大数据环境下智能制造装备健康状态预测与维修决策研究

项目名称： 大数据环境下智能制造装备健康状态预测与维修决策研究

项目编号： No.51475189

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 机械、仪表工业

项目作者： 吴军

作者单位： 华中科技大学

项目金额： 82万元

中文摘要： 健康状态预测与维修决策是高端装备制造业待突破的关键基础共性技术。本申请项目以智能制造装备为对象，从海量高维状态数据挖掘出发，针对性地研究大数据环境下的装备健康状态预测与维修决策新方法，主要包括：提出装备海量高维状态数据的自动清理、集成与变换方法，发现特征参数与健康状态之间复杂关联；建立基于随机微分方程的装备状态演化过程动力学模型，揭示装备在不同因素作用下的动力学行为；提出基于半监督聚类和动态贝叶斯网络的装备健康状态诊断与预测方法，构建超环检测器，揭示健康状态的微变化特征及变迁趋势；提出基于状态的装备预测性维修决策与优化方法，制定科学合理的维修策略；开发装备健康状态预测与维修决策软硬件平台，为上述技术的广泛应用提供支撑。研究结果对于从纵深方向发展智能制造装备运行安全的科学保障体系，提升智能制造装备的长时间稳定可靠运行能力和保证智能制造装备高精高效使用等都具有重要的理论意义和工程应用价值。

中文关键词： 智能制造装备；海量数据挖掘；健康状态预测；预测性维修

英文摘要： Health state prediction and maintenance decision is one of key and common techniques for high-end equipment manufacturing industry to be resolved. Intelligent manufacturing equipment is selectd as the research object in the proposal. Its main goal is to implement research on new methods of health state prediction and maintenance decision for the equipment in big data environment, starting from massive and high-dimensional data mining. Its main research contents are as follows: First of all, automatical disposal, integration and transformation methods for the massive and high-dimensional state data will be introduced, and the connection between characteristic parameters and health states will be obtained. Then, in order to find equipment dynamic behaviors under the effect of different factors, the dynamic model of health state evolution process based on stochastic differential equation will be built. In order to reveal the micro characteristics and tendency of health state, the dialogue and prediction methods of health state will be proposed using semi-supervised clustering and dynamic bayesian networks, and a hyper-ring detector will be set up. In order to produce scientific and reasonable maintenance strategy, the state-based predictive maintenance decision and optimization methods will be proposed. Finally, a software and hardware platform for health state prediction and maintenance decision will be developed so as to provide the application support for the above methods. Predictably, it has important theoretical significance and engineering application value for creating the operation safety guarantee system of intelligent manufacturing equipment, promoting the ability of intelligent manufacturing equipment to run stable and reliable for a long time, ensuring the high precision and high efficiency operation of intelligent manufacturing equipment and so on.

英文关键词： Intelligent Manufacturing Equipment;Big Data Mining;Health State Prediction;Predictive Maintenance