Gaussian mixture model and delay-and-sum based 4D imaging of damage in aircraft composite structures under time-varying conditions

• Published in: Mechanical systems and signal processing Vol. 135; p. 106390
• Main Authors: Ren, Yuanqiang, Qiu, Lei, Yuan, Shenfang, Fang, Fang
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 01.01.2020; Elsevier BV
• Subjects: 4D imaging; Aircraft; Aircraft composite structure; Aircraft structures; Carbon fibers; Composite structures; Construction; Damage localization; Delay; Fiber composites; Gaussian mixture model; Guided wave; Imaging; Invariants; Localization; Piezoelectricity; Plates (structural members); Probabilistic models; Signal processing; Structural damage; Structural health monitoring; Time-varying conditions; Guided wave; Time-varying conditions; 4D imaging; Gaussian mixture model; Aircraft composite structure
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2019.106390

•We propose a Gaussian mixture model and delay-and-sum based 4D imaging method.•The time-invariant feature signal can be constructed by adopting GMM.•The 4D imaging can generate a serial of images with damage gradually emerging.•Experimental results prove the proposed method under temperature variation. In the field of structural health monitoring (SHM) of aircraft composite structures, piezoelectric sensor network and guided wave (GW) based imaging method has proved to be a promising damage monitoring method and has been widely researched. However, the current work has barely considered that aircraft structures are usually subject to random and complex time-varying conditions, which may introduce uncertainties into the acquired GW signals and make it hard to realize reliable damage imaging and localization. Aiming at this issue, this paper proposes a Gaussian mixture model (GMM) and delay-and-sum based 4D imaging method to achieve reliable damage monitoring of aircraft composite structures under time-varying conditions. In this method, the GMM is adopted to suppress the time-varying influence and to construct time-invariant feature signal which is only affected by damage. During the monitoring process, by continuously updating GMM and constructing time-invariant feature signal, the delay-and-sum based 4D imaging can be performed to generate a serial of images with damage gradually emerging, from which the damage can be accurately located. The method is validated on a stiffened carbon fiber composite plate within a temperature range from −20 °C to 60 °C. Validation results indicate that reliable damage imaging and localization under temperature variation is achieved.