多类型冲击的竞争失效过程可靠性建模研究

针对连续性退化过程中同时存在多种类型冲击的问题,在变失效阈值模型的基础上,建立考虑多种类型冲击的竞争失效模型。首先,基于变阈值失效模型分析多种冲击类型同时存在时对系统可靠性的影响,给出模型的主要失效模式;然后结合极值冲击模型给出竞争失效可靠性建模的一般方法,求解竞争失效可靠性模型的解析表达式;最后,以某微型发动机为研究对象,对该文提出的方法进行对比验证,证明该方法能有效防止对系统可靠性的盲目乐观估计,防止突发故障的发生。     

弹载加速度记录仪在冲击环境下的失效研究

在弹体侵彻过程中,首先分析高g值冲击对弹载加速度记录仪的影响,得出应力波作用下加载到弹体内记录仪的加速度值,并研究了加速度记录仪壳体、缓冲材料及电路板的动态结构响应,进而提出可能出现的失效模式：壳体结构的失效、缓冲材料缓冲性能的不足、芯片与PCB板相对运动导致芯片的裂纹。针对各失效模式,利用ANSYS/LS-DYNA对记录仪各防护单元进行了数值模拟仿真,得出各防护单元失效的临界冲击加速度值: 电路板失效的临界冲击加速度为1.93×104g,当加载冲击加速度为1.63×105g时,壳体发生屈曲;增大冲击加速度至5.63×106g时,缓冲材料失效。经过实弹侵彻试验,得出记录仪在1.5×105g的冲击加速度下失效。该实验结果对后续弹体实际侵彻弹载记录仪的设计及优化提供数据支撑。     

不同冲击速度条件下矩形巷道围岩变形-开裂过程数值模拟

利用自主开发的拉格朗日元与变形体离散元耦合的连续-非连续方法,开展了不同冲击速度条件下矩形巷道围岩变形-开裂过程的数值模拟研究。当岩石单元的应力满足剪切开裂判据时,考虑了应力脆性跌落效应,在此过程中,围压保持不变。为了检验该方法的正确性,开展了单轴压缩条件下岩样变形-开裂过程的数值模拟研究。针对矩形巷道围岩的计算表明:①冲击速度低时载荷-位移曲线呈单峰特点;冲击速度高时载荷-位移曲线呈多峰特点;②冲击速度低时围岩的开裂呈渐进性特点;冲击速度高时围岩的开裂呈间歇性特点,这与在冲击过程中围岩中过去形成的一种较为稳定的结构(拱)被打破,并在其外围形成了新的稳定结构(拱)有关;③在模型相同垂直方向位移时,冲击速度低时围岩两帮的开裂深度较大,这说明冲击速度低时应力的传递较为均匀,冲击速度低时的结果(例如,V形坑内岩石碎块涌入巷道)与围岩的片帮类似;冲击速度高时的结果(例如,岩石碎块的弹射现象)与岩爆类似。     

钢质圆柱壳在侧向局部冲击荷载下的变形及失效破坏

基于动力有限元程序LS-DYNA及随动塑性Cowper-Symonds模型,对两端固支钢质薄壁圆柱壳经受半球头弹体侧向局部冲击的非线性动力响应问题进行数值模拟,获得了不同冲击条件下圆柱壳的变形及破坏模态,并研究了弹体在不同周向冲击倾角时壳壁产生穿透性破裂的最小速度（临界破裂速度）。研究表明,圆柱壳破坏模式与弹体冲击倾角θ0、冲击速度V等因素密切相关,将发生局部凹陷、碟形变形及穿透现象,且临界破裂速度随冲击倾角的增大而增大。研究结果可应用于圆柱壳在侧向局部冲击作用下的毁伤预测,从而为圆柱壳结构的安全防护设计提供理论依据。     

基于逆高斯过程的竞争失效建模研究北大核心CSSCI

考虑在逆高斯退化过程中发生突发失效,退化失效与突发失效相互竞争导致产品失效的情况,并且考虑突发失效与退化失效的相关性,建立基于逆高斯退化过程的竞争失效可靠性评估模型。采用极大似然估计法对模型进行了参数估计。最终通过某退化试验数据验证了模型的有效性。     

