Gravitational Search Algorithm for Microseismic Source Location in Tunneling: Performance Analysis and Engineering Case Study

Abstract

Microseismic source location (MSL) provides crucial information for the interpretation of rock mass stability and early warning of rock mass hazards. The accuracy of MSL mainly depends on the formation of the sensor array, the multi-velocity model, and the locating algorithm. Especially, the choice of algorithm plays a decisive role, which requires both optimal accuracy and efficiency for searching the global optimal solution. In this paper, an advanced heuristic algorithm, Gravitational Search Algorithm (GSA), is applied for MSL in tunnel engineering. A standard framework of the GSA-based searching process is first built. Its accuracy, stability, and speed of convergence are rigorously compared and analyzed with particle swarm optimization and simplex algorithm using synthetic and real microseismic data. Four types of equivalent velocity models are combined with the searching algorithm to further discuss the applicability and performance of GSA in different situations. The studies show that for all the cases, GSA has the highest speed of convergence with the best accuracy. Locating errors are controlled within 10 m, which fulfills the requirement of engineering accuracy. A representative case study is conducted using microseismic data prior to a major rockburst in a twin-tube highway tunnel. The calculated cluster of seismic events using GSA-based algorithm well matches the actual unstable areas. This work indicates that GSA is an optimal algorithm for microseismic source location and rockburst warning in tunneling.