基于观测器的液压系统健康状态评估方法研究

为了实时评估液压系统的健康状态,提出了基于观测器的健康状态评估原理,利用解析模型、仿真模型和数据模型及其配合等方法进行液压系统标准模型的建立,联合实际液压系统的监测数据,构建液压系统的状态观测器。将实际系统的相关参数作为输入,实际监测点的输出与标准模型的输出进行特征分析与对比,在数据处理的基础上形成残差及其向量,运用数据分析方法计算系统健康度,并解析各元素及其耦合所映射的故障类型与故障程度,实现液压系统的故障定位与评估。最后,利用某型装备的起竖液压系统进行了应用举例,介绍了模型构建、故障模式与参数选择、残差构成及健康度计算的方法。所研究的状态评估方法对实时评估液压系统,及开展液压系统视情维修具有参考价值。     

民用飞机健康状态评估方法 

飞机健康状态评估技术能够为飞机的健康状态提供量化评价的方法和手段,通过给出量化的飞机健康指数值,可以为后续的飞机维修提决策提供必要的技术基础;在分析了健康状态评估的技术现状的基础上,对飞机整机级的健康状态评估方法进行了研究,提出了健康状态评估技术方案,并对波音AHM系统健康指数模型进行了研究;提出的民用飞机健康状态评估方法,实现了从传统的对故障的状态识别转移至对性能退化程度的检测和量化描述,其应用可以为航空公司安排飞机运营提供参考,并为合理安排计划维修提供决策支持。     

有源相控阵雷达状态监测与健康管理技术

状态监测和健康管理技术作为新一代测试与诊断技术,是装备自主式保障的核心系统之一,在保障武器装备战备完好性,提高作战效能,降低全寿命周期费用等方面具有重要作用;从有源相控阵雷达的状态监测与健康管理入手,构建了分层式健康管理系统框架,以作用距离和副瓣电平等指标进行信息融合和健康评估,实现了有源相控阵雷达的状态监测和健康管理。     

民用飞机多级健康状态评估技术研究

健康状态评估技术是实现飞机派遣决策的关键技术。本文提出了一种民用飞机多级健康状态评估方法,该方法充分利用各类工程数据、技术数据和可靠性分析数据,建立飞机技术派遣量化评估方法,甄选影响飞机技术派遣的主要参数,并通过对各参数进行权重分配,建立综合量化分析模型,针对专机、VIP及其他特殊航线运行要求,精准高效地为飞机的技术派遣提供决策依据,保证特殊运行航班的安全性以及签派可靠度。经某航空公司的试用效果良好,验证了提出的方法的可行性。     

基于小波包能量谱的分布式光纤燃气管道泄漏监测及实验分析

基于Mach-Zehnder/Sagnac混合干涉仪原理,利用分布式光纤对城市燃气管道进行泄漏监测模拟实验研究。对测量光纤长4 km和6 km时的干涉信号利用小波包能量谱提取法和绝对距离法相结合的方法诊断管道泄漏与否,再结合频谱图进行泄漏定位,最后对系统的虚警率(false alarm rate,FAR)进行了分析。结果表明,与传统直接通过频谱图识别零点频率的方法相比,虚警率降低了8.475%,能够更准确地识别燃气管道泄漏与否,从而提高系统监测及定位的可靠性。     

某型复杂装备车载状态监测系统设计

某型复杂装备现有设备监测数据达不到对全车的故障诊断与健康状态评估所需数据的要求,通过分析其整车电气信号,为满足复杂装备对整车数据的监测需求,设计了车载状态监测系统;给出了车载监测系统的总体架构,对综合控制处理电路、实时数据采集处理电路、总线数据监控电路和车载显示系统硬件进行了设计,设计了车载采集与报警系统和显示系统软件,最后对系统进行了车载测试,表明系统能够对复杂装备的实时运行状态进行监测,完成基本的故障诊断功能,为早期发现故障缺陷,提出处置措施,开展系统健康管理提供了条件。     

基于贝叶斯决策的电传飞控系统状态监测与健康管理

针对飞控系统早期故障信号的微弱性和不易检测性,提出了一种基于贝叶斯决策的飞控系统状态监测和健康管理新算法;采用最大似然估计法对故障特征向量概率密度函数进行参数估计,监测飞控系统故障特征概率密度分布相对于正常状态的偏离,将不易检测的故障信号转化为容易观测到的偏离信息,实现飞控系统状态的健康评估;以某型电液伺服作动器为例,采用上述方法对其进行状态监测和健康管理,仿真结果证明了该方法的可行性和有效性。     

