalies cannot be met. SUMMARY

[0006] The technical problem to be solved by the present application is how to realize dynamic real-time warning in front of a tunneling roadway.

[0007] The present application solves the above technical problems by the following technical means:

[0008] In a first aspect, the present application provides a front abnormality warning method based on tunneling seismic migration results, comprising:

[0009] S10, for the current monitoring of the observation system in front of the tunneling head, the travel distance T i , the travel distance T i Every set interval distance cutting corresponding tunneling seismic signal, and processing the tunneling seismic signal to obtain the abnormal interface of the front position corresponding to each set interval distance of the tunneling machine;

[0010] S20, extracting the midpoint of the tangent line segment of the abnormal interface corresponding to each set interval distance as an abnormal point in the abnormal interface to obtain all abnormal points extracted after multiple set interval distances;

[0011] S30, for all the abnormal points in the T i mileage range, cluster analysis is performed, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined according to the proportion of the number of abnormal points in the collection area and the abnormal area is warned.

[0012] Further, after the cluster analysis of all the abnormal points in the T i mileage range, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined according to the proportion of the number of abnormal points in the collection area, comprising:

[0013] The abnormal area is regarded as a suspected abnormal area, the observation system is moved, and the steps S10-S20 are repeatedly executed to obtain all the abnormal points corresponding to the next travel distance T i+1 ;

[0014] According to all the abnormal points corresponding to the next travel distance T i+1 , it is determined whether the number of abnormal points in the suspected abnormal area is continuously increasing;

[0015] If yes, the center point of the suspected abnormal area is determined as the abnormal position and a warning is given.

[0016] If no, it is determined that the suspected abnormal area is a false abnormal area.

[0017] Further, the acquisition of the while-drilling seismic signals of the tunneling machine at every interval distance includes:

[0018] The while-drilling seismic monitoring system is connected to the control system of the tunneling machine, and based on a tunneling machine technical protocol, cutting technical parameters are acquired, including the position of the tunneling machine, the working time of the tunneling machine cutting rock mass, the position of the tunneling head of the tunneling machine, and the cutting current.

[0019] Based on the cutting technical parameters, the effective while-drilling seismic signals of the tunneling machine cutting are acquired.

[0020] Further, the midpoint of the tangent line segment of the abnormal interface at the corresponding front position of every set interval distance is extracted as an abnormal point in the abnormal interface, so as to obtain all abnormal points extracted after multiple set interval distances, including:

[0021] The midpoint position coordinates of the tangent line segment of each abnormal interface and the angle of the tangent line segment are extracted, and the midpoint position coordinates are taken as the position coordinates of the abnormal point, and the angle of the tangent line segment is taken as the angle information of the abnormal point. The two-dimensional plane expression form of the abnormal point is (x, y, a), wherein x represents the midpoint horizontal coordinate of the tangent line segment of the abnormal interface, y represents the midpoint vertical coordinate of the tangent line segment of the abnormal interface, and a represents the angle of the tangent line segment.

[0022] Further, the T i All the abnormal points in the mileage range are subjected to cluster analysis, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined and an alarm is given according to the proportion of the number of abnormal points in the collected area, including:

[0023] Based on the cluster radius and the position coordinates of all the abnormal points, the cluster analysis of all the abnormal points is performed, and the area containing the most abnormal points is obtained as the main abnormal area;

[0024] Based on the center coordinates of the main abnormal area, the distances between each abnormal point and the center coordinates are calculated, and a group of distance values are obtained;

[0025] The distances in the group of distance values are sorted from large to small, and the first n distance values are selected according to the sorting result. The position coordinates of the abnormal points corresponding to the n distance values are taken as the center coordinates of n secondary abnormal areas, and the number of abnormal points is scanned in combination with the cluster radius except for the main abnormal area, to determine the n secondary abnormal areas.

[0026] Based on the T iWithin the mileage range, the primary and secondary abnormal areas are identified, and an abnormal area is identified and an early warning is issued.

[0027] Furthermore, the T-based i Within the mileage range, the primary anomaly area and the secondary anomaly area are identified, and anomaly areas are identified and warnings are issued, including:

[0028] Determine the percentage of abnormal points in the main abnormal region or the secondary abnormal region relative to the total number of abnormal points.

[0029] When the proportion exceeds the set ratio, the main abnormal area or the secondary abnormal area is determined to be a suspected abnormal area, and the center coordinates of the suspected abnormal area are taken as the abnormal location within the current monitoring range.

[0030] If the percentage does not exceed the set ratio, then the primary abnormal region or the secondary abnormal region is discarded.

