Power quality diagnosis using time frequency analysis and rule based techniques

Faisal, Mohamed Fuad; Mohamed, Azah; Shareef, Hussain; Hussain, Aini

doi:10.1016/j.eswa.2011.04.047

Cited by 21 publications

(13 citation statements)

References 7 publications

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“…A novel method for conducting power quality diagnosis is presented by M. Faisal et al [9]. The method uses the S-Transform and rule based classification techniques.…”

Section: S-transform Techniques For Power Quality Signals Detection Amentioning

confidence: 99%

Review of power quality monitoring systems

Ahmad

ElSheikh

Fadoun

2015

2015 International Conference on Industrial Engineering and Operations Management (IEOM)

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Power quality is gaining a lot of interest lately by researchers and engineers as electricity is a vital part of our daily life. The aim of this paper is to survey some of the recent existing systems, techniques and methods that are being used to monitor power quality. The survey focuses mainly on power quality monitoring systems which are composed of various tools, software, communication links etc. that work together as one coherent system. Another goal is to develop an understanding about the quality management in the area of power industry. Some of the methods and techniques that are presented discuss about power quality meter placement techniques. Finding the best locations to place the power quality monitors in the electrical grid is done by developing algorithms and approaches to find the appropriate number of monitors and the appropriate locations to place them in order to reduce the cost of the PQM system and increase its efficiency. The paper discusses the basic idea of each method or system in order to have an understanding about its importance and role. Then, a simple comparison is made between the techniques in terms of their advantages and disadvantages. After that, international industry practices and guidelines for power quality monitoring and management are discussed. Lastly, some examples for the efforts that are made in the area of power quality improvement are discussed. , investigated the power quality monitoring system over the internet. The power quality monitoring system is defined as a collection of technologies including a web server, computers, communication networks and specialized PQM. The system transmits high-quality data over the communication line. The system uses technologies like GPS in order to synchronize the

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“…A novel method for conducting power quality diagnosis is presented by M. Faisal et al [9]. The method uses the S-Transform and rule based classification techniques.…”

Section: S-transform Techniques For Power Quality Signals Detection Amentioning

confidence: 99%

Review of power quality monitoring systems

Ahmad

ElSheikh

Fadoun

2015

2015 International Conference on Industrial Engineering and Operations Management (IEOM)

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“…The authors in [16][17][18] have utilized the Support Vector Machines (SVMs) to classify the disturbance types of PQ. Similar to SVM, artificial neural network (ANN) approaches have found applications in predicting the type of PQ disturbance [19].…”

Section: Introductionmentioning

confidence: 99%

An image processing based method for power quality event identification

Shareef¹,

Mohamed²,

Ibrahim³

2013

International Journal of Electrical Power & Energy Systems

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“…The field of timefrequency analysis has found wide spread application as a tool for analyzing non-stationary signals [2]. The need for processing such signals has led to the appearance of several types of time varying frequency filters, such as the Hilbert-Huang transform [3], short time Fourier transform [4], wavelets (DWT) [6][7][8][9], and more recently the S-Transform (ST) [10][11][12]. These transforms perform a conversion from a 1-dimension time signal to a 2-dimension time-frequency (or time-scale) signal.…”

Section: Introductionmentioning

confidence: 99%

Nonstationary signal pattern recognition using fast time-time filtering and decision tree

Dash

Sahu

Biswal³

2014

Journal of Intelligent &Amp; Fuzzy Systems

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This paper proposes a fast Time-Time (TT) filtering transform for analysis and pattern recognition of nonstationary signals. A fast TT-transform algorithm is developed with different types of frequency scaling, band pass filtering and interpolation techniques to reduce the computational cost. The new time-time transform uses dyadic and selective scaling that facilitates the extraction of relevant features from time-varying signals for recognizing their patterns. The extracted features are then passed through a decision tree based classifier for the identification of the signal patterns. Various real world simultaneous power signal disturbances have been simulated to prove the efficiency of the technique. The simulation results show superior performance of the new TT-Transform while classifying overlapping disturbance patterns. Because of the new fast TT -transform algorithm and a relatively simpler classifier methodology, this technique can be used for real time localization, detection, and classification of various power quality events including other nonstationary signal time series belonging to speech, biomedical signals, etc.

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Power quality diagnosis using time frequency analysis and rule based techniques

Cited by 21 publications

References 7 publications

Review of power quality monitoring systems

Review of power quality monitoring systems

An image processing based method for power quality event identification

Nonstationary signal pattern recognition using fast time-time filtering and decision tree

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