| contributor author | R. Tafreshi | |
| contributor author | F. Sassani | |
| contributor author | H. Ahmadi | |
| contributor author | G. Dumont | |
| date accessioned | 2017-05-09T00:36:02Z | |
| date available | 2017-05-09T00:36:02Z | |
| date copyright | April, 2009 | |
| date issued | 2009 | |
| identifier issn | 1048-9002 | |
| identifier other | JVACEK-28899#024501_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/142304 | |
| description abstract | This paper presents a novel wavelet-based methodology for feature extraction and classification. To compare the performance of the proposed approach with major existing methods, a number of sets of real-world machine data acquired by mounting accelerometer sensors on the cylinder head of an engine have been extensively tested. The developed method not only bypasses the demerits of the previous techniques but also demonstrates superior performance. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | An Approach for the Construction of Entropy Measure and Energy Map in Machine Fault Diagnosis | |
| type | Journal Paper | |
| journal volume | 131 | |
| journal issue | 2 | |
| journal title | Journal of Vibration and Acoustics | |
| identifier doi | 10.1115/1.2980367 | |
| journal fristpage | 24501 | |
| identifier eissn | 1528-8927 | |
| keywords | Machinery | |
| keywords | Entropy | |
| keywords | Algorithms | |
| keywords | Signals | |
| keywords | Wavelets | |
| keywords | Engines AND Fault diagnosis | |
| tree | Journal of Vibration and Acoustics:;2009:;volume( 131 ):;issue: 002 | |
| contenttype | Fulltext | |