کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1679549 | 1518429 | 2014 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Principal component analysis for feature extraction and NN pattern recognition in sensor monitoring of chip form during turning
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Experimental cutting tests on C45 carbon steel turning were performed for sensor fusion based monitoring of chip form through cutting force components and radial displacement measurement. A Principal Component Analysis algorithm was implemented to extract characteristic features from acquired sensor signals. A pattern recognition decision making support system was performed by inputting the extracted features into feed-forward back-propagation neural networks aimed at single chip form classification and favourable/unfavourable chip type identification. Different neural network training algorithms were adopted and a comparison was proposed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CIRP Journal of Manufacturing Science and Technology - Volume 7, Issue 3, 2014, Pages 202–209
Journal: CIRP Journal of Manufacturing Science and Technology - Volume 7, Issue 3, 2014, Pages 202–209
نویسندگان
T. Segreto, A. Simeone, R. Teti,