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基于可靠性理论的包装振动试验方法改进 总被引:1,自引:0,他引:1
目的基于可靠性理论改进包装件的振动试验方法。方法通过界定产品平均寿命、试验截止时间和失效数,研究了样本大小对整个试验可靠程度的影响,以及改变包装阻尼与振动频率对试件振动幅值的影响。结果保证包装产品的可靠性有必要明确样本的大小,样本过小将不能完全体现该批产品的可靠程度;样本过大,虽然能充分体现该批产品的可靠程度,但试验费用将大大提高。随着产品样本的增大,使用者的风险降低。结论在包装件振动试验中融入可靠性理论,并在试验标准中加入失效率验证程序和失效率等级等内容,提高了包装件的可靠性。 相似文献
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包装件或产品的共振频率、振动传输比、阻尼等因素组成了包装系统的动态特性,它是由包装材料与整体包装系统共同决定的。包装系统的动态特性能够反映出在一定的运输环境(冲击、振动)下,包装对产品的保护能力。因此在进行包装设计时,经常需要测试包装件或产品的共振频率,根据共振点来设计包装系统,避免包装件在实际运输过程中发生共振现象。 相似文献
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目的研究计算机有限元仿真在缓冲包装研发环节的可靠性。方法利用计算机仿真进行缓冲包装研发,能够较全面地提供所需参数,缩短开发周期,但计算机仿真的可靠性有待进一步验证。通过Ansys Workbench对智能灯泡包装件的缓冲特性进行仿真分析,主要分析包装衬垫的加速度响应,并结合传统的振动与跌落试验进行对比。结果振动、跌落的仿真结果与真实试验的结果误差分别为9%和15.91%,排除客观存在的误差,两者差异在可接受范围内。结论验证了有限元仿真方法在缓冲包装研发环节的可靠性,可为传统的包装研发环节提供新方法。 相似文献
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为了揭示开槽填充黏弹性材料对锯片振动特性的影响规律,分别对无槽及开槽填充材料两种锯片模型的阻尼以及动态响应特性进行比较研究.首先,基于模态应变能法计算锯片模态阻尼比,利用Rayleigh阻尼表征模型结构阻尼,获得2种锯片模型的模态阻尼常数;然后,建立锯片有限元瞬态动力学分析模型,得出2种锯片模型的振动响应及衰减历程曲线,分析开槽填充材料对锯片振动的影响;最后,针对2种锯片进行试验模态分析,获得振动响应曲线,对比数值分析结果与试验数据曲线,两者吻合良好,证明了有限元数值分析的可靠性.结果表明:在相同的动力学条件下,开槽填充材料会显著降低锯片上质点的振动速度,缩短锯片振动的衰减历程.研究结果为开槽低噪声锯片的结构创新设计与开发提供了有效的理论依据. 相似文献
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针对圆柱壳振动特性,给出局部约束阻尼柱壳模型。基于弹性、粘弹性本构方程用能量法建立动力学方程,研究阻尼段结构参数变化对振动特性影响。建立以阻尼轴向与周向分段数、阻尼段轴向与周向间隙、阻尼层厚度为设计变量,前三阶模态最大损耗因子为目标函数,利用多目标遗传算法对两端简支柱壳进行优化分析。通过分析、比较优化前后结构模态固有频率变化、损耗因子变化及幅频响应表明,合理贴敷阻尼段能有效减少阻尼材料用量,且在不改变柱壳固有振动属性条件下能达到更好的减振效果。 相似文献
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《噪声与振动控制》2016,(4)
创建气激载荷作用下的黏弹性阻尼板的振动特性分析模型是黏弹性阻尼减振研究的一项重要内容。基于实验数据,以薄板为对象,提出一种简单易行的气动载荷作用下黏弹性悬臂薄板振动特性的有限元建模方法。首先,简要介绍该建模方法的一般流程。接着,采用自制的气激试验台对贴敷黏弹性阻尼材料前后的悬臂薄板振动特性进行测试,获得气激载荷作用下板的共振频率及共振响应。再则,从有限元建模的需要出发,用计算流体力学仿真软件Fluent获取试验中作用于薄板上的气动载荷。然后按照反推法及薄板阻尼处理前后的耗能规律得到有限元建模所需的黏弹性材料杨氏模量和损耗因子。最后,引入所确定的气动载荷和黏弹性材料相关参数,对黏弹性阻尼板的谐响应进行计算,将分析结果与实验比对证实了分析模型的合理性。 相似文献
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包装件在流通过程中经常受到非高斯随机振动激励的作用,提出了一种包装件在非高斯随机振动激励条件下的时变可靠性的分析方法。结合多项式混沌扩展和Karhunen-Loeve扩展,提出了基于功率谱(或自相关函数)、均值、方差、偏斜度和峭度信息的非高斯随机振动激励的模拟方法;为减小数值分析量,应用拟蒙特卡洛法,在随机变量空间中合理控制变量的分布模拟非高斯随机振动激励,通过四阶龙格库塔法分析,用较少的随机振动模拟样本准确得到了包装件加速度响应的前四阶矩和自相关函数。基于响应的统计信息,应用该研究提出的多项式混沌扩展、Karhunen-Loeve扩展和拟蒙特卡洛分析,获得包装件加速度响应样本,计算包装件的时变可靠性,用原始蒙特卡洛法验证了计算的准确性;该方法在包装件的可靠性分析、包装系统优化等方面具有重要意义。 相似文献
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目的 考虑真实随机振动的非高斯特性,提出一种根据已知信息生成与其相符的非高斯随机振动过程的数值模拟方法。方法 基于均值、方差、偏斜度、峭度及功率谱密度函数(或自相关函数)等约束条件,对非高斯随机振动进行模拟。根据功率谱获取非高斯过程的自相关矩阵;通过Hermite多项式的正交性质和多项式混沌展开方法推导出的公式,构造满足标准正态分布随机过程的协方差矩阵,并对其进行谱分解和主成分分析;最后,利用Karhunen-Loeve展开和多项式混沌展开来表示所模拟的非高斯振动过程。结果 随着采样点个数的增加,实测数据与模拟数据之间的误差越来越小,该方法具有较好的模拟精度。结论 应用多项式混沌展开、Karhunen-Loeve展开以及蒙特卡洛等方法,可生成非高斯随机振动过程,并得到准确有效的各项统计参数模拟值。 相似文献
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Stochastic analysis of structures using probability methods requires the statistical knowledge of uncertain material parameters. This is often quite easier to identify these statistics indirectly from structure response by solving an inverse stochastic problem. In this paper, a robust and efficient inverse stochastic method based on the non-sampling generalized polynomial chaos method is presented for identifying uncertain elastic parameters from experimental modal data. A data set on natural frequencies is collected from experimental modal analysis for sample orthotropic plates. The Pearson model is used to identify the distribution functions of the measured natural frequencies. This realization is then employed to construct the random orthogonal basis for each vibration mode. The uncertain parameters are represented by polynomial chaos expansions with unknown coefficients and the same random orthogonal basis as the vibration modes. The coefficients are identified via a stochastic inverse problem. The results show good agreement with experimental data. 相似文献
