CN111965696A - Dynamic disaster prediction method based on elastic wave multi-target analysis - Google Patents
Dynamic disaster prediction method based on elastic wave multi-target analysis Download PDFInfo
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Abstract
The invention discloses a dynamic disaster prediction method based on elastic wave multi-target analysis, which comprises the following steps: s1, during operation, an acoustic emission monitoring device is used for collecting and sending elastic wave signals transmitted in a measured target body; s2, the ground comprehensive signal processing device receives and analyzes the elastic wave signals to obtain abnormal geologic bodies in the measured target body and dynamic inversion imaging of stress changes, and acoustic emission characteristic parameters of the elastic wave signals are extracted at the same time; and S3, the ground comprehensive signal processing device carries out disaster judgment and intelligent early warning according to the change condition of the abnormal geologic body dynamic inversion imaging or the change condition of the stress change dynamic inversion imaging or the change condition of the acoustic emission characteristic parameter in the measured target body. The dynamic disaster prediction method based on elastic wave multi-target analysis can comprehensively and accurately predict and early warn dynamic disasters, greatly improve prediction accuracy, greatly improve prediction work efficiency and reduce prediction cost.
Description
Technical Field
The invention relates to the field of disaster prediction, in particular to a dynamic disaster prediction method based on elastic wave multi-target analysis.
Background
Nowadays, mines gradually enter a deep mining stage, the mining environment of the mines is severe day by day, stress-dominated coal and rock dynamic disasters are increased day by day, the safe and efficient production of the coal mines is seriously affected, and the accurate prediction and early warning of the dynamic disasters are the key for preventing and controlling the dynamic disasters. The dynamic disaster occurs as a result of the combined action of multiple influence factors such as stress, geological conditions, coal body structure and the like, the currently widely used prediction technology and equipment mainly aim at processing single influence factors and obtain a better effect, but the multiple factors are mastered, multiple technologies and equipment are needed to be jointly detected and monitored for multiple times, so that the working efficiency and the reliability of prediction are seriously influenced, the comprehensive dynamic monitoring on multiple disaster-causing factors in the actual operation process is difficult, and the prediction investment cost is very high.
Disclosure of Invention
In view of the above, the invention aims to overcome the defects in the prior art, provide a dynamic disaster prediction method based on elastic wave multi-target analysis, and perform comprehensive and accurate prediction and early warning on the dynamic disaster, thereby greatly improving the prediction accuracy, greatly improving the prediction work efficiency and reducing the prediction cost.
The dynamic disaster prediction method based on elastic wave multi-target analysis comprises the following steps:
s1, during operation, an acoustic emission monitoring device is used for collecting and sending elastic wave signals transmitted in a measured target body;
s2, the ground comprehensive signal processing device receives and analyzes the elastic wave signals to obtain abnormal geologic bodies in the measured target body and dynamic inversion imaging of stress changes, and acoustic emission characteristic parameters of the elastic wave signals are extracted at the same time; the acoustic emission characteristic parameters include acoustic emission event number, ringing count, energy, amplitude, arrival time, and duration;
and S3, the ground comprehensive signal processing device carries out disaster judgment and intelligent early warning according to the change condition of the abnormal geologic body dynamic inversion imaging or the change condition of the stress change dynamic inversion imaging or the change condition of the acoustic emission characteristic parameter in the measured target body.
Further, the acoustic emission monitoring device comprises an acoustic emission monitoring device and an acoustic emission sensor; the acoustic emission sensor is used for collecting and transmitting elastic wave signals, and the acoustic emission monitoring equipment is used for receiving and sending the elastic wave signals collected by the acoustic emission sensor.
Further, the ground comprehensive signal processing device comprises a receiving unit, a calculating unit, a processing unit and a display unit; the receiving unit is used for receiving elastic wave signals; the computing unit carries out inversion imaging computation on the elastic wave signals and extracts acoustic emission characteristic parameters of the elastic wave signals; the processing unit analyzes the change condition of the inversion imaging and the change condition of the acoustic emission characteristic parameters to obtain a disaster early warning result; the display unit is used for displaying the disaster early warning result.
Further, before operation, acquiring and analyzing an elastic wave signal propagated in a measured target body under the condition of an active seismic source to obtain a primary inversion imaging of the abnormal geologic body; the active seismic sources comprise a blasting seismic source, a heading machine operation seismic source, a coal cutter operation seismic source and a bolting machine operation seismic source.
Further, in step S1, acquiring an elastic wave signal propagating in the measured object under the condition of an active seismic source and/or a passive seismic source; the passive seismic source is a seismic source generated in the measured target body.
