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| 基于核主成分分析的柴油机技术状态评估 | |
| 引用本文： | 孙宜权,张英堂,李志宁,李志伟,尹刚,杨宁. 基于核主成分分析的柴油机技术状态评估[J]. 车用发动机, 2012, 0(2): 89-92 |
| 作者姓名： | 孙宜权 张英堂 李志宁 李志伟 尹刚 杨宁 |
| 作者单位： | 1. 军械工程学院一系,河北石家庄 050003;66267部队,河北石家庄 050081 2. 军械工程学院一系,河北石家庄,050003 3. 66267部队,河北石家庄,050081 |
| 摘 要： | 提出了一种基于核主成分分析的柴油机技术状态评估方法,该方法通过跟踪柴油机全寿命周期内的机体振动信号,引入振动信号频域内振动烈度与统计特征值构成特征子集,利用核主成分分析方法获得特征子集的主分量,选用极限学习机对主分量特征样本进行分类和测试,可有效地消除冗余信息,提高识别精度。对柴油机技术状态评估后的结果表明,该方法较主成分分析法识别精度约提高了25个百分点。 |
| 关 键 词： | 柴油机 核主成分分析 振动烈度 极限学习机 状态评估 |
Evaluation of Diesel Engine Technical State Based on KPCA |
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| SUN Yi-quan , ZHANG Ying-tang , LI Zhi-ning , LI Zhi-wei , YIN Gang , YANG Ning. Evaluation of Diesel Engine Technical State Based on KPCA[J]. Vehicle Engine, 2012, 0(2): 89-92 | |
| Authors: | SUN Yi-quan ZHANG Ying-tang LI Zhi-ning LI Zhi-wei YIN Gang YANG Ning |
| Affiliation: | 1(1.The First Department of Ordnance Engineering College,Shijiazhuang 050003,China;2.The Army of 66267,Shijiazhuang 050081,China) |
| Abstract: | The evaluation method of diesel engine technical state based on KPCA was put forward.Based on the body vibration signals in life cycle,the feature subset was created with the frequency-domain vibration severity and statistical feature value,then the principal components of feature subset were acquired with the KPCA method,next the feature samples of primary components were classified and tested by the extreme learning machine,after that the redundant information could be efficiently eliminated,which improved the recognition precision.The evaluation result of diesel engine technical state shows that,compared with PCA,the method can improve the recognition precision by 25%. |
| Keywords: | diesel engine KPCA vibration severit ELM state evaluation |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |