Abstract
The paper addresses the issues of diagnosis and prognosis of fatigue failure in mechanical systems using symbolic time series analysis (STSA) of ultrasonic sensor data. Specifically, the paper presents a statistical analysis procedure for online estimation of remaining fatigue life in polycrystalline alloys using STSA-based information from an ensemble of fatigue experiments. This real-time information is useful for monitoring the evolving fatigue damage and life extending control of mechanical structures for prevention of widespread failures. The concept is experimentally validated on 7075-T6 aluminum alloy specimens on a special-purpose fatigue test apparatus that is equipped with ultrasonic flaw detectors and an optical travelling microscope.
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