Rock and Soil Mechanics ›› 2019, Vol. 40 ›› Issue (S1): 494-502.doi: 10.16285/j.rsm.2018.2026

• Numerical Analysis • Previous Articles     Next Articles

Numerical simulation of unknown wave velocity acoustic emission localization based on particle swarm optimization algorithm

YANG Dao-xue1, 2, ZHAO Kui1, 2, ZENG Peng1, 2, ZHUO Yu-long1, 2   

  1. 1. School of Resources And Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou,Jiangxi 341000, China; 2. Jiangxi Provincial Key Laboratory of Mining Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China
  • Received:2018-11-02 Online:2019-08-01 Published:2019-08-18
  • Supported by:
    This work was supported by the Technology Project Funding Support Plan(51664018, 51364012), the Jiangxi Advantage Technology Innovation Team Project(20165BCB19012), and Jiangxi University of Science and Technology Excellent Doctoral Thesis Cultivation Project(3105500025).

Abstract: To solve the problem that the positioning accuracy of the acoustic emission time difference localization algorithm is affected by many factors such as rock wave velocity in rock mechanics test, an unknown wave velocity acoustic emission localization algorithm based on particle swarm optimization is developed in this paper. The algorithm takes the rock wave velocity as an unknown value, establishing the objective function based on the least squares principle according to the picked time difference, applying the particle swarm optimization algorithm to solve the objective function and find the target position and wave velocity. The weight coefficient is an important factor affecting the accuracy and stability of the algorithm. Firstly, the optimal weight coefficient 0.729 8 is determined by numerical model, which can satisfy the accuracy and stability requirements of the algorithm. The numerical simulation results show that the calculation accuracy based on the selected weight coefficient is higher than the traditional wave velocity algorithm. In order to verify the algorithm in practical application, the lead-breaking test is carried out. It is proved that the algorithm is superior to the traditional wave velocity algorithm.

Key words: acoustic emission localization, unknown wave velocity, particle swarm optimization, weight coefficient

CLC Number: 

  • TE 351
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