Vibration Reliability Analysis Research Articles

Statistical method of extracting assembly stresses in over-constrained solder-less press-fit pin technology for vibration reliability analysis

Abstract Solderless press-fit technology is increasingly favored over lead-free solder mountings due to cost-effective design benefits amid lead-free regulations. However, its over-constrained nature causes assembly issues and preload stress in pins, leading to fatigue failure under vibration. This paper extends previous research by presenting a method to evaluate the robustness of these assemblies under vibration-induced fatigue, considering assembly-induced stresses as static preload stress. The proposed statistical method uses Monte Carlo simulations to compute the distribution of pin failures due to fatigue, providing a comprehensive analysis that traditional worst-case FEA simulations cannot. This approach aids in identifying worst-case scenarios, predicting failure percentages, ranking designs, and improving design robustness through iterative feedback during the design phase.

Analysis of Typical PCB Vibration Characteristics Based on Modal Simulation and Experiment

This study combines simulation and experimental methods to explore the vibration characteristics of a servo controller printed circuit board (PCB). CREO is used to build a simulation model based on PCB structure analysis. ANSYS was used to perform finite element simulation analysis of vibration characteristics. The hammering method is used to perform circuit board modal experiments. By comparing the results of simulation and experimentation, the PCB dynamic characteristics are analyzed. It was found that the fixed frequency error of the simulation and the experiment is within 6%, and the first three mode shapes are consistent. Hence, it is suggested to use the simulation model for the subsequent vibration reliability analysis of the electronic product.

A new approach for non‐Gaussian vibration analysis of hyperbolic tangent package with a critical component

A new approach is proposed to analyze the non‐Gaussian random vibration of hyperbolic tangent package. Firstly, the non‐Gaussian vibration noise of specified mean, variance, skewness, and kurtosis is developed by Hermite polynomial and verified by Gaussian mixture model theory. Secondly, next to analyzing an analytical and numerical response of the two degrees of freedom linear package, the acceleration response of the two degrees of freedom hyperbolic tangent package system under non‐Gaussian vibration excitation is obtained though the Hermite polynomial and Runge–Kutta method, and the effects of the external excitation and system parameters are investigated. Finally, on the basis of the first‐passage probability of the acceleration response, the reliability analysis method is introduced. The analysis provides a guidance to the vibration reliability analysis and packaging optimization design.

Probability Density Evolution Algorithm for Stochastic Dynamical Systems Based on Fractional Calculus

With the increasing load and speed of trains, the problems caused by various random excitations (such as safety and passenger comfort) have become more prominent and thus arises the necessity to analyze stochastic dynamical systems, which is important in both academic and engineering circles. The existing analysis methods are inadequate in terms of computational accuracy, computational efficiency, and applicability in solving complex problems. For that, a new efficient and accurate method is used in this paper, suitable for linear and nonlinear random vibration analysis of large structures as well as static and dynamic reliability assessment. It is the direct probability integration method, which is extended and applied to the random vibration reliability analysis of dynamical systems. Dynamical models of the dynamic system and coupled system “three-car vehicle-rail-bridge” are established, the time-varying differential equations of motion are derived in detail, and the dynamic response of the system is calculated using the explicit Newmark algorithm. The simulation results show the influence of the number of representative points on the smoothness of the image of the probability density function and the accuracy of the calculation results.

Vibration Reliability Analysis of Drum Brake Using the Artificial Neural Network and Important Sampling Method

This research aims to evaluate the calculation accuracy and efficiency of the artificial neural network-based important sampling method (ANN-IS) on reliability of structures such as drum brakes. The finite element analysis (FEA) result is used to establish the ANN sample in ANN-based reliability analysis methods. Because the process of FEA is time-consuming, the ANN sample size has a very important influence on the calculation efficiency. Two types of ANNs used in this study are the radial basis function neural network (RBF) and back propagation neural network (BP). RBF-IS and BP-IS methods are used to conduct reliability analysis on training samples of three different sizes, and the results are compared with several reliability analysis methods based on ANNs. The results show that the probability of failure of the RBF-IS method is closer to that of the Monte-Carlo simulation method (MCS) than those of other methods (including BP-IS). In addition, the RBF-IS method has better calculation efficiency than the other methods considered in this study. This research demonstrates that the RBF-IS method is well suited to structure reliability problems.

Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework

In order to improve the accuracy and calculation efficiency of aeroengine rotor vibration reliability analysis, a time‐varying rotor vibration reliability analysis method under the aeroengine operating state is proposed. Aiming at the highly nonlinear and strong coupling of factors affecting the reliability of aeroengine rotor vibration, an intelligent neural network modeling framework (short form‐INNMF) is proposed. The proposed method is based on DEA, with QAR information as the analysis data, and four factors including engine working state, fuel/oil working state, aircraft flight state, and external conditions are considered to analyse the rotor vibration reliability. INNMF is based on the artificial neural network (ANN) algorithm through improved particle swarm optimization (PSO) algorithm and Bayesian Regularization (BR) optimization. Through the analysis of the rotor vibration reliability of the B737‐800 aircraft during a flight mission from Beijing to Urumqi, the time‐varying rotor vibration reliability was obtained, which verified the effectiveness and feasibility of the method. The comparison of INNMF, random forest (RF), and ANN shows that INNMF improves analysis accuracy and calculation efficiency. The proposed method and framework can provide useful references for aeroengine rotor vibration analysis, special treatment, maintenance, and design.

