Space-time tomography method for vibration field in underground shallow complex space

Abstract

The invention relates to a space-time tomography method for a vibration field in a complex space of an underground shallow layer. According to the invention, an autocorrelation imaging technology is cooperatively used for eliminating the noise of a vibration signal and improve the imaging resolution of an energy field at each moment; a cross-correlation imaging technology is utilized to eliminateimaging interference generated by reverse time back propagation; a time window length is set by utilizing the time-varying characteristics of an explosion vibration signal, and energy field information in the time window length is linearly superposed; the energy focusing intensity of an instantaneous energy field is improved, a three-dimensional energy field image of a space domain is converted into a three-dimensional energy field image sequence of the time-space domain, and the number and quality of energy field images are improved; by utilizing the advantages of a generative adversarial network, the important spatio-temporal information of the three-dimensional energy field is self-learned in the generative adversarial process, and the stability of seismic source positioning is improved; and by utilizing the advantages of self-learning, self-confrontation and self-parameter adjustment of the generative adversarial network, the number of tests and the number of sensors are reduced, and seismic source positioning under a preset one-time detonation point is realized.

Description

technical field [0001] The invention belongs to the field of blasting vibration testing technology and passive positioning technology, and in particular relates to a space-time tomographic imaging method of a vibration field in an underground shallow complex space. Background technique [0002] The spatiotemporal distribution of explosion power field is to use the explosion physical parameters such as overpressure, stress wave energy, kinetic energy and other explosion physical parameters to reconstruct its intensity distribution after the explosion in an inversion way, and to characterize the distribution of damage effectiveness in the strike area after the explosion. This method is an important means to realize the damage effectiveness evaluation of underground explosions. [0003] In the process of spatio-temporal reconstruction of explosive power field, accurate measurement of underground detonation point is the key to reconstruction of spatio-temporal field. Compared w...

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Problems solved by technology

[0005] Due to the complexity of the underground medium, the small number of sensors and the random layout when locating the shallow seismic source, the imaging accuracy of the underground energy field is not high, and the positioning accuracy of the seismic source is low;

[0006] Researchers use the swarm intelligence algorithm to quickly locate the energy focal point. This method has certain blindness and randomness when searching for the focal point, which leads to unstable recognition of the focal point, poor robustness of source positioning, and positioning accuracy cannot be guaranteed. Ultimately, it is impossible to achieve effective space-time field reconstruction

[0007] When using a supervised deep learning method to locate the detonation point, it is necessary to preset multiple seismic source bombs to train the network model, resulting in long test periods and high test costs

[0008] Aiming at the problems of low accuracy and poor stability of underground shallow seismic source positioning, the present invention proposes a seismic source positioning method based on unsupervised deep learning

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