Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/65807
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Ren, MJ | en_US |
dc.creator | Sun, LJ | en_US |
dc.creator | Liu, MY | en_US |
dc.creator | Cheung, CF | en_US |
dc.creator | Yin, YH | en_US |
dc.creator | Cao, YL | en_US |
dc.date.accessioned | 2017-05-22T02:09:16Z | - |
dc.date.available | 2017-05-22T02:09:16Z | - |
dc.identifier.issn | 0141-6359 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/65807 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2016 Published by Elsevier Inc. | en_US |
dc.rights | © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.rights | The following publication Ren, M. J., Sun, L. J., Liu, M. Y., Cheung, C. F., Yin, Y. H., & Cao, Y. L. (2017). A weighted least square based data fusion method for precision measurement of freeform surfaces. Precision Engineering, 48, 144-151 is available at https://doi.org/10.1016/j.precisioneng.2016.11.014 | en_US |
dc.subject | B-spline | en_US |
dc.subject | Data fusion | en_US |
dc.subject | Freeform surfaces | en_US |
dc.subject | Precision surface measurement | en_US |
dc.subject | Weighted least square | en_US |
dc.title | A weighted least square based data fusion method for precision measurement of freeform surfaces | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 144 | en_US |
dc.identifier.epage | 151 | en_US |
dc.identifier.volume | 48 | en_US |
dc.identifier.doi | 10.1016/j.precisioneng.2016.11.014 | en_US |
dcterms.abstract | The trend towards product miniaturisation and multi-functionality constitutes a driving force for the application of complex surfaces in many fields such as advanced optics. The precision measurement of these surfaces should be carried out at multiple scales, of which process commonly involves several datasets obtained from different sensors. This paper presents a weighted least square based multi-sensor data fusion method for such measurement. The method starts from unifying the coordinate frames of the measured datasets using an intrinsic feature based surface registration method. B-spline surface is used to fit linear surface model to each identified overlapping area of the registered datasets, respectively. By forming a common basis function, the fitted surface models and the corresponding residuals are then combined to construct a weighted least square based data fusion system which is used to generate a fused surface model. An analysis of the uncertainty propagation in data fusion process is also given. Both computer simulation and actual measurement on various freeform surfaces are conducted to verify the validity of proposed method. The results indicate that the proposed method is capable of fusing multi-sensor measured datasets with notable reduction of the measurement uncertainty. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Precision engineering, Apr. 2017, v. 48, p. 144-151 | en_US |
dcterms.isPartOf | Precision engineering | en_US |
dcterms.issued | 2017-04 | - |
dc.identifier.scopus | 2-s2.0-85007320061 | - |
dc.identifier.ros | 2016001621 | - |
dc.identifier.rosgroupid | 2016001595 | - |
dc.description.ros | 2016-2017 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.validate | 201804_a bcma | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | ISE-0814 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China; China National Program on Key Basic Research Project; Shanghai Pujiang Program of China; PolyU | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6709092 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Cheung_Weighted_Least_Square.pdf | Pre-Published version | 1.79 MB | Adobe PDF | View/Open |
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