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Titlebook: Metal Magnetic Memory Technique and Its Applications in Remanufacturing; Haihong Huang,Zhengchun Qian,Zhifeng Liu Book 2021 Science Press

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發(fā)表于 2025-3-21 16:29:51 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Metal Magnetic Memory Technique and Its Applications in Remanufacturing
編輯Haihong Huang,Zhengchun Qian,Zhifeng Liu
視頻videohttp://file.papertrans.cn/632/631433/631433.mp4
概述Offers real engineering cases that apply the metal magnetic memory technique in remanufacturing.Includes over 200 figures and tables to help readers better understand the content.Covers several interd
圖書(shū)封面Titlebook: Metal Magnetic Memory Technique and Its Applications in Remanufacturing;  Haihong Huang,Zhengchun Qian,Zhifeng Liu Book 2021 Science Press
描述.This book introduces the metal magnetic memory (MMM) technique, one of the nondestructive testing methods, and its applications in remanufacturing engineering. It discusses the advantages of MMM and how to evaluate the early damage degree of remanufacturing cores, as well as the repairing quality of remanufactured components. Various MMM signal characteristics are extracted to reflect the damage degree of remanufacturing cores, coatings and interfaces. All the theoretical models, analysis methods and testing results of MMM in this book provide guidance to control the quality of remanufactured parts and products. This book can help readers make the best use of the MMM technique in remanufacturing engineering..
出版日期Book 2021
關(guān)鍵詞Metal magnetic memory; Remanufacturing; Damage degree; Repair quality; Nondestructive evaluation
版次1
doihttps://doi.org/10.1007/978-981-16-1590-0
isbn_softcover978-981-16-1592-4
isbn_ebook978-981-16-1590-0
copyrightScience Press 2021
The information of publication is updating

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d that are subject to varying levels of data uncertainty and environmental variability. The methods outlined in the following chapters represent many of the tools needed to fill that toolbox. When used in conjunction with adaptive management, they should provide information for improved monitoring,
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of the data available, are, however, not specific to BPs. Classically, the range of strategies thus spreads from a detailed PVA model, relying on extensive data (as in, e.g., Woolfenden and Fitzpatrick 1991), to a series of different scenarios corresponding to varying assumptions and parameter valu
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