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Abrupt changes are changes that occur at a time instant at which properties suddenly change, but before and after which properties are constant in some sense. The detection of abrupt changes refers to the determination whether, such a change occurred in the characteristics of the considered subject. Running Damage Extraction (RDE) method is a new technique that was developed based on the fatigue damage calculation in detecting the abrupt changes. The objective of this study was to observe the capability of RDE method in analyzing 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 sec at a sampling rate of 500 Hz, which gave 30,000 discrete data points. By using RDE algorithm, a running damage plot was constructed in monitoring the damage 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 RDE technique is applicable in detecting the abrupt changes that exist in fatigue time series data by isolating the high and low amplitude event into different segmentation.