Transformer fault diagnosis is a systematic process that combines multiple techniques to identify potential issues accurately and efficiently, ensuring the reliable operation of power systems. One of the most widely used methods is Dissolved Gas Analysis (DGA), which focuses on detecting and quantifying gases dissolved in transformer oil. When internal faults occur (such as overheating or partial discharge), insulation materials decompose and release gases like methane, ethane, ethylene, acetylene, and hydrogen. By analyzing the concentration and ratio of these gases (using standards like the Duval Triangle or Rogers’ Ratios), technicians can determine the type and severity of faults—for example, high acetylene levels often indicate arcing, while elevated methane and ethane suggest low-temperature overheating.

　　Another key diagnosis method is Thermal Imaging, which uses infrared cameras to capture temperature distributions across the transformer’s exterior and internal components (via accessible parts like bushings and tank surfaces). Abnormal temperature hotspots—such as localized heating in windings or connections—can reveal issues like poor contact resistance, winding short circuits, or core faults. Thermal imaging is non-invasive and allows for real-time monitoring, making it ideal for regular inspections.

　　Additionally, Partial Discharge (PD) Detection plays a critical role in diagnosing insulation degradation. PD refers to small, localized electrical discharges within insulation materials that do not fully bridge the electrodes. These discharges gradually erode insulation, leading to major faults if unaddressed. PD detection methods include ultra-high frequency (UHF) sensors, high-frequency current transformers (HFCT), and acoustic sensors. UHF sensors capture electromagnetic waves emitted during PD, while acoustic sensors detect sound waves, enabling technicians to locate the exact position of the discharge. Combining DGA, thermal imaging, and PD detection provides a comprehensive diagnostic framework, allowing for early fault identification and preventing catastrophic transformer failures.

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