[0031] Furthermore, after determining the center point of the suspected abnormal region as the abnormal location or determining that the suspected abnormal region is a false abnormal region, the method further includes:

[0032] Determine whether the tunnel excavation operation is complete;

[0033] If so, then the tunnel excavation operation shall be terminated;

[0034] If not, continue moving the observation system to obtain the next travel distance T. i+2 All corresponding anomalies, combined with the distance traveled T i+1 Corresponding anomalies and travel distance T i+2 For all corresponding anomalies, determine the travel distance T. i+2 Abnormal areas.

[0035] Secondly, the present invention also proposes a forward anomaly early warning system based on seismic migration results during excavation, the system comprising:

[0036] The anomaly identification module is used to determine the current travel distance T ahead of the tunnel face monitored by the observation system. i Obtain the distance traveled, T. i The seismic signals during excavation are corresponding to the cutting at each set interval distance, and the seismic signals during excavation are processed to obtain the abnormal interface at the front position corresponding to each set interval distance of the tunneling machine.

[0037] The anomaly point extraction module is used to extract the midpoint of the tangent line segment of the abnormal interface at each set interval distance, and use it as the anomaly point in the abnormal interface, so as to obtain all the anomaly points extracted after multiple set interval distances.

[0038] an abnormal region analysis module, configured to perform cluster analysis on all the abnormal points within a mileage range, to collect the abnormal points within a set range according to a cluster radius, and to determine an abnormal region and give a warning according to the proportion of the number of abnormal points in the collected region. i an abnormal region analysis module, configured to perform cluster analysis on all the abnormal points within a mileage range, to collect the abnormal points within a set range according to a cluster radius, and to determine an abnormal region and give a warning according to the proportion of the number of abnormal points in the collected region.

[0039] Further, the system further comprises a reinforcement module, configured to:

[0040] take the abnormal region as a suspected abnormal region, move the observation system, and obtain a next mileage T i+1 corresponding to all the abnormal points;

[0041] determine a center point in the suspected abnormal region as an abnormal position according to all the abnormal points corresponding to a next mileage T i+1 corresponding to all the abnormal points, and give a warning.

[0042] Further, the abnormal region analysis module comprises:

[0043] a cluster analysis unit, configured to perform cluster analysis on all the abnormal points based on a cluster radius and position coordinates of all the abnormal points, to obtain a region containing the most abnormal points as a main abnormal region;

[0044] a distance calculation unit, configured to calculate distances between each abnormal point and a center coordinate of the main abnormal region based on the center coordinate, to obtain a set of distance values;

[0045] a scanning unit, configured to sort the distances in the set of distance values from large to small, and select the first n distance values according to the sorting result, to take the position coordinates of the abnormal points corresponding to the n distance values as center coordinates of n secondary abnormal regions, to perform abnormal point number scanning of the secondary abnormal regions except the main abnormal region in combination with the cluster radius, and to determine the n secondary abnormal regions;

[0046] an abnormal region determination unit, configured to determine an abnormal region and give a warning based on the main abnormal region and the secondary abnormal regions within a mileage range T i .

[0047] The present application has the following advantages:

[0048] (1) The present application extracts abnormal points in an abnormal interface corresponding to a position in front of the tunneling machine at each set interval distance position according to a tunneling seismic signal, performs cluster analysis on the abnormal points to obtain an abnormal region, determines an abnormal position according to the abnormal region, and gives a real-time warning for the abnormal position in front, so as to realize dynamic real-time warning for the position in front of the tunneling roadway, and guide safe and efficient tunneling.

[0049] (2) through the determination of abnormal area position in the current monitoring range, when the heading machine moves to the next monitoring range, the abnormal point in the abnormal area is monitored by the heading seismic monitoring, the determined abnormal area is strengthened to realize the discrimination, the false abnormality in the advance prediction process is reduced, and the safe distance is ensured for efficient heading.

[0050] Additional aspects and advantages of the present application will be described in the description that follows, and will become apparent from the description, or will be learned from the practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 is a flowchart of a front abnormality early warning method based on the heading seismic migration result according to an embodiment of the present application;

[0052] Figure 2 is a field observation system layout diagram of the heading seismic monitoring system according to an embodiment of the present application, wherein (a) is a layout diagram of the current monitoring range, and (b) is a layout diagram of the next monitoring range;

[0053] Figure 3 is a single heading seismic migration result diagram according to an embodiment of the present application;

[0054] Figure 4 is a single heading seismic monitoring abnormal point distribution diagram according to an embodiment of the present application;

[0055] Figure 5 is a single heading seismic monitoring abnormal point cluster result diagram according to an embodiment of the present application;

