Integration of fault diagnosis based on case-based reasoning principles in brewing

被引：4
|
作者：
Riverol C. [1 ]
Carosi C. [2 ]
机构：
[1] Chemical Engineering Department, University of West Indies, St. Augustine
[2] Project Department, JC Engineering, Caracas, Prados del Este
来源：
Sensing and Instrumentation for Food Quality and Safety | 2008年 / 2卷 / 01期
关键词：
CBR; Deviation; Fault detection; Fuzzy; Maltaproduction; Observers; Sensor;
D O I：
10.1007/s11694-007-9030-0
中图分类号：
学科分类号：
摘要：
In this paper we describe an approach to Sensor Fault Detection, Isolation and Accommodation (SFDIA) that is mainly based on fuzzy processing of deviation from the model predictions. The predictive model is supported using a Decision Making Unit (DMU) and cased-based Reasoning principles (CRB) where pass cases are saved and filed in the Library for confirmed solution and repaired cases. This tool uses the sensor readings at the current time step to predict system state at the next time step using observers. Although the method lacks the mathematical basis that other analytical methods provide; this method is simple effective and useful. © Springer Science+Business Media, LLC 2007.
引用
收藏
页码：15 / 20
页数：5
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