A fault diagnosis of electrical equipment based on improved BP neural network

Key Points

• To investigate a method for diagnosing faults in electrical equipment using an improved BP neural network approach.
• Utilized an improved backpropagation (BP) neural network for fault detection.
• Analyzed electrical equipment performance data to identify fault patterns.
• Implemented machine learning techniques to enhance diagnosis accuracy.
• Significantly improved accuracy in diagnosing faults compared to traditional methods.
• Reduced diagnostic time and increased reliability in fault detection.

Abstract