Determination of working states of the rotating cutting assembly in forage harvesters by artificial neural networks
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AbstractThis work describes an algorithm which is able to determine the working states of a rotating cutting assembly automatically. The approach was validated at a self-propelled forage harvester under different environmental and harvest conditions. Data were recorded throughout different field trials near the cutting assembly using two built-in vibration sensors. The working states of the cutting assembly were divided into
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2021 ◽
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