[0056] Figure 6 is a flowchart of another front abnormality early warning method based on the heading seismic migration result according to an embodiment of the present application;

[0057] Figure 7 is a structure diagram of a front abnormality early warning system based on the heading seismic migration result according to an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely in combination with the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0059] As Figure 1As shown, the first embodiment of the present application proposes a front abnormality early warning method based on the results of the while-drilling seismic migration, which comprises the following steps:

[0060] S10, for the current monitored drilling head front travel distance of the observation system, the corresponding while-drilling seismic signal of the cutting at each set interval distance of the travel distance is obtained, and the while-drilling seismic signal is processed to obtain the abnormal interface of the front position corresponding to each set interval distance of the drilling machine;

[0061] S20, the midpoint of the tangent line segment where the abnormal interface of each set interval distance corresponding front position is located is extracted as the abnormal point in the abnormal interface, so as to obtain all abnormal points extracted after multiple set interval distances;

[0062] S30, cluster analysis is performed on all the abnormal points, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined and early warning according to the proportion of the number of abnormal points in the collection area.

[0063] According to the present embodiment, the abnormal interface of the front position corresponding to the drilling machine at each set interval distance position is obtained according to the while-drilling seismic signal, and the abnormal points in the abnormal interface are extracted and cluster analyzed to obtain the abnormal area, so as to determine the abnormal position according to the abnormal area and real-time early warning of the front abnormality, which can realize the dynamic real-time early warning of the front of the drilling roadway and guide the safe and efficient drilling of the mine.

[0064] In an embodiment, the step S10: for the current monitored drilling head front travel distance of the observation system, the corresponding while-drilling seismic signal of the cutting at each set interval distance of the travel distance is obtained, and the while-drilling seismic signal is processed to obtain the abnormal interface of the front position corresponding to each set interval distance of the drilling machine, specifically comprising the following steps:

[0065] S11, the while-drilling seismic signal of the drilling machine cutting at each set interval distance is obtained by using the while-drilling seismic monitoring system;

[0066] S12, the while-drilling seismic signal is processed by interference, and the continuous vibration signal of the drilling machine is converted into the active pulse source signal;

[0067] S13, the reflection wave extraction and migration imaging processing of the active pulse source signal are performed to obtain the abnormal interface of the front position corresponding to the drilling machine at each set interval distance position.

[0068] Specifically, the field arrangement of the while-drilling seismic monitoring system is as follows Figure 2As shown in (a), 16 sensors are arranged on the side of the roadway behind the starting position of the heading face, and each sensor is arranged at intervals, for example, with a sensor spacing of 5 m. The 16th sensor is 5 m away from the starting position of the heading face. The 16 sensors are connected to the tunneling seismic monitoring system through a connecting line. The tunneling seismic monitoring system is arranged inside the monitoring platform behind the tunneling machine. The tunneling seismic waveform signals of the tunneling machine at every 1 m cutting are obtained according to the tunneling seismic monitoring system arranged behind the heading face of the roadway.

[0069] The tunneling seismic records obtained by the tunneling machine at different positions are subjected to conventional tunneling seismic processing procedures such as interference processing, reflection wave extraction, and migration imaging to obtain the migration interface of the position corresponding to the front position at every 1 m, as shown by the black line. Figure 3

[0070] In an embodiment, the step S11 of obtaining the tunneling seismic signals of the tunneling machine at every set interval distance cutting includes the following steps.

[0071] S111, connect the tunneling seismic monitoring system to the control system of the tunneling machine, and obtain the cutting technical parameters based on the tunneling machine technical protocol. The cutting technical parameters include the position of the tunneling machine, the working time of the tunneling machine cutting rock mass, the position of the tunneling head of the tunneling machine, and the cutting current.

[0072] Specifically, the tunneling machine side is taken as the protocol server, and the tunneling seismic monitoring system side is taken as the client. The protocol communication is performed between the server and the client in the form of opening the server port through TCP / IP. The specific content of the tunneling machine protocol includes 1 byte for sending the cutting running state, 1 byte for sending the sensor spacing, 2 bytes for sending the heading mileage, 2 bytes for sending the feed amount, 2 bytes for sending the height of the gun head, and 2 bytes for sending the cutting current.

[0073] S112, obtain the effective tunneling seismic signals of the tunneling machine based on the cutting technical parameters.

[0074] Specifically, the position of the tunneling machine can be obtained according to the mileage position of the tunneling machine. The effective cutting time of the tunneling machine is determined according to the cutting current of the tunneling machine. The tunneling seismic signals mainly want to obtain the vibration signals generated when the tunneling machine cuts the coal rock mass. In this embodiment, the cutting state of the tunneling machine is determined according to the size of the cutting current of the tunneling machine, and then the tunneling seismic signals in the system are selected according to the cutting state time.

