多维性能极限状态平面不规则结构易损性分析

针对平面不规则框剪结构,在引入最不利输入角度的基础上,提出多维性能极限状态的易损性分析方法。首先,利用Matlab中小波变换系数法,判别地震动的最不利输入方向;然后,采用层间位移和层间扭转角作为性能量化指标并考虑量化指标间的相关性,计算超越概率,从而得到二维性能极限状态下结构的易损性曲线。利用该方法对平面不规则框剪结构进行分析得到结构在正常使用、可以使用、生命安全、防止倒塌4个性能水平下的易损性曲线。结果表明:对于平面不规则结构,地震动输入角度对结构的抗震性能有不可忽略的影响;对平面不规则结构进行易损性分析时,应同时考虑层间位移和层间扭转角双指标的影响,防止高估这类结构的抗震性能。基于多维性能极限状态的易损性分析方法对平面不规则结构抗震性能的评估更为安全、可靠。     

强度相关同级叶片系统可靠度区间估计方法

提出了考虑相关性的同级叶片系统强度可靠度区间估计方法.该方法包括同级叶片强度随机变量相关系数分布的数值模拟方法、同级叶片强度临界状态函数之间相关系数的确定方法.再将此方法应用于考虑材料相关性时同级叶片系统可靠度的置信区间下限估计.     

基于响应面的结构非概率可靠性优化设计

将结构系统中的不确定参数描述为区间变量,在基于区间模型的可靠性分析基础上,考虑到复杂结构的极限状态函数表达式往往很难直接求出,提出了基于响应面模型的非概率可靠性结构优化方法。该方法用二次多项式拟合结构的极限状态函数,通过区间模型计算出结构的非概率可靠度,并将其作为约束条件来对结构进行优化设计,应用嵌套优化模型解决此类优化问题。最后用该方法对25杆桁架结构进行了优化,结果表明提出的方法是正确可行的。     

考虑竞争失效的交流接触器可靠性评估方法

交流接触器广泛用于电力系统,精准评估其可靠性是保障系统安全平稳运行的关键。现有交流接触器可靠性研究没有考虑三相触头的竞争失效、退化相关性,及各相触头失效阈值均有随机性等问题,可能造成可靠性评估不精准。针对这些问题,本文用累积电弧侵蚀量表征性能状态,建立了考虑竞争失效、退化相关性和失效阈值随机性的退化模型;对模型参数较多且难以同时估计所有参数的问题,提出了基于极大似然估计的多阶段参数估计方法;基于蒙特卡洛技术提出了可靠度近似计算方法,并基于黎曼和技术推导出平均故障时间的近似式;最后,通过仿真与实例分析验证了所提方法的有效性。实例分析表明所提可靠性评估方法精度较高,其拟合优度比现有方法提升了约45%。     

基于PDEM的台风作用下柱式隔离开关随机可靠性及失效风险分析

为评估柱式隔离开关在台风过程中的结构失效风险,考虑了风场和材料抗力的随机性,建立了隔离开关结构随机可靠性高效求解模型。首先,基于功率谱密度模型,考虑了地面粗糙度、平均风速和分界波数的随机性,给出了台风的随机场模型;其次,利用Abaqus有限元分析软件,建立了隔离开关结构的三维结构力学分析模型。同时,基于概率密度演化(Probability Density Evolution Model, PDEM)理论,给出了结构目标变量的概率密度函数计算方法;最后,采用Matlab-Abaqus进行联合模拟分析计算,实现了隔离开关结构可靠性的高效求解。结果表明,隔离开关绝缘支柱底部的极限应力为结构控制参数,风场和材料抗力的随机性对结构易损性曲线影响显著,设计过程中应控制材料抗力层次的随机性。     

