Qingwu Gong

Title: Qingwu Gong: Innovator in Transformer Fault Diagnosis

Introduction

Qingwu Gong is a notable inventor based in Wuhan, China. He has made significant contributions to the field of electrical engineering, particularly in the diagnosis of transformer faults. His innovative approach utilizes advanced neural network techniques to enhance diagnostic accuracy.

Latest Patents

Qingwu Gong holds a patent titled "Method for diagnosing transformer fault based on deep coupled dense convolutional neural network." This method involves obtaining datasets of dissolved gas in oil from transformers in both normal and fault states. It expands these datasets using an adaptive synthetic oversampling method. The process includes performing feature reconstruction on characteristic gases dissolved in the oil, building a transformer fault diagnosis model based on a deep coupled dense convolutional neural network, and dividing the expanded dataset into training and test sets. This innovative approach addresses the challenge of low fault diagnosis accuracy due to insufficient and unbalanced fault samples in the dissolved gas in the oil.

Career Highlights

Qingwu Gong has worked with prominent organizations, including Wuhan University and State Grid Tianjin Electric Power Company. His experience in these institutions has allowed him to develop and refine his expertise in electrical engineering and fault diagnosis.

Collaborations

He has collaborated with notable colleagues such as Yigang He and Zihao Li, contributing to advancements in their respective fields.

Conclusion

Qingwu Gong's work in transformer fault diagnosis exemplifies the intersection of innovation and technology. His contributions are paving the way for more accurate and efficient diagnostic methods in electrical engineering.