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Titlebook: Data-Driven Fault Detection for Industrial Processes; Canonical Correlatio Zhiwen Chen Book 2017 Springer Fachmedien Wiesbaden GmbH 2017 Mu

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發(fā)表于 2025-3-21 16:20:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Data-Driven Fault Detection for Industrial Processes
副標(biāo)題Canonical Correlatio
編輯Zhiwen Chen
視頻videohttp://file.papertrans.cn/264/263295/263295.mp4
概述Publication in the field of technical sciences
圖書封面Titlebook: Data-Driven Fault Detection for Industrial Processes; Canonical Correlatio Zhiwen Chen Book 2017 Springer Fachmedien Wiesbaden GmbH 2017 Mu
描述.Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed..
出版日期Book 2017
關(guān)鍵詞Multivariate statistical process monitoring; Performance evaluation; Data-Driven method; Subspace metho
版次1
doihttps://doi.org/10.1007/978-3-658-16756-1
isbn_softcover978-3-658-16755-4
isbn_ebook978-3-658-16756-1
copyrightSpringer Fachmedien Wiesbaden GmbH 2017
The information of publication is updating

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發(fā)表于 2025-3-21 22:20:47 | 只看該作者
https://doi.org/10.1007/978-3-031-49193-1ul implementations have been reported [40, 89, 125], the existing data-driven FD methods pay often less attention to deterministic disturbances. Recently, Luo . [75] proposed a data-driven FD approach for static processes with deterministic disturbances.
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發(fā)表于 2025-3-22 01:21:44 | 只看該作者
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發(fā)表于 2025-3-22 10:17:51 | 只看該作者
New Results for Network Pollution GamesAdditive faults normally represent changes such as an abrupt increase in feed or a biased sensor, while multiplicative faults usually refer to changes, like variation in system parameters and variance of measurement noise [10, 16, 25, 90].
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發(fā)表于 2025-3-22 13:12:57 | 只看該作者
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發(fā)表于 2025-3-22 20:03:28 | 只看該作者
Occluded Face Recognition with Deep LearningIn this dissertation, the evaluation and comparison of two basic detection statistics for data-driven FD methods have been carried out, and advanced data-driven FD methods have been developed for complex industrial processes.
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發(fā)表于 2025-3-22 22:34:00 | 只看該作者
Improved CCA-based Fault Detection Methods,Additive faults normally represent changes such as an abrupt increase in feed or a biased sensor, while multiplicative faults usually refer to changes, like variation in system parameters and variance of measurement noise [10, 16, 25, 90].
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發(fā)表于 2025-3-23 06:00:51 | 只看該作者
Conclusions and Future Work,In this dissertation, the evaluation and comparison of two basic detection statistics for data-driven FD methods have been carried out, and advanced data-driven FD methods have been developed for complex industrial processes.
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