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基于GM-SVR的小样本条件下化工设备可靠性预测
引用本文:赵江平,丁洁,陈敬龙.基于GM-SVR的小样本条件下化工设备可靠性预测[J].中国安全生产科学技术,2019,15(1):145-150.
作者姓名:赵江平  丁洁  陈敬龙
作者单位:(西安建筑科技大学 资源工程学院,陕西 西安 710055)
基金项目:基金项目: 陕西省自然科学基础研究计划一般项目(青年)(2018JQ5131)
摘    要:为了准确预测化工设备可靠性趋势,针对化工设备失效寿命数据为小样本的情形,基于灰色估计法与支持向量回归机在小样本数据处理中的优势,建立了失效寿命时间服从三参数威布尔分布的化工设备可靠性模型;结合GM(1,1)和SVR对模型进行参数估计,在压缩机可靠性分析中进行了实例应用,对比分析了最小二乘法、灰色估计法和GM-SVR的估计效果。研究结果表明:GM-SVR对威布尔分布参数的估计精度明显优于最小二乘法和灰色估计法,可以有效地应用于化工设备失效数据为小样本时的可靠性预测。

关 键 词:化工设备  小样本  GM(1  1)  支持向量回归机  可靠性

Reliability prediction of chemical equipment under small sample condition based on GM and SVR
ZHAO Jiangping,DING Jie,CHEN Jinglong.Reliability prediction of chemical equipment under small sample condition based on GM and SVR[J].Journal of Safety Science and Technology,2019,15(1):145-150.
Authors:ZHAO Jiangping  DING Jie  CHEN Jinglong
Affiliation:(College of Resources Engineering, Xi’an University of Architecture and Technology, Xi’an Shaanxi 710055, China)
Abstract:In order to predict the trend of the reliability of chemical equipment accurately, aiming at the situation that the failure life data of chemical equipment are the small sample, a model for the reliability of chemical equipment with the failure life data obeying the three parameter Weibull distribution was established based on the advantages of grey estimation method and support vector regression machine (SVR) in the data processing of small sample. The parameters estimation of the model was carried out by combining GM(1,1) with SVR, then the example application was conducted on the reliability analysis of compressor, and the estimation effect of the least square method, grey estimation method and GM-SVR were compared and analyzed. The results showed that the estimation accuracy of GM-SVR model for the parameters with Weibull distribution was obviously better than those of the least square method and grey estimation method, which can be effectively applied to the reliability prediction of chemical equipment with the failure data as small sample.
Keywords:chemical equipment  small sample  GM(1  1)  support vector regression machine (SVR)  reliability
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