Abstract--This paper presents the detection and classifications of power quality disturbances using time-frequency signal analysis. The method used is based on the pattern recognition approach. It consists of parameter estimation followed classification. Based on the spectrogram time-frequency analysis, a set of signal parameters are estimated as input to a classifier network. The power quality events that are analyzed are swell, sag, interruption, harmonic, interharmonic, transient, notching and normal voltage. The parameter estimation is characterized by voltage signal in rms per unit, waveform distortion, harmonic distortion and interharmonic distortion. A rule based system is developed to detect and classify the various types of power quality disturbances. The system has been tested with 100 data for each power quality event at SNR from 0dB to 50dB to verify its performance. The results show that the system gives 100 percent accuracy of power quality signals at 30dB of SNR. Index Terms-- Spectrogram, pattern classification, power quality, time-frequency analysis, Signal to Noise Ratio (SNR). I. INTRODUCTION ith the rapid advance in industrial applications that rely on sophisticated electronic devices, a demand for power quality and reliability has become a great concern because the smallest interruption of power quality event can cause equipment failure, data loss and loss revenue. Voltage disturbances are the most frequent cause of a broad range of disruption in industrial and commercial power supply systems. These disturbances often referred to as power quality problems, which significantly affect many industries [1]. Major causes of power quality related revenue losses are interrupted manufacturing processes and computer network downtime. The examples abound in semiconductor industry, chemical industry, automobile industry, paper manufacturing, and e- commerce. A report by Consortium for Electric Infrastructure to Support a Digital Society (CEIDS) [2] shows that the U.S. economy is losing between $104 billion and $164 billion a year due to outages and another $15 billion to $24 billion due to power quality phenomena. The conventional methods Abdul Rahim Abdullah is a student at the Faculty of Electrical Engineering, Universiti Teknologi Malaysia - (email: abdulr@utem.edu.my) Ahmad Zuri Sha’ameri is with the Faculty of Electrical Engineering, Universiti Teknologi Malaysia - (email: ahmadzs@yahoo.com) currently used by utilities for power quality monitoring are primarily based on visual inspection of voltage and current waveforms [2]. Therefore, a highly automated monitoring software and hardware is needed in order to provide adequate coverage of the entire system, understand the causes of these disturbances, resolve existing problems, and predict future problems. This paper looks at the use of time-frequency representation in the interpretation of power quality disturbances. Spectrogram distribution is performed to detect and classify the power quality events. By using its time- frequency characteristics, each of the disturbance signal’s features is distinguished for the classification of the respective types of power quality problems. II. POWER QUALITY PHENOMENA The term power quality refers to a wide variety of electromagnetic phenomena that characterize the voltage and current at a given time and at a given location on the power system. According to the International Electrotechnical Commission (IEC), electromagnetic phenomena are classified into several groups as shown in Table 1 [3], [4]. This paper focused on seven types of power quality problems: voltage swell, voltage sag, interruption, harmonic, interharmonic, transient and notching. A. Voltage Swell A swell is defined as an increase in rms voltage at the power frequency for durations from 0.5 cycles to 1 minute. Typical magnitudes are between 1.1 and 1.8pu. B. Voltage Sag Voltage sag is a decrease to between 0.1 to 0.9pu in rms voltage at the power frequency for duration of 0.5 cycles to 1 minute. C. Interruption An interruption occurs when the supply voltage or load current decreases to less than 0.1pu for a period of time not exceeding 1 minute. D. Harmonic Harmonics are sinusoidal voltages or currents having frequencies that are integer multiples of the frequency at which the supply system is designed to operate (50Hz for Detection and Classification of Power Quality Disturbances Using Time-Frequency Analysis Technique Abdul Rahim Abdullah and Ahmad Zuri Sha’ameri W The 5 th Student Conference on Research and Development –SCOReD 2007 11-12 December 2007, Malaysia 1-4244-1470-9/07/$25.00 ©2007 IEEE.