<title>Intelligent approach to prognostic enhancements of diagnostic systems</title>

Abstract

This paper introduces a novel methodology to prognostics based on a dynamic wavelet neural network construct and notions from the virtual sensor area. This research has been motivated and supported by the U.S. Navy's active interest in integrating advanced diagnostic and prognostic algorithms in existing Naval digital control and monitoring systems. A rudimentary diagnostic platform is assumed to be available providing timely information about incipient or impending failure conditions. We focus on the development of a prognostic algorithm capable of predicting accurately and reliably the remaining useful lifetime of a failing machine or component. The prognostic module consists of a virtual sensor and a dynamic wavelet neural network as the predictor. The virtual sensor employs process data to map real measurements into difficult to monitor fault quantities. The prognosticator uses a dynamic wavelet neural network as a nonlinear predictor. Means to manage uncertainty and performance metrics are suggested for comparison purposes. An interface to an available shipboard Integrated Condition Assessment System is described and applications to shipboard equipment are discussed. Typical results from pump failures are presented to illustrate the effectiveness of the methodology.

Early Detection of System Failure in Complex Chemical or Non-Electrical Based Systems Using a Nerual Network

“…Although much relevant recent work has been reported in the literature [1][2][3][4][5][6][7], no mention is found in recent literature of techniques providing intelligent prognosis for a large class of systems based on chemical or other non-electrical processes where the interactions of the various operating parameters are subtle, complex, and correlated in unknown or difficult to elicit ways. Examples of such systems are semiconductor manufacturing appliances, rocket engines, and chemical oxygen-iodine lasers (COILs), which depend on flow, pressures and temperatures for successful operation.…”