融合多源信息与知识模型的印刷机故障逆向定位及耦合机理研究

项目名称： 融合多源信息与知识模型的印刷机故障逆向定位及耦合机理研究

项目编号： No.51305340

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 机械、仪表工业

项目作者： 侯和平

作者单位： 西安理工大学

项目金额： 25万元

中文摘要： 印刷机是一种结构复杂、高速度运转的高精密设备，其运行过程中频繁的故障常导致大量印刷物料的浪费。由于印刷机中多组执行机构与多介质物料系统之间存在强耦合作用，已有的故障诊断方法难以有效应用于印刷机故障诊断和耦合机理解析。针对上述问题，本项目提出融合多源信息与知识模型的印刷机故障诊断方法，以实现故障逆向定位，阐明耦合机理：首先，构建多传感器系统监测印刷机运行状态，采集多源信息，结合印刷画面中隐含的印刷机故障信息，建立信息丰富的印刷机故障特征集；其次，通过多元统计方法构建表征印刷机状态的主元特征，确立故障现象之间的映射关系及影响权重，完成故障源的逆向追溯，从而实现故障耦合机理解释；最后，融合人工知识模型，建立印刷机故障诊断的智能决策算法，完成印刷机故障的精确诊断。本项目的研究将为印刷机故障诊断和状态监测提供一种全新的方法，同时为大型复杂过程装备故障诊断提供有益的探索，将丰富机械故障诊断的理论体系。

中文关键词： 印刷机；故障诊断；多源信息；流形学习；

英文摘要： The printing machine is a type of equipment which is characterized with high-speed operation and complex structure. The frequent failure during operation often leads to a waste of numerous printed materials. It is difficult to apply the well-established failure diagnosis method to accurately diagnose the fault and analyze the coupling mechanism of printing failure, due to the strong coupling between the multiple actuators of press groups and multi-media materials system. In this project, we propose a new failure diagnosis method by integrating multi-source information and knowledge model to achieve the reverse positioning of the failure and analyze the coupling mechanism to address the above limitations. Firstly, the printing press fault feature database of rich information will be established with the construction of a multi-sensor system to monitor the working state of printing machines, as well as collecting multi-source information, combining with implicit failure information form the printing screen. Secondly, multivariate statistical approaches will be utilized to help characterize the main element feature of printing press, establishing the mapping relationship and the affecting weights between the failures of machine. As a result, the reverse fault source trace will be completed, which will bring about t

英文关键词： printing machine；fault dagnosis；multi-sources information；manifold learning；