Zihan Wang

Title: Innovations of Zihan Wang in Superconducting Technology

Introduction

Zihan Wang is a prominent inventor based in Chengdu, China. He has made significant contributions to the field of superconducting technology, particularly through his innovative patent that utilizes deep learning for temperature detection in superconducting levitation devices. His work reflects a blend of advanced technology and practical application, showcasing his expertise in this specialized area.

Latest Patents

Zihan Wang holds a patent titled "Method and device for detecting temperature rise inside superconducting levitation device based on deep learning." This patent describes a method for detecting temperature increases within a superconducting levitation device. The process involves obtaining initial vibration acceleration information, initial temperature rise information, and vibration acceleration detection information. Feature extraction is performed on the initial vibration acceleration data to derive high-frequency and low-frequency feature parameter sets. Subsequently, wavelet band energy calculations are conducted on these parameter sets to generate wavelet band energy information. This information, along with the initial temperature rise data, is then input into a deep learning network for training, resulting in a model that predicts internal temperature rises in real-time.

Career Highlights

Zihan Wang is affiliated with Southwest Jiaotong University, where he continues to advance his research and development in superconducting technologies. His academic background and research endeavors have positioned him as a key figure in the field, contributing to both theoretical and practical advancements.

Collaborations

Zihan Wang has collaborated with notable colleagues, including Jun Zheng and Peng Pang. Their combined efforts in research and development have further enhanced the impact of their work in superconducting technology.

Conclusion

Zihan Wang's innovative approach to detecting temperature rises in superconducting devices through deep learning exemplifies the intersection of technology and practical application. His contributions are paving the way for advancements in superconducting technology, making a significant impact in the field.