基于〖WTHZ〗Copula函数的渡槽结构地震动易损性分析

在结构易损性分析中,由于构件之间的地震需求存在相关性,直接建立渡槽系统中基本构件的联合概率分布函数较为困难,为此引入二维Copula函数对构件地震需求之间的相关结构进行描述,简化联合分布函数的建模过程。首先,对某输水渡槽中的一跨进行时程分析,以地面峰值加速度为自变量,以排架的位移延性比和橡胶支座的变形大小为损伤指标,考虑地震动和结构参数的不确定性,建立排架、橡胶支座的易损性曲线;其次,通过Copula函数建立渡槽系统的易损性曲线;最后,通过1阶界限法得到渡槽系统易损性的上、下界。计算结果表明,基于Copula函数计算得到的失效概率均位于1阶界限法的上、下界之间。研究结果有助于简化渡槽系统易损性曲线的建模过程,为研究渡槽构件地震需求之间的相关性提供新思路和方法。     

基于单目视觉可视空间的视点规划方法

通过确定单目线激光视觉测量系统的可视区域,提出将系统可视区域与未知模型极限面相结合的未知三维模型自动重建新方法.依据初始视点下所获模型信息,构造未知空间的极限面模型,结合系统可视区域确定下一视点的可视性区间,并将可视性区间内能获取最大极限面面积的位置定为下一个最优视点的位置.最后,通过对实体模型的自动重构,验证方法的可行性及有效性.     

基于Copula函数的渡槽结构地震动易损性分析

在结构易损性分析中,由于构件之间的地震需求存在相关性,直接建立渡槽系统中基本构件的联合概率分布函数较为困难,为此引入二维Copula函数对构件地震需求之间的相关结构进行描述,简化联合分布函数的建模过程。首先,对某输水渡槽中的一跨进行时程分析,以地面峰值加速度为自变量,以排架的位移延性比和橡胶支座的变形大小为损伤指标,考虑地震动和结构参数的不确定性,建立排架、橡胶支座的易损性曲线;其次,通过Copula函数建立渡槽系统的易损性曲线;最后,通过1阶界限法得到渡槽系统易损性的上、下界。计算结果表明,基于Copula函数计算得到的失效概率均位于1阶界限法的上、下界之间。研究结果有助于简化渡槽系统易损性曲线的建模过程,为研究渡槽构件地震需求之间的相关性提供新思路和方法。     

一种区间不确定性参数的敏感度与可靠性分析方法

针对机械零部件可靠性分析时存在区间不确定性参数盲目性选择问题,提出一种基于偏弹性理论的全局敏感度与可靠性分析方法。通过用响应面法获取未知或高度非线性的极限状态函数,构建了包括区间不确定性参数的二阶多项式极限状态函数代理模型。以该函数关系为基础,结合偏弹性理论,建立了相应的加法法则和乘法法则来辨识参数间交互作用的来源,并推导了敏感度指数的计算方法。根据敏感度指数确定出区间不确定性参数的改变对可靠性影响较小的方向,进而指导参数选择时的可靠域取值范围。以滚动轴承的可靠性敏感度分析为例,验证了该方法的可行性和实用性。     

细胞分析仪取液系统的改进型FORM算法可靠性评估

加速寿命试验是设备系统可靠性分析的重要方法,如何进行加速寿命试验以及在少量数据样本状态下进行精确的可靠性评估是亟待解决的问题。本文在采用逆幂律加速模型的基础上运用ADAMS对细胞分析仪取液系统机械传动结构进行仿真。在确定易失效部件自身所能承受的最大应力条件下,利用ADAMS分析方法来获得故障数据并通过改进型FORM算法进行可靠性评估,进一步确定故障数据的极限状态函数曲线并获得验算点。通过对极限状态函数曲线及验算点的Nataf空间变换,促使维度降低并获取验算点的精确位置。利用Newton迭代方式以及MC抽样原理计算并修正可靠度值,通过对比发现,在相同数量的样本状态下评估可靠度同比LD-FORM算法提高了2.7%,在数量小于MC算法的样本状态下,比MC算法的可靠度提高了0.6%。     