[0075] ​The embodiment can directly obtain cutting technical parameters based on a tunneling technical protocol by intercommunication between the tunneling seismic monitoring system and the tunneling machine control system, including: tunneling machine position, tunneling machine cutting rock mass working time, tunneling head position of the tunneling machine, cutting current and other related information, and using the cutting technical parameters to assist in obtaining effective tunneling seismic signals.

[0076] In an embodiment, the step S20 of extracting the midpoint of the tangent line segment of the abnormal interface at the corresponding front position of each set interval distance as an abnormal point in the abnormal interface to obtain all abnormal points extracted after multiple set interval distances, specifically includes:

[0077] The midpoint position coordinates of the tangent line segment of each abnormal interface and the angle of the tangent line segment are extracted, and the midpoint position coordinates are taken as the position coordinates of the abnormal point, and the angle of the tangent line segment is taken as the angle information of the abnormal point, and the two-dimensional plane expression form of the abnormal point is (x, y, a), wherein x represents the midpoint horizontal coordinate of the tangent line segment of the abnormal interface, y represents the midpoint vertical coordinate of the tangent line segment of the abnormal interface, and a represents the angle of the tangent line segment.

[0078] Specifically, after cutting 1 m, abnormal points (generally not more than three) are extracted in the formed abnormal interface, assuming that three abnormalities are extracted for one cut, and 20 m is taken as a monitoring range, then 60 abnormal points are generated by the tunneling seismic monitoring system after cutting 20 m, which are expressed in a two-dimensional plane as (x, y, a), wherein a represents the inclination angle of the abnormal interface, and the x and y coordinates implicitly contain the inclination angle information of each point, as shown by the cross in the middle. Figure 4

[0079] In an embodiment, the step S30 of performing cluster analysis on all the abnormal points, collecting the abnormal points within a set range according to a cluster radius, determining an abnormal area and giving an early warning, specifically includes the following steps:

[0080] S31, based on the cluster radius and the position coordinates of all the abnormal points, performing cluster analysis on all the abnormal points to obtain a region containing the most abnormal points as a main abnormal region;

[0081] Specifically, the cluster analysis is performed on the abnormal points (assuming 60 abnormal points) extracted within the current monitoring range, assuming that the position coordinates of the abnormal point 1 are (x1, y1), the position coordinates of the abnormal point 2 are (x2, y2), and so on, based on the distance calculation formula The distance between each two abnormal points is calculated, and according to the relationship between the distance value d and 2 times the cluster radius r, (1) if d>2r, the two abnormal points are not aggregated into one abnormal region; (2) if d≤2r, the two abnormal points can be aggregated into one abnormal region, and the cluster analysis of the 60 points is completed in turn, and the optimal cluster region can be formed as the main abnormal region.​

[0082] S32, calculate the distance between each of the abnormal points and the center coordinate of the main abnormal area, to obtain a set of distance values;

[0083] S33, sort the distances in the set of distance values from large to small, and select the first n distance values according to the sorting result, and take the position coordinates of the abnormal points corresponding to the n distance values as the center coordinates of n secondary abnormal areas, and combine the cluster radius to scan the abnormal points except the main abnormal area to determine the n secondary abnormal areas.

[0084] Specifically, the distance between each of the abnormal points and the center coordinate (x', y') is calculated, and the maximum distance is taken, which is expressed as The center coordinates of max1 and max2 are determined as the center coordinates of the first abnormal area and the second abnormal area, and the center coordinates are taken as the center of the circle and the cluster radius r is taken as the radius of the circle to form an abnormal circle to scan the abnormal points except the main abnormal area (see Figure 5 circle 1) to determine the first abnormal area (see Figure 5 circle 2) and the second abnormal area (see Figure 5 circle 3) except the main abnormal area; thus, three abnormal areas of the cluster in the 20m monitoring range are obtained after cutting.

[0085] S34, determine the abnormal area based on the main abnormal area and the secondary abnormal area and give an early warning.

[0086] This embodiment considers that there may not be only one abnormal interface in the migration result of a seismic record, and there are not only one actual abnormal interface in front during a tunneling process. The possible abnormal interfaces can be more comprehensively expressed by determining the secondary abnormal area based on the main abnormal area, and the warning accuracy is improved.

