Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electroni...Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electronics-rich system including avionics.Prognostics and health management（PHM） have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system,combining three baseline prognostic approaches that are model-based,data-driven and knowledge-based approaches,and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation.A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline approaches correspondingly,and the presented case study shows that the fusion prognostics can provide RUL estimation more accurate and more robust than either algorithm alone.展开更多
Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for rad...Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to implement.This paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also investigated.Several experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.展开更多
PHM(prognostics and health management)系统健康评估作为连接故障诊断和故障预测的纽带,具有十分重要的作用。针对自动驾驶仪PHM系统健康评估存在的多工况、非线性和小子样问题,提出了一种面向自动驾驶仪PHM系统的贝叶斯网络简化推理...PHM(prognostics and health management)系统健康评估作为连接故障诊断和故障预测的纽带,具有十分重要的作用。针对自动驾驶仪PHM系统健康评估存在的多工况、非线性和小子样问题,提出了一种面向自动驾驶仪PHM系统的贝叶斯网络简化推理模型,建立了一种基于可变信息的改进贝叶斯节点和迭代交叉熵测度的变模型快速推理算法。算法理论仿真实验验证了其有效性和工程可行性,最后在某型直升机电动舵机平台上验证了该改进算法,具有较好的工程应用前景。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
The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuse...The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.展开更多
面向电子设备故障预测与健康管理(Prognostics and Health Management,PHM),基于自适应谱峭度与核概率距离聚类提出一种振动载荷下板级封装潜在故障特征提取与模式辨识方法.首先,基于最大谱峭度原则利用经验模态分解的方法对电子组件的...面向电子设备故障预测与健康管理(Prognostics and Health Management,PHM),基于自适应谱峭度与核概率距离聚类提出一种振动载荷下板级封装潜在故障特征提取与模式辨识方法.首先,基于最大谱峭度原则利用经验模态分解的方法对电子组件的应变响应数据进行滤波,计算并重构包含潜在故障信息的包络谱形成故障征兆向量;其次,应用高斯径向基核函数概率距离方法,将非线性故障征兆数据映射到高维Hilbert空间,对其进行聚类分析形成表征板级封装健康状态与各故障模式的类中心;最后,根据实时监测的板级封装的包络谱数据计算与各中心的概率距离,判断其所属的状态从而实现对封装故障模式的早期辨识.通过试验分析,该方法可以有效辨识与预测板级封装即将发生的故障模式,为实现电子设备PHM提供了一种新式的思路与手段.展开更多
对已有的航空装备可用度分析方法进行了综述,将航空装备可用度影响因素分为三类.通过PHM(Prognostics and Health Management)技术对航空装备保障过程的影响分析,梳理了基于PHM的航空装备可用度影响因素,并将这些因素按照其来源分为使...对已有的航空装备可用度分析方法进行了综述,将航空装备可用度影响因素分为三类.通过PHM(Prognostics and Health Management)技术对航空装备保障过程的影响分析,梳理了基于PHM的航空装备可用度影响因素,并将这些因素按照其来源分为使用影响因素和设计影响因素两大类.给出了4个合理的仿真假设条件以简化仿真过程,并进一步将设计影响因素分为5种,并结合一个实例给出了基于PHM的航空装备可用度影响因素仿真过程中的输入.提出给定装备系统及其保障系统参数条件下的稳态可用度为仿真的输出,并给出与仿真输入相符的解析计算公式.详细描述了仿真程序的构成及其流程图.最后,以图形的方式给出了仿真结果,给出了案例的单因素分析及多因素耦合分析的过程及结论,验证了所提出的分析方法的可行性.展开更多
为了提高综合航空电子的可靠性、可用性以及寿命周期内的经济可承受性,将故障预测与健康管理(prognostics and health management,PHM)技术应用到该系统中。分析PHM技术的目标和优势,构建基于OSA-CBM的综合航电PHM系统的框架结构,从可...为了提高综合航空电子的可靠性、可用性以及寿命周期内的经济可承受性,将故障预测与健康管理(prognostics and health management,PHM)技术应用到该系统中。分析PHM技术的目标和优势,构建基于OSA-CBM的综合航电PHM系统的框架结构,从可预测性设计、故障预测技术和健康管理技术3个方面,阐述构建综合航电PHM系统的支撑技术。该研究对综合航电PHM系统的应用和开发具有重要意义。展开更多
文摘Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life（RUL） prognostics of electronics-rich system including avionics.Prognostics and health management（PHM） have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system,combining three baseline prognostic approaches that are model-based,data-driven and knowledge-based approaches,and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation.A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline approaches correspondingly,and the presented case study shows that the fusion prognostics can provide RUL estimation more accurate and more robust than either algorithm alone.
基金National Natural Science Foundation of China (42027805)。
文摘Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering systems.However, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to implement.This paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also investigated.Several experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.
文摘PHM(prognostics and health management)系统健康评估作为连接故障诊断和故障预测的纽带,具有十分重要的作用。针对自动驾驶仪PHM系统健康评估存在的多工况、非线性和小子样问题,提出了一种面向自动驾驶仪PHM系统的贝叶斯网络简化推理模型,建立了一种基于可变信息的改进贝叶斯节点和迭代交叉熵测度的变模型快速推理算法。算法理论仿真实验验证了其有效性和工程可行性,最后在某型直升机电动舵机平台上验证了该改进算法,具有较好的工程应用前景。
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。
基金supported by the National Natural Science Foundation of China(51175502)
文摘The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.
文摘面向电子设备故障预测与健康管理(Prognostics and Health Management,PHM),基于自适应谱峭度与核概率距离聚类提出一种振动载荷下板级封装潜在故障特征提取与模式辨识方法.首先,基于最大谱峭度原则利用经验模态分解的方法对电子组件的应变响应数据进行滤波,计算并重构包含潜在故障信息的包络谱形成故障征兆向量;其次,应用高斯径向基核函数概率距离方法,将非线性故障征兆数据映射到高维Hilbert空间,对其进行聚类分析形成表征板级封装健康状态与各故障模式的类中心;最后,根据实时监测的板级封装的包络谱数据计算与各中心的概率距离,判断其所属的状态从而实现对封装故障模式的早期辨识.通过试验分析,该方法可以有效辨识与预测板级封装即将发生的故障模式,为实现电子设备PHM提供了一种新式的思路与手段.
文摘对已有的航空装备可用度分析方法进行了综述,将航空装备可用度影响因素分为三类.通过PHM(Prognostics and Health Management)技术对航空装备保障过程的影响分析,梳理了基于PHM的航空装备可用度影响因素,并将这些因素按照其来源分为使用影响因素和设计影响因素两大类.给出了4个合理的仿真假设条件以简化仿真过程,并进一步将设计影响因素分为5种,并结合一个实例给出了基于PHM的航空装备可用度影响因素仿真过程中的输入.提出给定装备系统及其保障系统参数条件下的稳态可用度为仿真的输出,并给出与仿真输入相符的解析计算公式.详细描述了仿真程序的构成及其流程图.最后,以图形的方式给出了仿真结果,给出了案例的单因素分析及多因素耦合分析的过程及结论,验证了所提出的分析方法的可行性.
文摘为了提高综合航空电子的可靠性、可用性以及寿命周期内的经济可承受性,将故障预测与健康管理(prognostics and health management,PHM)技术应用到该系统中。分析PHM技术的目标和优势,构建基于OSA-CBM的综合航电PHM系统的框架结构,从可预测性设计、故障预测技术和健康管理技术3个方面,阐述构建综合航电PHM系统的支撑技术。该研究对综合航电PHM系统的应用和开发具有重要意义。
