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Titlebook: Data-Driven Technology for Engineering Systems Health Management; Design Approach, Fea Gang Niu Book 2017 Springer Science+Business Media S

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楼主: 郊区
发表于 2025-3-23 10:36:49 | 显示全部楼层
Algorithms in Multidimensional ScalingThe process of condition monitoring, fault diagnosis, and prognosis can be summarized as follows: data acquisition, data processing, data analysis, and decision making. Here, data represent system condition, so it can be called condition-based (data-driven) systems health management.
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Social Capital and New Forms of TrustReduction of feature dimensionality is a considerable importance data-driven PHM/CBM. The reason for being so is twofold: to reduce the computational complexity and to improve the algorithm’s generalization ability.
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Women’s Aspirations Towards “STEM” CareersThe word . comes from the Greek . (of knowledge beforehand). It combines . (before) and . (a knowing). Hippocrates used the word prognosis, much as we do today, to mean a foretelling of the course of a disease. In the field of engineering systems health management, prognosis is regarded as science and often called prognostics.
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Design Approach for Systems Health Management,Over the last several decades, there has been a wide range of approaches and implementation strategies for performing manual, semiautomated, or fully automated fault diagnosis and prognosis (i.e., health management) on critical systems in commercial and defense markets.
发表于 2025-3-24 19:48:28 | 显示全部楼层
Overview of Data-Driven PHM,In this book, technical approaches of data-driven PHM are introduced. The related methodology and frameworks are explained. The CBM can be regarded as a technical architecture and engineering strategy for data-driven PHM.
发表于 2025-3-25 01:35:29 | 显示全部楼层
Data Acquisition and Preprocessing,The process of condition monitoring, fault diagnosis, and prognosis can be summarized as follows: data acquisition, data processing, data analysis, and decision making. Here, data represent system condition, so it can be called condition-based (data-driven) systems health management.
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