[0087] In an embodiment, the step S34 of determining the abnormal area based on the main abnormal area and the secondary abnormal area and giving an early warning specifically includes the following steps:

[0088] S341, judge the proportion of the number of abnormal points in the main abnormal area or the secondary abnormal area in the total number of abnormal points;

[0089] S342, when the proportion exceeds a set proportion, determine that the main abnormal area or the secondary abnormal area is a suspected abnormal area, and take the center coordinates of the suspected abnormal area as the abnormal position in the current monitoring range;

[0090] S343, when the proportion does not exceed the set proportion, discard the main abnormal area or the secondary abnormal area.

[0091] It should be noted that the embodiment is aimed at the main abnormal area and the secondary abnormal area obtained by clustering, and the effect of single-time drilling seismic anomaly point clustering is evaluated to determine whether the proportion of the number of anomaly points in the abnormal area exceeds 40% of the total number of anomaly points. If it exceeds, the secondary abnormal area is considered as a suspected abnormal area, and the center coordinates of the abnormal area are reserved as the suspected abnormal position in the monitoring range of 20 m of this section. If it is determined that the proportion of the number of anomaly points in the abnormal area does not exceed 40% of the total number of points, it is considered to be a false abnormal area, and is discarded.

[0092] It should be understood that the ratio is set to 40% in the embodiment, which is only for illustration. A person skilled in the art can select a suitable ratio according to the actual situation, and the embodiment is not limited specifically.

[0093] It should be noted that the travel distance T i of the observation system is moved once i , that is, the observed range is 20 m. After completing the monitoring range of 0-20 m of the T1 distance in the single observation, the abnormal point distribution of the T2 distance of 20-40 m and the T3 distance of 40-60 m in front and the abnormal area delineation of the T3 distance of 40-60 m are obtained. The station is moved with the drilling seismic monitoring system, and the next monitoring range of the T2 distance of 20-40 m is monitored while drilling. The abnormal point distribution of the T3 distance of 40-60 m in front is obtained through the warning judgment, and the cycle is repeated in turn until the tunneling operation is completed.

[0094] As shown in Figure 6 , the second embodiment of the present application proposes a front abnormality warning method based on the drilling seismic migration result. On the basis of the disclosure of the first embodiment, the method comprises the following steps:

[0095] S10, for the drilling head in front of the monitoring system currently monitored, the travel distance T i is obtained i , the corresponding drilling seismic signal is obtained every set interval distance, and the drilling seismic signal is processed to obtain the abnormal interface of the front position corresponding to each set interval distance of the drilling machine;

[0096] S20, the midpoint of the tangent line segment where the abnormal interface of each set interval distance corresponding to the front position is located is extracted as an anomaly point in the abnormal interface to obtain all the anomaly points extracted after multiple set interval distances;

[0097] S30, the abnormal points in the T i range are clustered and analyzed, the abnormal points in the set range are collected according to the radius, and the suspected abnormal area is determined according to the proportion of the number of anomaly points in the collected area;

[0098] S40, moving the observation system, and repeating steps S10-S20 to obtain all abnormal points corresponding to the next advancing mileage;

[0099] S50, according to the next advancing mileage T i+1 The center point of the suspected abnormal region is determined as the abnormal position and a warning is given when the number of abnormal points in the suspected abnormal region continues to increase.

[0100] It should be understood that if it is determined that the number of abnormal points in the suspected abnormal region does not continue to increase, the suspected abnormal region is determined to be a false abnormal region.

[0101] It should be noted that in the embodiment, the observation system moves once every advancing mileage T i That is, the observed range is 20m, and after completing a single observation of the 20m monitoring range, the tunneling seismic monitoring system is moved, as shown in (b) of FIG. 8, at this time, the rear 1-4 sensors are moved forward and arranged in front of the 16th sensor, the inter-channel spacing is kept at 5m, and the first sensor (at this time, it is the original 4th sensor) is kept at 5m from the head position; after completing the movement of the tunneling seismic monitoring system, the abnormal regions and abnormal positions determined above are judged based on the newly obtained abnormal points in the abnormal interface to ensure efficient production within the safe distance of tunneling. Figure 2 Specifically, after determining all suspected abnormal positions and suspected abnormal regions in the previous 20m monitoring range, the next monitoring range is determined, at this time, 3 abnormal extraction interfaces are formed per meter, and the strengthened judgment process is as follows: for the suspected abnormal region, if the abnormal interface extraction points of the tunneling seismic offset results after each 1m cutting remain continuously increasing in the suspected abnormal region in (b) of FIG. 8, the suspected abnormal region is determined to be abnormal and a warning is given.

