The increasing use of electronics in electrical equipment has made them more vulnerable to power quality disturbances. Customers are becoming more knowledgeable in these issues and demand for more detailed and precise information whenever an unfortunate event occurs. Therefore, power companies are expanding the use of information processing techniques in the attempt to determine the cause and severity of power quality event so that remedy actions can be undertaken swiftly. One such process is to pinpoint the type of disturbance that has occurred. This is achieved through some form of pattern matching where signature patterns from past experiences or simulations are used to match the recorded event. However, there are many uncertainties with...
This paper describes an algorithm to detect and classify electrical events related to power quality....
The quality of electric power and disturbances occurred in power signal has become a major issue amo...
The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to powe...
The increasing use of electronics in electrical equipment has made them more vulnerable to power qua...
Power quality is becoming increasingly important in power systems. The proliferation of modem power ...
The development of intelligent power quality (PQ) disturbances classification and analysis tools exp...
This paper proposes a wavelet-based extended fuzzy reasoning approach to power-quality disturbance r...
The nature of electric power and unsettling influences happened in power signal has become a signifi...
The paper presents a new approach for the classification of transient disturbance waveforms in a pow...
Power quality disturbances can interrupt production lines, cause damage to products and equipment, r...
The paper presents a neural-fuzzy technique-based clarifier for pattern recognition problems with un...
The power quality of the electric power has become an important issue for the electric utilities and...
During the recent decades the evolution of electrical Power systems increases the interest in the po...
This paper presents the two main types of classification methods for power quality disturbances bas...
Abstract Recognition of power quality (PQ) troubles is a critical task in the electrical power syste...
This paper describes an algorithm to detect and classify electrical events related to power quality....
The quality of electric power and disturbances occurred in power signal has become a major issue amo...
The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to powe...
The increasing use of electronics in electrical equipment has made them more vulnerable to power qua...
Power quality is becoming increasingly important in power systems. The proliferation of modem power ...
The development of intelligent power quality (PQ) disturbances classification and analysis tools exp...
This paper proposes a wavelet-based extended fuzzy reasoning approach to power-quality disturbance r...
The nature of electric power and unsettling influences happened in power signal has become a signifi...
The paper presents a new approach for the classification of transient disturbance waveforms in a pow...
Power quality disturbances can interrupt production lines, cause damage to products and equipment, r...
The paper presents a neural-fuzzy technique-based clarifier for pattern recognition problems with un...
The power quality of the electric power has become an important issue for the electric utilities and...
During the recent decades the evolution of electrical Power systems increases the interest in the po...
This paper presents the two main types of classification methods for power quality disturbances bas...
Abstract Recognition of power quality (PQ) troubles is a critical task in the electrical power syste...
This paper describes an algorithm to detect and classify electrical events related to power quality....
The quality of electric power and disturbances occurred in power signal has become a major issue amo...
The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to powe...