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Examining methods in data filtering, trend shift detection, and fault isolation, this book provides a variety of new research tools for use in the condition monitoring of jet engines. Each method is demonstrated through numerical simulations that can be easily done using worksheets such as Excel® or through MATLAB®. The signal processing algorithms presented will be useful to engineers, scientists, and researchers working on fault diagnosis of gas turbine engines. The algorithms can also be used for condition and health monitoring problems in general.
Dr. Ranjan Ganguli is a professor in the Aerospace Engineering Department of the Indian Institute of Science (IISc), Bangalore. He received his MS and Ph.D. degrees from the Department of Aerospace Engineering at the University of Maryland, College Park, and his B.Tech. degree in aerospace engineering from the Indian Institute of Technology. He has worked at Pratt & Whitney on engine gas path diagnostics and, during his academic career at IISc, has conducted sponsored research projects for companies such as Boeing, Pratt & Whitney, Honeywell, and HAL. He has authored or coauthored three books, published more than 140 papers in refereed journals, and presented more than 80 papers at conferences. He is a fellow of the American Society of Mechanical Engineers, the Royal Aeronautical Society, and the Indian National Academy of Engineering, and an associate fellow of the American Institute of Aeronautics and Astronautics. He received the Alexander von Humboldt Fellowship and the Fulbright Fellowship in 2007 and 2011, respectively. He is an associate editor of the AIAA Journal and the Journal of the American Helicopter Society.
Introduction. Idempotent Median Filters. Median-Rational Hybrid Filters. FIR-Median Hybrid Filters. Transient Data and the Myriad Filter. Trend Shift Detection. Optimally Weighted Recursive Median Filters. Kalman Filter. Neural Network Architecture. Fuzzy Logic System. Soft Computing Approach. Vibration-Based Diagnostics. References. Index.
