Bi‐Signature optical spectroscopy for online fault detection in electrical machines

Author:

Alalibo Belema P.1,Cao Wenping1,Liu Zheng1

Affiliation:

1. School of Engineering and Applied ScienceAston UniversityBirminghamUK

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Reference20 articles.

1. GallinatC.S. WeylD.K.: ‘Motors are everywhere and efficient – but they can be even better’ CLEANENERGY MINISTERIAL 2014. Available athttp://www.cleanenergyministerial.org/Blog/motors‐are‐everywhere‐and‐efficient‐but‐they‐can‐be‐even‐better‐414

2. A survey of condition monitoring and protection methods for medium‐voltage induction motors;Zhang P.J.;IEEE Trans. Ind. Appl.,2011

3. ABB: ‘4 types of maintenance strategy which one to chose?’ 2017. Available athttp://new.abb.com/medium‐voltage/service/maintenance/feature‐articles/4‐types‐of‐maintenance‐strategy‐which‐one‐to‐choose

4. PlanteT. StanleyL. NejadpakA.et al.: ‘Rotating machine fault detection using principal component analysis of vibration signal’ 2016

5. YangW. TavnerP.J. WilkinsonM.: ‘Wind turbine condition monitoring and fault diagnosis using both mechanical and electrical signatures’.2008 IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics Xi'an China 2008 pp.1296–1301

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