Heuristic-based Prognostic and Diagnostic Methods to Enhance Intelligent Power Management for Tactical Electric Power Generator Sets

Period of Performance: 02/29/2012 - 03/01/2014

$371K

Phase 2 SBIR

Recipient Firm

Williams-pyro, Inc.
20 Grenleaf St.
Fort Worth, TX -
Principal Investigator

Abstract

Williams-Pyro has established the feasibility of its Generator Fault Investigation Technology (GenFIT) system architecture for heuristic prognosis of tactical quiet generators (TQGs). The GenFIT architecture will provide real-time, measurement-based health status and fuel use rates of the TQG as a system. Williams-Pyro addressed two tasks to verify our approach for improved diagnostic and prognostic methodologies of diesel engine generators. The first task focused on finding methods for extracting the Discrete Event Set (DES) from sensor data. The DES approach is unique. It works on different types and sizes of diesel engines with little or no modification because it relies on the exact sequence of events that must occur for any diesel engine to run. The DES is extracted from sensor data using discrete wavelet transforms, and is compared to a baseline model of the four cycle diesel engine. The second task involved evaluating traditional sending unit data from instrument panel gauge. This type of evaluation provides additional details which the operator cannot see, even if they were to monitor the gauge continually. Successfully completing these two tasks has addressed any technical uncertainty about our approach to the challenging problem of automating the evaluation of diesel engine generator conditions.