基于卡尔曼滤波和数学形态学分形分析的齿轮箱故障诊断
Aiming at the problem that traditional signal time-frequency analysis methods are not suitable for non-stationary signal,by using gearbox time domain vibration signals to build AR model,least squares method to calculate model parameters,and AIC formula to ascertain model order,status space model is...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2014-01-01
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| Series: | Jixie chuandong |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2014.07.030 |
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| Summary: | Aiming at the problem that traditional signal time-frequency analysis methods are not suitable for non-stationary signal,by using gearbox time domain vibration signals to build AR model,least squares method to calculate model parameters,and AIC formula to ascertain model order,status space model is also built for Kalman filter.Mathematical morphology fractal dimension method is used for calculating signal fractal dimension after filtering.This method is used for signal analysis of normal gears,tooth surface abrasion,gear tooth crack and tooth fracture.The analysis results of measured signal show that the method based on Kalman filter and mathematical morphology can recognize gear fault types effectively,and it offers a new feature extract method for gearbox fault diagnosis. |
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| ISSN: | 1004-2539 |