Noninvasive Approach to Health Management of Aircraft Power Systems Using Torque Ripple

Posted by on Oct 22, 2009 in Aircraft, Distributed Heterogeneous Optimization, Eric A. Walters, Prognostics and Health Management, Publications, Tommy Baudendistel | 0 comments

T. Baudendistel, PC Krause and Associates, inc;  S. Pekarek, Purdue University;  Steve Peecher, GE Aerospace; Sean Field, Nathan Kumbar, Naval Air Systems Command; E. A. Walters, PC Krause and Associates, inc.

In this presentation, a recently developed hardware and software tool for the health management of electric generators, motors, power electronic components, and electric power systems will be presented. This tool enables higher fidelity health management prognostics.

The hardware component of this tool is a vibration sensor that is low cost, durable, and relatively straightforward to implement in a drive system or power electronic module. The sensor has been used to detect torque-ripple-induced vibration created by electric machines. It provides a convenient means to detect faults of both electrical and mechanical components of electric drive systems and also facilitates feedback-based control to mitigate the vibration source through control of the excitation to a machine.

The first software tool analyzes the raw data acquired by the vibration sensor.  This software utilizes both signal processing and statistical algorithms to reduce the acquired data into a user friendly pareto chart format.  This format allows vehicle level PHM systems to cost-effectively analyze and store pertinent data relating to the health of the power system.  This format also allows ground maintenance teams to quickly assess the health changes between flights without adding to “information overload”.

The second software tool is a method of Distributed Heterogeneous Simulation (DHS) that provides a means to simulate the healthy and faulted behavior of large-scale systems at a speed and level of detail heretofore unachievable. Specifically, DHS enables the synchronized interconnection of any number of dynamic subsystem simulations, developed using any combination of a variety of programs/languages, and implemented on a single computer/workstation/supercomputer, a local area network (Intranet), a distributed, and any combination thereof. Theoretically, using an -computer network, DHS can approach an  gain in computational speed over single computer, single numerical algorithm implementation.

It is shown that through coupling of these tools, a comprehensive prognostics and health management system (PHM) for aircraft generators and associated electrical systems can be developed. Specifically, using DHS, component and system-level simulations of aircraft generator systems under nominal and failure modes can be performed efficiently. Using the simulation results obtained, the vibration sensor, unique monitoring concepts and advanced signal conditioning are coupled to establish an approach that can effectively detect component degradation and predict time-to-failure, and to develop feedback-based strategies for operation of generator electrical systems under component degradation or failure. Hence, maintaining the war fighting capabilities by extending the life of the aircraft electrical systems.

Contact information: baudendistel@pcka.com