Xianzhen Huang

Sensitivity analysis for vibration transfer path systems with non-viscous damping:

In this paper, based on the dynamic sensitivity technique, we propose a method for sensitivity analysis of vibration transfer path systems with respect to their path parameters. It is well known that non-viscous damping is an important factor in causing the nonlinearity of vibration systems. The sensitivity of nonlinear vibration systems with respect to different kinds of non-viscous damping is discussed. With the sensitivity of dynamic responses with respect to transfer path parameters as an evaluation criterion, the contribution level of each transfer path to the vibration of acceptance structures was listed in order. Using the proposed method, the sensitivity of the vibration system with multiple and/or multi-dimensional transfer paths could be determined explicitly and accurately in the time domain.In this paper, based on the dynamic sensitivity technique, we propose a method for sensitivity analysis of vibration transfer path systems with respect to their path parameters. It is well known that non-viscous damping is an important factor in causing the nonlinearity of vibration systems. The sensitivity of nonlinear vibration systems with respect to different kinds of non-viscous damping is discussed. With the sensitivity of dynamic responses with respect to transfer path parameters as an evaluation criterion, the contribution level of each transfer path to the vibration of acceptance structures was listed in order. Using the proposed method, the sensitivity of the vibration system with multiple and/or multi-dimensional transfer paths could be determined explicitly and accurately in the time domain.

Reliability Sensitivity Analysis for Rack-and-Pinion Steering Linkages

In this paper, a reliability sensitivity analysis methodology for the kinematic accuracy of rack-and-pinion steering linkages (RPSLs) is developed. The direct linearization method is applied to obtain the kinematic accuracy errors of planar linkages due to link-length variations. The RPSL widely used in many types of vehicles is chosen as an example to propose an analytical model for reliability analysis of the kinematic accuracy of planar linkages. Furthermore, reliability sensitivity analysis of planar linkages, which is the main focus of this paper, is used to compute the reliability sensitivity of the kinematic accuracy of steering linkages with respect to the statistical parameters (e.g., mean, standard deviation, or higher moments) of the basic errors of random variables. Finally, the practicality and efficiency of the proposed method are demonstrated by a numerical example.

Probabilistic Approach to System Reliability of Mechanism with Correlated Failure Models

In this paper, based on the kinematic accuracy theory and matrix-based system reliability analysis method, a practical method for system reliability analysis of the kinematic performance of planar linkages with correlated failure modes is proposed. The Taylor series expansion is utilized to derive a general expression of the kinematic performance errors caused by random variables. A proper limit state function (performance function) for reliability analysis of the kinematic performance of planar linkages is established. Through the reliability theory and the linear programming method the upper and lower bounds of the system reliability of planar linkages are provided. In the course of system reliability analysis, the correlation of different failure modes is considered. Finally, the practicality, efficiency, and accuracy of the proposed method are shown by a numerical example.

Reliability Sensitivity-based Correlation Coefficient Calculation in Structural Reliability Analysis

The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored, which cannot actually reflect the effects of parameter uncertainties on reliability. To discuss the selection problem of the correlation coefficients from the reliability-based sensitivity point of view, the theory principle of the problem is established based on the results of the reliability sensitivity, and the criterion of correlation among random variables is shown. The values of the correlation coefficients are obtained according to the proposed principle and the reliability sensitivity problem is discussed. Numerical studies have shown the following results: (1) If the sensitivity value of correlation coefficient ρ is less than (at what magnitude 0.000 01), then the correlation could be ignored, which could simplify the procedure without introducing additional error. (2) However, as the difference between ρs, that is the most sensitive to the reliability, and ρR, that is with the smallest reliability, is less than 0.001, ρs is suggested to model the dependency of random variables. This could ensure the robust quality of system without the loss of safety requirement. (3) In the case of |Eabs|>0.001 and also |Erel|>0.001, ρR should be employed to quantify the correlation among random variables in order to ensure the accuracy of reliability analysis. Application of the proposed approach could provide a practical routine for mechanical design and manufactory to study the reliability and reliability-based sensitivity of basic design variables in mechanical reliability analysis and design.

Reliability-based Robust Optimization Design of Automobile Components with Non-normal Distribution Parameters

In the reliability designing procedure of the vehicle components, when the distribution styles of the random variables are unknown or non-normal distribution, the result evaluated contains great error or even is wrong if the reliability value R is larger than 1 by using the existent method, in which case the formula is necessary to be revised. This is obviously inconvenient for programming. Combining reliability-based optimization theory, robust designing method and reliability based sensitivity analysis, a new method for reliability robust designing is proposed. Therefore the influence level of the designing parameters’ changing to the reliability of vehicle components can be obtained. The reliability sensitivity with respect to design parameters is viewed as a sub-objective function in the multi-objective optimization problem satisfying reliability constraints. Given the first four moments of basic random variables, a fourth-moment technique and the proposed optimization procedure can obtain reliability-based robust design of automobile components with non-normal distribution parameters accurately and quickly. By using the proposed method, the distribution style of the random parameters is relaxed. Therefore it is much closer to the actual reliability problems. The numerical examples indicate the following: (1) The reliability value obtained by the robust method proposed increases (>0.04%) comparing to the value obtained by the ordinary optimization algorithm; (2) The absolute value of reliability-based sensitivity decreases (>0.01%), and the robustness of the products’ quality is improved accordingly. Utilizing the reliability-based optimization and robust design method in the reliability designing procedure reduces the manufacture cost and provides the theoretical basis for the reliability and robust design of the vehicle components.

Fatigue Reliability Sensitivity Analysis of Complex Mechanical Components under Random Excitation

Fatigue failure is the typical failure mode of mechanical components subjected to random load-time history. It is important to ensure that the mechanical components have an expected life with a high reliability. However, it is difficult to reduce the influence of factors that affect the fatigue reliability and thus a reliability sensitivity analysis is necessary. An approach of fatigue reliability sensitivity analysis of complex mechanical components under random excitation is presented. Firstly, load spectra are derived using a theoretical method. A design of experiment (DOE) is performed to study the stresses of dangerous points according to the change of design parameters of the mechanical component. By utilizing a Back-Propagation (BP) algorithm, the explicit function relation between stresses and design parameters is formulated and thus solves the problem of implicit limit state function. Based on the damage accumulation (DA) approach, the probability perturbation method, the fourth-moment method, the Edgeworth expansion is adopted to calculate the fatigue reliability and reliability-based sensitivity. The fatigue reliability sensitivity analysis of a train wheel is performed as an example. The results of reliability are compared with that obtained using Monte Carlo simulation. The reliability sensitivity of design parameters in the train wheel is analyzed.

Reliability Analysis of the Chatter Stability during Milling Using a Neural Network

The parameters of a system have the randomness generally in the process of milling, which influences the stability of the milling. This paper uses the neural network to get a comprehensive analysis of the influences of random factors in milling and proposes a method for reliability analysis of the regenerative chatter stability in milling. Dynamic model of milling regenerative chatter is established, and stability lobe diagram is obtained by the full-discretization method (FDM). The neural network is applied to approximate the functional relationship of the limit axial cutting depth; then the reliability is computed with the Monte Carlo simulation method (MCSM) and the moment method (MM), respectively. Finally, the results of an example are used to demonstrate the efficiency and accuracy of the proposed method.