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M. Zauner, F. Altenberger, H. Knapp, M. Kozek:
"Phase independent finding and classification of wheel-loader work-cycles";
Automation in Construction, 109 (2020), 109.

Wheel-loaders are versatile multi-purposemachines used in construction and mining. Recent studies have shown that
wheel-loaders have a significant optimization potential as different operators can account for up to 300% difference
in productivity and 150% in fuel efficiency. A better understanding of the different work tasks a wheel-loader performs
on-site allows for the implementation of various optimization strategies. In this paper a method for finding
and classifying wheel-loader work-cycles is presented. The proposed method uses a dynamic time warping path to
align the sensor data to predefined class templates. With this alignment method a phase independent detection and
classification of work-cycles can be performed in a robust manner. The proposed method also allows for a short-term
prediction of the future signal trajectories, which could be used for an online optimization task of the wheel-loader.
The performance of the method was tested with data from field trials and validated with video-recordings.

Wheel-loader,Work-cycle, Classification, Dynamic time warping (DTW), Prediction, Construction

http://dx.doi.org/10.1016/j.autcon.2019.102962