Self-Diagnosis of Damage Criticality of Fibrous Composites Based on Multifunctional Characteristics

Impact Technologies has teamed with the University of Dayton Research Institute (UDRI) and Professor William Curtin from Brown University to develop an autonomous damage detection, classification, and prognostic system for carbon-fiber-reinforced polymer(CFRP) structures. The proposed approach fuses data and information from a set of optimally placed electrodes and associated electro-mechanical models that recognize the quantitative relationships between specific CFRP damage types, sizes and locationproduced by the electrical resistivity signatures.The proposed workscope will be achieved through a series of well-designed tests that introduce known damage (in terms of type, size and location) in the CFRP laminates that will then be correlated with the measured electrode signatures. The electrode gridpattern will be optimally designed for best observation and reliability to provide isolation for the various damage types and severities. A full investigation on the role that the electrode lead and sensing array geometries have on the measured electricalresponse to known internal damage will also be performed. Based on the implementation of the chosen design grid, electrode measurements will be processed with a combination of damage detection and isolation techniques, including neural networks andstochastic classifiers, to detect and isolate all damage types. Additionally, a coupled micro-electromechanical model will guide the geometrical arrangement and spatial separation used to attain the appropriate damage mapping. At the end of Phase I, ourteam will demonstrate a verified, electro-mechanical model and autonomous damage detection/isolation software that directly relates changes in electrical resistance to the mechanical and damage state of a CFRP laminate as a function of the laminatestructure, orientation, loading, interfacial bonding between laminates, and internal anisotropic resistance. Data generated from the experimental program will be used as inputs to the theoretical models for analysis and validation. With the successful developments and implementation of this proposed technology, it is strongly anticipated that the prototype CFPR fault detection and classification system will be developed for specific USAF aerostructures. In addition, based on theadaptable nature of the CFPR fault detection/classification architecture, the developed modules can be adapted for use on other composite structures used in variety of commercial or DoD applications. Examples of key industrial customers that could benefitthrough use of the developed CFPR technologies include; commercial airlines, OEM airframers such as Boeing, Lockheed Martin and Northrop Grumman, as well as various robotic and unmanned vehicle applications just to name a few.