Development of a Universally Applicable Condition Monitoring System for Predictive Maintenance and Efficiency Evaluation of Low-voltage Motors

被引:0
|
作者
Reuter T. [1 ]
Schmidt J. [1 ]
Grundmann A. [1 ]
机构
[1] Wissenschaftlicher Mitarbeiter am ICM e. V. beschäftigt, Germany
来源
关键词
Characteristic Value Identification; Classifica-tion; Condition Monitoring; Electric Drives; Machine Learning; Maintenance; Vibration Measurement;
D O I
10.1515/zwf-2022-1139
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学科分类号
摘要
Development of a Universally Applicable Condition Monitoring System for Predic-tive Maintenance and Efficiency Evaluation of Low-voltage Motors. The consumption of electric drives in industry and manufacturing accounts for almost two-fifths of all electricity in Germany. Electric motors are thus consid-ered to play a key role in energy savings. Energy savings are particularly high in the power range between 0.75 kW and 40 kW, since this is where most operating hours occur each year. At same time, in addition to energy savings, the maintenance of electric drives also plays a decisive role, as sudden failures can result in high costs due to production downtime or repairs. To meet both criteria, a universally applicable condition monitoring system was developed. Using integrated vibration measurement, it was possible to derive prediction models and trend analyses from different load and damage cases and the characteristic values determined from them. © 2022 Walter de Gruyter GmbH, Berlin/Boston, Germany.
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页码:659 / 666
页数:7
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