Abstract
The detection of abrupt changes refers to a time instant at which properties suddenly change, but before and after which properties are constant in some sense. CUSUM (Cumulative Sum) is a sequential analysis technique that is used in the detection of abrupt changes. The objective in this study is to apply CUSUM technique in analysing fatigue data for detection of abrupt changes. For the purpose of this study, a collection of nonstationary data that exhibits a random behavior was used. This random data was measured in the unit of microstrain on the lower suspension arm of a car. Experimentally, the data was collected for 60 seconds at a sampling rate of 500 Hz, which gave 30,000 discrete data points. By using CUSUM method, a CUSUM plot was constructed in monitoring the mean changes for fatigue data. Global signal statistical value indicated that the data were non Gaussian distribution in nature. The result of the study indicates that CUSUM method is only applicable for certain type of data with mixed high amplitude in a random background data.
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