Correction Factor for Unbiased Estimation of Weibull Modulus by the Linear Least Squares Method

Jia, Xiang; Xi, Guoguo; Nadarajah, Saralees

doi:10.1007/s11661-019-05216-x

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…At present, the main methods of estimating parameters of Weibull distribution are statistical estimation method, 8,9 gray estimation method, 10,11 maximum likelihood method, 12–15 genetic algorithm, 16–20 and right approximation method. 21–27 These methods have different adaptability to different sample sizes, but basically all of them have high requirements on the initial value of iteration and need to go through complex calculations.…”

Section: Introductionmentioning

confidence: 99%

Research on parameter estimation methods of fatigue life distribution model of automotive chassis parts

Liu

et al. 2022

Advances in Mechanical Engineering

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The reliability assessment of fatigue life of automotive chassis parts is an important part of automobile safety. The fatigue endurance tests of automotive half-axles were carried out. The three-parameter Weibull distribution model was established according to the fatigue life distribution of samples. Using the right approximation method and the genetic algorithm to estimate three parameters of the distribution model and a comparative analysis was made. The results show that the initial life unreliability estimated by the median rank in the right approximation method had a large deviation from the true value, which may cause the iterative algorithm fall into the local optimal solution and affect the estimation accuracy. Therefore, a new parameter estimation method based on dual genetic algorithm was proposed. The newly proposed dual genetic algorithm not only improves the iteration speed, but also improves the accuracy of parameter estimation, which provides new ideas and theoretical basis for reliability assessment of mechanical components.

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