Further, in step S2, analyzing the elastic wave signal to obtain a dynamic inversion image of the abnormal geologic body and the stress variation in the measured target body, specifically including:
s21, inverting the elastic wave signals by using an inversion imaging algorithm to obtain a once inversion imaging of the geologic body and the stress variation;
and S22, obtaining a new inversion imaging of the abnormal geologic body and the stress change in the measured target body by analogy according to the step S21 by taking the set dynamic update interval time T as a period.
The invention has the beneficial effects that: according to the dynamic disaster prediction method based on elastic wave multi-target analysis, comprehensive analysis is performed by comprehensively acquiring the evolution of the abnormal geologic body, the evolution of the stress state and the acoustic emission advanced appearance characteristic of the dynamic disaster in the operation process, so that comprehensive and accurate prediction and early warning of the dynamic disaster are realized, the prediction accuracy is greatly improved, the prediction work efficiency is greatly improved, and the prediction cost is reduced.
Drawings
The invention is further described below with reference to the following figures and examples:
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings, in which:
the dynamic disaster prediction method based on elastic wave multi-target analysis comprises the following steps:
s1, during operation, an acoustic emission monitoring device is used for collecting and sending elastic wave signals transmitted in a measured target body;
s2, the ground comprehensive signal processing device receives and analyzes the elastic wave signals to obtain abnormal geologic bodies in the measured target body and dynamic inversion imaging of stress changes, and acoustic emission characteristic parameters of the elastic wave signals are extracted at the same time; the acoustic emission characteristic parameters comprise acoustic emission event number, ringing count, energy, amplitude, arrival time, duration and the like;
and S3, the ground comprehensive signal processing device carries out disaster judgment and intelligent early warning according to the change condition of the abnormal geologic body dynamic inversion imaging or the change condition of the stress change dynamic inversion imaging or the change condition of the acoustic emission characteristic parameter in the measured target body.
The disaster forecasting method can select only one of the three change conditions to carry out disaster early warning according to actual conditions and requirements, can also be combined and applied, has rich functions and flexible application selection, meets the requirements of automation, informatization and intellectualization, can obviously improve the disaster forecasting accuracy, makes up the defect of a single forecasting means, and greatly reduces the forecasting cost.
According to the dynamic disaster comprehensive identification and intelligent prediction method, elastic wave signals transmitted in a measured target body are collected and transmitted through the acoustic emission monitoring device, dynamic inversion imaging of abnormal geologic bodies and stress changes in the measured target body and extraction of acoustic emission characteristic parameters are carried out after synchronization of the ground comprehensive signal processing device, and then the change rules of the dynamic inversion imaging and the acoustic emission characteristic parameters are analyzed, so that dynamic disaster comprehensive identification and intelligent prediction based on elastic wave inversion imaging and real-time monitoring multi-target fusion are realized.
In this embodiment, the acoustic emission monitoring device includes an acoustic emission monitoring device and a matched acoustic emission sensor; the acoustic emission sensor is used for collecting and transmitting elastic wave signals, and the acoustic emission monitoring equipment is used for receiving and sending the elastic wave signals collected by the acoustic emission sensor. The acoustic emission sensor is fixedly arranged in a measured target body in a space hierarchical symmetry mode, and the measured target body is a monitored object in a monitoring range; the acoustic emission monitoring device is connected with the acoustic emission sensor through a shielding signal cable, and the acoustic emission monitoring device is arranged according to the actual environment of the measured target body.
In this embodiment, the ground integrated signal processing apparatus includes a receiving unit, a calculating unit, a processing unit, and a display unit. The receiving unit is used for receiving elastic wave signals sent by the acoustic emission monitoring equipment; the computing unit carries out inversion imaging computation based on the elastic wave signals to obtain dynamic inversion imaging of abnormal geologic bodies and stress changes in the measured target body, and acoustic emission characteristic parameters in the elastic wave signals are extracted; the processing unit analyzes the change condition of the dynamic inversion imaging of the abnormal geologic body, the change condition of the dynamic inversion imaging of the stress change and the change condition of the acoustic emission characteristic parameter to obtain a disaster early warning result; the display unit is used for displaying the disaster early warning result.
In this embodiment, before operation, elastic wave signals propagated in the measured target body may be collected and analyzed under the condition of an active seismic source to obtain a single inversion imaging of an abnormal geologic body in the measured target body, so as to preliminarily grasp a geologic occurrence condition in the measured target body. The inversion imaging adopts the existing high-precision imaging algorithm to carry out inversion. The active seismic sources comprise a blasting seismic source, a heading machine operation seismic source, a coal cutter operation seismic source and a bolting machine operation seismic source; the active seismic sources also include sources generated by other standard seismic source generators.
