Condition monitoring of induction motors is a fast emerging technology in the field of electrical equipment maintenance and has attracted more and more attention worldwide as the number of unexpected failure of a critical system can be avoided. Keeping this in mind a bearing fault detection scheme of three-phase inductionmotor has been attempted. In the present study, Support VectorMachine (SVM...

In this paper, we propose a novel face recognition method for the one sample problem. This approach is based on local appearance feature extraction using directional multiresolution decomposition offered by dual tree complex wavelet transform (DT-CWT). It provides a local multiscale description of images with good directional selectivity, effective edge representation and invariance to shifts a...

The information extraction capability of two widely used signal processing tools, Hilbert Transform (HT) and Wavelet Transform (WT), is investigated to develop a multi-class fault diagnosis scheme for induction motor using radial vibration signals. The vibration signals are associated with unique predominant frequency components and instantaneous amplitudes depending on the motor condition. Usi...

We present a purely group-theoretical derivation of the continuous wavelet transform (CWT) on the (n ? 1)-sphere S n?1 , based on the construction of general coherent states associated to square integrable group representations. The parameter space of the CWT, Y SO(n)R + , is embedded into the generalized Lorentz group SO o (n; 1) via the Iwasawa decomposition, so that X ' SO o (n; 1)=N, where ...

Near-infrared (NIR) spectrometry will present a more promising tool for quantitative measurement if the robustness and predictive ability of the partial least square (PLS) model are improved. In order to achieve the purpose, we present a new algorithm for simultaneous wavelength selection and outlier detection; at the same time, the problems of background and noise in multivariate calibration a...

This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG da...

This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel g...

In this technical report we build Discrete Wavelet Frames on the sphere S, discretizing the existing Spherical Continuous Wavelet Transform (CWT). We first explore the spherical half-continuous frames, i.e. where the position remains a continuous variable; and then we proceed to the fully discrete frames. We introduce the notion of controlled frames, which reflects the particular nature of the ...

Abstract— In our present work, we propose a nature inspired population based speech enhancement technique to find the dynamic threshold value using Teaching-Learning Based Optimization (TLBO) algorithm by using shift invariant property of dual tree complex wavelet transform (DT-CWT). The performance of these proposed methods are evaluated in terms of Perceptual Evaluation of Speech Quality (PES...

We describe a generalized scale-redundant wavelet transform which approximates a dense sampling of the continuous wavelet transform (CWT) in both time and scale. The dyadic scaling requirement of the usual wavelet transform is relaxed in favor of an approximate scaling relationship which in the case of a Gaussian scaling function is known to be asymptotically exact and irrational. This scheme y...