Abstract
For the first time worldwide, innovative techniques, generic non-linear higher-order unnormalized cross-correlations of spectral moduli, for the diagnosis of complex assets, are proposed. The normalization of the proposed techniques is based on the absolute central moments, that have been proposed and widely investigated in mathematical works. The existing higher-order, cross-covariances of complex spectral components are not sufficiently effective. The novel technology is comprehensively experimentally validated for induction motor bearing diagnosis via motor current signals. Experimental results, provided by the proposed technique, confirmed high overall probabilities of correct diagnoses for bearings at early stages of damage development. The proposed diagnosis technology is compared with existing diagnosis technology, based on the triple cross-covariance of complex spectral components.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference63 articles.
1. Ciszewski, T., Gelman, L., and Ball, A. (2020). Novel fault identification for electromechanical systems via spectral technique and electrical data processing. Electronics, 9.
2. Gelman, L., Soliński, K., and Ball, A. (2020). Novel higher-order spectral cross-correlation technologies for vibration sensor-based diagnosis of gearboxes. Sensors, 20.
3. Current-based higher-order spectral covariance as a bearing diagnostic feature for induction motors;Insight-Non-Destr. Test. Cond. Monit.,2016
4. Motor bearing damage detection, using stator current monitoring;IEEE Trans. Ind. Appl.,1995
5. Areias, I.A.d.S., Borges da Silva, L.E., Bonaldi, E.L., de Lacerda de Oliveira, L.E., Lambert-Torres, G., and Bernardes, V.A. (2019). Evaluation of Current Signature in Bearing Defects by Envelope Analysis of the Vibration in Induction Motors. Energies, 12.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献