Acoustics

Acoustics

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

Yazarlar: Zia Ullah, Xinhua Wang, Yingchun Chen, Tao Zhang, Haiyang Ju and Yizhen Zhao

Cilt 1 , Sayı 1 , 2019 , Sayfalar 199-219

Konular:-

DOI:10.3390/acoustics1010013

Anahtar Kelimeler:Blind source separation,Pipeline flaw detection,Structure health monitoring,Complexity pursuit,Output modal identification

Özet: 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.


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BibTex
KOPYALA
@article{2019, title={Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit}, volume={1}, number={199–219}, publisher={Acoustics}, author={Zia Ullah, Xinhua Wang, Yingchun Chen, Tao Zhang, Haiyang Ju and Yizhen Zhao}, year={2019} }
APA
KOPYALA
Zia Ullah, Xinhua Wang, Yingchun Chen, Tao Zhang, Haiyang Ju and Yizhen Zhao. (2019). Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit (Vol. 1). Vol. 1. Acoustics.
MLA
KOPYALA
Zia Ullah, Xinhua Wang, Yingchun Chen, Tao Zhang, Haiyang Ju and Yizhen Zhao. Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit. no. 199–219, Acoustics, 2019.