A Noninvasive Sensor/Control Suite for Health Monitoring and Extended Life of Aircraft Generation Systems

Posted by on Oct 24, 2009 in Aircraft, Contracts, Eric A. Walters, Generator, Power Systems, Prognostics and Health Management, SBIR Phase I, SBIR Phase II | 0 comments

Type of Awards: STTR Phase I and Phase II Contract Numbers: N00014-06-M-0281and N68335-08-C-0108 Agency: U.S. Naval Air Systems Command Status: On Going Periods: 08/01/06 to 8/30/07 and 2/25/08 to 2/25/10 Principal Investigator: E. A. Walters Abstract: Catastrophic failures in aircraft electrical power systems can compromise the readiness, safety, and capabilities of the war-fighter.  In this effort, a multi-physics suite of tools will be developed based upon the successful Phase I research to provide a comprehensive prognostics and health management system (PHM) for aircraft generators and associated electrical systems. The PHM will be based upon a set of recently developed tools that include a novel sensor to measure torque-ripple-induced vibration created by electric machinery, a thermal condition monitor that can predict the temperatures within an electric machine under healthy and damaged operation, and numerical simulation tools that enable rapid development and solution of component and system-level models of electric machinery and power electronic systems operated in fault conditions.  Validation of the PHM concepts and the computer simulations used will be performed with hardware using an F-18 generator as the test...

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Tools for Health Management of Aircraft Power Systems

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

T. Baudendistel, PC Krause and Associates, Inc; Steve Pekarek, Mario Rotea, Purdue University;E. A. Walters, Steve Peecher, Hao Huang, Smiths Aerospace; Sean A. Field, Nathan E. Kumbar, H. Huang, Naval Air Systems Command In this presentation, a pair of recently developed hardware and software tools for the prognostics and health-monitoring of electric generators, motors, power electronic components, and electric power systems will be presented. The first tool is a vibration sensor that is low cost, durable.  This 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 second tool is a thermal-observer based health monitor.  This tool effectively predicts the thermal behavior of stator, rotor, and winding structures based upon input from a minimal number of thermocouples and stator current sensors. It is shown that through coupling of these two tools, a comprehensive prognostic and health management system (PHM) for aircraft generators and associated electrical systems can be developed. Using this multi-physics approach it is possible to effectively detect component degradation and aid in prediction of time-to-failure as well as provide information to feedback-based strategies for operation of generator electrical systems under component degradation or failure.  This will improve the warfighting capabilities by extending the life of the generator electrical system. 2nd Annual Propulsion-Safety and Affordable Readiness Conference, March 2007, San Diego, CA. Contact information:...

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Advanced Tools for Aircraft Power and Propulsion Simulation and Analysis

Posted by on Oct 22, 2009 in Aircraft, Eric A. Walters, Generator, Jason R. Wells, Prognostics and Health Management, Publications, Tommy Baudendistel | 0 comments

T. Baudendistel, M. Corbett, E. A. Walters, K. Miller, J. Williams, J. Wells, S. Pekarek, M. Rotea, S. Field, , S. Peecher, N. Kumbar, M. Wolff, J. Dalton, P. Lamm It will be shown that through coupling a set of multi-physics tools in a sensor suite, 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, using Hardware-In-The-Loop (HIL), 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. In addition, as aircraft power demands continue to increase with the increase in electrical subsystems. These subsystems directly affect the behavior of the power and propulsion systems and can no longer be neglected in system analyses. The performance of the whole aircraft must also be considered with the combined interactions between the power and propulsion systems. The larger loading demands placed on the power and propulsion subsystems result in thrust, speed, and altitude transients that affect the whole aircraft. This results in different operating parameters for the engine. The complex models designed to integrate new capabilities have a high computational cost. This paper investigates the possibility of using a hardware-in-the-loop (HIL) analysis with real time integration of the aircraft/propulsion system. Using this method, a significant reduction in computational runtime is observed, and the airframe/turbine engine model is usable in a HIL environment. This also allows for a more complete analysis of the interactions between engine loading and aircraft performance by including some real hardware components. The dynamic interactions between aircraft subsystems highlight the need for system-level modeling using a combination of high-fidelity computer models and hardware in a real-time environment.   Hence, maintaining the war fighting capabilities by extending the life of the aircraft electrical systems. IAPG Mechanical Workgroup, May 2007, Alexandria, VA. Contact information:...

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Tools for Prognostics and Health-Monitoring of Aircraft Power Systems

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

T. Baudendistel, PC Krause and Associates, Inc; Steve Pekarek, Mario Rotea, Purdue University; E. A. Walters, PC Krause and Associates, Inc; Steve Peecher, Smiths Aerospace; Sean A. Field, Nathan E. Kumbar, Naval Air Systems Command In this presentation, a cadre of recently developed hardware and software tools for the prognostics and health-monitoring of electric generators, motors, power electronic components, and electric power systems will be presented. One of the tools is a vibration sensor that is low cost, durable, and relatively straightforward to implement in a drive system or power electronic module. This 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. In addition to providing vibration feedback, it has also been shown to be effective as a back-up position sensor. Specifically, in applications where fault tolerance is critical, the sensor has been used to determine the position of the rotor of the machine when in-line or Hall-effect sensors fail. A second tool is a thermal-based health monitor for electric machines that effectively predicts the thermal behavior of stator, rotor, and winding structures based upon input from a minimal number of thermocouples and stator current sensors. This observer has been tested on a 3.7 kW generator and is presently being used to evaluate the short- and long-term effects of pulsed loading of electric machines. A third 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 M-computer network, DHS can approach an 3M gain in computational speed over single computer, single numerical algorithm implementation. It is shown that through coupling of these three tools, a comprehensive prognostic 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 and thermal-condition monitor concepts are coupled to establish a multi-physics 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 warfighting capabilities by extending the life of the generator electrical system. 2007 ISHM Conference, August 2007. Contact information:...

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An Automated State Model Generation Algorithm for Simulation/Analysis of Power Systems with Power Electronic Components

Posted by on Oct 21, 2009 in Aircraft, Automated State Model Generator, Electronics, Eric A. Walters, Generator, Oleg Wasynczuk, Power Systems, Publications | 0 comments

S. D. Pekarek, E. A. Walters, T. L. Skvarenina, O. Wasynczuk, PC Krause and Associates, Inc. In this paper, a recently developed algorithmic method of deriving the state equations of power systems containing power electronic components is described. Therein the system is described by the pertinent branch parameters and the circuit topology; however, unlike circuit-based algorithms, the difference equations are not implemented at the branch level. Instead, the composite system state equations are established. A demonstration of the computer implementation of this algorithm to model a variable-speed, constant-frequency aircraft generation system is described. Because of the large number of states and complexity of the system, particular attention is placed on the development of a model structure which provides optimal simulation efficiency. SAE Transactions Journal of Aerospace, sec. 1, vol. 107, Month 1998, pp....

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