High-Cycle Fatigue Life Prediction for Pb-Free BGA Under Random Vibration Loading ⇑ Da Yu A, Abdullah Al-Yafawi A, Tung T
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Vibration Fatigue Reliability Analysis of Aircraft Landing Gear Based on Fuzzy Theory Under Random Vibration
Vibration fatigue reliability analysis of aircraft landing gear based on fuzzy theory under random vibration Yan Song1, Jun Yao2, Jingyue Yang3 School of Reliability and System Engineering, Beihang University, Beijing, China 1Corresponding author E-mail: [email protected], [email protected], [email protected] (Accepted 15 July 2014) Abstract. The failure of aircraft landing gear (ALG) is major caused by vibration fatigue. And its main failure mode is fatigue fracture. Currently the reliability of ALG is usually calculated by the stress strength interference (SSI) model, which is based on the binary state assumption. While in reality, the strength is degraded with time and the boundary of the failure and success is blur, so the binary state assumption is deviated from the fact. To overcome this problem, this paper uses the membership function (MF) to represent fuzzy safe state which caused by the strength degradation under the failure mode of vibration fatigue. Moreover, a fuzzy reliability model (FRM) of ALG is proposed based on fuzzy failure domain (FFD). Finally, the feasibility of method is tested through a simulation example. By comparing the simulation results (SRs) of the FRM with SRs of the static SSI model and the dynamic SSI model, the rationality of the method is verified. The FRM can calculate the reliability without the gradual degradation processes, thus it is used more widely. Keywords: vibration fatigue, fuzzy reliability analysis, SSI model, membership function. 1. Introduction With the high requirement for safe operation of ALG, the issue of structure reliability under vibration fatigue becomes more and more prominent. ALG is one of the key components of aircraft. -
Vibration Fatigue Damage Estimation by New Stress Correction Based on Kurtosis Control of Random Excitation Loadings
sensors Article Vibration Fatigue Damage Estimation by New Stress Correction Based on Kurtosis Control of Random Excitation Loadings Yuzhu Wang 1,2 and Roger Serra 1,* 1 INSA Centre Val de Loire, Laboratoire de Mécanique G. Lamé E.A.7494, Campus de Blois, Equipe DivS, 3 rue de la Chocalaterie, 41000 Blois, France; [email protected] 2 China Academy of Railway Sciences, Locomotive Car Research Institute, Beijing 100081, China * Correspondence: [email protected] Abstract: In the pioneer CAE stage, life assessment is the essential part to make the product meet the life requirement. Commonly, the lives of flexible structures are determined by vibration fatigue which accrues at or close to their natural frequencies. However, existing PSD vibration fatigue damage estimation methods have two prerequisites for use: the behavior of the mechanical system must be linear and the probability density function of the response stresses must follow a Gaussian distribution. Under operating conditions, non-Gaussian signals are often recorded as excitation (usually observed through kurtosis), which will result in non-Gaussian response stresses. A new correction is needed to make the PSD approach available for the non-Gaussian vibration to deal with the inevitable extreme value of high kurtosis. This work aims to solve the vibration fatigue estimation under the non-Gaussian vibration; the key is the probability density function of response stress. This work researches the importance of non-Gaussianity numerically and experimentally. The beam specimens with two notches were used in this research. All excitation stays in the frequency Citation: Wang, Y.; Serra, R. range that only affects the second natural frequency, although their kurtosis is different. -
Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculations Yuzhu Wang, Roger Serra, Pierre Argoul
Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculations Yuzhu Wang, Roger Serra, Pierre Argoul To cite this version: Yuzhu Wang, Roger Serra, Pierre Argoul. Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculations. Surveillance, Vishno and AVE conferences, INSA-Lyon, Université de Lyon, Jul 2019, Lyon, France. hal-02188557 HAL Id: hal-02188557 https://hal.archives-ouvertes.fr/hal-02188557 Submitted on 18 Jul 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculation. Yuzhu WANG1, Roger SERRA1 et Pierre ARGOUL2 1INSA Centre Val de Loire, Laboratoire de Mécanique G. Lamé, Campus de Blois, Equipe DivS, 3 rue de la chocalaterie, 41000 Blois, France 2IFSTTAR, Laboratoire Mast – EMGCU, 14-20 Boulevard Newton, Cité Descartes, 77447 Marne-la-Vallée Cedex 2 Abstract In the study of random vibration problems, Gaussian vibration and non-Gaussian vibrations are usually classified according to the excitation signal. The skewness and kurtosis are usually used to distinguish. Here we discuss a non-strict Gaussian signal, which is the error that exists in skewness and kurtosis and usually unavoidable in actual experiments or signals analysis. -
FATIGUE LIFE for NON-GAUSSIAN RANDOM EXCITATIONS Frédéric Kihm
