Caterpillar, Inc. and Frontier Technology, Inc. (FTI) are investigating prognostic health monitoring technologies for application to Caterpillar equipment. In particular, robust detection of mechanical damage in a wheel loader has been demonstrated via processing of high-speed, three-axis accelerometer data. Data collected with and without the damaged parts show distinctive signatures that are quantitatively separable. FTI's Pattern Recognition of Health (PRoH™) technology drives the signature generation and abnormality detection process through the use of data-driven techniques that estimate deviation from normal behavior.
Detection of mobile machine damage using accelerometer data and prognostic health monitoring techniques
2009-03-01
524005 byte
Conference paper
Electronic Resource
English
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