Online monitoring and fault diagnosis technology for power transformers

The online monitoring and fault diagnosis technology of power transformers is a key link to ensure the safe and stable operation of the power grid. Here is a detailed introduction to these technologies:

1、 Online monitoring technology

1. Vibration analysis method: By collecting and analyzing the vibration signals of transformers, the type and degree of internal faults in transformers can be determined. This method is sensitive to the mechanical structural characteristics of transformers and can effectively reflect changes in mechanical structural parameters such as winding deformation, looseness, and displacement.

2. Online monitoring of partial discharge: Local damage and air gap faults often occur in solid insulation. Online monitoring of partial discharge can detect and locate these faults in real time, thereby preventing transformer accidents.

3. Online monitoring of dissolved gases in oil: By analyzing the composition and content of dissolved gases in transformer oil, the type and severity of transformer faults can be determined. This method has the advantages of real-time, continuity, and high accuracy.

4. Infrared thermal imaging method: By detecting the heat distribution on the surface of the transformer, the internal fault situation of the transformer can be determined. This method can monitor the heating situation of transformers in real time and quickly locate the fault location.

2、 Fault diagnosis technology

1. Fault diagnosis based on vibration signals: using vibration analysis to extract transformer fault characteristic information, combined with pattern recognition and artificial intelligence technologies, to achieve automatic diagnosis and localization of transformer faults.

2. Fault diagnosis based on dissolved gases in oil: Using expert systems or neural networks to determine the type and cause of transformer faults based on changes in the composition and content of dissolved gases in oil.

3. Multi information fusion fault diagnosis: Integrating various monitoring information such as vibration signals, dissolved gases in oil, and partial discharge, using data mining and fusion techniques to improve the accuracy and reliability of fault diagnosis.

In summary, there are various online monitoring and fault diagnosis technologies for power transformers, each with its own advantages and disadvantages. In practical applications, it is necessary to select appropriate monitoring and diagnostic techniques based on specific situations, and combine multiple methods to make comprehensive judgments to ensure the safe operation of transformer equipment and the stability of the power system. Meanwhile, with the continuous development of technology, these technologies will become more intelligent, automated, and efficient in the future, providing stronger guarantees for the safe and stable operation of the power grid.