变速器新产品故障特征提取与分类方法
文献类型:期刊论文
作者 | 周晓锋![]() ![]() ![]() |
刊名 | 计算机集成制造系统
![]() |
出版日期 | 2012 |
卷号 | 18期号:4页码:761-767 |
关键词 | 阶次分析 特征提取 特征选择 故障诊断 变速器 |
ISSN号 | 1006-5911 |
其他题名 | Fault feature extraction and classification method for new transmission |
产权排序 | 1 |
中文摘要 | 针对汽车变速箱原始故障特征向量维数过高导致的检测效率低、准确率低的问题,提出一种基于阶次分析理论的特征提取方法和基于遗传算法—反向传播神经网络的特征选择与分类方法。首先运用阶次分析理论提取变速器的阶次域特征,与时域特征共同组成特征向量集;然后将类内类间距离比与惩罚系数之和作为目标函数值,利用遗传搜索策略对特征向量集进行特征选择,得到特征子集;最后用反向传播神经网络算法进行故障分类,得到检测结果,并通过实验验证了所提出方法的有效性。 |
英文摘要 | During the process of new transmission products quality inspecting,the original fault feature vector dimension was too high to cause the detection in a low efficiency rate and low accuracy rate.To solve this problem,a feature extraction method based on order analysis theory together with a feature selection and classification method based on Genetic Algorithm-Back Propagation(GA-BP)algorithm were presented.The transmission’s order domain feature was extracted by using the order analysis theory,and it was composed with the domain’s feature to form a feature vector set.The sum of the penalty factor and the distance ratio of inner-class and between-class was taken as the objective function value,the features of feature vector set were selected by Genetic Algorithm(GA),and the feature subset was obtained.Back-propagation neural network algorithmare was applied to classify the fault.The effectiveness of proposed algorithm was validated by experiments. |
收录类别 | EI ; CSCD |
资助信息 | 国家自然科学基金资助项目(60904047),国家自然科学基金新疆地区科学基金(61164012); 辽宁省科技攻关资助项目(2011020085-301) |
语种 | 中文 |
CSCD记录号 | CSCD:4521246 |
公开日期 | 2012-10-24 |
源URL | [http://ir.sia.cn/handle/173321/9917] ![]() |
专题 | 沈阳自动化研究所_自动化系统研究室 |
推荐引用方式 GB/T 7714 | 周晓锋,史海波,胡东平,等. 变速器新产品故障特征提取与分类方法[J]. 计算机集成制造系统,2012,18(4):761-767. |
APA | 周晓锋,史海波,胡东平,&尚文利.(2012).变速器新产品故障特征提取与分类方法.计算机集成制造系统,18(4),761-767. |
MLA | 周晓锋,et al."变速器新产品故障特征提取与分类方法".计算机集成制造系统 18.4(2012):761-767. |
入库方式: OAI收割
来源:沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。