Recent Development in Structural Damage Diagnosis and Prognosis

Xiaomo      Jiang

doi:10.2174/187221210791233434

Abstract

Prognostics and health management (PHM) integrates diagnostic and prognostic technologies, provides the ability to assess the current health status of a structural system, predict its future health status for a given time period, and predict its time-to-failure for cost-effective maintenance schedule. It deals with system fault and anomaly conditions by automatic detection, classification, and prediction of critical component failures. The development of an effective PHM system for a structural system relies on both the sensing technology and the associated diagnostic and prognostic algorithms. Many sensor technologies such as strain gages, thermocouples, and accelerometers are available for use in PHM. In the meantime, a broad variety of techniques are available for damage diagnosis and prognosis of engineering structures, including but not limited to physical, statistical, intelligent, heuristic, or hybrid methods. This paper provides a state-of-the-art review on the recent development in damage diagnostics and prognostics methods applied in civil, mechanical and energy structures over the past decade. In addition, this paper introduces the basic concepts of various maintenance philosophies including corrective, preventive, and predictive maintenance. Predictive maintenance approaches such as condition based maintenance (CBM) combine the best features of corrective and preventive maintenance while avoiding the disadvantages of both. Currently it has become a popular maintenance philosophy for most high-value engineering structural systems such as airplane and gas turbine. In view of the number of recent patent applications it is reasonable to speculate that the combination of CBM and PHM will ultimately not only become the core maintenance philosophy for high-value engineering structures, but also foster further groundbreaking development and commercialization of PHM in a broad range of engineering fields.

Keywords: CBM, damage diagnosis, data-driven method, gas turbine, intelligent method, model-based method, PHM, predictive maintenance, probabilistic method, prognostics