Sparse estimation based monitoring method for damage detection and localization: A case of study

Mahjoub El Mountassir (1, 2) , Slah Yaacoubi (2) , Gilles Mourot (1) , Didier Maquin (1)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 Institut de soudure

This paper suggests a Structural Health Monitoring (SHM) method for damage detection and localization in pipeline. The baseline signals, used in SHM, could change due to the variation of environmental and operational conditions (EOCs). Hence, the damage detection method could give rise to false alarm. In this study, this issue is addressed by selecting from the database of reference signals those with similar or very close EOCs. Such an operation can be performed by calculating a sparse estimation of the current signal. The estimation error is used as an indication of the presence of damage. Actually, a damage signal will be characterized by a high estimation error compared to that of a healthy signal. The damage location is obtained by calculating the estimation error on a sliding window over the damaged state signal. This method was tested on signals collected on a 6 m pipeline segment placed in a workshop under natural temperature variations. Results have shown that the created damage was successfully detected and localized.

Mots clés: Structural Health Monitoring; sparse estimation; damage detection; damage localization; environmental and operational conditions

Domaines: Automatique / Robotique

Mahjoub El Mountassir, Slah Yaacoubi, Gilles Mourot, Didier Maquin. Sparse estimation based monitoring method for damage detection and localization: A case of study. Mechanical Systems and Signal Processing, 2018, 112, pp.61-76. ⟨10.1016/j.ymssp.2018.04.024⟩. ⟨hal-01767339⟩