DUCG动态立体因果图的构建和推理方法及其实验验证研究

项目名称： DUCG动态立体因果图的构建和推理方法及其实验验证研究

项目编号： No.61273330

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： 张勤

作者单位： 清华大学

项目金额： 80万元

中文摘要： 本研究充分考虑智能故障诊断技术的发展趋势、困难和应用需求，以现有动态不确定因果图DUCG理论框架为基础，并针对其不足，重点解决存在负反馈情况下的概率推理和逻辑解释问题。在新理论中，推理机将自动在线构造特定情况下的立体DUCG图，允许因果关系穿越任意时间片，并据此进行动态不确定推理和预测。这种直接用动态模型来处理动态问题的方式改变了过去学术界普遍采用的将动态问题静态化处理的基本模式，是一种全新的思路，也是对我国原创的DUCG理论体系的重要扩展，特别适用于解决大型复杂系统动态工况下的故障智能诊断、推理结果解释和预测问题。课题组将研究如何按照时序构建立体因果图的规则、因果影响的延滞和叠加、多参数组合推理、虚假信号和有错知识库处理、模糊证据、动态负反馈，高效计算，推理结果可视化解释等关键技术，开发基于新理论的软件系统，手算和在核电模拟机上做在线故障实验，以验证新理论的正确性、实用性和效率。

中文关键词： 负反馈；因果图；动态；概率推理；知识表达

英文摘要： Fully considering the development trend of the fault diagnosis technology,difficulties and application demands, based on the present Dynamic Uncertain Causality Graph (DUCG) framework and knowing its incapability, this study will focus on solving, in particularly in the cases of negative feedback, the probabilistic reasoning and logic interpretation to the inference results. In the new theory, the inference engine will autimatically construct the specific cubic-DUCG online, allow any causality penetration among different time slices, and make dynamic uncetain inference and prediction. This mode of directly constructing dynamic model to deal with dynamic problem changes the present popular mode of treating a dynamic problem as a number of static problems, which is commonly used in the international academic community.The suggested theory is a new thought, and is an important development to the present DUCG theory originally presented in China, particularly useful to solve large and complex dynamic intelligent fault diagnosis problems，interprete the inference results and make predictions. The research group will study the rules how to construct the cubic DUCG according to the time sequence, the causality influence delay and overlap, multi-parameter inference, the treatment to the spurious signals and imperfect kno

英文关键词： feedback；causality；dynamic；probabilistic reasnoing；knowledge representation