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Gantry Health Monitoring and Fault D...

Song, Rui.

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Gantry Health Monitoring and Fault Detection Based on Process Status Sequence.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Gantry Health Monitoring and Fault Detection Based on Process Status Sequence./
作者:	Song, Rui.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	46 p.
附註:	Source: Masters Abstracts International, Volume: 80-12.
Contained By:	Masters Abstracts International80-12.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13422504
ISBN:	9781392221815

Gantry Health Monitoring and Fault Detection Based on Process Status Sequence.
Song, Rui.

Gantry Health Monitoring and Fault Detection Based on Process Status Sequence. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 46 p.

Source: Masters Abstracts International, Volume: 80-12.

Thesis (M.S.)--Rutgers The State University of New Jersey, School of Graduate Studies, 2019.

This item must not be sold to any third party vendors.

Gantry refers to the system that moves the hoist by the machinery house along tracks on the floor level and transfers the material. As a critical asset, gantry has wide applications in many fields such as medical image area, infrastructure, and heavy industry. Mostly, gantry is reliable, however, the loss led by the gantry lockout is inestimable enormous. Moreover, there are limited previous gantry studies concentrate on the statistical quality control to detect the fault not to mention the research that focuses on the algorithms applied to the process status sequence to detect the fault. The categorical process status sequence is hard to obtain the features when dealing with fault identification. This thesis proposal provides a novel method applying texture extraction in image processing to obtain the features of gantry process status sequence. Texture extraction techniques such as the histogram of oriented gradients (HOG) and local binary pattern are applied to the process status sequence. To demonstrate the effectiveness of image-based feature extraction, k-nearest neighbors, support vector machine, linear discriminant analysis, and quadratic discriminant analysis are applied to the time-series gantry process status sequences provided by a leading automobile manufacturer. Result demonstrates that the sequence after the transformation of both texture extraction techniques have improved the accuracy. The process status sequence after HOG transformation has the best performance. Besides, the HOG technique also dramatically reduces the dimension of the process status sequence. This result can help the on-site expert prognosis the fault as well as prepare the corresponding troubleshooting guide to save time and resources.

ISBN: 9781392221815Subjects--Topical Terms:

586835
Engineering.

Gantry Health Monitoring and Fault Detection Based on Process Status Sequence.
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506 $a This item must not be sold to any third party vendors.
520 $a Gantry refers to the system that moves the hoist by the machinery house along tracks on the floor level and transfers the material. As a critical asset, gantry has wide applications in many fields such as medical image area, infrastructure, and heavy industry. Mostly, gantry is reliable, however, the loss led by the gantry lockout is inestimable enormous. Moreover, there are limited previous gantry studies concentrate on the statistical quality control to detect the fault not to mention the research that focuses on the algorithms applied to the process status sequence to detect the fault. The categorical process status sequence is hard to obtain the features when dealing with fault identification. This thesis proposal provides a novel method applying texture extraction in image processing to obtain the features of gantry process status sequence. Texture extraction techniques such as the histogram of oriented gradients (HOG) and local binary pattern are applied to the process status sequence. To demonstrate the effectiveness of image-based feature extraction, k-nearest neighbors, support vector machine, linear discriminant analysis, and quadratic discriminant analysis are applied to the time-series gantry process status sequences provided by a leading automobile manufacturer. Result demonstrates that the sequence after the transformation of both texture extraction techniques have improved the accuracy. The process status sequence after HOG transformation has the best performance. Besides, the HOG technique also dramatically reduces the dimension of the process status sequence. This result can help the on-site expert prognosis the fault as well as prepare the corresponding troubleshooting guide to save time and resources.
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