Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
1
College of Mechanical Engineering & Applied Electronics Technology, Beijing University of Technology, Chao Yang District, Beijing 100124, China
2
Department of Mechanical Engineering, Harbin Institute of Technology, Harbin 15001, China
*
Author to whom correspondence should be addressed.
Sensors 2012, 12(7), 9551-9565; https://doi.org/10.3390/s120709551
Received: 24 May 2012
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Revised: 28 June 2012
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Accepted: 3 July 2012
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Published: 12 July 2012
(This article belongs to the Section Physical Sensors)
This paper proposes a novel method for identifying carriage errors. A general mathematical model of a guideway system is developed, based on the multi-body system method. Based on the proposed model, most error sources in the guideway system can be measured. The flatness of a workpiece measured by the PGI1240 profilometer is represented by a wavelet. Cross-correlation analysis performed to identify the error source of the carriage. The error model is developed based on experimental results on the low frequency components of the signals. With the use of wavelets, the identification precision of test signals is very high.
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Keywords:
carriage error; multi-body system; error identification; cross-correlation analysis; wavelet transform
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MDPI and ACS Style
Mu, D.; Chen, D.; Fan, J.; Wang, X.; Zhang, F. Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation. Sensors 2012, 12, 9551-9565. https://doi.org/10.3390/s120709551
AMA Style
Mu D, Chen D, Fan J, Wang X, Zhang F. Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation. Sensors. 2012; 12(7):9551-9565. https://doi.org/10.3390/s120709551
Chicago/Turabian StyleMu, Donghui, Dongju Chen, Jinwei Fan, Xiaofeng Wang, and Feihu Zhang. 2012. "Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation" Sensors 12, no. 7: 9551-9565. https://doi.org/10.3390/s120709551
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