Failure behavior analysis of phased-mission systems considering functional and physical isolation effects

Phased-Mission Systems(PMS) are widely applied in aerospace, telecommunication and intelligent systems for multiple, consecutive and non-overlapping phases of missions. The phasedependent stresses and system structure cause some difficulties to the reliability analysis of PMSs.In this paper, we analyze the physical isolation effects on the degradation speeds and across-phase damage accumulations of failure mechanisms. And, some corresponding reliability and unreliability formulas are derived. Be...     

机载机电系统可靠性的计算机辅助分析方法

 为了提高机载机电系统的可靠性,机载机电系统常采用余度系统,以达到故障容错,进而实现整个飞机系统的高可靠性和安全性。开发适应于余度间耦合、动态性能降级的ReliaApp可靠性分析评价软件平台,通过有效综合故障模式影响（FMEA）、故障树分析（FTA）和Markov状态转移链法,实现不同容错设计方案的选择、机电系统的可靠性定量评价并给出系统的薄弱环节,为系统的余度配置和改进设计提供软件设计与评估平台,以确保飞机系统的高可靠性和安全性。实例应用表明该软件平台是飞机机载机电系统可靠性设计与评价有效的计算机辅助工具。     

考虑两种失效竞争的多状态冷贮备系统可靠性模型

针对装备系统中多状态工作部件存在退化失效与突发失效竞争的情况，以冷贮备系统为研究对象，假设系统内3个维修台可分别提供预防性维修与两种不同类型的修复性维修，采用随机检测策略，系统性能水平在一定范围内退化时进行预防性维修，部件完全退化失效时进行退化失效修复性维修，而突发失效时进行突发失效修复性维修；利用PH （Phase-type）分布描述模型中各类随机时间变量，外部冲击的到达则采用PH更新过程描述，建立了考虑退化失效与突发失效的多状态冷贮备系统可靠性模型。最后通过算例验证了模型的适用性，演示了预防性维修阈值以及三类维修速率对系统可靠性的影响。     

基于加速退化模型的卫星组件寿命与可靠性评估方法

针对卫星产品长寿命、高可靠性的特点,提出了使用加速退化试验的方法来评估卫星用微波接收机的寿命与可靠性指标.首先,在确定微波接收机关键模块与相应失效机理的基础上,选择了适用的加速模型.然后,通过分析产品性能的实际退化过程,选择漂移布朗运动对此进行拟合,并结合漂移布朗运动首达时(first passage time)服从逆高斯分布的特点,建立了产品的可靠性模型.最后,采用极大似然结合最小二乘的评估方法,对该关键模块的恒定应力加速退化试验的蒙特卡罗仿真结果,进行了产品的寿命与可靠性评估并且得到了合理的结果,从而验证了本文方法的正确性.     

多阶段任务系统可靠性建模研究

随着系统复杂性和自动化程度的提高,多阶段任务系统(PMS)的应用越来越多。与单一阶段系统相比,PMS的可靠性分析由于阶段之间的相关性而变得更加复杂。在对PMS作简要介绍基础上,文中对PMS可靠性建模的故障树方法作了系统描述,并以某个多阶段系统为例,进行了比较计算分析。     

A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

Prognostics and health management (PHM) significantly improves system availability and reliability, and reduces the cost of system operations. Design for testability (DFT) developed concurrently with system design is an important way to improve PHM capability. Testability modeling and analysis are the foundation of DFT. This paper proposes a novel approach of testability modeling and analysis based on failure evolution mechanisms. At the component level, the fault progression-related information of each unit under test (UUT) in a system is obtained by means of failure modes, evolution mechanisms, effects and criticality analysis (FMEMECA), and then the failure-symptom dependency can be generated. At the system level, the dynamic attributes of UUTs are assigned by using the bond graph methodology, and then the symptom-test dependency can be obtained by means of the functional flow method. Based on the failure-symptom and symptom-test dependencies, testability analysis for PHM systems can be realized. A shunt motor is used to verify the application of the approach proposed in this paper. Experimental results show that this approach is able to be applied to testability modeling and analysis for PHM systems very well, and the analysis results can provide a guide for engineers to design for testability in order to improve PHM performance.     