K8型单层球面网壳顶点竖向冲击下的冲击荷载特征及荷载简化模型

为简化网壳结构遭受冲击作用时复杂的接触分析过程,基于ANSYS/LS-DYNA建立了单层K8型球面网壳模型,并模拟其在不同冲击作用下的失效过程,辨别网壳的失效模式,并获取了冲击过程中的冲击力曲线。通过对网壳遭受竖向冲击荷载下的这些冲击力曲线特征进行分析,提出了简化的冲击荷载模型,并应用能量守恒定律和动量定理确定了模型相关参数。利用此冲击力模型对网壳结构在冲击荷载下的响应进行分析并与实体冲击物作用下的响应进行了对比,验证了该模型的准确性,应用该模型可以实现对网壳抗冲击性能的简单有效评估。     

冲击-切削联合破碎瓷砖机理与建模

为了研究磨头磨粒的破碎瓷砖机理,分析抛光机的结构和运行原理,提出磨粒在冲击与切削联合作用下破碎瓷砖,并分析其机理。建立磨粒冲击破碎瓷砖和切削破碎瓷砖的模型,综合理论分析得出：磨头转速、磨头压力、磨粒粒度号是影响瓷砖破碎的主要因素。多磨块磨头可以提高瓷砖的磨削深度。     

冰雹冲击复合材料层合板失效模式分析与数值模拟

针对复合材料层合板结构,建立了冰雹冲击复合材料层合板的有限元模型,在充分考虑冲击过程中冰雹的流体特性下,给出了冰雹和复合材料层合板的材料模型和损伤准则,利用显式有限元分析工具LS-DYNA研究了不同冰雹冲击速度下复合材料层合板的临界破坏速度和破坏形式。结果表明,文中给出的冰雹、复合材料层合板的材料模型和损伤准则能够合理地再现冰雹冲击复合材料板的过程;复合材料层合板(AS4/8552)在冰雹高速冲击下首先发生的是基体开裂,当冰雹速度到达125m/s时,层合板上表面纤维发生断裂,但在整个冰雹冲击过程中层合板没有发生压缩失效     

水下爆炸条件下不同装药对水面舰船冲击环境的影响试验研究

水下非接触爆炸产生的冲击往往会造成舰船设备的大范围破坏,从而影响舰船的生命力和战斗力。为此,对以船体结构动响应为输入条件的船用设备冲击环境的研究受到了各国海军的重视。其中,研究水下爆炸载荷与舰船冲击环境之间的联系对于舰船设备抗冲击设计以及提高水中兵器作战效能等都具有极其重要的意义。利用某型船的整体缩比模型进行水下非接触爆炸试验,通过自由场水下爆炸载荷和缩比模型冲击环境变化规律对比,得出了冲击环境主要参数与水下爆炸载荷之间的关系,试验结果具有参考价值。     

船桥碰撞过程引发的冲击动力学论题

对船桥撞击过程引发的几个冲击动力学论题进行了分析。研究表明:1为降低船撞力,应采用柔性(低的结构动态广义波阻抗)防撞装置;2撞击力所做的功,通过应力波传播转化为内能(变形能)与动能之和;而变形能中的不可逆部分愈高,防撞装置发挥的整体作用愈大,则愈有利于防撞装置发挥缓冲耗能作用。并且如何让船舶尽早结束撞击并带走尽量多的剩余动能,应是防撞装置设计的关键点;3黏性耗能可缓冲撞击过程、延长撞击历时,有利于防撞装置发挥整体作用,进而为船舶在低应力下转向滑离、从而带走尽可能多的剩余动能创造条件。因此,船撞桥防护装置的设计应该建立在如下的科学设计理念上:ⅰ低波阻抗意义上的冲击柔性,ⅱ缓冲撞击过程意义上的粘性耗能,ⅲ防撞装置能及早发挥整体作用,化撞击集中力为分布载荷,以及ⅳ让船尽早滑离而带走尽量多的剩余动能。以钢丝绳防撞圈为主要元件的柔性耗能防撞装置是这一防撞理念的工程应用实例,其有效性已为工程实践和实船撞击试验证实。     

Reliability modeling for multistage systems subject to competing failure processes

