| contributor author | P. G. Li | |
| contributor author | S. M. Wu | |
| date accessioned | 2017-05-08T23:27:35Z | |
| date available | 2017-05-08T23:27:35Z | |
| date copyright | August, 1988 | |
| date issued | 1988 | |
| identifier issn | 1087-1357 | |
| identifier other | JMSEFK-27732#297_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/104122 | |
| description abstract | This paper introduces a new approach for on-line monitoring of drill wear states by using a fuzzy C-means algorithm. Experimental and simulation results have shown that drill wear conditions can be represented by four fuzzy grades. They are: “initial,” “small,” “normal,” and “severe.” The grade “severe” is proposed to be used as the prediction of tool replacement. This fuzzy technique is more adequate than conventional pattern recognition technqiues. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Monitoring Drilling Wear States by a Fuzzy Pattern Recognition Technique | |
| type | Journal Paper | |
| journal volume | 110 | |
| journal issue | 3 | |
| journal title | Journal of Manufacturing Science and Engineering | |
| identifier doi | 10.1115/1.3187884 | |
| journal fristpage | 297 | |
| journal lastpage | 300 | |
| identifier eissn | 1528-8935 | |
| keywords | Wear | |
| keywords | Drilling | |
| keywords | Pattern recognition | |
| keywords | Drills (Tools) | |
| keywords | Algorithms AND Simulation results | |
| tree | Journal of Manufacturing Science and Engineering:;1988:;volume( 110 ):;issue: 003 | |
| contenttype | Fulltext | |
