Optimal partitioning of ultrasonic data for fatigue damage detection?
Dheeraj Sharan Singh, Soumik Sarkar, Shalabh Gupta, Asok Kumar Ray · 2011
This paper presents an analytical tool for online fatigue damage detection in polycrystalline alloys that are commonly used in mechanical structures. The underlying theory is built upon symbolic dynamic filtering (SDF) that optimally partitions time series data for feature extraction and pattern classification. The proposed method has been experimentally validated on a fatigue test apparatus that is equipped with ultrasonics sensors and a traveling optical microscope for fatigue damage detection.