Vibration condition monitoring in a paper industrial plant: Supreme project

Mario Eltabach 1 Sophie Sieg-Zieba 1 Guanghan Song 2 Zhongyang Li 2 Pascal Bellemain 3 Nadine Martin 2
2 GIPSA-SAIGA - SAIGA
GIPSA-DA - Département Automatique, GIPSA-DIS - Département Images et Signal
3 GIPSA-Services - GIPSA-Services
GIPSA-lab - Grenoble Images Parole Signal Automatique
Abstract : This paper presents a condition monitoring methodology applied to the suction roll and the Press roll of a paper machine. Experimental results obtained for the detection and identification of many defects that may occur to different mechanical components are presented. To this end, many fault indicators are calculated using a set of signal processing methods. We endeavor to propose robust fault indicators with respect to the variations of the operation parameters as the speed variation. Cyclostationary and cepstral approaches are used in order to make vibration source separation and to extract pertinent indicators closely related to the health of the paper machine. AStrion strategy, a stand-alone, data-driven and automatic tracking analyzer, is applied in order to characterize a sensor failure on the suction roll and a fault on the motor that drives the press roll. The trends of these parameters have shown the effectiveness of these methods to detect and identify the failure modes of the equipment thus allowing the reduction of the overall maintenance cost. This work has been done within the SUPREME project, funded by the European Commission, under the FP7 program.
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Mario Eltabach, Sophie Sieg-Zieba, Guanghan Song, Zhongyang Li, Pascal Bellemain, et al.. Vibration condition monitoring in a paper industrial plant: Supreme project. 13th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM2016/MFPT2016), Oct 2016, Paris, France. ⟨hal-01399036⟩

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