In this embodiment, in step S1, the acquisition of the elastic wave signal propagating in the measured object is realized under the condition of at least one of the active seismic source and the passive seismic source; the passive seismic source is a seismic source generated in the measured target body.
In this embodiment, in step S2, analyzing the elastic wave signal to obtain a dynamic inversion image of an abnormal geologic body and a stress change in the measured target body, specifically including:
s21, a computing unit of the acoustic emission processing equipment uses a built-in high-precision inversion imaging algorithm to invert the elastic wave digital signals to obtain abnormal geologic bodies in the measured target body and one-time inversion imaging of stress variation; the inversion imaging algorithm adopts the prior art, and is not described herein again;
s23, taking the set dynamic update interval time T as a period, obtaining new inversion imaging of the abnormal geologic body and the stress change in the measured target body by analogy according to the step S21, and further continuously updating the inversion imaging of the abnormal geologic body and the stress change, so that dynamic inversion imaging is realized; in this embodiment, the interval time T is set according to an actual working condition environment.
In this embodiment, in step S3, a multi-information coupling cooperative analysis is performed according to the change condition of the abnormal geologic body dynamic inversion imaging, the change condition of the stress change dynamic inversion imaging, and the change condition of the acoustic emission characteristic parameter in the measured target body, and an identification early warning result is issued in combination with a field actual given comprehensive identification criterion. The early warning result can be divided according to the severity to obtain different early warning levels, and the early warning levels can be divided into different levels according to actual field use, such as three levels of safety, general danger and severe danger.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (6)
1. A dynamic disaster prediction method based on elastic wave multi-target analysis is characterized by comprising the following steps: the method comprises the following steps:
s1, during operation, an acoustic emission monitoring device is used for collecting and sending elastic wave signals transmitted in a measured target body;
s2, the ground comprehensive signal processing device receives and analyzes the elastic wave signals to obtain abnormal geologic bodies in the measured target body and dynamic inversion imaging of stress changes, and acoustic emission characteristic parameters of the elastic wave signals are extracted at the same time; the acoustic emission characteristic parameters include acoustic emission event number, ringing count, energy, amplitude, arrival time, and duration;
and S3, the ground comprehensive signal processing device carries out disaster judgment and intelligent early warning according to the change condition of the abnormal geologic body dynamic inversion imaging or the change condition of the stress change dynamic inversion imaging or the change condition of the acoustic emission characteristic parameter in the measured target body.
2. The dynamic disaster prediction method based on elastic wave multi-target analysis according to claim 1, characterized in that: the acoustic emission monitoring device comprises an acoustic emission monitoring device and an acoustic emission sensor; the acoustic emission sensor is used for collecting and transmitting elastic wave signals, and the acoustic emission monitoring equipment is used for receiving and sending the elastic wave signals collected by the acoustic emission sensor.
3. The dynamic disaster prediction method based on elastic wave multi-target analysis according to claim 1, characterized in that: the ground comprehensive signal processing device comprises a receiving unit, a calculating unit, a processing unit and a display unit; the receiving unit is used for receiving elastic wave signals; the computing unit carries out inversion imaging computation on the elastic wave signals and extracts acoustic emission characteristic parameters of the elastic wave signals; the processing unit analyzes the change condition of the inversion imaging and the change condition of the acoustic emission characteristic parameters to obtain a disaster early warning result; the display unit is used for displaying the disaster early warning result.
4. The dynamic disaster prediction method based on elastic wave multi-target analysis according to claim 1, characterized in that: before operation, acquiring and analyzing an elastic wave signal propagated in a measured target body under the condition of an active seismic source to obtain a primary inversion imaging of an abnormal geologic body; the active seismic sources comprise a blasting seismic source, a heading machine operation seismic source, a coal cutter operation seismic source and a bolting machine operation seismic source.
5. The dynamic disaster prediction method based on elastic wave multi-target analysis according to claim 1, characterized in that: in step S1, acquiring an elastic wave signal propagated in the measured object under the condition of an active seismic source and/or a passive seismic source; the passive seismic source is a seismic source generated in the measured target body.
6. The dynamic disaster prediction method based on elastic wave multi-target analysis according to claim 1, characterized in that: in step S2, analyzing the elastic wave signal to obtain a dynamic inversion image of the abnormal geologic body and the stress variation in the target body, specifically including:
s21, inverting the elastic wave signals by using an inversion imaging algorithm to obtain a once inversion imaging of the geologic body and the stress variation;
and S22, obtaining a new inversion imaging of the abnormal geologic body and the stress change in the measured target body by analogy according to the step S21 by taking the set dynamic update interval time T as a period.
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