A Novel Hybrid Method to Detect Arrival Times of Elastic Waves with Low SNR Based on Jensen-Shannon Divergence and Cumulative Sum Algorithm

• Published in: IEEE transactions on instrumentation and measurement Vol. 71; p. 1
• Main Authors: Chen, Hongpeng, Xu, Handong, Yang, Zhensheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustic emission; Algorithms; Background noise; Cumulative Sum algorithm; Elastic waves; Jensen-Shannon Divergence; Localization; Scratching; Seismic signal; Signal to noise ratio; Time of arrival; Windows (intervals)
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2022.3212529

Arrival-time detection is one fundamental step in the time of arrival (TOA) based localization for elastic wave signals in acoustic emission (AE), ultrasonic, and seismic localization systems. The precise TOA picking is of great importance for high localization accuracy. In some cases, signals are often hidden with a low signal-to-noise ratio (SNR), making it difficult to detect TOA from strong background noise. The picking accuracy of traditional TOA detection methods decreases rapidly in low SNR condition. The present work proposes a new method for evaluating arrival times based on Jensen-Shannon Divergence and Cumulative Sum algorithm. A criterion and a standard procedure for determining TOA are formulated in detail, and two key parameters are discussed, namely, the length of the time window and the size of the chosen time series. Tests on AE signals from single-grit scratching, the pencil-lead break, and seismic signals for P-phase identification reveal the feasibility and effectiveness of the proposed method. Compared with 3 different methods, it is more precise in low SNR condition since its offsets are much smaller than those. The proposed method could be applied as a better alternative method for TOA detection in various fields.