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In the earth-moving industry manymachines work in typical loading cycles that are repeated periodically. For a statistic examination of the overall load configuration and the dynamic fatigue of these machines, it is necessary to develop an adaptive algorithm for the separation of the individual cycles. This article presents methods for an automatic detection of the cycle borders. Adaptive algorithms are constructed for a reliable separation at different points during the loading cycle. Additionally, each cycle can be divided into different operating phases by extending the algorithms to a tool for the identification of each single phase. To avoid problems during the cycle detection, the data are checked for outliers and sensor faults first. To guarantee a meaningful statistical analysis, the separated cycles have to be tested for incorrect or atypical characteristics. Therefore, statistical classification numbers are calculated and compared for each cycle.