A significant limitation of non-destructive evaluation (NDE) became apparent in the nineteen-sixties with the advent of fracture mechanics as a major consideration for the prevention of structural failure. Fracture mechanics requires quantitative information that has to be obtained by non-destructive testing procedures. The 1970’s marked the start of research and development to achieve a quantitative capability, which added the Q to NDE. Since that time significant advances have been made in methods of QNDE that are the basis of structural health monitoring (SHM). Very important contributions to diagnostics were also made by the development of measurement models.

Diagnostic techniques provide the input for prognostics. Material-science-level modeling of constitutive properties, supported by experimental results, provides damage growth laws, which in turn provide information on damage evolution and remaining life. Depending on its magnitude, the resulting statement of failure probability may either result in a recommendation for repair or replacement of a structural component, or for an additional cycle in the diagnostics/prognostics loop of the structural health management system.

In this talk, we will devote particular attention to the probabilistic aspects of diagnostics and prognostics. Probabilistic considerations play a dominant role in the four stages of the diagnostics and prognostics of fatigue damage in metals. Considerable attention has been given to the evolution and detection of pre-crack fatigue damage and probabilistic aspects of subsequent macrocrack formation (Stage 1). For stage 2 (macrocrack growth and detection), Paris law for crack growth under cyclic loading conditions can be useful, particularly if it is placed in a probabilistic context. By introducing the probability of detection concept, various probabilities related to the existence, after N cycles, of a crack larger than a critical size, some based on a Bayesian approach, can be determined in Stage 3 for purposes of prognostication.

Experimental ingenuity, improved hardware, analytical simulation techniques, use of statistical methods and improved signal processing techniques have produced significant progress in QNDE. On the other hand, SHM has not yet broken through in a big way. Among the impediments, SHM systems are often not yet affordably maintainable, with near zero false alarm rates. Huge benefits can, however, be achieved if SHM can justify reduced design margins, longer life spans and reduced service interruptions of structural systems.