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| 基于小波分形技术的发动机曲轴轴承故障特征分析 | |
| 引用本文： | 赵慧敏,夏超英,肖云魁,付少波.基于小波分形技术的发动机曲轴轴承故障特征分析[J].河北工业大学学报,2010,39(1). |
| 作者姓名： | 赵慧敏 夏超英 肖云魁 付少波 |
| 作者单位： | 1. 天津大学,电气与自动化工程学院,天津,300072;军事交通学院,汽车工程系,天津,300161 2. 天津大学,电气与自动化工程学院,天津,300072 3. 军事交通学院,汽车工程系,天津,300161 4. 军事交通学院,基础部,天津,300161 |
| 基金项目： | 总装备部预研项目(40407030302) |
| 摘 要： | 为提取柴油发动机曲轴轴承振动信号的故障特征,采用小波分形技术,对发动机加速振动信号进行分解和各层低频带信号重构,计算并比较了各重构信号的分形维数.结果表明,曲轴轴承磨损故障最佳诊断部位为缸体与油底接合处右侧及缸体正下方油底壳处;最佳转速为1800r/min、2100r/min;小波分解后特定层的时域重构信号的分形维数,能够敏感反应柴油机曲轴轴承的技术状态,有效提取曲轴轴承的故障特征. |
| 关 键 词： | 小波变换 分形理论 网格维数 曲轴轴承 故障诊断 |
Using Wavelet Fractal Technology to Recover the Crankshaft Bearing Fault Feature |
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| ZHAO Hui-min,XIA Chao-ying,XIAO Yun-kui,FU Shao-bo.Using Wavelet Fractal Technology to Recover the Crankshaft Bearing Fault Feature[J].Journal of Hebei University of Technology,2010,39(1). | |
| Authors: | ZHAO Hui-min XIA Chao-ying XIAO Yun-kui FU Shao-bo |
| Affiliation: | 1. School of Electrical Engineering and Automation;Tianjin University;Tianjin 300072;China;2. Department of Automotive Engineering;Academy of Military Transportation;Tianjin 300161;3. General Courses Department;China |
| Abstract: | For the sake of extracting the fault characters of crankshaft bearing of diesel engine,the wavelet fractal technology is adopted in this paper. The acceleration vibration signal is wavelet analyzed,and then the data of each low frequency band is reconstructed. The fractal dimension of reconstructed data is calculated and compared. The result shows that the best diagnostic places for crankshaft bearing abrasion are the right side of engine where crankshaft located and inferior side of engine. The best revolv... |
| Keywords: | wavelet transform fractal theory grid dimension crankshaft bearing fault diagnosis |
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