{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:47:42Z","timestamp":1762004862391},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,3,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This work describes an algorithm which is able to determine the working states of a rotating cutting assembly\nautomatically. The approach was validated at a self-propelled forage harvester under different environmental and harvest\nconditions. Data were recorded throughout different field trials near the cutting assembly using two built-in vibration\nsensors. The working states of the cutting assembly were divided into <jats:italic>processing<\/jats:italic>, <jats:italic>neutral<\/jats:italic> and\n<jats:italic>grinding<\/jats:italic>. The analysis was performed using evolutionary optimized Artificial Neural Networks. The generated\nmodels for classification are able to determine the working states robustly for this type of a rotating cutting\nassembly. Case-specific and sensor-specific confusion matrices are presented for performance evaluation. As a conclusion\nvibration data is suitable for automatic and robust classification in this context.<\/jats:p>","DOI":"10.1515\/auto-2016-0082","type":"journal-article","created":{"date-parts":[[2017,3,11]],"date-time":"2017-03-11T10:00:44Z","timestamp":1489226444000},"page":"198-206","source":"Crossref","is-referenced-by-count":3,"title":["Determination of working states of the rotating cutting assembly in forage harvesters by artificial neural networks"],"prefix":"10.1515","volume":"65","author":[{"given":"Christian","family":"Walther","sequence":"first","affiliation":[{"name":"University of Applied Sciences Schmalkalden, Faculty of Electrical Engineering, Blechhammer 4\u20139, D-98574 Schmalkalden Germany"},{"name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Advanced System Technologies, Am Vogelherd 50, D-98693 Ilmenau Germany"}]},{"given":"Andreas","family":"Wenzel","sequence":"additional","affiliation":[{"name":"University of Applied Sciences Schmalkalden, Faculty of Electrical Engineering, Blechhammer 4\u20139, D-98574 Schmalkalden Germany"},{"name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Advanced System Technologies, Am Vogelherd 50, D-98693 Ilmenau Germany"}]},{"given":"Frank","family":"Beneke","sequence":"additional","affiliation":[{"name":"University of Goettingen, Department of Crop Sciences, Section of Agricultural Engineering, Gutenbergstrasse 33, D-37075 Goettingen Germany"}]},{"given":"Oliver","family":"Hensel","sequence":"additional","affiliation":[{"name":"University of Kassel, Agricultural Engineering, Nordbahnhofstrasse 1a, D-37213 Witzenhausen Germany"}]},{"given":"Jochen","family":"Huster","sequence":"additional","affiliation":[{"name":"CLAAS Selbstfahrende Erntemaschinen GmbH, Advanced Engineering Electronics, M\u00fcnsterstr. 33, D-33428 Harsewinkel Germany"}]}],"member":"374","published-online":{"date-parts":[[2017,3,11]]},"container-title":["at - Automatisierungstechnik"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/auto.2017.65.issue-3\/auto-2016-0082\/auto-2016-0082.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0082\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0082\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T16:08:51Z","timestamp":1624291731000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0082\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,11]]},"references-count":0,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2017,3,11]]},"published-print":{"date-parts":[[2017,3,28]]}},"alternative-id":["10.1515\/auto-2016-0082"],"URL":"https:\/\/doi.org\/10.1515\/auto-2016-0082","relation":{},"ISSN":["0178-2312","2196-677X"],"issn-type":[{"value":"0178-2312","type":"print"},{"value":"2196-677X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,3,11]]}}}