Structural Health Monitoring (SHM) of Polymer-Matrix Composites (PMC) with the insertion of piezoelectric transducers and Data Fusion approach
Topic(s) : Multifunctional and smart composites
Co-authors :
Loan DOLBACHIAN (FRANCE), Walid HARIZI (FRANCE), Zoheir ABOURA (FRANCE)Abstract :
Nowadays, Polymer-Matrix Composite (PMC) materials are extensively employed in various domains such as aeronautics, automotive, wind power, and sports. Their increasing utilization is attributable to their notable combination of high mechanical properties and reduced weight, progressively replacing more traditional materials like metals. Hence, understanding the damage mechanisms of these PMCs and effectively detecting, locating, identifying, and quantifying such damage has become a highly sought-after research area, known as Structural Health Monitoring (SHM). In the context of SHM, there is a significant quest for materials capable of autonomously carrying information about their health status and providing automatic assessments of their service continuity. These materials are known as smart materials and PMCs emerge as promising candidates for smart transformation, achievable through the incorporation of optical fibers, piezoelectric transducers, and other advanced technologies.
In this work, an experimental methodology developed in the work of Tuloup [1] has been used to efficiently integrate a piezoelectric transducers network (PZT, PVDF and P(VDF-TrFE)/CP) within PMC, giving smart capabilities to the material. This smart PMC allows us to use several Non-Destructive Testing (NDT) techniques to obtain information about damage occurrence and its propagation within the material: Acoustic Emission (AE), Electrical Capacitance variation, UltraSonic testing (US) and Vibration analysis. Four-point bending self-heating tests were performed on these smart PMC. Conducting such tests permits us to gradually introduce damage within the material while following it by testing the NDT methods. To effectively assess its damages and compare the results with the internal NDT techniques, the smart PMC was also inspected by external techniques such as external AE sensors, laser, thermocouples, strain gauges and C-scan. Through the definition of original Damage Indicators (DI), the internal NDT techniques show promising potential for detecting damage occurrence and propagation within the material. In addition, according to the multi-physics of the obtained information (electrical, ultrasonic, acoustic), it is necessary to develop an effective tool to combine the results. To do so, a data fusion approach of the different NDT results has to be developed and will represent the future step of this work, in order to make a complete SHM diagnostic to evaluate the structure integrity and the service life continuity.
In this work, an experimental methodology developed in the work of Tuloup [1] has been used to efficiently integrate a piezoelectric transducers network (PZT, PVDF and P(VDF-TrFE)/CP) within PMC, giving smart capabilities to the material. This smart PMC allows us to use several Non-Destructive Testing (NDT) techniques to obtain information about damage occurrence and its propagation within the material: Acoustic Emission (AE), Electrical Capacitance variation, UltraSonic testing (US) and Vibration analysis. Four-point bending self-heating tests were performed on these smart PMC. Conducting such tests permits us to gradually introduce damage within the material while following it by testing the NDT methods. To effectively assess its damages and compare the results with the internal NDT techniques, the smart PMC was also inspected by external techniques such as external AE sensors, laser, thermocouples, strain gauges and C-scan. Through the definition of original Damage Indicators (DI), the internal NDT techniques show promising potential for detecting damage occurrence and propagation within the material. In addition, according to the multi-physics of the obtained information (electrical, ultrasonic, acoustic), it is necessary to develop an effective tool to combine the results. To do so, a data fusion approach of the different NDT results has to be developed and will represent the future step of this work, in order to make a complete SHM diagnostic to evaluate the structure integrity and the service life continuity.