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An Experimental Study of the Acoustic Signal Characteristics of Locked-Segment Damage Evolution in a Landslide Model.
Zhu, Xing; Chen, Hui; Wu, Zhanglei; Yang, Shumei; Li, Xiaopeng; Li, Tiantao.
Afiliación
  • Zhu X; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.
  • Chen H; College of Computers and Cyber Security, Chengdu University of Technology, Chengdu 610059, China.
  • Wu Z; Sichuan Engineering Technology Research Center of Industrial Internet Intelligent Monitoring and Application, Chengdu University of Technology, Chengdu 610059, China.
  • Yang S; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.
  • Li X; The Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China.
  • Li T; Powerchina Chengdu Engineering Corporation Limited, Chengdu 610050, China.
Sensors (Basel) ; 24(15)2024 Jul 30.
Article en En | MEDLINE | ID: mdl-39123993
ABSTRACT
Three-section landslides are renowned for their immense size, concealed development process, and devastating impact. This study conducted physical model tests to simulate one special geological structure called a three-section-within landslide. The failure process and precursory characteristics of the tested samples were meticulously analyzed using video imagery, micro-seismic (MS) signals, and acoustic emission (AE) signals, with a focus on event activity, intensity, and frequency. A novel classification method based on AE waveform characteristics was proposed, categorizing AE signals into burst signals and continuous signals. The findings reveal distinct differences in the evolution of these signals. Burst signals appeared exclusively during the crack propagation and failure stages. During these stages, the cumulative AE hits of burst signals increased gradually, with amplitude rising and then declining. High-amplitude burst signals were predominantly distributed in the middle- and high-frequency bands. In contrast, cumulative AE hits of continuous signals escalated rapidly, with amplitude monotonously increasing, and high-amplitude continuous signals were primarily distributed in the low-frequency band. The emergence of burst signals and high-frequency AE signals indicated the generation of microcracks, serving as early-warning indicators. Notably, the early-warning points of AE signals were detected earlier than those of video imagery and MS signals. Furthermore, the early-warning point of burst signals occurred earlier than those of continuous signals, and the early-warning point of the classification method preceded that of overall AE signals.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China