Study On Source Information Processing And Inversion Locating Method

Coal occupies a dominant position as usual in China's energy production and consumption structure.The production of coal is the driving force of economic development in china.The prevention of coal accidents is a guarantee of safe production.The microseismic monitoring technology receives seismic signals through sensors arranged underground in coal mines,to invert the true location of the source,to predict damaging impacts such as mine pressure.It can be seen that the information processing and inversion positioning of the source is an important part of microseismic monitoring.Among them,the information processing of the source mainly includes the microseismic monitoring and the pretreatment of the seismic wave signal.First of all,We designed a coal mine microseismic monitoring system,mainly to complete the underground network construction and high-precision time module synchronization.After that,seismic data processing system was used to combine Lab VIEW's visual programming and hardware interface capabilities with MATLAB's powerful numerical computation and simulation capabilities to complete seismic wave data acquisition,reception,storage,Wavelet denoising and first-pass extraction.After acquiring the information of the first arrival extraction wave,the inversion positioning of the source is completed by means of an upper computer.The realization of the inversion location of the source is to transform the solution of the source by the objective function into a solution of the mathematical equations,that is,to use a certain linear method or nonlinear method to complete the inversion of the source.However,these methods often have their drawbacks.Some are prone to pathological equations,and some are easily trapped in local minimum.The results are unreliable.To solve these problems,many domestic and foreign scholars have put forward their own solutions.Based on the research of many scholars,this paper studies the method of inverting the source.1.Analyzing the limitations of the commonly used objective function,adopting the objective function without prior measurement,and using the genetic algorithm to achieve the initial positioning of the source.The reasons for the abnormal fluctuations in the source location were analyzed.Due to the genetic algorithm in the space search process,the early period was faster and the speed was slower in the later period.To solve this problem,the quasi-Newton method has the characteristics of fast convergence.Finally,the genetic-quasi-Newton hybrid algorithm is used to realize the source location and analyze the localization performance.2.When the source is located in the far field,the limitation of the objective function without prior measurement is analyzed.The objective function with twoaxis optimization characteristics is used to determine the location of source,and the objective function is compared with the objective function without prior measurement.Verifying that the positioning accuracy of the two-axis optimization objective function is higher and more stable.3.Firstly,the genetic parameters of the genetic-quasi-Newton hybrid algorithm based on the two-axis optimization objective function are designed,Describing its principles and characteristics,and verifying the feasibility of the source location.Finally,the test is applied to verify the advantages of the new method by comparing the two groups.It not only has the characteristics of two-axis optimization,but also guarantees the accuracy of two-axis positioning,combine fast convergence's characteristics and global optimization of the genetic-quasi-Newton hybrid algorithm.