[0102] Figure 4

[0103] The embodiment determines abnormal conditions by judging whether the number of abnormal points in the abnormal region increases based on the abnormal region position accumulated by the first observation range and the abnormal points extracted after moving the observation system forward, gives real-time warnings for abnormalities in the monitoring range in front of the tunneling head, ensures efficient production within the safe distance of tunneling, ensures that the tunneling conditions are transparent, predictable and controllable, maintains real-time monitoring and warning within the safe distance during tunneling, provides important support for the transparency of mine geological conditions, and provides strong support for the construction of intelligent mines and the intelligent and precise mining of coal.

[0104] ​​In one embodiment, after step S50: based on all abnormal points corresponding to the next travel mileage, when it is determined that the number of abnormal points in the suspected abnormal area continues to increase, the center point of the suspected abnormal area is determined as the abnormal location and an early warning is issued, the method further includes:

[0105] Determine whether the tunnel excavation operation is complete;

[0106] If so, then the tunnel excavation operation shall be terminated;

[0107] If not, continue moving the observation system to obtain the next travel distance T. i+2 All corresponding anomalies, combined with the distance traveled T i+1 Corresponding anomalies and travel distance T i+2 For all corresponding anomalies, determine the travel distance T. i+2 abnormal areas

[0108] This embodiment identifies suspected anomaly areas based on anomaly points corresponding to the current travel distance ahead of the tunnel face monitored by the observation system. Then, the observation system is moved to acquire anomaly points corresponding to the next travel distance. The number of suspected anomaly points is assessed based on these anomaly points to determine whether an alert is issued. These anomaly points at the next travel distance not only serve as the basis for alert assessment but also as the basis for identifying the next anomaly area. This process continues, with two moves of the observation system constituting one cycle, until the entire tunnel excavation operation is completed.

[0109] In addition, such as Figure 7 As shown, the third embodiment of the present invention proposes a forward anomaly early warning system based on seismic migration results during excavation, the system comprising:

[0110] The anomaly identification module 10 is used to determine the current travel distance T ahead of the tunnel face monitored by the observation system. i Obtain the distance traveled, T. i The seismic signals during excavation are corresponding to the cutting at each set interval distance, and the seismic signals during excavation are processed to obtain the abnormal interface at the front position corresponding to each set interval distance of the tunneling machine.

[0111] The anomaly point extraction module 20 is used to extract the midpoint of the tangent line segment of the abnormal interface at each set interval distance, and use it as the anomaly point in the abnormal interface, so as to obtain all the anomaly points extracted after multiple set interval distances.

[0112] Anomaly region analysis module 30 is used for T i All the aforementioned anomalies within the mileage range are subjected to cluster analysis. The anomalies within the set range are aggregated according to the cluster radius, and the anomaly area is determined and an alert is issued based on the proportion of the number of anomalies in the aggregated area.

[0113] The embodiment extracts the abnormal interfaces corresponding to the front position of the tunneling machine when acquiring the position at each set interval distance according to the tunneling seismic signal, extracts and cluster analyzes the abnormal points in the abnormal interfaces to obtain an abnormal region, determines the abnormal position according to the abnormal region, and gives a real-time early warning for the front abnormality, so that the dynamic real-time early warning for the front of the tunneling roadway can be realized, and the tunneling machine can be safely tunneled without stopping.

[0114] In an embodiment, the abnormal point extraction module 20 is configured to extract the midpoint position coordinates of the tangent line segment where each abnormal interface is located and the angle of the tangent line segment, and take the midpoint position coordinates as the position coordinates of the abnormal point and take the angle of the tangent line segment as the angle information of the abnormal point, and the two-dimensional plane expression form of the abnormal point is (x, y, a), wherein x represents the midpoint horizontal coordinate of the tangent line segment where the abnormal interface is located, y represents the midpoint vertical coordinate of the tangent line segment where the abnormal interface is located, and a represents the angle of the tangent line segment.

[0115] In an embodiment, the abnormal region analysis module 30 comprises:

[0116] The cluster analysis unit is configured to perform cluster analysis on all the abnormal points based on the cluster radius and the position coordinates of all the abnormal points, and obtain a region containing the most abnormal points as a main abnormal region.

[0117] The distance calculation unit is configured to calculate the distance between each abnormal point and the center coordinates of the main abnormal region based on the center coordinates of the main abnormal region, and obtain a group of distance values.

[0118] The scanning unit is configured to sort the distances in the group of distance values from large to small, select the first n distance values according to the sorting result, take the position coordinates of the abnormal points corresponding to the n distance values as the center coordinates of n secondary abnormal regions, and perform abnormal point number scanning on the abnormal points other than the main abnormal region in combination with the cluster radius to determine the n secondary abnormal regions.

[0119] The abnormal region determination unit is configured to determine an abnormal region and give an early warning based on the main abnormal region and the secondary abnormal region in the T i mileage range.

