本文介绍了故障预测与健康管理技术(prognostics and health management,PHM)的基本概念和研究内涵,重点对故障预测体系结构、方法、相关标准以及国内外研究现状进行了综合论述和分析,总结了当前的研究热点和存在的技术难点,展望了未来...本文介绍了故障预测与健康管理技术(prognostics and health management,PHM)的基本概念和研究内涵,重点对故障预测体系结构、方法、相关标准以及国内外研究现状进行了综合论述和分析,总结了当前的研究热点和存在的技术难点,展望了未来研究发展趋势。展开更多
故障预测与健康管理(Prognostics and Health Management PHM)系统对于推动作战飞机从"事后维修"、"定时维修"向"视情维修"转变具有十分重要的意义。针对新一代作战飞机的技术特点以及在维修保障方面的需...故障预测与健康管理(Prognostics and Health Management PHM)系统对于推动作战飞机从"事后维修"、"定时维修"向"视情维修"转变具有十分重要的意义。针对新一代作战飞机的技术特点以及在维修保障方面的需求,对机载PHM系统体系结构的3种备选方案进行了对比分析,提出了一种由模块/单元层PHM、子系统级PHM、区域级PHM和平台级PHM等4层集成的层次化体系结构,并着重从层次的划分、组成要素的功能描述、信息传输和外部逻辑等几个方面进行了论述。展开更多
针对锂离子电池在线剩余寿命预测时容量难以直接测量以及预测表达的不确定性等问题,提出一种利用锂离子电池充放电监测参数构建剩余寿命预测健康因子的方法框架,实现了锂电池健康状态的表征,同时利用高斯过程回归(Gaussian process regr...针对锂离子电池在线剩余寿命预测时容量难以直接测量以及预测表达的不确定性等问题,提出一种利用锂离子电池充放电监测参数构建剩余寿命预测健康因子的方法框架,实现了锂电池健康状态的表征,同时利用高斯过程回归(Gaussian process regression,GPR)方法给出剩余寿命预测的不确定性区间,从而构建了锂离子电池在线剩余寿命预测的方法体系。基于NASA锂离子电池数据集和卫星锂离子试验数据的剩余寿命预测验证和评估实验,表明本文提出的方法框架可以很好地支撑电池在线剩余寿命预测的应用,具备较好的电池剩余寿命预测精度和不确定性管理能力。展开更多
Prognostics and Health Management(PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model,one of the challenges for airborne syste...Prognostics and Health Management(PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model,one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System(ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System(ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance.展开更多
文摘故障预测与健康管理(Prognostics and Health Management PHM)系统对于推动作战飞机从"事后维修"、"定时维修"向"视情维修"转变具有十分重要的意义。针对新一代作战飞机的技术特点以及在维修保障方面的需求,对机载PHM系统体系结构的3种备选方案进行了对比分析,提出了一种由模块/单元层PHM、子系统级PHM、区域级PHM和平台级PHM等4层集成的层次化体系结构,并着重从层次的划分、组成要素的功能描述、信息传输和外部逻辑等几个方面进行了论述。
文摘针对锂离子电池在线剩余寿命预测时容量难以直接测量以及预测表达的不确定性等问题,提出一种利用锂离子电池充放电监测参数构建剩余寿命预测健康因子的方法框架,实现了锂电池健康状态的表征,同时利用高斯过程回归(Gaussian process regression,GPR)方法给出剩余寿命预测的不确定性区间,从而构建了锂离子电池在线剩余寿命预测的方法体系。基于NASA锂离子电池数据集和卫星锂离子试验数据的剩余寿命预测验证和评估实验,表明本文提出的方法框架可以很好地支撑电池在线剩余寿命预测的应用,具备较好的电池剩余寿命预测精度和不确定性管理能力。
基金supported by the National Natural Science Foundation of China (61403198)the Jiangsu Province Natural Science Foundation of China (BK20140827)China Postdoctoral Science Foundation (2015M581792)
文摘Prognostics and Health Management(PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model,one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System(ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System(ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance.