In this paper, a novel multistage reliability model is provided as systems are often divided into many stages according to system degradation characteristics. Multistage hard failure (caused by random shock) process (MHFP) and multistage soft failure (caused by random shock and continuous degradation) process (MSFP) are introduced to describe the competing failure processes, where either the MSFP or MHFP would break down the system. The shock processes impact the system in three ways: (1) fatal load shocks cause hard failure immediately in the hard failure process; (2) time shocks cause a hard failure threshold changing; (3) damage load shocks cause degradation level increasing in the soft failure process. In this paper, a density function dispersion method is carried out to address the multistage reliability model, and the effectiveness of the proposed models is demonstrated by reliability analysis with the one-stage model. Finally, the multistage model is applied to a case study, the degradation process is divided into three stages, and the hard failure threshold can be transmitted twice. The proposed model can be applied in other multistage situations, and the calculation method can satisfy the accuracy requirements.     

Reliability modeling for competing failure processes considering degradation rate variation under cumulative shock

Most systems experience both random shocks (hard failure) and performance degradation (soft failure) during service span, and the dependence of the two competing failure processes has become a key issue. In this study, a novel dependent competing failure processes (DCFPs) model with a varying degradation rate is proposed. The comprehensive impact of random shocks, especially the effect of cumulative shock, is reasonably considered. Specifically, a shock will cause an abrupt degradation damage, and when the cumulative shock reaches a predefined threshold, the degradation rate will change. An analytical reliability solution is derived under the concept of first hitting time (FHT). Besides, a one-step maximum likelihood estimation method is established by constructing a comprehensive likelihood function. Finally, the reasonability of the closed form reliability solution and the feasibility and effectiveness of the proposed DCFPs modeling methodology are demonstrated by a comparative simulation study.     

Reliability assessment models for dependent competing failure processes considering correlations between random shocks and degradations

This article develops reliability models for systems subject to two dependent competing failure processes, considering the correlation between additional damage size on degradation in soft failure process and stress magnitude of shock load in hard failure process, both of which are caused by the same kth random shock. The generalized correlative reliability assessment model based on copulas is proposed, which is then extended to three different shock patterns: (1) δ‐shock, (2) m‐shock, and (3) m‐run shocks. There are some statistical works to be introduced in reliability modeling, including data separation of total degradation amount, inferring the distribution of amount of aging continuous degradation at time t, and fitting copula to the specific correlation. The developed reliability models are demonstrated for an application example of a micro‐electro‐mechanical system.     

Reliability analysis for multi-state systems subject to distinct random shocks

This paper analyzes the competing and dependent failure processes for multi-state systems suffering from four typical random shocks. Reliability analysis for discrete degradation is conducted by explicitly modeling the state transition characteristics. Semi-Markov model is employed to explore how the system vulnerability and potential transition gap affect the state residence time. The failure dependence is specified as that random shocks can not only lead to different abrupt failures but also cause sudden changes on the state transition probabilities, making it easier for the system to stay at the degraded states. Reliability functions for all the exposed failure processes are presented based on the corresponding mechanisms. Interactions between different failure processes are also taken into account to evaluate the actual reliability levels in the context of degradation and distinct random shocks. An illustrative example of a multi-state air conditioning system is studied to demonstrate how the proposed method can be applied to the engineering practice.     

Reliability modeling for consecutive k-out-of-n: F systems with local load-sharing components subject to dependent degradation and shock processes

Traditional k-out-of-n models assume that the components are independent, while recent research studies assume that the components are dependent caused by global load-sharing characteristic. In this paper, we investigate the consecutive k-out-of-n systems with dependent components by local load-sharing characteristic. The work load and shock load on failed components will be equally shared by adjacent components, so the components tend to fail consecutively. Consequently, the components degradation processes may be diverse, since their degradation rate (dependent on work load) and abrupt degradation (dependent on shock load) become unequal because of local load-sharing effect. Furthermore, the system failure will be path-dependent on the failure sequences of components, which results in that the same system states may have different system failure probabilities. This new dependence makes the system reliability model more complex. In this work, an analytical model that can be solved numerically is derived to compute the reliability with this complex dependence. The developed model is demonstrated by a cable-strut system in the suspension bridge. The results show that the reliability decreases significantly when the new dependence is considered.     

