摘要：AbstractWithin Prognostics and Health Management (PHM), State Assessment (SA) consists in the classification of the health state of a physical asset starting from the processing of signals acquired by selected sensors. Nowadays, Infrared Thermography (IRT) is successfully utilized with this purpose in different domains. However, the literature lacks of studies concerning the use of IRT for the SA of rolling bearings. In response to this issue, this work analyzes the potential that indicators obtained with passive thermography may have for classifying the severity of failures in the outer-race of rolling bearings. With this purpose, different single point defects were generated in the bearing outer-race with electrical discharge machining. Then, thermal images were acquired during the operation of the bearings, and indicators of the transient and steady-state behavior were calculated for the classification of the different health states. Four indicators presented a monotonic tendency with respect to the dimension of the defect, resulting promising for the SA of rolling bearings. Given the effectiveness that IRT has in other domains, we hope that this study may impulse the research in PHM of rolling bearings through IRT.
