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Machine management systems in off-highway machines such as tractors or wheel loaders are designed for efficient operation and reduced fuel consumption in some predefined scenarios for which the machine has been developed. In this paper, we outline how concepts from Organic Computing may be used to realize a self-organizing, reliable, adaptive, and robust machine management system that is capable of adjusting to new situations. We propose an architecture for a machine management system based on the generic Observer/Controller architecture and focus on the structure of the Observer. Furthermore, we study the feasibility of working cycle detection by the Observer and analyze real and synthetic data from an off-highway machine. To extract features by which different working cycles of an off-highway machine can be distinguished, we employ principal component analysis.

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