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Volumn , Issue , 2016, Pages 1330-1335

Towards intelligent lubrication control: Infrared thermal imaging for oil level prediction in bearings

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BEARINGS (MACHINE PARTS); ENERGY DISSIPATION; IMAGE PROCESSING; IMAGE SEGMENTATION; INFRARED IMAGING; LEARNING SYSTEMS; SHAFTS (MACHINE COMPONENTS); VIDEO SIGNAL PROCESSING;

EID: 84994201604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCA.2016.7587991     Document Type: Conference Paper
Times cited : (7)

References (16)
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    • Skf Energy Efficient
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    • H. Fandino-Toro, O. Cardona-Morales, J. Garcia-Alvarez, and G. Castellanos-Dominguez, "Bearing Fault Identification using Watershed-Based Thresholding Method, " in Advances in Condition Monitoring of Machinery in Non-Stationary Operations, ser. Lecture Notes in Mechanical Engineering, G. Dalpiaz, R. Rubini, G. D'Elia, M. Cocconcelli, F. Chaari, R. Zimroz, W. Bartelmus, and M. Haddar, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014, pp. 137-147
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    • Lim, G.-M.1    Bae, D.-M.2    Kim, J.-H.3
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    • 84878337747 scopus 로고    scopus 로고
    • Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis
    • V. T. Tran, B.-S. Yang, F. Gu, and A. Ball, "Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis, " Mechanical Systems, and Signal Processing, vol. 38, no. 2, pp. 601-614, 2013
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.