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Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit

College of Mechanical Engineering, Beijing University of Technology, Beijing 100124, China
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Acoustics 2019, 1(1), 199-219; https://doi.org/10.3390/acoustics1010013
Received: 15 December 2018 / Revised: 4 February 2019 / Accepted: 14 February 2019 / Published: 19 February 2019
Vital defect information present in the magnetic field data of oil and gas pipelines can be perceived by developing such non-parametric algorithms that can extract modal features and performs structural assessment directly from the recorded signal data. This paper discusses such output-only modal identification method Complexity Pursuit (CP) based on blind signal separation. An application to the pipeline flaw detection is presented and it is shown that the complexity pursuit algorithm blindly estimates the modal parameters from the measured magnetic field signals. Numerical simulations for multi-degree of freedom systems show that the method can precisely identify the structural parameters. Experiments are performed first in a controlled laboratory environment secondly in real world, on pipeline magnetic field data, recorded using high precision magnetic field sensors. The measured structural responses are given as input to the blind source separation model where the complexity pursuit algorithm blindly extracted the least complex signals from the observed mixtures that were guaranteed to be source signals. The output power spectral densities calculated from the estimated modal responses exhibit rich physical interpretation of the pipeline structures. View Full-Text
Keywords: blind source separation; pipeline flaw detection; structure health monitoring; complexity pursuit; output modal identification blind source separation; pipeline flaw detection; structure health monitoring; complexity pursuit; output modal identification
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Ullah, Z.; Wang, X.; Chen, Y.; Zhang, T.; Ju, H.; Zhao, Y. Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit. Acoustics 2019, 1, 199-219.

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