Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation

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 t...

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Main Authors: Xiaofeng Wang, Feihu Zhang, Donghui Mu, Dongju Chen, Jinwei Fan
Format: Article
Language:English
Published: MDPI AG 2012-07-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/7/9551
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spelling doaj-42333f31b9a64102b7937d8023505ca32020-11-24T23:58:56ZengMDPI AGSensors1424-82202012-07-011279551956510.3390/s120709551Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet TransformationXiaofeng WangFeihu ZhangDonghui MuDongju ChenJinwei FanThis 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.http://www.mdpi.com/1424-8220/12/7/9551carriage errormulti-body systemerror identificationcross-correlation analysiswavelet transform
collection DOAJ
language English
format Article
sources DOAJ
author Xiaofeng Wang
Feihu Zhang
Donghui Mu
Dongju Chen
Jinwei Fan
spellingShingle Xiaofeng Wang
Feihu Zhang
Donghui Mu
Dongju Chen
Jinwei Fan
Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
Sensors
carriage error
multi-body system
error identification
cross-correlation analysis
wavelet transform
author_facet Xiaofeng Wang
Feihu Zhang
Donghui Mu
Dongju Chen
Jinwei Fan
author_sort Xiaofeng Wang
title Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
title_short Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
title_full Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
title_fullStr Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
title_full_unstemmed Carriage Error Identification Based on Cross-Correlation Analysis and Wavelet Transformation
title_sort carriage error identification based on cross-correlation analysis and wavelet transformation
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2012-07-01
description 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.
topic carriage error
multi-body system
error identification
cross-correlation analysis
wavelet transform
url http://www.mdpi.com/1424-8220/12/7/9551
work_keys_str_mv AT xiaofengwang carriageerroridentificationbasedoncrosscorrelationanalysisandwavelettransformation
AT feihuzhang carriageerroridentificationbasedoncrosscorrelationanalysisandwavelettransformation
AT donghuimu carriageerroridentificationbasedoncrosscorrelationanalysisandwavelettransformation
AT dongjuchen carriageerroridentificationbasedoncrosscorrelationanalysisandwavelettransformation
AT jinweifan carriageerroridentificationbasedoncrosscorrelationanalysisandwavelettransformation
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