Integrated diagnostic/prognostic tools for small cracks in structures

An integrated system for diagnosis of the 'health' of a structural componen t subjected to high-cycle fatigue (HCF) consists of sets of embedded or emp laced sensors at various locations, extracting information related to the g eneration of material defects, the presence of crack-like discontinuities a nd their progression and changes in system dynamics that may relate to this progression. Conceptually, signals from these sensors are fed into a proce ssing environment that can project deleterious conditions related to the on set of loss of function or propagation of cracks to critical dimensions. Si nce the idea is to monitor the gradual changes of component performance and various local related indices before catastrophic failure to enable the op erator to respond with a maintenance hold, it is essential to couple the di agnostics with prognostic capability; this facilitates a prediction of how much time remains within the window of viable servicing or repair. In the H CF regime, the dominant fraction of total fatigue life may be spent at crac k lengths of the order of 20-500 mum. The detection of longer cracks near t he end of component life is critical since component failure may lead to fa ilure of the overall structure. This necessitates the identification of (a) algorithms for identifying component 'hot spots' where failure is likely t o occur, (b) development of appropriate crack growth laws for cracks of dif ferent length scales, ranging from the order of grain size to the order of component dimensions, including consideration of contacting components (fre tting fatigue) and environmental effects and (c) development of algorithms for identifying the progression of component degradation on the basis of mu ltiple-sensor inputs at different time and length scales, providing feedbac k to support cause for maintenance shutdown. This paper discusses each of t hese issues.