Acoustic Emission Sensor Network Optimization Based on Grid Loop Search and Particle Swarm Source Location

TL;DR

This paper introduces a grid loop search and particle swarm optimization method for sensor layout in acoustic emission testing, significantly improving source localization accuracy over traditional methods through synthetic and experimental validation.

Contribution

The study presents a novel grid-based optimization approach combined with PSO for sensor placement, enhancing multi-source localization accuracy in structural testing.

Findings

Achieved an average location error of 1.78 mm in synthetic tests.

Improved location accuracy by up to 59.15% in experiments.

Outperformed traditional layout, GA, and SA methods in accuracy.

Abstract

The layout of acoustic emission sensors plays a critical role in non-destructive structural testing. This study proposes a grid-based optimization method focused on multi-source location results, in contrast to traditional sensor layout optimization methods that construct a correlation matrix based on sensor layout and one source location. Based on the seismic source travel-time theory, the proposed method establishes a location objective function based on minimum travel-time differences, which is solved through the particle swarm optimization (PSO) algorithm. Furthermore, based on location accuracy across various configurations, the method systematically evaluates potential optimal sensor locations through grid search. Synthetic tests and laboratory pencil-lead break (PLB) experiments are conducted to compare the effectiveness of PSO, genetic algorithm, and simulated annealing, with the following conclusions: (1) In synthetic tests, the proposed method achieved an average location error of 1.78 mm, outperforming that based on the traditional layout, genetic algorithm (GA), and simulated annealing (SA). (2) For different noise cases, the location accuracy separately improved by 24.89% ({\sigma}=0.5{\mu}s), 12.59% ({\sigma}=2{\mu}s), and 15.06% ({\sigma}=5{\mu}s) compared with the traditional layout. (3) For the PLB experiments, the optimized layout achieved an average location error of 9.37 mm, which improved the location accuracy by 59.15% compared with the Traditional layout.