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基于改进多模型FDA的间歇生产过程的故障诊断
Abstract：Since there are not enough fault data in historical data sets, it is very difficult to diagnose faults for batch processes. In addition, a complete batch trajectory can be obtained till the end of its operation. In order to overcome the need for estimated or filled up future unmeasured values in the online fault diagnosis, sufficiently utilize the finite information of faults, and enhance the diagnostic performance, an improved multi-model Fisher discriminant analysis is represented. The trait of the proposed method is that the training data sets are made of the current measured information and the past major discriminant information, and not only the current information or the whole batch data. An industrial typical multi-stage streptomycin fermentation process is used to test the performance of fault diagnosis of the proposed method. 作者： 蒋丽英 谢磊 王树青 Author： JIANG Liying XIE Lei WANG Shuqing 作者单位： 浙江大学 期 刊： 中国化学工程学报（英文版） ISTICEISCI Journal： CHINESE JOURNAL OF CHEMICAL ENGINEERING 年，卷(期)： 2006, 14(3) 分类号： N94 Keywords： fault diagnosis Fisher discriminant analysis batch processes 机标分类号： TP3 S63 机标关键词： 多模型 间歇 生产过程 故障诊断 Discriminant Analysis fault diagnosis discriminant analysis fermentation process batch processes diagnosis of 基金项目： 国家自然科学基金 基于改进多模型FDA的间歇生产过程的故障诊断[期刊论文] 中国化学工程学报（英文版） --2006, 14(3)蒋丽英 谢磊 王树青Since there are not enough fault data in historical data sets, it is very difficult to diagnose faults for batch processes. In addition, a complete batch trajectory can be obtained till the end of its ...【基于改进多模型FDA的间歇生产过程的故障诊断】相关文章：
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