KEYWORDS: Diagnostics, Reliability, Sensors, Model-based design, Detection and tracking algorithms, Information fusion, Filtering (signal processing), Wavelets, Signal detection, Systems modeling
Axial flow compressors are subjected to demands for ever-increasing levels of pressure ratio at a compression efficiency that augments the overall cycle efficiency. However, unstable flow may develop in the compressor, which can lead to a stall or surge and subsequently to gas turbine failure resulting in significant downtime and cost to repair. To protect against these potential aerodynamic instabilities, compressors are typically operated with a stall margin. This means operating the compressor at less than peak pressure rise which results in a reduction in operating efficiency and performance. Therefore, it is desirable to have a reliable method to determine the state of a compressor by detecting the onset of a damaging event prior to its occurrence. In this paper, we propose a health monitoring scheme that gathers and combines the results of different diagnostic tools to maximize the advantages of each one while at the same time minimizing their disadvantages. This fusion scheme produces results that are better than the best result by any one tool used. In part this is achieved because redundant information is available that when combined correctly improves the estimate of the better tool and compensates for the shortcomings of the less capable tool. We discuss the usage of diagnostic information fusion for a compressor event coupled with proactive control techniques to support improved compressor performance while at the same time avoid the increased damage risk due to stall margin reduction. Discretized time to failure windows provide event prediction in a prognostic sense.
This paper summarizes the development, structure, verification, and applications of the Multi-Target Acquisition System (MTAS) Fire Control (FC) simulation. Development of the simulation began in 1982 as part of the Center for Night Vision and Electro-Optics (CNVEO) "Search and Target Acquisition Radar for Target Location and Engagement" (STARTLE) Program. Originally, a milli-meter wave radar sensor was employed to locate and tract multiple targets. Since then, the simulation has been extended to include a FLIR/ electro-optical sensor, a manual tracking system, and more sophisticated FC algorithms applicable to multiple targets. The purpose of this paper is to describe the beginnings of a generic, multi-target fire control structure that is applicable to armored vehicles, and to illustrate the key error contributors of accurate target location and subsequent motion prediction.
Descriptions of the key FC algorithms are provided. Sample results for stationary firer/maneuvering multiple targets for different tracking systems are presented. Also, the timeline characteristics of addressing three targets in succession is presented to illustrate the multi-target analysis capability of the simulation. Finally, applications to current and future Army programs are discussed.
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