Induction Machine Stator Inter-Turn Short Circuit Fault Detection using Discrete Wavelet Transform

A novel technique for the detection of stator inter-turn short circuit fault of the induction motor is presented. At first, the discrete wavelet transform (DWT) is performed on the windowed steady state stator currents to obtain the detailed coefficients at higher wavelet level. It has been observed that the faulty motor produces higher statistical parameters of the reconstructed details- RMS and Power Detailed Energy (PDE) than those values for the healthy one. Illustrative laboratory test results confirm the validity and accurate performance of the proposed method. Keywords: inter-turn short, induction motor, Discrete wavelet transform, power detail energy, RMS value

Certified Organization, Volume3, Special Issue 6

ABSTRACT: The paper describes the development of a low cost and simple amplifier circuit for ECG acquisition from a single lead. The acquisition circuit uses clip-type flat metal plate limb electrodes to sense the heart signals and a basic amplifier circuit is designed using JFET OP-AMP IC LF-353 with the required gain to suitably amplify the signal. The amplified data fed into a computer using USB-6009 is then denoised, processed and displayed using LabVIEW software. The developed ECG acquisition module is evaluated by visual comparison of simultaneously recorded data acquired by the module with and by the MP-150 amplifier system from BIOPAC Systems Inc. Tests have been performed in the laboratory on several volunteers in the age group of 28-60 and the results were quiet satisfactory

ECG Signal Denoising and QRS Complex Detection by Wavelet Transform Based Thresholding

Biomedical signals like heart waves commonly change their statistical property over time and are highly non stationary signals. For the analysis of this kind of signals wavelet transform is a powerful tool. Electrocardiogram (ECG) is one of the most widely used diagnostic tools for heart disease. Automatic detection of R peaks in a QRS complex is a fundamental requirement for automatic disease identification. This paper presents a novel algorithm and its implementation details for denoising an ECG signal along with accurate detection of R peaks and hence the QRS complex using Discrete Wavelet Transform (DWT) where db6 is selected as the mother wavelet for analysis as it is found to be most similar to the morphology of QRS complexes. Decomposition and selective reconstruction by elimination of higher scale details from the signal, denoises it considerably. Thresholding along with slope inversion method is used for detection of QRS complex. The performance of the system is validated using the 12-lead ECG recordings collected from physionet PTB diagnostic database giving a sensitivity of 99.4 %

Area-Based Approach in Power Quality Assessment

This paper presents an approach for assessment of power quality parameters using analysis of fundamental and harmonic voltage and current waveforms. Park transformation technique has been utilized for the analysis in three-phase system, which has reduced the computational effort to a great extent. Contributions of fundamental and harmonic components in power system voltage and current signals have been assessed separately. An algorithm has been developed to calculate the power quality parameters from online signals. This algorithm has been simulated for a radial system, and the results have been compared with that obtained from a standard FFT-based system. The results are seen to be in good agreement with that of the standard system

ECG acquisition and automated remote processing

The book is focused on the area of remote processing of ECG in the context of telecardiology, an emerging area in the field of Biomedical Engineering Application. Considering the poor infrastructure and inadequate numbers of physicians in rural healthcare clinics in India and other developing nations, telemedicine services assume special importance. Telecardiology, a specialized area of telemedicine, is taken up in this book considering the importance of cardiac diseases, which is prevalent in the population under discussion. The main focus of this book is to discuss different aspects of ECG acquisition, its remote transmission and computerized ECG signal analysis for feature extraction. It also discusses ECG compression and application of standalone embedded systems, to develop a cost effective solution of a telecardiology system

Diagnosis of Broken Rotor Bar Fault of Induction Motor through Envelope Analysis of Motor Startup Current using Hilbert and Wavelet Transform

This paper proposes a new method for extraction of low frequency oscillation from the envelope analysis of Motor Startup Current for diagnosis of Broken Rotor Bar Fault of Induction motor through Wavelet and Hilbert Transforms. The Envelope is the modulus of the Complex Analytic signal generated by using the original signal as the real part and its Hilbert Transform as the imaginary part. The concept of instantaneous frequency introduced in this paper is quite efficient to extract important transient fault informations, specially for non- stationary signal which is nonlinear. This method overcomes the difficulties of traditional FFT and Prony analysis as well as difficulties in selection of mother wavelet. Higher level detail coefficients correspond to narrow band low frequency components below the supply frequency are used to distinguish the faulty motor from the healthy one. Simultaneously this method has higher detectability and higher resolution and it can also deal with short data effectively, so it can be used online. This method has been validated in a laboratory standard

ECG Acquisition and Automated Remote Processing

XVII, 131 p. 65 illus.online resource