基于果蝇优化算法小波支持向量数据描述的滚动轴承性能退化评估OA北大核心CSCDCSTPCD
Rolling Bearing Performance Degradation Assessment Based on FOA-WSVDD
针对支持向量数据描述(SVDD)算法对滚动轴承早期故障不敏感、参数选择困难的问题,提出了一种基于果蝇优化算法 小波支持向量数据描述(FOA-WSVDD)的滚动轴承性能退化评估方法.提取滚动轴承早期无故障振动信号的时域、时频域特征向量,并基于单调性进行特征选择;针对现有核函数对滚动轴承早期故障不敏感问题,将小波核函数引入到 SVDD 算法中;针对 SVDD 算法参数选择困难的问题,以支持向量个数与总样本数的比值作为适应度函数,采用改进的 FOA 算…查看全部>>
A rolling bearing performance degradation assessment method was proposed based on FOA-WSVDD,aiming at the problems that the SVDD algorithm was not sensitive to rolling bearing early faults and difficult to select suitable kernel parameters.The feature vectors of the time and time frequency domains were extracted from bearing fault-free stages and then were selected based on monotonicity.Then,the FOA-WSVDD model was established where the wavelet kernel functi…查看全部>>
朱朔;白瑞林;刘秦川
江南大学轻工过程先进控制教育部重点实验室,无锡,214122江南大学轻工过程先进控制教育部重点实验室,无锡,214122江南大学轻工过程先进控制教育部重点实验室,无锡,214122
机械制造
轴承果蝇优化算法小波支持向量数据描述小波核
bearingfruit fly optimization algorithm(FOA)wave support vector data description (WSVDD)wavelet kernel
《中国机械工程》 2018 (5)
602-608,7
江苏高校优势学科建设工程资助项目(PAPD)江苏省产学研前瞻性联合研究资助项目(BY2015019-38)江苏省科技成果转化专项资金资助项目(BA2016075)
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