A new method of elimination of power line noise in electrocardiogram signals is presented. The proposed method employs, as its main building block, a recently developed signal processing algorithm capable of extracting a specified component of a signal and tracking its variations over time. Design considerations and performance of the proposed method are presented with the aid of computer simulations. Superior performance is observed in terms of effective elimination of noise under conditions of varying powerline interference frequency. The proposed method presents a simple and robust structure which complies with practical constraints involved in the problem such as low computational resource availability and low sampling frequency.
Previous work on condition monitoring of induction machines has focused on steady-state speed operation. Here, a new concept is introduced based on an analysis of transient machine currents. The technique centers around the extraction and removal of the fundamental component of the current and analyzing the residual current using wavelets. Test results of induction machines operating both as a motor and a generator shows the ability of the algorithm to detect broken rotor bars.
A new algorithm is introduced for motor current signature analysis of induction machines operating during transients. The algorithm is able to extract the amplitude, phase and frequency of a single sinusoid embedded in a non-stationary waveform. The algorithm is applied to the detection of broken rotor bars in induction machines during startup transients. The fundamental component of current, which varies in amplitude, phase and frequency, is extracted using the algorithm. The residual current is then analyzed using wavelets for the detection of broken rotor bars. This method of condition monitoring does not require parameters such as speed or number of rotor bars, is not load dependent and can be applied to motors that operate continuously in the transient mode e.g. wind generators or motor operated valves.
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