小样本威布尔分布参数估计的比较研究——应用于弹簧疲劳失效数据

IF 1.3 4区工程技术 Q4 ENGINEERING, INDUSTRIAL

Quality Engineering Pub Date : 2022-12-21 DOI:10.1080/08982112.2022.2158745

Xiaoyu Yang, Liyang Xie, Yifeng Yang, Bingfeng Zhao, Yuan Li

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引用次数: 1

摘要

摘要威布尔分布是可靠性分析中应用最广泛的模型。本文的主要目的是提出一种称为最小差异法的简单方法，该方法适用于威布尔分布参数估计的完整数据和截尾数据，并通过模拟研究在13种方法的小样本量中根据几个标准进行详细比较。此外，将参数估计方法应用于弹簧疲劳失效数据。通过大量的仿真和比较，推荐了广义最小二乘法、加权最小二乘法、最大似然估计法和最小方差法用于小样本参数估计。

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A comparative study for parameter estimation of the Weibull distribution in a small sample size: An application to spring fatigue failure data

Abstract The Weibull distribution is the most widely applied model in reliability analysis. The main objective of this paper is to present a simple method called the minimum discrepancy method that is applicable to both complete and censored data for the parameter estimation of the Weibull distribution and a detailed comparison in a small sample size of thirteen methods in terms of several criteria by a simulation study. Additionally, parameter estimation methods are applied to the spring fatigue failure data. By extensive simulations and comparisons, the generalized least square 1, the weighted least square 1, the weighted Maximum likelihood estimation and the minimum discrepancy method are recommended for parameter estimation with small samples.

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来源期刊

Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY

CiteScore

3.90

自引率

10.00%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.