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车-桥耦合系统不可避免的受到系统参数不确定性的影响,为了研究车-桥耦合系统参数随机性的影响,提出了可考虑动态时变系统参数不确定性的PC-ARMAX (Polynomial Chaos expansions and AutoRegressive Moving-Average with eXogenous inputs) 模型。该模型采用ARMAX模型建立了不同系统参数条件下的代理模型,针对不同系统参数条件下代理模型的参数进行混沌多项式展开。在不考虑随机轨道不平顺影响的条件下,分析了车体质量、二系刚度和阻尼等参数随机性对车-桥响应的影响。研究了轨道不平顺随机性和参数不确定性共同作用的影响。结果表明:该模型的预测结果和蒙特卡洛模拟(MCS)的结果吻合,最大误差仅为2%,计算效率较MCS提高了2个~3个数量级;车体质量参数随机对车辆响应的影响最大,系统参数随机性的影响在车-桥耦合振动分析中是不可忽略,且同时考虑参数不确定性和激励随机性的影响是必要的。 相似文献
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借助参数化UM(universal mechanism)仿真模型,考虑车辆载重、悬挂参数和轮轨参数的随机性,建立某型跨座式单轨车辆的随机平稳性模型。然后,在有限试验设计样本数限制下,以最佳近似精度为目标,结合低阶交互截断、最小角回归、最小二乘法和留一法交叉验证等实现广义多项式混沌(generalized polynomial chaos,gPC)的自适应稀疏展开。分别基于拉丁超立方抽样(Latin hypercube sampling,LHS)方法和自适应稀疏gPC方法,讨论三种速度等级下单轨车辆平稳性指标的概率分布特征和全局灵敏度。算例表明:相比LHS结果,基于gPC近似模型的随机结果更为准确可靠,尤其是在高阶统计矩方面;同一速度等级下垂向平稳性指标均值要大于横向平稳性指标均值,并且随着速度的增大各平稳性指标的离散性在减小,而75 km/h下的分布特征与正态分布的差异最为明显;车辆载重、走行轮垂向刚度、水平轮径向刚度、空气弹簧垂向阻尼是对平稳性指标方差贡献最主要的随机参数。 相似文献
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铁路非高斯随机振动的数字模拟与包装件响应分析 总被引:4,自引:3,他引:1
目的研究铁路振动环境的非高斯特性,并分析包装件在非高斯随机振动环境条件下的响应情况。方法结合离散傅里叶变换与EARPG(1)模型,模拟了铁路随机振动信号。根据采集的数据的PSD曲线计算幅值,利用EARPG(1)模型生成了具有尖峰特征的模拟信号,计算了相位并进行了相位整体平移,根据幅值和相位,合成了所需的非高斯随机振动信号。将包装件简化为单自由度系统,分析了包装件在非高斯振动条件下的响应情况。结果铁路随机振动的峭度大于3,偏斜度为0,属于对称超高斯随机振动,提出的模型可准确模拟出铁路振动的非高斯特性,峭度和偏斜度的误差均小于3%,包装系统的固有频率、阻尼比、激励峭度对系统的响应的峭度、均方根均有较大的影响。结论通过合理地选择包装系统的固有频率和阻尼比,可有效减小系统的响应峭度和均方根,提高包装系统的可靠性。 相似文献
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This paper is concerned with aircraft aeroelastic interactions and the propagation of parametric uncertainties in numerical simulations using high-fidelity fluid flow solvers. More specifically, the influence of variable operational and structural parameters (random inputs) on the drag performance and deformation (outputs) of a flexible wing in transonic regime, is assessed. Because of the complexity of fluid flow solvers, non-intrusive uncertainty quantification techniques are favored. Polynomial surrogate models based on homogeneous chaos expansions in the random inputs are commonly considered in this respect. The polynomial expansion coefficients are constructed using either structured sampling sets of the input parameters, as Gauss quadrature nodes, or unstructured sampling sets, as in Monte-Carlo methods. In complex systems such as the advanced aeroelastic test case studied here, the output quantities of interest generally depend only weakly on the multiple cross-interactions between the random inputs. Consequently, only low-order polynomials significantly contribute to their surrogates, which thus have a sparse structure in the underlying polynomial bases. This feature prompts to use compressed sensing, or compressive sampling theory for the construction of the polynomial surrogates. The proposed methodology is non-adapted and considers unstructured sampling sets orders of magnitude smaller than the ones required by the usual techniques with structured sampling sets. It is illustrated in the present work for a moderately to high dimensional parametric space. 相似文献
