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A. Lorenz, M. Kozek:
"Automatic cycle border detection for a statistic evaluation of the loading process of earth-moving vehicles";
Talk: 2007 SAE Commercial Vehicle Engineering Congress & Exhibition, Rosemont, Illinois, USA; 2007-10-30 - 2007-11-01; in: "SAE Technical Paper Series", SAE International, 400 Commonwealth Drive, Warrendale, PA, USA, 2007-01-4191 (2007).

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 five 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 is checked for outliers
and sensor problems 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. Furthermore,
the cross correlation function of the data with an average
loading cycle is considered. Robustness with
respect to outliers is especially addressed and suitable
procedures are incorporated. The presented algorithms
have been tested on several measured data
sets of different machine-types and -configurations
as well as different drivers. These experimental results
prove that an excellent and reliable performance
can be achieved.