Online field performance evaluation system of a grain combine harvester
•An online field performance evaluation system of the combine harvester was constructed in the paper, and this system could collect the field operation data of the harvester in real time.•Based on the Markov model and real-time data in the field, the proposed system realized the field operation perf...
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Veröffentlicht in: | Computers and electronics in agriculture 2022-07, Vol.198, p.107047, Article 107047 |
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Sprache: | eng |
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Zusammenfassung: | •An online field performance evaluation system of the combine harvester was constructed in the paper, and this system could collect the field operation data of the harvester in real time.•Based on the Markov model and real-time data in the field, the proposed system realized the field operation performance dynamic evaluation of the combine harvester.•To avoid the multi-step transfer of the Markov chain and the demanding condition of obtaining a stable probability distribution only under the limited state, the degree of progress is used, which dynamically evaluates the changes in the field performance of the grain combine harvester.
Considering the lack of real-time evaluation systems for the field operation performance of combine harvesters, as well as the urgent demand of users and enterprises for combine harvester field operation performance data, this paper constructs an online field operation performance evaluation system for a combine harvester. The proposed field operation performance evaluation system for a combine harvester can obtain information on the field operation parameters of a combine harvester in real-time. This system determines the field operation performance evaluation index of the test model and establishes a field operation performance evaluation system for a combine harvester based on the Markov evaluation model. The system divides the evaluation index levels of a combine harvester, determines the weight coefficient of the index using the entropy method, and uses the degree of progress of the probability transition matrix to evaluate the combine harvester’s field operation performance. The results show that compared with the manual detection method, the average absolute errors of the crushing rate, impurities rate, and loss rate of the proposed method are 0.08%, 0.14%, and 0.10%, respectively. On the validation dataset, the changing trends of the crushing rate, impurities rate, and loss rate of the proposed system are consistent with those of the manual detection method. The proposed field operation performance evaluation system of a combine harvester has a high sensitivity to the change in each index. When there is a large span change of an index, the system can respond in real time and accurately reflect evaluation results. The proposed field operation performance evaluation system evaluates the real-time operating performance of a combine harvester according to the degree of progress. The evaluation results obtained by the propose |
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ISSN: | 0168-1699 |
DOI: | 10.1016/j.compag.2022.107047 |