When diagnosing intermittent power quality issues, which feature of the power quality analyzer is essential?

Data logging is crucial when diagnosing intermittent power quality issues because it allows the analyst to capture and store data over time. This feature is essential for examining fluctuations in voltage, current, and other parameters that may not be immediately observable. Intermittent issues can occur sporadically, and having a historical record of data enables users to correlate power quality events with specific occurrences or patterns, which is vital for accurate diagnosis.

By reviewing logged data, technicians can identify trends or anomalies that align with the timing of the power quality issues, such as peak usage times, equipment operation cycles, or environmental factors. This capability can significantly improve troubleshooting efficiency and accuracy.

While real-time analysis provides immediate feedback and could be useful for ongoing issues, it alone may not capture the necessary evidence of intermittent events that are infrequent or short-lived. Visual inspections may help uncover obvious physical or environmental issues affecting power quality, but they do not replace the comprehensive dataset that logging provides. Signal filtering is useful for minimizing noise in readings but does not assist in understanding the overall historical performance required for diagnosing intermittent problems.