Electrical Modification and Experimental Study of Combine Harvester Reaping Unit

Wang, Pengfei; Tian, Muhao; Hai-li, Wang; Jiang, Wenjun; Cao, Qixin

doi:10.1088/1757-899x/790/1/012168

Cited by 3 publications

References 9 publications

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Experimental Study on Electric Harvesting of Combine Harvester

Yang

Wang

Sun

et al. 2022

J. Phys.: Conf. Ser.

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The electrification and intelligent transformation of harvester to make it have independent operation ability is an important embodiment of the development trend of agricultural automation and intelligence. Based on a full feed combine provided by relative company, this paper makes an electric transformation for its reaping and threshing part, including mechanical design, electric circuit construction, brushless DC(Direct Current) motor installation and test. Based on the finite automatic state mechanism, the control system of the electric operation part is built. Its sequential start and stop functions, reel speed following function and blockage detection and discharge function are tested in no-load experiment and farmland harvesting experiment. Through the continuous wheat harvesting test for 30 minutes, the power characteristics when harvesting wheat are measured, and the stability of its work is verified.

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Experimental Study on Electric Harvesting of Combine Harvester

Yang

Wang

Sun

et al. 2022

J. Phys.: Conf. Ser.

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Knowledge Modeling in Troubleshooting

Dimitrov

Borisova

2021

Engineering Technologies and Systems

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Introduction. The article describes the approach to solving the problem of complex technical system troubleshooting based on expert knowledge modeling. Intelligent information systems are widely used to solve the problems of diagnostics of multilevel systems including combine harvesters. The formal description of the subject domain knowledge is the framework for building the knowledge base of these systems. The sequence of creating an expert system knowledge base in accordance with production rules is considered. Materials and Methods. The approach is founded on the fault function table. As the object of diagnostics, one of the subsystems of the combine harvester electric equipment “opening the hopper roof flaps” is considered. The basis for constructing a sequence of elementary checks is a system of logical equations describing both the serviceable and possible faulty states of the subsystem. Results. A structural logic model is developed. As a result of analyzing the fault function table, the sets of elementary checks are determined. Four criteria have been used to analyze the weight of these checks. The authors have determined optimal sequence of checks and have developed a decision tree, which allows finding the cause of the malfunction and is the basis for creating the knowledge base of an intelligent information system. A fragment of the knowledge base is given. Discussion and Conclusion. The proposed approach of expert knowledge modelling increases the efficiency of the unit for troubleshooting of the intelligent decision support system. It makes possible to structure the base of expertise and establishing the optimal sequence of elementary checks. This allows determining the optimal sequence of application of the knowledge base production rule that makes it possible to reduce the time of restoring the serviceability of combines.

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Simulation and Experimental Research on Speed Control of Electric Threshing Drum in Combine Harvester Based on Fonssmo-Mpc Control Strategy

Zhu,

xiaoyu,

et al. 2024

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Electrical Modification and Experimental Study of Combine Harvester Reaping Unit

Cited by 3 publications

References 9 publications

Experimental Study on Electric Harvesting of Combine Harvester

Experimental Study on Electric Harvesting of Combine Harvester

Knowledge Modeling in Troubleshooting

Simulation and Experimental Research on Speed Control of Electric Threshing Drum in Combine Harvester Based on Fonssmo-Mpc Control Strategy

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