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In the field of machine health monitoring, vibration analysis is a proven method for detecting and diagnosing bearing faults in rotating machines. One popular method for interpreting vibration signals is envelope-demodulation, which allows the maintainer to clearly identify an impulsive fault source and its severity. In some cases, in-band noise can make impulses associated with incipient faults difficult to detect and interpret. In this paper, we use Wavelet De-Noising (WDN) after envelope-demodulation to improve the accuracy of bearing fault diagnostics. This contrasts the typical approach of de-noising raw vibration signals prior to demodulation. We find that WDN removes low amplitude harmonics and spurious reflections which may interfere with FFT techniques to identify low-frequency peaks in the signal spectrum. When measuring impact frequencies in the time-domain using a peakthresholding method, the proposed algorithm exhibits increasingly confident periodicity at bearing fault frequencies.

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This paper describes a new method of comparing images of circular/near-circular symmetry so as to elucidate the similarity details between them. If one such image is a test-entity and the other is a reference template, the comparison in question will lead to find the unique features (and their locations) in the test-image vis-à-vis the template. The method of comparison and similarity assessment indicated thereof is to use the so-called Needleman-Wunsch (NW) and Smith-Waterman (SW) algorithms commonly adopted in bioinformatic contexts of comparing two linear sequences (like DNA chains). Relevant procedure is extended in this study to address 2D-patterns. It involves first transforming the test-image (of circular symmetry) from polar-plane to a rectangular format. Next, the transformed test-image is digitised and compared against a template (also in digital rectangular format) on row-to-row and column-to-column basis. The resulting alignment of pixel bits in the test-image versus the template leads to an optimal score-of-similarity on the comparisons made. Biomedical applications of the proposed strategy are explored with reference to typical and circular/quasi-circular MRI images, and the associated image recognition, interpretation, and locating of the artefacts are discussed.