科研之友
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摘要
Extreme loads have a significant effect on the fatigue damage of components. The block maximummethod (BMM) is widely used to estimate extreme values in various fields. Selecting a reasonable block size for BMM is crucial to ensure that proper extreme values are extracted to get extreme sample to estimate extreme values. Aiming at this issue, this study proposed a comprehensive evaluation approach based onmultiple-criteria decisionmaking(MCDM) method to select a proper block size. A wheel loaderwith six sections in one operating cycle was illustrated as an example. First, spading sections of each operating cycle were extracted and connected as extreme loads often occur at that section. Then extreme sample was obtained by BMM for fitting the generalized extreme value (GEV) distribution. Kolmogorov-Smirnov (K-S) test, Pearson's Chi-Square (chi(2)) test, and average deviation in Probability Distribution PDF) are selected as the fitting test. The comprehensive weights are calculated by the maximum entropy principle. Finally, the optimal block size corresponding to the minimum comprehensive evaluation indicator is obtained and the result exhibited a good fitting effect. The proposed method can also be flexibly used in various situations to select a block size.
- 出版日期2016
- 单位吉林大学