基于风洞的设备健康管理与数据有效性判定平台研究

低速增压风洞是满足我国航空工业科技发展而建设的一座气动力重大基础试验设施。为了保障该设施的高效率和可靠地运行,以各机电设备、电气测控设备、机械装置为对象,根据其故障模式和故障特点选取合适的监测点,获取实时工作状态数据,再以数据为基础,进行状态监测、故障诊断、故障预测,实现预先性决策和针对性快速维修。基于OSA-CBM 体系构建的风洞健康管理系统,根据设备的运行状态,实现对试验数据的有效性进行实时判定,并实现了风洞装备由事后维修向视情维修转变;实现了装备从使用、维护、管理模式由分散式管理向集约式管理的转变;实现了装备系统故障诊、预测及判读从人工智能向机器智能的转变。     

无人机健康状态综合评估技术研究

无人机健康状态综合评估技术是以无人机视情维修体系为背景发展起来的,已成为先进的无人机核心技术之一,现已发展成为一门新兴的科学技术;国外的许多军用无人机由于采用健康状态评估技术,极大降低无人机的使用和维修成本、提高无人机的使用可靠性;结合某型无人侦察机的典型部件,阐述了无人机健康状态评估技术的提出、实现方法和发展趋势,并以无人机的动力分系统为例,验证了所提方法的可行性,为实现无人机状态即时评估提供科学依据。     

加注系统信息融合式健康监测方案研究

为解决当前发射场加注系统维修维护与状态监测所面临的问题,提出针对加注系统开展基于信息融合的健康监测;分析针对加注系统开展健康监测研究以及将信息融合技术引入系统健康监测的意义,总结加注系统健康监测现状,得出开展加注系统健康监测所面临的困难与启示;针对加注系统典型设备,设计融合式健康监测方案,包括健康监测信息特点分析、典型设备健康监测信息分析以及典型设备健康监测方案设计;为后续进一步深入开展加注系统融合式健康监测研究奠定了良好基础。     

Factors Related to Continuation of Health Behaviours among Stroke Survivors

Purpose: This study investigated stroke survivors'' perspectives of health behaviours after stroke. We aimed to explore the actual process by which stroke survivors changed their health behaviours. Method: Semi-structured interviews were conducted with 40 people in a 1-year prospective study in the regional city of Chiba, Japan. Interviews covered views of health behaviours in order to explore why patients change their risk factors. Data were analysed using the principles of modified grounded theory. Results: Six categories related to practising health behaviours were identified: cause of stroke, antithetic thinking, awareness of the body, fear of disease progression, view of health, and psychological meaning of practise. Stroke survivors constructed a meaning of practise for each health behaviour. The recognition of previous lifestyle as cause of stroke, hope for recovery, and fear of future progression influenced health behaviours. Conclusions: The key finding of this study is that when cognitive behavioural therapy principles are enforced, an important aspect is that stroke survivors recognize the possibility that previous lifestyle was a cause of stroke and appreciate the necessity of preventing a new stroke.     

Health implications of nanoparticles

Nanoparticles are increasingly used in a wide range of applications in science, technology and medicine. Since they are produced for specific purposes which cannot be met by larger particles and bulk material they are likely to be highly reactive, in particular, with biological systems. On the other hand a large body of know-how in environmental sciences is available from toxicological effects of ultrafine particles (smaller than 100 nm in size) after inhalation. Since nanoparticles feature similar reactivity as ultrafine particles a sustainable development of new emerging nanoparticles is required. This paper gives a brief review on the dosimetry of nanoparticles, including deposition in the various regions of the respiratory tract and systemic translocation and uptake in secondary target organs, epidemiologic associations with health effects and toxicology of inhaled nanoparticles. General principles and current paradigms to explain for the specific behaviour of nanoparticles in toxicology are discussed. With that respect we consider nanoparticles to be in the range from 1 to 2 nm (clusters of atoms/molecules) to particles that are smaller than 100 nm at least in one dimension. Since the evidence for health risks of ultrafine and nanoparticles after inhalation has been increasing over the last decade, the paper attempts to extrapolate these findings and principles observed in particle inhalation toxicology into recommendations for an integrated concept of risk assessment of nanoparticles for a broad range of use in science, technology and medicine.Based on this article a book chapter will appear soon (Kreyling et al., 2006).     

重复使用运载器预测与健康管理PHM技术研究

为了实现传统一次性运载火箭的可重复使用特性,提高重复使用运载器的安全性、可靠性及维修保障性,破解重复使用运载器研制难度大、技术风险高的难题,研究了一种重复使用运载器的预测与健康管理系统方案;该系统采用一种“机载-地面”辅助决策的系统设计方案,机载部分采用分层分布式的系统架构设计方案,地面部分采用区域管理和综合调度的设计方案,有效实现运载器在线式健康状态监测与诊断;重复使用运载器预测与健康管理设计方案的应用,确保运载器在全寿命周期内,实现在线实时故障检测、故障预测和健康评估,为故障处理、维修保障和系统操作优化提供决策支持,显著提升了重复使用运载器的安全性、可靠性、保障性和效费比。     