[0120] In an embodiment, the abnormal region determination unit is configured to:

[0121] determine the proportion of the number of abnormal points in the main abnormal region or the secondary abnormal region in the total number of abnormal points.

[0122] When the proportion exceeds a set proportion value, the main abnormal region or the secondary abnormal region is determined as a suspected abnormal region, and the center coordinates of the suspected abnormal region are taken as the abnormal position in the current monitoring range.

[0123] When the proportion does not exceed the set ratio, the main abnormal region or the secondary abnormal region is discarded.

[0124] In an embodiment, the system further comprises a reinforcing module for:

[0125] The abnormal region is taken as a suspected abnormal region, the observation system is moved, and a next travel distance T i+1 All abnormal points corresponding to the travel distance T

[0126] According to the next travel distance T i+1 All abnormal points corresponding to the travel distance T, the center point in the suspected abnormal region is determined as an abnormal position, and a warning is given.

[0127] In an embodiment, the system further comprises:

[0128] A judging module for judging whether the tunnel excavation operation is completed;

[0129] An executing module for ending the tunnel excavation operation when the judging module outputs a result of yes;

[0130] An executing module for continuing to move the observation system to obtain a next travel distance T i+2 All abnormal points corresponding to the travel distance T i+1 All abnormal points corresponding to the travel distance T and the travel distance T i+2 All abnormal points corresponding to the travel distance T i+2 An abnormal region.

[0131] It should be noted that other embodiments of the front abnormality warning system based on the tunneling seismic migration result or the implementation method of the present application can refer to the above-mentioned method embodiments, which will not be repeated here.

[0132] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0133] Furthermore, the terms "first", "second", etc. are used only for descriptive purposes and do not connote or imply relative importance or a quantity of the indicated technical features. Thus, a feature defined with "first", "second", etc. can include at least one of the features implicitly or explicitly. In the description of the present application, the meaning of "a plurality" is at least two, for example, two, three, etc., unless otherwise specifically defined.

[0134] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that changes, modifications, substitutions and variations can be made by those skilled in the art without departing from the scope of the present application.

Claims

1. A method for early warning of abnormality ahead based on seismic migration results while drilling, characterized in that, The method comprises: S10, for the observation system currently monitored heading front travel mileage T i , get the travel mileage T i Every set interval distance cutting corresponding with the excavation of seismic signals, and the excavation of seismic signals are processed, get the heading machine every set interval distance corresponding to the front position of abnormal interface; S20, extracting the midpoint of the tangent line segment of the abnormal interface corresponding to the front position of each set interval distance as an abnormal point in the abnormal interface to obtain all abnormal points extracted after multiple set interval distances; S30, to T i The abnormal points in the mileage range are subjected to cluster analysis, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined and warned according to the proportion of the number of abnormal points in the collected area.

2. The method of claim 1, wherein the method is characterized by, In the pair T i After the cluster analysis of all the abnormal points in the mileage range, the abnormal points in the set range are collected according to the cluster radius, and the abnormal area is determined according to the proportion of the number of abnormal points in the collected area. The abnormal region is taken as a suspected abnormal region, the observation system is moved, and the steps S10-S20 are repeatedly executed to obtain a next travel distance T i+1 All corresponding abnormal points According to the next travel distance T i+1 For all abnormal points corresponding to the suspected abnormal area, it is determined whether the number of abnormal points in the suspected abnormal area is continuously increasing; If yes, determining the center point of the suspected abnormal area as an abnormal position and giving a warning; If no, determining the suspected abnormal area as a false abnormal area.

3. The method of claim 1, wherein the method is characterized by, The method comprises: connecting the drilling machine control system with the drilling machine, obtaining the cutting technical parameters based on the drilling machine technical protocol, the cutting technical parameters comprising the drilling machine position, the drilling machine cutting rock mass working time, the drilling head position of the drilling machine, and the cutting current; obtaining the effective drilling seismic signal of the drilling machine based on the cutting technical parameters.

4. The method of claim 1, wherein the method is characterized by, The method comprises: extracting the midpoint position coordinates of the tangent line segment of each abnormal interface and the angle of the tangent line segment, and taking the midpoint position coordinates as the position coordinates of the abnormal point and the angle of the tangent line segment as the angle information of the abnormal point, the two-dimensional plane expression form of the abnormal point being (x, y, a), wherein x represents the midpoint horizontal coordinate of the tangent line segment of the abnormal interface, y represents the midpoint vertical coordinate of the tangent line segment of the abnormal interface, and a represents the angle of the tangent line segment.