Dynamic Reliability Analysis of Tower Crane with Wind Loading

The wind-induced dynamic reliability of tower cranes was studied. A linear filter autoregressive (AR) model is used to simulate the time history of multidimensional fluctuating wind samples, and the corresponding wind load is applied to the finite element model of tower crane to analyze the wind vibration response. Based on Poisson process method, wind vibration reliability analysis of tower crane is carried out.The results show that under the action of wind speed of 20m/s, the probability of strength reliability is over 0.99, and the structural strength reserve of this type of tower crane is relatively sufficient; the displacement reliability is 0.98, when the wind speed is large, the displacement reliability decreases obviously, and the stiffness reserve is slightly insufficient.

Vortex-induced Vibration Reliability Analysis in Cable-stayed Bridges: Wind and Aerodynamic Uncertainties

This paper proposes a vortex-induced vibration (VIV) reliability analysis method based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of fractional moments involving uncertain wind characteristics, structural properties, and bluff-body aerodynamics. The multiplicative dimensional reduction method (M-DRM) is used to calculate the fractional moments. A new threshold is obtained based on the stopping sight distance in the highway engineering technique standard, which is less strict than the China–Japan standard and the British code and thus better-suited to VIV reliability evaluation. A long-span cable-stayed bridge model is used to illustrate the accuracy and efficiency of the proposed method in comparison to Monte Carlo simulation (MCS) on three performance functions of VIV reliability. The results indicate that VIV maximum amplitude and wind speed failure probability are not sensitive to the selected performance function, but the effect of the wind attack angle on probability is significant. The M-DRM provides a workable alternative approach to analyzing the highly complex VIV reliability of long-span bridges.

A Vibration Reliability Analysis Method for the Uncertain Space Beam Structure

Considering that uncertainty is inherent and unavoidable in engineering practice and the available information about the uncertain parameters is always not sufficient, the paper tries to carry out the nonprobabilistic vibration reliability analysis so as to avoid resonance on uncertain structure with bounded parameters. The input uncertain-but-bounded parameters are treated as interval variables, and an interval model is adopted to describe bounded uncertainties. Then a theory of nonprobabilistic reliability is introduced, in which the dimensionless nonprobabilistic reliability index and system reliability index are defined. In order to investigate the resonance failure with reliability method, the resonance failure domains are stated according to the relationships between the natural frequencies and the excitation frequencies. Then the uncertain structure is modeled as a series system and a system reliability index is proposed to evaluate the safety of the structure. The paper also takes a frequency analysis on the uncertain space beam structure to get the resonance failure modes. A frequency analysis method based on the monotonicity discriminant of the frequency sensitivity is presented. Then an optimization algorithm is introduced to verify the validity of the former frequency analysis method. Two examples are provided to illustrate the effectiveness and feasibility of the presented method.

Vibration reliability analysis for aeroengine compressor blade based on support vector machine response surface method

To ameliorate reliability analysis efficiency for aeroengine components, such as compressor blade, support vector machine response surface method (SRSM) is proposed. SRSM integrates the advantages of support vector machine (SVM) and traditional response surface method (RSM), and utilizes experimental samples to construct a suitable response surface function (RSF) to replace the complicated and abstract finite element model. Moreover, the randomness of material parameters, structural dimension and operating condition are considered during extracting data so that the response surface function is more agreeable to the practical model. The results indicate that based on the same experimental data, SRSM has come closer than RSM reliability to approximating Monte Carlo method (MCM); while SRSM (17.296 s) needs far less running time than MCM (10958 s) and RSM (9840 s). Therefore, under the same simulation conditions, SRSM has the largest analysis efficiency, and can be considered a feasible and valid method to analyze structural reliability.

Vibration reliability sensitivity analysis of general system with correlation failure modes

The vibration problem of the general system is the main object of research. The material properties and geometry of general system are random parameters because of the manufacturing environment, technical conditions, manufacturing and installation errors, multiphase materials, features and other factors. According to the relation criterion that the difference between the natural frequency and the driving frequency of general systems is not beyond a specific value, the vibration reliability mode and vibration reliability of general systems are defined considering the correlation of the multi-order natural frequency and the random characteristics of structure size and material, and the vibration reliability analysis method for avoiding the resonant is carried out. The second-order joint failure probability is obtained by using the numerical integration method. Based on the reliability design theory and sensitivity analysis method, the vibration reliability sensitivity of the general system with correlation failure modes is extensively discussed and a numerical method for vibration reliability sensitivity design is presented. The variation regularities of vibration reliability sensitivity are obtained and the effects of random parameters on vibration reliability of the general system are studied. The presented method provided the theoretic basis for the reliability design of the general system. A numerical example demonstrated that the proposed method is effective.

Application of FEM Simulation Technology on Vibration Reliability Analysis of Electronic Components

Vibration capability and reliability is necessarily to be considered for electronic components design. In this paper, the vibration characteristics of electronic components were studied using FEM, for example, gridded electron gun. The dynamical mode of girded electron gun was established. Modal frequency and model obtained by simulation shows tendency as tested experiment results, verifying the correctness of the simulation model and method used. The Parameters showed an inherent property of structure, which provided a theoretical basis for production design, the optimization of parameters and the vibration-resistance reliability improvement of microwave tube. In the aspects of electronic components reliability analysis, the variations of production capability parameters under various stress environments can be gained by FEM simulation technology to evaluate environment adaptability and reliability.