Data Driven Fault Detection for Industrial Processes is popular PDF and ePub book, written by Zhiwen Chen in 2017-01-02, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Data Driven Fault Detection for Industrial Processes can be Read Online from any device for your convenience.
Data Driven Fault Detection for Industrial Processes Book PDF Summary
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.
Detail Book of Data Driven Fault Detection for Industrial Processes PDF
- Author : Zhiwen Chen
- Release : 02 January 2017
- Publisher : Springer
- ISBN : 9783658167561
- Genre : Technology & Engineering
- Total Page : 112 pages
- Language : English
- PDF File Size : 9,7 Mb
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