Probabilistic modeling of stress-based FLD in tube hydroforming process

Recently a stress-based FLD due to its path-independency has become a new mainstream technology for prediction of forming limit in tube hydroforming processes, which usually have non-linear strain path. However, the random characteristics owing to experimental errors, inherent measuring equipment errors, dimensional tolerance of as-received blank, inconsistent lubrication condition and so on lead to uncertainty with regard to the position of the forming limit curve on the stress-based FLD. In this work, to take into account the uncertainty on the stress-based FLD, a probabilistic modeling on the stress-based FLD with confidence level is firstly attempted. With the assumption of all experimentally measured data as normally distributed random variables, stochastic evaluation of the reliability of the stress-based FLD is carried out. Moreover the statistical correlation between measured data during a bulge test and the material parameters is investigated by using the first-order approximated mean value and variance. The reliability is analytically calculated based on first-order reliability method (FORM) and verified with Monte-Carlo simulation (MCS). Finally, at a given deviation of measured data, the band width of forming limit curve on the stress-based FLD to be able to satisfy the required confidence level is determined.     

滚动轴承振动性能的混沌特性与不确定性之间的灰关系评估

鉴于滚动轴承振动性能的失效概率分布呈现多变性、非线性、不确定性等特征,提出分别用振动数据序列的Hurst指数和最大熵指标表征滚动轴承振动性能的混沌特性和不确定性。基于滚动轴承服役过程中的振动数据序列,在对数坐标系中运用最小二乘法拟合得到Hurst指数值,判断各个振动序列对应时间段内轴承运行性能状态的混沌特性。运用最大熵法求解各振动序列的最大熵值,进而对轴承振动性能的不确定性进行定量分析。运用灰关系分析法,计算均值归一化后的Hurst指数和最大熵序列之间的灰置信水平,分析轴承振动性能的混沌特性和不确定性之间的非线性相关程度。两个案例中Hurst指数与最大熵序列之间的灰置信水平分别为96.99%和82.1%,表明轴承振动性能的混沌特性和不确定性之间的关系非常紧密。     

Bayesian nonlinear structural equation modeling for hierarchical validation of dynamical systems

This paper presents a new Bayesian nonlinear structural equation modeling approach to hierarchical model assessment of dynamic systems, considering uncertainty in both predicted and measured time series data. A generalized structural equation modeling with nonlinear latent variables is presented to model two sets of relationships in multivariate hierarchical model assessment, namely, the computational model to system-level data, and low-level data to system-level data. A hierarchical Bayesian network with Markov Chain Monte Carlo simulation and Gibbs sampling is developed to represent the two relationships and estimate the influencing factors between them. A Bayesian interval hypothesis testing-based method is employed to quantify the confidence in the predictive model at various levels. The effect of low-level data on the model assessment at the system level is identified by Bayesian inference and factor analysis. The proposed methodology is implemented for hierarchical model validation of three dynamic system problems.     

Bayes filter for dynamic coordinate measurements – Accuracy improvment,data fusion and measurement uncertainty evaluation

This paper presents a novel methodology to improve the measurement accuracy of dynamic measurements. This is achieved by deducing an online Bayes optimal estimate of the true measurand given uncertain, noisy or incomplete measurements within the framework of sequential Monte Carlo methods. The estimation problem is formulated as a general Bayesian inference problem for nonlinear dynamic systems. The optimal estimate is represented by probability density functions, which enable an online, probabilistic data fusion as well as a Bayesian measurement uncertainty evaluation corresponding to the “Guide to the expression of uncertainty in measurement“. The efficiency and performance of the proposed methodology is verified and shown by dynamic coordinate measurements.     

A dynamic multi-scale Markov model based methodology for remaining life prediction

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.     