UNIVERSITY OF SOUTHAMPTON FACULTY OF ENGINEERING AND THE ENVIRONMENT Institute of Sound and Vibration Research Fatigue Life for non-Gaussian Random Excitations by Frédéric Kihm Thesis for the degree of Doctor of Philosophy December 2017 UNIVERSITY OF SOUTHAMPTON ABSTRACT FACULTY OF ENGINEERING AND THE ENVIRONMENT Institute of Sound and Vibration Research Thesis for the degree of Doctor of Philosophy FATIGUE LIFE FOR NON-GAUSSIAN RANDOM EXCITATIONS Frédéric Kihm This thesis presents several developments in analysing the fatigue life of mechanical components subjected to various kinds of random excitations and the subsequent mechanical vibration. Typically components must be designed in such a way that they can withstand the effects of the exposure to environmental conditions without being damaged. Their design must be verified using laboratory testing or by Finite Element (FE) calculations. Often, design and testing are performed on the basis of specifications taken from internal, national or international standards, with the implicit assumption that if the equipment survived the particular environment it would also survive the vibrations it will see in service. Previous work in the area has developed computer-based models to predict the fatigue damage witnessed by components under random loads, but most of these are limited to only stationary Gaussian random excitations. A few have concentrated on non-Gaussian responses, not excitation, resulting from some non-linearities in the structure being activated. This thesis describes the development of original statistical analysis methods with the ability to determine extreme responses and fatigue life estimates for linear structures when subjected to non-Gaussian random excitations. The emphasis is mainly on two sources of non-Gaussian random excitations namely clipped random excitations and random excitations with a high kurtosis value. -
Transient and Spectral Fatigue Analysis for Random Base Excitation Master’S Thesis in Applied Mechanics
Transient and Spectral Fatigue Analysis for Random Base Excitation Master's thesis in Applied Mechanics ALBIN BACKSTRAND¨ PRITHVIRAJ MADHAVA ACHARYA Department of Mechanics and Maritime Sciences CHALMERS UNIVERSITY OF TECHNOLOGY G¨oteborg, Sweden 2019 MASTER'S THESIS IN APPLIED MECHANICS Transient and Spectral Fatigue Analysis for Random Base Excitation ALBIN BACKSTRAND¨ PRITHVIRAJ MADHAVA ACHARYA Department of Mechanics and Maritime Sciences Division of Dynamics CHALMERS UNIVERSITY OF TECHNOLOGY G¨oteborg, Sweden 2019 Transient and Spectral Fatigue Analysis for Random Base Excitation ALBIN BACKSTRAND¨ PRITHVIRAJ MADHAVA ACHARYA © ALBIN BACKSTRAND¨ , PRITHVIRAJ MADHAVA ACHARYA, 2019 Master's thesis 2019:37 Department of Mechanics and Maritime Sciences Division of Dynamics Chalmers University of Technology SE-412 96 G¨oteborg Sweden Telephone: +46 (0)31-772 1000 Cover: Rainflow count algorithm performed on a stress signal at the top left image. PSD signal at the top right image. S-N curves at the bottom left image, and histogram plot generated from a density function at the bottom right image. Chalmers Reproservice G¨oteborg, Sweden 2019 Transient and Spectral Fatigue Analysis for Random Base Excitation Master's thesis in Applied Mechanics ALBIN BACKSTRAND¨ PRITHVIRAJ MADHAVA ACHARYA Department of Mechanics and Maritime Sciences Division of Dynamics Chalmers University of Technology Abstract This thesis work gives an insight on how to estimate the fatigue damage using transient and spectral fatigue analysis for both uniaxial and multiaxial stress states in case of random vibration base excitation. The transient method involves a rainflow count algorithm that counts the number of cycles causing the fatigue damage, while the spectral method is based on probabilistic assumptions from which an expected value of fatigue damage can be estimated. -
Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculation
Influence of Gaussian Signal Distribution Error on Random Vibration Fatigue Calculation. Yuzhu WANG1, Roger SERRA1 et Pierre ARGOUL2 1INSA Centre Val de Loire, Laboratoire de Mécanique G. Lamé, Campus de Blois, Equipe DivS, 3 rue de la chocalaterie, 41000 Blois, France 2IFSTTAR, Laboratoire Mast – EMGCU, 14-20 Boulevard Newton, Cité Descartes, 77447 Marne-la-Vallée Cedex 2 Abstract In the study of random vibration problems, Gaussian vibration and non-Gaussian vibrations are usually classified according to the excitation signal. The skewness and kurtosis are usually used to distinguish. Here we discuss a non-strict Gaussian signal, which is the error that exists in skewness and kurtosis and usually unavoidable in actual experiments or signals analysis. Through experiments and simulation calculations, the influence of this error on the traditional fatigue calculation method is discussed. The PSD approach will be discussed primarily, and time domain signals based on the rain-flow counting method will be recorded and verified. Total nine calculation model studied in this process. Finally, through a threshold, the range of skewness and kurtosis is indicated, that within this range, Gaussian signal-based calculations can be continued. By comparing the performance of different methods, a better method for signal adaptability can be obtained. Keywords: Random vibration fatigue, Damage cumulative calculation and Gaussian random vibration. 1. Introduction For many mechanical components, the working load is in the form of random vibrations. In the fatigue design project, the load cycle of the structure is usually obtained by the rain flow counting method according to the conventional time domain signal, with the material property, the damage of the structure could be obtained by using the Miner‘s Law, and then prediction the life of the structure.