## Abstract This study involves realβtime monitoring and fault diagnosis in batch baker's yeast fermentation. A specific Real Time Statistical Process Analysis and Control (RTβSPAC) program was developed to monitor instantaneous reaction conditions. The air flow rate fed to the reactor, temperature
Monitoring and Fault Diagnosis for Batch Process Based on Feature Extract in Fisher Subspace
β Scribed by Xu ZHAO; Weiwu YAN; Huihe SHAO
- Book ID
- 114337864
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 588 KB
- Volume
- 14
- Category
- Article
- ISSN
- 1004-9541
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## Abstract The aim of this paper is to propose a novel realβtime process monitoring and fault diagnosis method based on the principal component analysis (PCA) and kernel Fisher discriminant analysis (KFDA). There is a need to develop this method in order to overcome the inherent limitations of the
The vibration signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. However, in many cases, because these signals have very low signal-to-noise ratio (SNR), to extract feature components becomes di$cult