Identification of sensor faults on combine harvesters using intelligent methods
| Authors: | Craessaerts Geert, KULEUVEN, Belgium
Coen Tom, KULEUVEN, Belgium
De Baerdemaeker Josse, KULEUVEN, Belgium |
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| Topic: | 8.1 Control in Agriculture |
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| Session: | Mechatronics in Agriculture |
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| Keywords: | fault identification, self organizing system, feedforward networks, backpropagation algorithms, agriculture |
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Abstract
Considering the automation and control of agricultural machinery, condition monitoring of machines is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. In this paper, the general applicability of intelligent methods, like self-organizing maps and multilayer feedforward networks with backpropagation, for the identification of sensor failure on combine harvesters will be illustrated. Both neural network types showed comparable results in order to classify normal and faulty sensor conditions.