Grey Relation between Nonlinear Characteristic and Dynamic Uncertainty of Rolling Bearing Friction Torque

The rolling bcaring friction torque which is characterized by its uncertainty and nonlinearity affects heavily the dynamic performance of a system such as missiles, spacecrafls and radars, etc. It is difficult to use the classical statistical theory to evaluate the dynamic evaluation of the rolling bearing friction torque for the lack of prior information about both probability distribution and trends. For this reason, based on the information poor system theory and combined with the correlation dimension in chaos theory, the concepts about the mean of the dynamic fluctuant range (MDFR) and the grey relation are proposed to resolve the problem about evaluating the nonlinear characteristic and the dynamic uncertainty of the rolling bearing friction torque. Friction torque experiments are done for three types of the rolling bearings marked with HKTA, HKTB and HKTC separately; meantime, the correlation dimension and MDFR are calculated to describe the nonlinear characteristic and the dynamic uncertainty of the friction torque, respectively. And the experiments reveal that there is a certain grey relation between the nonlinear characteristic and the dynamic uncertainty of the rolling bearing friction torque, viz. MDFR will become the nonlinear increasing trend with the correlation dimension increasing. Under the condition of fewer characteristic data and the lack of prior information about both probability distribution and trends, the unitive evaluation for the nonlinear characteristic and the dynamic uncertainty of the rolling bearing friction torque is realized with the grey confidence level of 87.7%-96.3%.     

基于参数估计区间的应力-强度干涉模型

经典干涉模型未考虑设计变量的统计性不确定性影响,笔者从应力-强度干涉模型和统计区间估计理论出发,给出了考虑统计性不确定性的可靠性指标β的描述与计算,建立了基于参数估计区间的应力-强度干涉模型,获得了统计性不确定性和样本容量之间的关系。分析结果表明:笔者提出的干涉模型可以很好地描述统计性不确定性。     

Reliability estimation for cutting tools based on logistic regression model using vibration signals

As an important part of CNC machine, the reliability of cutting tools influences the whole manufacturing effectiveness and stability of equipment. The present study proposes a novel reliability estimation approach to the cutting tools based on logistic regression model by using vibration signals. The operation condition information of the CNC machine is incorporated into reliability analysis to reflect the product time-varying characteristics. The proposed approach is superior to other degradation estimation methods in that it does not necessitate any assumption about degradation paths and probability density functions of condition parameters. The three steps of new reliability estimation approach for cutting tools are as follows. First, on-line vibration signals of cutting tools are measured during the manufacturing process. Second, wavelet packet (WP) transform is employed to decompose the original signals and correlation analysis is employed to find out the feature frequency bands which indicate tool wear. Third, correlation analysis is also used to select the salient feature parameters which are composed of feature band energy, energy entropy and time-domain features. Finally, reliability estimation is carried out based on logistic regression model. The approach has been validated on a NC lathe. Under different failure threshold, the reliability and failure time of the cutting tools are all estimated accurately. The positive results show the plausibility and effectiveness of the proposed approach, which can facilitate machine performance and reliability estimation.     

基于被动激励的结构应变监测系统在线校准方法

针对在役桥梁结构应变监测系统全天时工况下的在线校准问题,提出了一种基于被动激励的在线校准方法,建立了在线校准系统模型。该模型以桥梁正常通行车辆的动态荷载为激励源,通过应变监测系统与参考系统对结构应变响应参量的同步测量,构建校准溯源链,实现在役应变监测系统不间断工作状态下的在线校准。根据结构应变监测系统计量性能评测需要,建立了基于大样本数据的期间测量误差、基本误差及置信区间的量化分析模型。依托广东九江大桥开展了试验验证,结果表明,所提方法具有现场实施的可行性,由不同数据集计算所得的在线校准结果一致性较好,在包含概率大于90%时,基本误差区间的半宽度偏差不大于±0.005。     

质量相关的回转窑故障诊断

针对水泥烧制过程工艺复杂,各变量数据之间存在强耦合关系的特点,提出了偏最小二乘(partial least squares,PLS)算法结合贡献图分析的方法,应用到回转窑系统中进行故障诊断。该文选取质量变量,建立过程变量和质量变量之间的回归关系,构建PLS模型实现通过过程变量数据对质量变量数据的预测。设置一定置信度的控制限,对超过控制限的故障进行报警。通过相对贡献图方法找出对故障贡献最大的变量,分析故障原因。仿真结果表明,该方法可以及时检测到影响水泥品质的故障并确定故障原因。