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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Verma, Nishchal K. Gupta, Rajat Sevakula, Rahul K. Salour, Al |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Electronics & Communication Engineering, Indian Institute of Information Technology Allahabad (Gupta, Rajat) || Boeing Company, St. Louis, MO, USA (Salour, Al) || Dept. of Electrical Engineering, Indian Institute of Technology Kanpur, India (Verma, Nishchal K.; Sevakula, Rahul K.) |
| Abstract | Machine monitoring and fault diagnostics have become a major and a prominent area for research now days. For doing the same, there is great scope for using better signal processing tools in extracting key features from machine's acoustic and vibration data. This paper provides a brief survey and comparison of various transforms that can be performed on vibration data for extracting features. The transforms used are Fast Fourier Transform, Discrete Cosine Transform, Autocorrelation function, Convolution with Sinusoidal, Short Time Fourier Transform, Cohen's Class Distributions, S-Transform and various Wavelet Transforms. A case study of fault diagnosis was performed on an air compressor in three different states namely Healthy, Leakage Outlet Valve fault and Leakage Inlet Valve fault. The features from these transforms have been compared with respect to their precision in recognizing the three states. Results showed that instead of using a huge feature set, finding out the right transform for recognizing a certain fault could be a very good course of action. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 762055 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479940769 |
| ISSN | 21593450 |
| e-ISBN | 9781479940752 |
| DOI | 10.1109/TENCON.2014.7022275 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-10-22 |
| Publisher Place | Thailand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems Zinc Field-flow fractionation air compressor fault diagnosis condition monitoring feature extraction time-frequency representation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Computer Science Applications |
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