Research On The Adaptive Algorithm For Identifying Microseismic Signal And P Wave First Time Automatically Base On The Allen Algorithm Under The Project Scale

Project scale refers microseismic monitoring in range between a few meters to several hundred meters,microseismic signal at that scale with respect to the natural earthquake has the following features,such as short duration,low SNR,small energy,complex background noise,Signal characteristics change with engineering,etc.The algorithm suitable for identifying microseismic signal and P wave first time automatically under the project scale has been a research and analysis of microseismic difficulties and hotspots.This results seismic signal processing method of mature Allen algorithm into the microseismic field need to adjust the Allen algorithm STA/LTA parameters,improved characteristic function,so that the algorithm will achieve the best pick-up effect,improve positioning accuracy.The thesis mainly takes the microseismic monitoring data of JinPing deep underground laboratory as the source,makes detailed analysis on signal under the engineering scale.According to the difficulty of selecting the STA/LTA coefficient of the Allen algorithm,RMA microseismic signal classification method is put forward.The greater RMA value is,the clearer the signal will be.Combining the RMA signal classification,Particle Swarm Optimization algorithm and the evaluation model of picking-up effect,we can pro vide the microseismic signal recognition and P wave first time collecting under the engineering scale model based on Allen algorithm.Through the Allen algorithm processing microseismic signal parameters and database accumulation and improvement,the ability of the initial self-adjusting between the microseismic signal and its P wave under the engineering scale dealing with the Allen algorithm is improved.This is conducive to the realization of microseismic monitoring system for fast and accurate positioning analysis,warning timely,reducing accidents.The AB(Allen coupled with Bear algorithm)algorithm is put forward based on the advantages of Allen algorithm that can quickly and effectively pickup vibration signal and the Bear algorithm that is good at p icking up the P wave first time of low SNR vibration signal.The AB algorithm introduces the weighted factor and the characteristic function of the Bear algorithm to improve Allen algorithm,which is suitable for identifying microseismic signal and P wave first time automatically under the project scale.Research shows that:(1)the weight factor K,characteristic function CF and ? value of AB algorithm have higher sensitivity to frequency and amplitude changes than Allen algorithm;(2)AB algorithm is more sensitivity to frequency and amplitude changes than frequency changes;(3)the seismic signal pickup rate of AB algorithm is higher than Allen algorithm,and the accuracy of P wave pickup automatically is higher than Allen algorithm under the project scales The seismic signal analysis of Jinping deep underground laboratory shows that,for the weak signal,the microseismic source positioning results have higher reliability and stability based on the AB algorithm.The AB algorithm is effective,simple and suitable for real time monitoring of microseismic signal and the P wave first-break picking.