摘要
利用小波技术对发动机曲轴轴承振动信号进行分解,对特定层的信号进行重构,并计算重构信号的分形维数,来实现发动机曲轴不同技术状态下特征提取。实验结果表明,特定频率带振动信号的分形维数更能敏感反应发动机曲轴轴承技术状态,它可以作为诊断发动机曲轴轴承故障的一个重要特征量。
In this paper, the wavelet transform technology was applied to analyze the crankshaft bear- ing vibration signal, then is reconstructed the specifically vibration series of signal, and fractal dimension of them is computed to pick up the fault characteristic in different technology state of the crankshaft bear- ing. The experiment result shows that the fractal dimension of the vibration signal of specifically frequency bands can reflect the technology state of the crankshaft bearing, and can be as an important characteristic parameter to diagnose the crankshaft bearing fault.
出处
《工业仪表与自动化装置》
2013年第4期116-120,共5页
Industrial Instrumentation & Automation
关键词
小波分析
分形维数
曲轴轴承
故障诊断
wavelet analysis
fractal dimension
crankshaft bearing
fault diagnosis
作者简介
耿纪洲，男，硕士研究生，从事汽车检测研究。