基于比例危险模型的产品竞争失效分析

突发型失效与退化型失效共存的竞争失效问题在实践中大量存在，一般情况下突发失效是受退化量大小影响的。文中利用比例危险模型分析了突发失效与退化量的关系，给出了竞争失效的一般模型及模型的参数估计方法，最后利用所给模型对强激光装置所用的金属化膜脉冲电容器进行了可靠性分析。     

A new combinatorial model for deterministic competing failure analysis

Components in many engineering and industrial systems can experience propagated failures, which not only cause the failure of the component itself but also affect other components, causing extensive damage to the entire system. However, in systems with functional dependence behavior where failure of a trigger component may cause other components (referred to as dependent components) to become unusable or inaccessible, failure propagation originating from a dependent component could be isolated if the corresponding trigger component fails first. Thus, a time-domain competition exists between the failure propagation effect and the failure isolation effect, which poses a great challenge to the system reliability modeling and analysis. In this work, a new combinatorial model called competing binary decision diagram (CBDD) is proposed for the reliability analysis of systems subject to the competing failure behavior. In particular, special Boolean algebra rules and logic manipulation rules are developed for system CBDD model generation. The corresponding evaluation algorithm for the constructed CBDD model is also proposed. The proposed CBDD modeling method has no limitation on the type of component time-to-failure distributions. A memory system example and a network example are provided to demonstrate the application of the proposed model and algorithms. Correctness of the proposed method is verified using the Markov method.     

Reliability Analysis and Condition‐based Maintenance for Failure Processes with Degradation‐dependent Hard Failure Threshold

In this study, we introduce reliability models for a device with two dependent failure processes: soft failure due to degradation and hard failure due to random shocks, by considering the declining hard failure threshold according to changes in degradation. Owing to the nature of degradation for complex devices such as microelectromechanical systems, a degraded system is more vulnerable to force and stress during operation. We address two different scenarios of the changing hard failure threshold due to changes in degradation. In Case 1, the initial hard failure threshold value reduces to a lower level as soon as the overall degradation reaches a critical value. In Case 2, the hard failure threshold decreases gradually and the amount of reduction is proportional to the change in degradation. A condition‐based maintenance model derived from a failure limit policy is presented to ensure that a device is functioning under a certain level of degradation. Finally, numerical examples are illustrated to explain the developed reliability and maintenance models, along with sensitivity analysis. Copyright © 2016 John Wiley & Sons, Ltd.     

Reliability analysis of electronic devices with multiple competing failure modes involving performance aging degradation

This paper presents an extension of reliability analysis of electronic devices with multiple competing failure modes involving performance aging degradation. The probability that a product fails on a specific mode is derived. Using this probability, the dominant failure mode on the product can be predicted. A practical example is presented to analyze an electronic device with two kinds of major failure modes–solder/Cu pad interface fracture (a catastrophic failure) and light intensity degradation (a degradation failure). Reliability modeling of an individual failure mode and device reliability analysis is presented and results are discussed. Copyright © 2003 John Wiley & Sons, Ltd.     

Optimal Bayesian maintenance policy for a gearbox subject to two dependent failure modes

Most maintenance optimization models of gear systems have considered single failure mode. There have been very few papers dealing with multiple failure modes, considering mostly independent failure modes. In this paper, we present an optimal Bayesian control scheme for early fault detection of the gear system with dependent competing risks. The system failures include degradation failure and catastrophic failure. A three‐state continuous‐time–homogeneous hidden Markov model (HMM), namely the model with unobservable healthy and unhealthy states, and an observable failure state, describes the deterioration process of the gear system. The condition monitoring information as well as the age of the system are considered in the proposed optimal Bayesian maintenance policy. The objective is to maximize the long‐run expected average system availability per unit time. The maintenance optimization model is formulated and solved in a semi‐Markov decision process (SMDP) framework. The posterior probability that the system is in the warning state is used for the residual life estimation and Bayesian control chart development. The prediction results show that the mean residual lives obtained in this paper are much closer to the actual values than previously published results. A comparison with the Bayesian control chart based on the previously published HMM and the age‐based replacement policy is given to illustrate the superiority of the proposed approach. The results demonstrate that the Bayesian control scheme with two dependent failure modes can detect the gear fault earlier and improve the availability of the system.