Kalman filter based neutral axis tracking in composites under varying temperature conditions

• Published in: Mechanical systems and signal processing Vol. 110; pp. 485 - 498
• Main Authors: Soman, Rohan, Malinowski, Pawel, Majewska, Katarzyna, Mieloszyk, Magdalena, Ostachowicz, Wieslaw
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 15.09.2018; Elsevier BV
• Subjects: Ambient temperature; Composite; Composite materials; Damage detection; Data fusion; Data integration; Fiber bragg grating (FBG) strain sensor; Fiberglass; Finite element method; Fusion; Glass fiber reinforced plastics; Glass-epoxy composites; Kalman filter (KF); Kalman filters; Load; Maintenance costs; Multisensor fusion; Neutral axis (NA); Noise measurement; Observability (systems); Structural damage; Structural health monitoring; Temperature; Temperature effects; Neutral axis (NA); Fiber bragg grating (FBG) strain sensor; Data fusion; Temperature; Composite; Kalman filter (KF)
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2018.03.046

•New method for Neutral Axis (NA) tracking under different temperature conditions.•Multi-rate data fusion of strain and temperature data using Kalman Filter.•Robustness in the presence of bulk and gradient temperature changes on the sample.•FE simulated studies supported by experimental data. Structural Health Monitoring (SHM) systems allow early detection of damage which allows maintenance planning and reduces the maintenance cost. There is a lot of active research in the area for SHM of civil and mechanical structures. The SHM system should be low cost, suitable for continuous monitoring, able to detect small levels of damage, and insensitive to ambient loading, changes in ambient temperature, and measurement noise. Change in Neutral Axis (NA) has been used by several researchers as a damage sensitive feature. It has been shown to be sensitive to small levels of damage, and independent of the ambient loading. This paper aims at showing the insensitivity of the NA to ambient condition changes. This paper demonstrates a methodology for overcoming the effect of temperature on the accurate tracking of the NA. A multi-rate Kalman Filter (KF) has been used for data fusion from temperature and strain sensors. The paper shows that through the use of KF one can easily compensate the effect of temperature on the observability of the NA. The work applies the methodology on a finite element (FE) model of a glass fiber- epoxy composite as well as validation through actual experiments. Based on the results obtained, it is apparent that the NA tracking using KF allows stable estimation even in changing temperature conditions and as such shows that NA location can indeed be used as a damage sensitive feature.