Total Non-harmonic Distortion Research Articles

An implementation of Short Time Fourier Transform for Harmonic Signal Detection

Power electronic components has the tendency to induce a non-linear signal called harmonic distortion. Without proper monitoring tools, harmonic distortion can harm sensitive electronic equipment, and in worse case scenarios, may lead to unreliable operation of controller and misalignment of motoring unit. This matter can be compromised by taking safety precaution, by identifying the level of harmonic rise in the electrical system. This paper presents analysis on different characteristics of harmonic signal using frequency distribution technique, namely Fourier transform (FT), and proposal of time-frequency distribution (TFD) technique, which is a short time Fourier transform (STFT). The novelty of utilizing STFT is the analyzed signal is represented in both time and frequency marginals, hence providing extra information of the spectral over the time. Simulation was carried out using MATLAB, by means the results consisting of the magnitude of multi-frequency components signal were represented in time-frequency representation (TFR). From the TFR, parameters such as instantaneous RMS fundamental voltage, V1RMS(t), instantaneous RMS voltage, VRMS(t), instantaneous total waveform distortion, VTWD(t), instantaneous total harmonic distortion, VTHD(t) and instantaneous total nonharmonic distortion, VTnHD(t) had been extracted. The performance of different harmonic signals such as normal, single-level harmonic, multi-level harmonic, short duration harmonic and interharmonic had been analyzed. The performance based on absolute percentage error (APE) index indicated average of 93% of correctness using 256 window length in STFT measurement.

Harmonic Contribution Analysis of Electric Arc Furnace by Using Spectrogram

In this paper, spectrogram, a fast and accurate technique is introduced for the analysis of the contribution. Based on a rule-based classifier and the threshold settings that referred to the IEEE Standard 1159 2009, the analysis of the harmonic and interharmonic contribution of EAF are carried out successfully. Moreover, the impact of contribution is measured using total harmonic distortion (THD) and total non-harmonic distortion (TnHD). In addition, spectrogram also gives 100 percent correct detection and able to analyze the contribution impact. It is proven that the proposed method is accurate, fast and cost efficient for analyzing the impact of harmonic and interharmonic of EAF.

An Evaluation of Linear Time Frequency Distribution Analysis for VSI Switch Faults Identification

This paper present an evaluation of linear time frequency distribution analysis for voltage source inverter system (VSI). Power electronic now are highly demand in industrial such as manufacturing, industrial process and semiconductor because of the reliability and sustainability. However, the phenomenon that happened in switch fault has become a critical issue in the development of advanced. This causes problems that occur study on fault switch at voltage source inverter (VSI) must be identified more closely so that problems like this can be prevented. The TFD which is STFT and S-transform method are analyzed the switch fault of VSI. To identify the VSI switches fault, the parameter of fault signal such as instantaneous of average current, RMS current, RMS fundamental current, total waveform distortion, total harmonic distortion and total non-harmonic distortion can be estimated from TFD. The analysis information are useful especially for industrial application in the process for identify the switch fault detection. Then the accuracy of both method, which mean STFT and S-transform are identified by the lowest value of mean absolute percentage error (MAPE). In addition, the S-transform gives a better accuracy compare with STFT and it can be implement for fault detection system.

Performance Evaluation of Real Power Quality Disturbances Analysis Using S-Transform

Power quality is main issue because of the impact to electricity suppliers, equipments, manufacturers and user.To solve the power quality problem, an analysis of power quality disturbances is required to identify and rectify any failures on power system. Most of researchers apply fourier transform in power quality analysis, however the ability of fourier transform is limited to spectral information extraction that can be applied on stationary disturbances. Thus, time-frequency analysis is introduced for analyzing the power quality distubances because of the limitation of fourier transform. This paper presents the analysis of real power quality disturbances using S-transform. This time-frequency distribution (TFD) is presented to analyze power quality disturbances in time-frequency representation (TFR). From the TFR, parameters of the disturbances such as instantaneous of root mean square (RMS), fundamental RMS, total harmonic distortion (THD), total nonharmonic distortion (TnHD) and total waveform distortion (TWD) of the disturbances are estimated. The experimental of three phase voltage inverter and starting motor are conducted in laboratory to record the real power quality disturbances. The disturbances are recorded via data logger system which is mplemented using LabVIEW while the analysis is done using Matlab in offline condition. The results show that S-transform gives good performance in identifying, detecting and analyzing the real power quality disturbances, effectively.

Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions

Voltage source inverter (VSI) plays an important roles in electrical drive systems. Consistently, expose to hash environmental condition, the lifespan of the electronic component such as insulated-gate bipolar transistor (IGBT) may shorten and many faults related to the inverter especially switches can be occur. The present of VSI switches faults causing equipment failure and increased the cost of manufacturing process. Therefore, faults detection analysis is mandatory to identify the VSI switches faults. This paper presents the analysis of VSI switches faults using time-frequency distributions (TFDs) which are short times Fourier transform (STFT) and spectrogram. From time-frequency representation (TFR) obtained by using the TFDs, parameters of the faults signal are estimated such as instantaneous of average, root mean square (RMS), fundamental, Total Waveform Distortion (TWD), Total Harmonics Distortion (THD) and Total non-Harmonic Distortion (TnHD) of current signals. Then, based on the characteristics of the faults calculated from the signal parameters, VSI switches faults can be detected and identified. The performance of TFD for the faults analysis is also demonstrated to obtain the best TFD for switches faults detection and identification system. The results show that, STFT is the best technique to classify and identify VSI switches faults and can be implemented for automated system.

Performance Verification of Power Quality Signals Classification System

Power quality has become a greater concern nowadays. The increasing number of power electronics equipment contributes to the poor quality of electrical power supply. The power quality signals will affect manufacturing process, malfunction of equipment and economic losses. This paper presents the verification analysis of power quality signals classification system. The developed system is based on linear time-frequency distribution (TFD) which is spectrogram that represents the signals jointly in time-frequency representation (TFR). The TFD is very appropriate to analyze power quality signals that have magnitude and frequency variations. Parameters of the signal such as root mean square (RMS) and fundamental RMS, total waveform distortion (TWD), total harmonic distortion (THD) and total non-harmonic distortion (TnHD) of voltage signal are estimated from the TFR to identify the characteristics of the signal. Then, the signal characteristics are used as input for signal classifier to classify power quality signals. In addition, standard power line measurements are also calculated from voltage and current such as RMS and fundamental RMS voltage and current, real power, apparent power, reactive power, frequency and power factor. The power quality signals focused are swell, sag, interruption, harmonic, interharmonic, and transient based on IEEE Std. 1159-2009. The power quality analysis has been tested using a set of data and the results show that, the spectrogram gives high accuracy measurement of signal characteristics. However, the system offers lower accuracy compare to simulation due to the limitation of the system.

Analysis of Power Quality Disturbances Using Spectrogram and S-transform

The performance analysis of spectrogram and S-transform for power quality disturbances such as swell, sag, interruption, harmonic, inter-harmonic, and transient based on IEEE Std 1159-2009 are presented. These analyses are performed to identify the best performance for detection of power quality disturbances. This is important to provide the improvement of power quality which capable to accurately measured, detect the power quality phenomena. Therefore the accurate detection of power quality disturbances can be developed based on the best techniques. By using both techniques, the temporal and spectral information are obtained. From the time frequency representation (TFR) the signal parameters are estimated such as instantaneous root means square voltage (RMS), total waveform distortion (TWD), total harmonic distortion (THD) and total non harmonic distortion (TnHD).The signal characteristics are calculated from signal parameters to verify the performances of both techniques, the APE results are used to identify the accuracy of these techniques. By perform the analysis; the result show the S-transform is a better tool to analyze the transient disturbances whereas for voltage variation and harmonic disturbances the spectrogram gives higher accuracy result. As a conclusion both techniques are capable to analyzed power quality disturbances, and it clearly shows that, the S-transform has an advantages in term of time-frequency resolution which capable to detect and localized various kind of power quality disturbances and it essential for the development of advanced real-time monitoring.