基于GSPN的机载液压作动系统可靠性模型

机载液压系统具有余度降级、故障检测、隔离等动态时序过程,传统基于两元可靠性模型很难描述其动态行为和性能降级过程.针对这一问题,采用分层聚类和广义随机Petri网相结合建立了机载液压系统可靠性模型.利用该模型,详细分析了故障检测装置的故障检测率对系统可靠性的影响.分析结果表明,由于故障检测装置故障检测率的影响,机载液压作...     

Reliability evaluation of avionics system with imperfect fault coverage and propagated failure mechanisms

Fault tolerance designs are essential techniques for systems that require high levels of reliability, such as aircraft or spacecraft control system. Imperfect Fault Coverage (IFC) may lead to the failure of a system or subsystem even with adequate redundancy. Previous studies of IFC mostly concentrated on evaluating Coverage Factor (CF), whereas the system failure behaviors with IFC have rarely been involved. Failures that occur in low-layer may be covered by high-layer. However, if the coverage is imperfect, uncovered failure will have functional and physical impact on the system behavior. In this thesis, the failure behavior and reliability of IFC of multi-layer systems are studied and a Binary Decision Diagram (BDD)-based modeling and simulation method are proposed to evaluate system reliability. As a case, the failure behavior of an aero engine electronic controller with IFC is studied. The results show that the IFC may impact system behavior without taking the IFC into account, the system maintenance intervals may reduce, and thus the maintenance costs will increase.     

基于改进发生函数方法的多状态系统可靠性分析

发生函数(UGF)是多状态系统可靠性分析的重要数学手段。通过分解算子,对载荷发生函数进行展开,再结合内积算子和强度发生函数建立考虑共因失效时计算多状态系统可靠度的数学模型。提出了考虑载荷多次作用效应和多种载荷作用时的可靠度计算模型。通过实例研究了共因失效和载荷多次作用效应对多状态系统可靠性的影响。研究表明,共因失效和载荷多次作用效应均对系统及零件可靠度产生影响,而且系统可靠度随着载荷作用次数的增加显著下降。运用本文模型可以直接计算指定载荷作用次数下,存在共因失效时的多状态系统可靠度。     

余度舵机系统的性能降级与可靠性分析

余度舵机是电传飞控系统的关键部件,其通道间存在着较严重的力纷争现象。在建立四余度舵机数学模型的基础上,研究了力均衡算法,对四余度舵机一次故障、二次故障情况下的性能降级和可靠性进行了仿真分析。仿真结果标明,优化的力均衡算法可以有效解决力纷争的问题,四余度舵机可以在一次故障、二次故障的情况下持续工作。采用动态故障树分析方法进行了四余度舵机可靠性分析,证明了其具有非常高的可靠性。     

ACT验证机FBW系统的率模可靠性分析

率模(Profust)可靠度是一种新的可靠性指标,能全面刻划系统的可靠性行为。将ACT验证机FBW系统的故障分为三个等级:影响安全的故障、影响任务的故障和需要维修的故障,从而对该系统进行率模可靠性分析。还基于率模不可靠度定义故障危害度,使得故障危害度不仅可以合理比较不同故障模式的影响大小,而且直接反映故障模式对系统可靠性行为的影响程度。结论是将率模可靠度作为系统的一个设计指标是可取的。     

Using PoF models to predict system reliability considering failure collaboration

Existing Physics-of-Failure-based (PoF-based) system reliability prediction methods are grounded on the independence assumption, which overlooks the dependency among the compo-nents. In this paper, a new type of dependency, referred to as failure collaboration, is introduced and considered in reliability predictions. A PoF-based model is developed to describe the failure behavior of systems subject to failure collaboration. Based on the developed model, the Bisection-based Reliability Analysis Method (BRAM) is exploited to calculate the system reliabil-ity. The developed methods are applied to predicting the reliability of a Hydraulic Servo Actuator (HSA). The results demonstrate that the developed methods outperform the traditional PoF-based reliability prediction methods when applied to systems subject to failure collaboration.     

