Temperature variation effects on sparse representation of guided-waves for damage diagnosis in pipelines

Matineh Eybpoosh; Mario Berges; Hae Young Noh

doi:10.1117/12.2084434

1 April 2015 Temperature variation effects on sparse representation of guided-waves for damage diagnosis in pipelines

Matineh Eybpoosh, Mario Berges, Hae Young Noh

Proceedings Volume 9437, Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015; 94371N (2015) https://doi.org/10.1117/12.2084434
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2015, San Diego, California, United States

Abstract

Multiple ultrasonic guided-wave modes propagating along a pipe travel with different velocities which are themselves a function of frequency. Reflections from the features of the structure (e.g., boundaries, pipe welding, damage, etc.), and their complex superposition, adds to the complexity of guided-waves. Guided-wave based damage diagnosis of pipelines becomes even more challenging when environmental and operational conditions (EOCs) vary (e.g., temperature, flow rate, inner pressure, etc.). These complexities make guided-wave based damage diagnosis of operating pipelines a challenging task. This paper reviews the approaches to-date addressing these challenges, and highlights the preferred characteristics of a method that simplifies guided-wave signals for damage diagnosis purposes. A method is proposed to extract a sparse subset of guided-wave signals in time-domain, while retaining optimal damage information for detection purpose. In this paper, the general concept of this method is proved through an extensive set of experiments. Effects of temperature variation on detection performance of the proposed method, and on discriminatory power of the extracted damage-sensitive features are investigated. The potential of the proposed method for real-time damage detection is illustrated, for wide range of temperature variation scenarios (i.e., temperature difference between training and test data varying between -2°C and 13°C).

Citation Download Citation

Matineh Eybpoosh, Mario Berges, and Hae Young Noh "Temperature variation effects on sparse representation of guided-waves for damage diagnosis in pipelines", Proc. SPIE 9437, Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015, 94371N (1 April 2015); https://doi.org/10.1117/12.2084434

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