基于遗传神经网络的伺服机构健康状态预测

为了及时把握伺服机构的健康状态,为装备的管理维护与任务执行提供必要的决策支持,从装备的自然退化趋势出发,提出了一种基于遗传算法优化BP神经网络的预测模型。利用BP神经网络优秀的非线性映射能力构造预测模型,将神经网络初始权值阈值编码,利用改进的自适应遗传算法确定最优解。将该模型应用到伺服机构的健康状态预测上,并与标准BP神经网络及径向基神经网络做比较。结果表明该模型有更好的预测精度及收敛速度,从而验证了模型的有效性。     

飞机综合健康管理系统的应用与发展

飞机综合健康管理技术的应用对于提高飞机的安全性、维护性、降低运营成本等具有重要意义。本文通过对相关文献的整理,归纳和总结了飞机综合健康管理系统的含义,梳理了飞机综合健康管理系统发展过程,并以综合健康管理系统在B787、A380以及F-35飞机的应用为典型案例,从系统架构、功能组成等方面详细阐述了综合健康管理系统在民用和军用飞机上的最新应用,最后对飞机综合健康管理系统的发展趋势进行了探讨和展望。希望通过本文能够使读者对飞机综合健康管理技术的发展历程、最新技术水平以及未来发展方向有更加详尽的了解,对我国开展相关技术领域的研究提供有力的帮助。     

Health risk assessment for nanoparticles: A case for using expert judgment

Uncertainties in conventional quantitative risk assessment typically relate to values of parameters in risk models. For many environmental contaminants, there is a lack of sufficient information about multiple components of the risk assessment framework. In such cases, the use of default assumptions and extrapolations to fill in the data gaps is a common practice. Nanoparticle risks, however, pose a new form of risk assessment challenge. Besides a lack of data, there is deep scientific uncertainty regarding every aspect of the risk assessment framework: (a) particle characteristics that may affect toxicity; (b) their fate and transport through the environment; (c) the routes of exposure and the metrics by which exposure ought to be measured; (d) the mechanisms of translocation to different parts of the body; and (e) the mechanisms of toxicity and disease. In each of these areas, there are multiple and competing models and hypotheses. These are not merely parametric uncertainties but uncertainties about the choice of the causal mechanisms themselves and the proper model variables to be used, i.e., structural uncertainties. While these uncertainties exist for PM2.5 as well, risk assessment for PM2.5 has avoided dealing with these issues because of a plethora of epidemiological studies. However, such studies don’t exist for the case of nanoparticles. Even if such studies are done in the future, they will be very specific to a particular type of engineered nanoparticle and not generalizable to other nanoparticles. Therefore, risk assessment for nanoparticles will have to deal with the various uncertainties that were avoided in the case of PM2.5. Consequently, uncertainties in estimating risks due to nanoparticle exposures may be characterized as ‘extreme’. This paper proposes a methodology by which risk analysts can cope with such extreme uncertainty. One way to make these problems analytically tractable is to use expert judgment approaches to study the degree of consensus and/or disagreement between experts on different parts of the exposure–response paradigm. This can be done by eliciting judgments from a wide range of experts on different parts of the risk causal chain. We also use examples to illustrate how studying expert consensus/disagreement helps in research prioritization and budget allocation exercises. The expert elicitation can be repeated over the course of several years, over which time, the state of scientific knowledge will also improve and uncertainties may possibly reduce. Results from expert the elicitation exercise can be used by risk managers or managers of funding agencies as a tool for research prioritization.     

面向复杂装备的信息融合式健康监测分析研究

为解决当前复杂装备维修维护与状态监测所面临的问题,提出面向复杂装备的信息融合式健康监测;对复杂装备健康监测需求进行研究,明确针对复杂装备开展健康监测研究的意义;完成装备健康监测概念辨析,明确将信息融合技术引入复杂装备健康监测的意义;对信息融合技术国内外研究现状进行分析,针对信息融合技术的数据级、特征级及决策级,对各层级典型信息融合算法进行概要分析;论文研究为后续进一步深入开展复杂装备信息融合式健康监测研究奠定了良好基础。     

基于DBN深度学习算法的民航发动机状态监测

民航飞机发动机设备构造精密、复杂,其监测系统收集的数据中蕴含了丰富的故障信息。传统发动机状态诊断依靠数据统计分析和机器学习模型,但其在深入理解与归类信号特性方面的表现难以尽如人意。此外近年兴起了多层神经网络降维算法——深度学习理论,其通过模拟人脑分析过程建立由浅入深的算法模型,数据处理效果较好。本文将民航发动机自身特点与深度学习理论有机结合,研究发动机状态监测方法。其优势在于克服了传统方法人工提取数据特征的不确定性与状态分类陷入局部最优的缺陷,可对发动机参数进行自主学习与特征提取。实验结果表明该算法具有出色的特征提取能力与分类准确率,能够准确识别发动机的不同状态。