5. The method of claim 1, wherein the method is characterized by, The pair T i The cluster analysis is performed on all the abnormal points in the mileage range, the abnormal points in the range are collected according to a cluster radius, and an abnormal area is determined and an early warning is given according to the proportion of the number of abnormal points in the collected area. Based on the cluster radius and the position coordinates of all the abnormal points, performing cluster analysis on all the abnormal points to obtain a region containing the most abnormal points as a main abnormal area; Based on the center coordinates of the main abnormal area, calculating the distance between each abnormal point and the center coordinates to obtain a group of distance values; sorting the distances in the group of distance values from large to small, and selecting the first n distance values according to the sorting result, taking the position coordinates of the abnormal points corresponding to the n distance values as the center coordinates of n secondary abnormal areas, and performing abnormal point number scanning in combination with the cluster radius except for the main abnormal area to determine the n secondary abnormal areas; Based on T i The main abnormal area and the secondary abnormal area within the mileage range are determined, and an abnormal area is determined and a warning is given.

6. The method of claim 5, wherein the seismic migration result is obtained by using a seismic migration method selected from the group consisting of Kirchhoff migration, Stolt migration, wave equation migration, and reverse time migration. The T i The main abnormal area and the secondary abnormal area within the mileage range are determined, and an abnormal area is determined and a warning is given. judging the proportion of the number of abnormal points in the main abnormal area or the secondary abnormal area in the total number of abnormal points; if the proportion exceeds a set ratio, determining the main abnormal area or the secondary abnormal area as a suspected abnormal area, and taking the center coordinates of the suspected abnormal area as an abnormal position in the current monitoring range; if the proportion does not exceed the set ratio, discarding the main abnormal area or the secondary abnormal area.

7. The method of claim 2, wherein the seismic migration result is obtained by using a seismic migration method selected from the group consisting of Kirchhoff migration, Stolt migration, wave equation migration, and reverse time migration. After determining the center point of the suspected abnormal area as an abnormal position or determining the suspected abnormal area as a false abnormal area, the method further comprises: judging whether the roadway excavation operation is completed; if yes, ending the roadway excavation operation; If not, continue moving the observation system to get next travel distance T i+2 All abnormal points corresponding, combined with travel distance T i+1 All abnormal points corresponding and travel distance T i+2 All abnormal points corresponding, determine travel distance T i+2 Abnormal area of T 8. A system for early warning of anomalies ahead based on seismic migration results as the ground is excavated, characterized in that, The system comprises: An abnormal interface determination module is configured to determine, for a travel distance T in front of a heading face currently monitored by an observation system i , obtain the travel distance T i Every set interval distance cutting corresponding to the excavation of the seismic signal, and processing the seismic signal, get the corresponding position of the abnormal interface of the heading machine every set interval distance The abnormal point extraction module is configured to extract a midpoint of a tangent line segment of an abnormal interface at a corresponding front position of each set interval distance as an abnormal point in the abnormal interface, so as to obtain all abnormal points extracted after multiple set interval distances; An abnormal region analysis module is configured to perform cluster analysis on the abnormal points in the T i The abnormal region analysis module is configured to perform cluster analysis on all the abnormal points in the T mile range, gather the abnormal points in the T mile range according to a cluster radius, and determine an abnormal region according to a proportion of the number of the abnormal points in the gathered region and issue a warning.

9. The system for warning of an anomaly ahead based on seismic migration results as the borehole is drilled according to claim 8, wherein, The system further comprises a strengthening module configured to: moving the observation system and obtaining a next travel distance T i+1 all corresponding abnormal points; According to the next travel distance T i+1 Corresponding to all the abnormal points, the center point in the suspected abnormal area is determined as the abnormal position and a warning is given.

10. The system for warning of an anomaly ahead based on seismic migration results as the borehole is drilled according to claim 8, wherein, The abnormal area analysis module comprises: A cluster analysis unit is configured to perform cluster analysis on all the abnormal points based on a cluster radius and position coordinates of all the abnormal points, so as to obtain an area containing the most abnormal points as a main abnormal area; A distance calculation unit is configured to calculate distances between each of the abnormal points and a center coordinate of the main abnormal area based on the center coordinate, so as to obtain a set of distance values; A scanning unit is configured to sort the distances in the set of distance values from large to small, select the first n distance values according to the sorting result, and take position coordinates of abnormal points corresponding to the n distance values as center coordinates of n secondary abnormal areas, so as to perform abnormal point number scanning on the main abnormal area except for the cluster radius, and determine the n secondary abnormal areas. Anomaly region determination unit, used for T-based i Within the mileage range, the primary and secondary abnormal areas are identified, and an abnormal area is identified and an early warning is issued.

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