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Xiaohui Guo Jia Li Dongbin Xiu Alina Alexeenko 《International journal for numerical methods in engineering》2010,84(10):1257-1272
Two squeeze‐film gas damping models are proposed to quantify uncertainties associated with the gap size and the ambient pressure. Modeling of gas damping has become a subject of increased interest in recent years due to its importance in micro‐electro‐mechanical systems (MEMS). In addition to the need for gas damping models for design of MEMS with movable micro‐structures, knowledge of parameter dependence in gas damping contributes to the understanding of device‐level reliability. In this work, two damping models quantifying the uncertainty in parameters are generated based on rarefied flow simulations. One is a generalized polynomial chaos (gPC) model, which is a general strategy for uncertainty quantification, and the other is a compact model developed specifically for this problem in an early work. Convergence and statistical analysis have been conducted to verify both models. By taking the gap size and ambient pressure as random fields with known probability distribution functions (PDF), the output PDF for the damping coefficient can be obtained. The first four central moments are used in comparisons of the resulting non‐parametric distributions. A good agreement has been found, within 1%, for the relative difference for damping coefficient mean values. In study of geometric uncertainty, it is found that the average damping coefficient can deviate up to 13% from the damping coefficient corresponding to the average gap size. The difference is significant at the nonlinear region where the flow is in slip or transitional rarefied regimes. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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M. Arnst R. Ghanem E. Phipps J. Red‐Horse 《International journal for numerical methods in engineering》2014,97(5):352-376
We address the curse of dimensionality in methods for solving stochastic coupled problems with an emphasis on stochastic expansion methods such as those involving polynomial chaos expansions. The proposed method entails a partitioned iterative solution algorithm that relies on a reduced‐dimensional representation of information exchanged between subproblems to allow each subproblem to be solved within its own stochastic dimension while interacting with a reduced projection of the other subproblems. The proposed method extends previous work by the authors by introducing a reduced chaos expansion with random coefficients. The representation of the exchanged information by using this reduced chaos expansion with random coefficients enables an expeditious construction of doubly stochastic polynomial chaos expansions that separate the effect of uncertainty local to a subproblem from the effect of statistically independent uncertainty coming from other subproblems through the coupling. After laying out the theoretical framework, we apply the proposed method to a multiphysics problem from nuclear engineering. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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目的 在多种类型的模型中挑选出最优包装件模型,并实现参数识别的方法。方法 文中将包装件模型构建为参数不确定模型,在贝叶斯推理的框架下,采用马尔可夫链蒙特卡洛法识别模型参数,采用偏差信息准则(DIC)计算各备选模型的DIC参数,选择出最优包装件模型。结果 在振动实验台用质量块–缓冲材料模拟包装件并进行随机振动测试,分析结果表明,Bouc–Wen(n=2)模型为文中包装系统的最佳模型。结论 文中提出的基于贝叶斯推理的包装件模型优化选择和参数识别方法考虑了模型不确定性,构建的模型可准确预测包装件在随机振动下加速度响应的时域信号。 相似文献