power quality applications. One can see that a power quality monitor could become an doctor” if it is added with data analytics capabilities. “equipment Table . Comparison of two applications of disturbance data. Type of Quality Condition Monitoring Applications (Current Practice) (Future Practice) Illustrative A customer complains repeated of A utility company needs to determine if problem its variable frequency drives an aging underground cable needs to be replaced A power quality monitor is used to A power quality monitor is used to record disturbances experienced by record voltage and current responses of the customer the cable during its operation Solution steps The data are then analyzed to find The data are then analyzed to check if the cause of the drive trips the cable exhibits abnormal V & I responses such as partial discharges. The frequency & severity of abnormal responses may be compared with those collected from various cables Outcomes Methods to mitigate the PQ problem Decision on if the cable needs to be are recommended replaced is made Nature of Diagnostic monitoring Preventive monitoring monitoring Medical Find the causes and damages of a Determine if a patient has the risk of analogy attack after it has occurred attack METHODS TO DETECT WAVEFORM ABNORMALITY The first step to identify equipment failure or malfunction is to detect abnormality in voltage and current waveforms. Once an abnormality is detected, the waveforms and RMS values associated with the period of abnormality can then be extracted for detailed analysis. This may include signature evaluation, pattern recognition, statistical analysis and other types of assessments. Eventually equipment condition can be determined from the results. As discussed earlier, is a wide variety of equipment failure signatures and many of them are not well understood. Methods to detect power quality disturbances are not applicable either. A proper approach to solving the problem is, therefore, to create general methods that can detect all types of abnormalities. Some research has been conducted in this direction for a few types of equipment failures. The objective of this section is to review these developments. It also uses a practical method to demonstrate the characteristics and challenges of abnormal waveform detection. Finally, a recent development in this direction is presented. The overall objective of this section is to
power quality applications. One can see that a power quality monitor could become an “equipment doctor” if it is added with data analytics capabilities. Table . Comparison of two applications of disturbance data. Type of Applications Quality (Current Practice) Condition Monitoring (Future Practice) Illustrative problem A customer complains repeated of its variable frequency drives A utility company needs to determine if an aging underground cable needs to be replaced Solution steps A power quality monitor is used to record disturbances experienced by the customer The data are then analyzed to find the cause of the drive trips A power quality monitor is used to record voltage and current responses of the cable during its operation The data are then analyzed to check if the cable exhibits abnormal V & I responses such as partial discharges. The frequency & severity of abnormal responses may be compared with those collected from various cables Outcomes Methods to mitigate the PQ problem are recommended Decision on if the cable needs to be replaced is made Nature of monitoring Diagnostic monitoring Preventive monitoring Medical analogy Find the causes and damages of a attack after it has occurred Determine if a patient has the risk of attack METHODS TO DETECT WAVEFORM ABNORMALITY The first step to identify equipment failure or malfunction is to detect abnormality in voltage and current waveforms. Once an abnormality is detected, the waveforms and RMS values associated with the period of abnormality can then be extracted for detailed analysis. This may include signature evaluation, pattern recognition, statistical analysis and other types of assessments. Eventually equipment condition can be determined from the results. As discussed earlier, is a wide variety of equipment failure signatures and many of them are not well understood. Methods to detect power quality disturbances are not applicable either. A proper approach to solving the problem is, therefore, to create general methods that can detect all types of abnormalities. Some research has been conducted in this direction for a few types of equipment failures. The objective of this section is to review these developments. It also uses a practical method to demonstrate the characteristics and challenges of abnormal waveform detection. Finally, a recent development in this direction is presented. The overall objective of this section is to