Comparative analysis of grain size for bearing coating using variational mode decomposition of vibration signal
Abstract One of the prime factors behind variation in properties of the given material is the change in its grain size. In this work, any change in grain size of bearing coating selected as an indicator to alert deterioration in coated surface of the bearing. Here, an online method to differentiate the level of grain size for the bearing surface is presented using vibration signature analysis. Five ball bearings (Make: NBC, Model: 6205) were electroplated with industry specified coatings, Black oxide, Silver, Copper, Zinc phosphate (ZnP), Nickel. These coated bearings were installed in customised bearing test rig, one after another. Each coated bearing was made to run at five different speeds varying from 300 rpm to 1500 rpm and its vibration signatures were captured. The obtained vibration signals must be carrying unique characteristics corresponding to interaction of bearing balls with surfaces of different grain size thus distributed in general. The signals were decomposed into six modes using Variational mode decomposition (VMD) for band wise evaluation Further, to study distributed characteristics present in the signal in relevance to grain size, prominently used statistical parameters: Root Mean Square (RMS), crest factor, Variance, Skewness, Kurtosis, Shannon entropy and Log energy were selected. Then, all previously mentioned statistical parameters were calculated individually for newly generated frequency bands. Further, it has been noted that at 300 & 1500 rpm, RMS has shown considerable correlation to grain size variation. Additionally, it has been noted that these responded Intrinsic Mode Functions (IMFs) were not having high energy contents of the signal which indicates the miniscule presence of grain size signature in vibration signal in comparison to other rotational characteristics. On further analysis based on the chain indexing, RMS was found to be most relevant statistical parameter at low rpm as well as high rpm in reference to grain size.
Authors
- Manpreet Singh (ORCID: https://orcid.org/0000-0002-3916-6927)
- Rameshwar Cambow (ORCID: https://orcid.org/0000-0002-5369-7433)
Institutions
- Lovely Professional University (IN)
Publication Details
- Journal
- Engineering Research Express
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1088/2631-8695/ad9e83
- Citations
- 2
- Primary Topic
- Machine Fault Diagnosis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.66