Measure The Similarity Of Each Two Successive Cycles For The Same Electrical Signals

The comparison of above three algorithms for 8, 16 and 32 bit operands with corresponding voltage and frequency are tabulated in table I

Figure.10 (a) Hardware test bench set up (b) Gating pulses for 70 KHz from DSP processor (c) Input voltage and input current waveforms for 230Vrms (d) Input voltage and input current waveforms for 110 Vrms

During lab, we have designed circuits proving each of these electrical principles. Now, let's apply this knowledge to a real world application.

The impact of the proposed sequences has been simulated for 0.4 modulation index with a 0.5 lagging power factor load (power factor angle 60°). The simulation setup consists of the following software: 1) MATLAB/Simulink – used to implement the modulation strategies and switching sequences, and 2) PSIM – used to simulate the T-NPC inverter running with an R-L load and to provide conduction and switching losses of each switch. The inverter switching pulses were generated within Simulink and were fed to PSIM through sim-coupler module which provides a link between PSIM and simulink for the purpose of co-simulation [29].

Autocorrelation test aims to determine whether there is a correlation between bully errors in period t to period t-1 (previously). If correlation occurs, then there is a problem called autocorrelation. Autocorrelation appears because successive observations over time are related to each other.

The DVR is one of the most common and effective solutions for protecting critical load against voltage sags [10] [11]. The DVR is a power electronic device used to inject three-phase voltages in series and in synchronism with the distribution feeder voltages in order to compensate for voltage sags. Moreover, it can be efficiently used to augment the fault ride through capability in wind applications. Detection time is an important factor in the voltage restitution process. Fast detection

In this project, we would like to study more on pulse width modulation (PWM) technique which is a powerful technique to control analog circuits with digital outputs. For that, we have to understand about digital oscillation and how its width can affect the output of PWM. Example has been provided in manual and simulation forms to improve our knowledge on PWM. We would also like to study the different types of PWM available today. Lastly, we would like to look at the applications of PWM in our industry especially in power controlling.

Below is an array of the circuit configurations we created and tested. The title is within the images themselves, under “TITLE”, and the observations are right below the image.

Autocorrelation is defined as the correlation between the value of time series at a specific time and previous values of the same series (Reference). In other words, with time series what happens in time t contains information about what will happen at time t+1. Autocorrelation plots are a commonly-used tool for checking randomness in a data set. This randomness is ascertained by computing autocorrelations for data values at varying time lags. If random, such autocorrelations should be near zero for any and all time-lag separations. If non-random, then one or more of the autocorrelations will be significantly non-zero. The autocorrelation plots can provide answers to questions such as are the data random? Is an observation related to an adjacent observation? Is the observed time series white noise, sinusoidal or autoregressive? They help in understanding the underlying relationship between the data points. The autocorrelation plots of 4 time series of heating operating system are as follows :

The most advantage is that it requires only three voltage pulse injections of small duration for the estimation of rotor position. A resolution of 30o can be achieved. The effectiveness of the method is validated by simulation results in Matlab Simulink platform.

Accordingly, the magnitude of energy density produces the spectrum of function, which is commonly indicated as color plots. To investigate the signal around time t of interest, window function has chosen that is peaked around t. Therefore, the modified signal S_t (τ) is short and its Fourier transform is called short-time Fourier transform (Satish 1998). The principle of STFT is to divide the initial waveform signal into small segments with short-time window, apply Fourier transform to each segment. However, due to the signal segmentation, this method has limitation in time–frequency resolution. It can only be applied to analyze the segmented stationary signal or the approximate

A Thesis Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering

selection scheme from multiple SISO relays was proposed in [10] to minimize the energy consumption of

In this method three modulating signals ( mR for R-phase, mY for Y-phase, mB for B-phase) with 120 degree phase shift when compared with high frequency carrier triangular signal it generates switching pulse.

The aim of this project is to construct a single phasing monitor and prevention system using 8bit microcontroller. Anti-single phasing relays or single phasing preventer are required for critical