Reliability assessment of engine electronic controllers based on Bayesian deep learning and cloud computing

The reliability of an Engine Electronic Controller (EEC) attracts attention, which has a critical impact on aircraft engine safety. Reliability assessment is an important part of the design phase. However, the complex composition of EEC and the characteristic of the Phased-Mission System (PMS) lead to the difficulty of assessment. This paper puts forward an advanced approach, considering the complex products and uncertain mission profiles to evaluate the Mean Time Between Failures (MTBF) in the design phase. The failure mechanisms of complex components are deduced by Bayesian Deep Learning (BDL) intelligent algorithm. And copious samples of reliability simulation are solved by cloud computing technology. Based on the result of BDL and cloud computing, simulations are conducted with the Physics of Failure (PoF) theory and Failure Behavior Model (FBM). This reliability assessment approach can evaluate MTBF of electronic products without reference to physical tests. Finally, an EEC is applied to verify the effectiveness and accuracy of the method.     

Reliability estimation of mechanical seals based on bivariate dependence analysis and considering model uncertainty

The reliability estimation of mechanical seals is of crucial importance due to their wide applications in pumps in various mechanical systems. Failure of mechanical seals might cause leakage, and might lead to system failure and other relevant consequences. In this study, the reliability estimation for mechanical seals based on bivariate dependence analysis and considering model uncertainty is proposed. The friction torque and leakage rate are two degradation performance indicators of mechanical seals that can be described by the Wiener process, Gamma process, and inverse Gaussian process. The dependence between the two indicators can be described by different copula functions. Then the model uncertainty is considered in the reliability estimation using the Bayesian Model Average (BMA) method, while the unknown parameters in the model are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method. A numerical simulation study and fatigue crack study are conducted to demonstrate the effectiveness of the BMA method to capture model uncertainty. A degradation test of mechanical seals is conducted to verify the proposed model. The optimal stochastic process models for two performance indicators and copula function are determined based on the degradation data. The results show the necessity of using the BMA method in degradation modeling.     

星敏感器低频误差与陀螺漂移离线校正方法

获取高精度事后姿态数据是提高遥感平台成像质量的必要条件之一,离线处理可有效降低敏感器测量误差,从而获得更高的姿态确定精度。基于滤波的校正方法中,星敏感器低频误差(LFE)与陀螺漂移将产生耦合影响导致校正精度低,本文针对该问题推导了耦合误差的数学模型,并设计了一种两步双向平滑事后处理算法,将陀螺漂移与低频误差分两步校正,通过反复滤波剥离陀螺漂移与低频误差。同时,针对低频误差参数收敛速度慢、噪声参数调节困难的问题,利用一种基于极大似然估计(MLE)的固定窗口自适应双向滤波算法进行处理以获得更好的噪声估计,提高了收敛速度和收敛精度。文中仿真工况下,离线姿态确定精度可达到0.8″(3σ),低频误差参数完全收敛时间不超过4个轨道周期。     

考虑性能退化的航空发动机故障诊断量化评估

航空发动机全生命周期内的故障诊断一直是研究的热点,为保障航空发动机在性能退化条件下故障诊断算法的可靠性,对考虑性能退化的航空发动机进行故障可诊断性量化评估有着重要的意义。本文从状态量的可测量性以及最优观测器设计两个方面对退化状态下航空发动机的滑动窗口模型进行解耦处理。从故障可检测及可隔离两个方面对故障的可诊断性进行量化评估,以巴氏距离为量化标准,将量化评估问题转换为多元分布概率距离求解问题。同时,从故障空间的角度对故障可隔离性进行定义,剥离了参考故障模式的影响,将可隔离性转化为故障空间中故障模式的固有属性,并给出航空发动机故障可检测及可隔离的判据。仿真实验证明,本文所提出的方法可以在发动机性能退化条件下对控制系统传感器、执行机构故障以及发动机气路部件故障进行可诊断性量化评估。     

