Experimental characterization of piezoelectric transducers for automotive composite structural health monitoring 2020-01-0609
Composite materials are a natural choice for engineering applications where mechanical performance and lightweight are required, as in state-of-the-art components in the automotive field. Nevertheless, close attention should be paid to defects present in this kind of structure. Several innovative ways to investigate the failure mode of structures in composite material has been developed in time.
This paper presents the experimental characterization of piezoelectric transducers as a Structural Health Monitoring System: a continuous acquisition system of data in order to real time detect the presence of faults inside automotive components under analysis.
Several tests have been executed over a PI-DuraAct piezoceramic patch coupled to a host structure, characterizing the acquisition and transmission of a signal. Contribution about bonding quality, shape wave distortion of imposed signal and best frequency for transmission have been evaluated. Furthermore, the damage was created in a controlled drop-dart tower and its intensity analyzed with a C-scan non-destructive test. An algorithm has been then implemented in MATLAB to obtain detection of defects and their intensity, by processing the data acquired.
Two case studies were designed to build up a structural health monitoring system: The first consists of a beam in composite material with two piezoelectric transducers glued over its surface, where signals transmitted by one piezo actuator and received by one piezo sensor are used to detect presence of defect with the guided wave method; The second is composed of six transducers bonded over a plate, used both as actuators and receivers, aiming not only to detect the presence of a defect, but also estimate its position in the surface.
The research importance of this advanced technology and the positive results obtained in the case study constitute the starting point for future application of piezoelectric based structural health monitoring systems over real industrial automotive components.
Massimiliana Carello, Alessandro Ferraris, Andrea Giancarlo Airale, Alessandro Messana, Lorenzo Sisca, Henrique de Carvalho Pinheiro, Simone Reitano