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Titlebook: Condition Monitoring and Control for Intelligent Manufacturing; Lihui Wang (Senior Research Officer),Robert X. Gao Book 2006 Springer-Verl

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發(fā)表于 2025-3-21 17:58:26 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Condition Monitoring and Control for Intelligent Manufacturing
編輯Lihui Wang (Senior Research Officer),Robert X. Gao
視頻videohttp://file.papertrans.cn/236/235200/235200.mp4
概述Only book to cover state of the art research into intelligent condition monitoring, an important area of manufacturing engineering research
叢書(shū)名稱(chēng)Springer Series in Advanced Manufacturing
圖書(shū)封面Titlebook: Condition Monitoring and Control for Intelligent Manufacturing;  Lihui Wang (Senior Research Officer),Robert X. Gao Book 2006 Springer-Verl
描述.Manufacturing systems and processes are becoming more complex, so more rational decision-making in process control is a necessity. Better information gathering and analysis techniques are needed and condition ?monitoring is seen as a framework that will enable these improvements...Condition Monitoring and Control for Intelligent Manufacturing. brings together the world’s authorities on condition monitoring to provide a broad treatment of the subject accessible to researchers and practitioners in manufacturing industry...The book presents a review of the key areas of research in machine condition monitoring and control, before focusing on an in-depth treatment of each important technique, from multi-domain signal processing for defect diagnosis to web-based information delivery for real-time control. ..Researchers in manufacturing and control engineering, as well as practising engineers in industries from automotive to packaging manufacturing will find this book valuable..
出版日期Book 2006
關(guān)鍵詞Adaptive control; Automotive Engineering; Intelligent manufacturing; Monitoring; Real-time system; grindi
版次1
doihttps://doi.org/10.1007/1-84628-269-1
isbn_softcover978-1-84996-568-2
isbn_ebook978-1-84628-269-0Series ISSN 1860-5168 Series E-ISSN 2196-1735
issn_series 1860-5168
copyrightSpringer-Verlag London 2006
The information of publication is updating

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https://doi.org/10.1007/978-94-010-1257-7amples are explained. Signal processing techniques to gain more benefits of vibration monitoring are covered. Wear debris monitoring methods include magnetic plugs, ferrography, particle counter and spectrographic oil analysis.
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Inaugural Ceremony 2 August 1988,the chapter. Section 8.3 presents an effective online monitoring method based on support vector regression (SVR). Section 8.4 gives a new diagnosis method based on infarred thermal imaging. Finally, Section 8.5 contains conclusions.
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https://doi.org/10.1007/978-94-010-2208-8tate detection of a gearbox, which is independent of variable load conditions, as well as remarkable stability, early alarm for incipient fault and significant presence of fault effects. The proposed three gear state indicators can be directly employed by an online maintenance program as reliable qu
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W. J. Eckert,G. N. Duboshin,P. J. Message for exchanging complex sensor information between condition-based maintenance (CBM) systems. With the capability and wide availability of the Web, any sensor connected to a wired or wireless network can be accessed anywhere via the network or Internet. This will greatly enhance the effectiveness an
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Condition Monitoring and Control for Intelligent Manufacturing
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Monitoring and Diagnosis of Sheet Metal Stamping Processes,the chapter. Section 8.3 presents an effective online monitoring method based on support vector regression (SVR). Section 8.4 gives a new diagnosis method based on infarred thermal imaging. Finally, Section 8.5 contains conclusions.
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