部分可观测信息条件下装备剩余寿命预测

 针对部分可观测信息条件下退化系统的剩余寿命(RUL)预测问题,综合利用装备的历史寿命信息和性能退化信息,采用隐马尔可夫模型(HMM)对系统进行状态评估,得到系统的转移概率矩阵和观测概率矩阵;采用Bayes方法不断更新系统状态空间的条件概率分布;利用比例故障率模型(PHM)对系统进行可靠性分析,得到系统的故障率和可靠度函数,进而得到装备的剩余寿命分布。研究表明,该方法可较准确地预测装备的剩余寿命,为保障人员提供科学的维修决策依据。     

Digital Computation Makes AFCS More Reliable

In airline service the reliability of a system is more than the confirmed failures for the system; it is the total removal experience of the system. Thus, the reliability of a system lies not only in the piece part failure rates, but also in the capability to verify and isolate failures. The application of digital technology brings several significant reliability improvements to automatic flight control systems (AFCS) when compared to contemporary analog systems. These advantages are demonstrated by the experience of the digital air data computer (DADC) of the DC-10 and the digital AFCS of the JA-37 Viggen. Experience with this equipment is reviewed, and the results are interpreted in terms of projections for airline DAFCS reliability. The digital system built-in test implemented by a stored program and the central processor gives a system integrity and dispatch reliability unequaled by analog systems. This high-integrity self-test reduces removal rates by giving line personnel a trustworthy tool and more complete automatic test processes for verifying maintenance actions. Digital circuit technology is directly suitable to largescale integrated circuits (LSIC) which reduce piece part counts and improve LRU reliability. Digital circuits are less subject to drift and the attendant difficulty to detect failures. These factors, coupled with the inherent high-integrity self-test, provide the basis for a significant improvement in reliability by the use of a digital automatic flight control system.     

Model-driven degradation modeling approaches: Investigation and review

The second law of thermodynamics implies that any animate and inanimate systems degrade and inevitably stops functioning. It is irreversible over time that can be labeled as “the degradation arrow of time”. From perspective of products’ reliability design, it is essential to build appropriate models of describing the degradation arrow of time. The current modeling approaches mainly include the model-driven (having assumed forms based on cognitive experience of mankind) and data-driven (using data learning techniques without form hypothesis) approaches. In this paper, we just investigate and review the model-driven degradation approaches, hoping to provide suggestions of the model construction or selection for scholars or engineers. First, for the single mechanism, degradation law models and stochastic process models are classified as separately depicting the tendency and fluctuation of degradation. For the degradation law model, we propose the concept of meta-models as original types for various personal models. For the stochastic process model, two main types including the non-monotonic and monotonical types are presented. Then, four multi-mechanism degradation types are discussed, that are competitive degradation, multi-stage degradation, coexistence of degradation and impact, and coexistence of degradation and failure. Besides, for the multi-performance degradation, independent and coupling models are introduced. The forms, connotations, applicability and insufficiency of these models are described with a series of examples from the literature and our own experiences. The final explicit suggestions about the potential future work are provided for the development of new degradation models.     

重力姿轨耦合效应引起的太阳能电站轨道共振

以任意相控阵天线式空间太阳能电站为研究对象,主要研究了其在轨运行过程中受到的重力姿轨耦合效应对其轨道运动的影响。首先,通过Hamilton原理建立起考虑重力姿轨耦合效应时的姿态运动和轨道运动的方程。其中,任意相控阵天线式空间太阳能电站被简化成刚体,它的重力势能以其结构尺寸和其轨道半径的比值为小量进行泰勒展开,并保留至二阶项。之后,采用解析的方法对方程进行分析,并发现当电站的姿态运动满足一定条件时,其轨道运动将会出现共振现象。此外,重力姿轨耦合效应还会引起空间太阳能电站轨道运动长期的漂移,通过选择合适的轨道运动初始条件可以消除漂移;而且,在一定条件下,重力姿轨耦合效应还会引起轨道运动的发散。最后,数值仿真结果验证了分析的正确性。