Application of Partial Discharge and Operational Parameters in Online Early Warning Systems for Enhanced Generator Reliability

Generators are vital to the power generation industry, ensuring uninterrupted and reliable electricity supply. To avoid costly downtime and prevent catastrophic failures, maintaining their health is essential. Traditional offline assessments of generator health often result in delayed detection of potential faults and may not provide precise diagnostics. Partial Discharge analysis is widely used for identifying insulation defects in generator stators through discharge magnitude measurement. However, despite the use of Partial Discharge technology, catastrophic failures continue to occur, largely due to a lack of comprehensive understanding of Partial Discharge signals and the absence of an effective early warning system. To address this, an innovative online early warning system has been developed, integrating Partial Discharge monitoring and operational parameters for real-time health assessments. By utilizing Digital Signal Input Modules connected to Program Vision, the system collects real-time data for Partial Discharge analysis and compares it with operational parameters to quickly detect anomalies. The system's online monitoring dashboard provides operators with an integrated view of all operational parameters, offering actionable insights to improve maintenance strategies. This approach significantly enhances generator reliability by enabling proactive issue detection and reducing the likelihood of unexpected failures, ultimately ensuring seamless and efficient generator operation.