دورية أكاديمية
ESTIMATION METHOD OF LOAD SPECTRUM DISTRIBUTION BASED ON EM ALGORITHM
العنوان: | ESTIMATION METHOD OF LOAD SPECTRUM DISTRIBUTION BASED ON EM ALGORITHM |
---|---|
المؤلفون: | SU Fang, CHEN XiaoNan, WANG ChenSheng, ZHAO HaiYan |
المصدر: | Jixie qiangdu, Vol 42, Pp 1119-1124 (2020) |
بيانات النشر: | Editorial Office of Journal of Mechanical Strength, 2020. |
سنة النشر: | 2020 |
المجموعة: | LCC:Mechanical engineering and machinery LCC:Materials of engineering and construction. Mechanics of materials |
مصطلحات موضوعية: | Harvester, Mixture of Gaussian function, Parameter estimate, Rainflow method, Distribution estimation, Mechanical engineering and machinery, TJ1-1570, Materials of engineering and construction. Mechanics of materials, TA401-492 |
الوصف: | As the real load is very complicated during the process of harvester operation,it is of great significance for the prediction of fatigue life to describe the load characteristics and distribution form accurately. In order to obtain the probability density distribution model of the load cycles. Take RF-half shaft torque as the research object,the mixture Gaussian fitting method based on EM was suggested. n Code software was used for rain flow counting and the load cycle was described with the vector S.The cluster number and cluster center loading were got from the clustering of the loading cycle by the SPSS software,and using EM algorithm to resolve the mean and covariance matrix of Gaussian component. The index value of SSE and RSME are close to0,but R and Raare both up to 0. 85 based on the index model. It showed that the Gaussian mixture indeed fitting out of the original data of load-cycle. The results of research can provide a theory evidence for the fatigue life analysis and load spectrum extrapolation. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | Chinese |
تدمد: | 1001-9669 |
Relation: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.05.016; https://doaj.org/toc/1001-9669 |
DOI: | 10.16579/j.issn.1001.9669.2020.05.016 |
URL الوصول: | https://doaj.org/article/59534aa3f004412eba5da782316e8590 |
رقم الأكسشن: | edsdoj.59534aa3f004412eba5da782316e8590 |
قاعدة البيانات: | Directory of Open Access Journals |
كن أول من يترك تعليقا!