Our recent developments on performance assessment of structrural health monitoring systems have been published in Sensors journal. This work, coordinated by Manuel Rao, is a collaboration between the University of Naples and the University of Siegen.
Abstract:
Radar technology in the microwave and millimeter-wave frequency range are subject of current research for structural health monitoring of composite materials, e.g. damage detection in wind turbine blades. Performance assessment, enabling widespread practical application of this promising and non-contact sensing approach, can be realized via probability of detection (POD) theory which is a statistical method for determining the detectability of damage through response metrics as a function of flaw size. This paper deals with the experimental investigation of a delamination model represented by two parallel glass fiber reinforced polymer plates separated from each other from 0mm to 1mm in steps of 0.01mm. Experimental studies with a frequency modulated continuous wave radar are performed under laboratory conditions in the frequency range from 57GHz to 65GHz. The signal response is represented by two damage indicators (DIs) according to the root mean square deviation and Mahalanobis distance. Since the reflection of electromagnetic waves exhibits a nonlinear behavior, this also implies a nonlinear response in the DI characteristic. The novelties in this work are the successful implementation of a nonlinear regression model combined with optimal threshold decision through receiver operating characteristic curves for a high-resolution POD representation. The POD with 95% confidence bounds indicates the flaw size at which the delamination can be detected reliably. Depending on the radar distance in experimental studies, the binary structural condition (damaged or undamaged) was correctly assessed from 95% to 100%. The minimum detectable size ranges from 0.01mm to 0.08mm.
More information:
Rao, M. ; Memmolo, V. ; Moll, J. & Kraemer, P., Performance Characterization of Radar-based Delamination Assessment in Glass Fiber Reinforced Composites, 2026, Sensors (accepted: May 2026)
