基于多维差异感知的生产工况异常检测与故障预测方法研究

项目名称： 基于多维差异感知的生产工况异常检测与故障预测方法研究

项目编号： No.61273169

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 彭涛

作者单位： 中南大学

项目金额： 80万元

中文摘要： 对流程工业等复杂过程，及时准确感知工况异常变化并采取相应措施，是确保生产质量及安全、及时消除事故隐患、避免生产事故的必然要求。本项目针对引起流程工业生产工况异常的因素复杂多变，反映工况的特征和生产指标、操作变量及工艺参数众多且相互关联，感知工况变化及通过该变化感知故障或故障先兆和事故隐患困难等特点，系统研究基于差异感知的工况异常检测与故障预测方法，主要研究：基于多维数据体结构描述的特征向量、特征分布及特征趋势序列等工况特征模式表征方法；基于异构不平坦属性的多维差异性测度方法；通过多维差异感知和多维特征向量、特征分布及特征趋势序列模式匹配实现复杂工况动态检测，形成基于多核框架的复杂工况异常检测与故障预测理论与方法。项目的研究成果将为流程工业生产过程的工况异常检测、故障预测与优化控制及维修决策提供新的解决模式，对提高产品质量、确保生产安全、降低维护成本具有十分重要的理论意义和显著的实用价值。

中文关键词： 特征差异分析；多维异构特征模式；异常检测；工况识别；泡沫浮选

英文摘要： It is very necessary that anomaly of operating condition is perceived timely and accurately so as to ensure production quality and safety, eliminate potential accidents, avoid accidents for complex process industry. Considering the problems that anomaly is caused by complex and varied factors, features reflecting the conditions is correlate with production targets, numerous operational variables and parameters, and it is very difficult to condition changes are perceived and then fault or failure foretastes and potential accidents are perceived through these changes, approaches to anomaly detection and fault prediction based on multi-way dissimilarity perception are researched systematically in this project for process operating condition. A novel method based on multi-way day for describing the modes of features vectors, features distributions and features trending sequence is proposed. Multi-way dissimilarity measurement methods based on heterogeneous and uneven property of features are presented. Dynamic detection for complex condition is achieved by multi-way dissimilarity perception and pattern matching of multi-way features vectors, multi-way features distributions and multi-way features trending sequences. Theories and methods of anomaly detection and fault prediction based on multiple kernel learning are

英文关键词： Feature difference analysis；Multidimensional Heterogeneous Feature Mode；anomaly detection；Condition identification；froth flotation