Xiangrong Liu

Title: Innovations of Xiangrong Liu in Optical Fiber Sensing Technology

Introduction

Xiangrong Liu is a notable inventor based in Sichuan, China. He has made significant contributions to the field of optical fiber sensing technology, holding two patents that address critical challenges in this area. His work focuses on enhancing the adaptive capabilities of distributed optical fiber sensing systems in complex environments.

Latest Patents

Xiangrong Liu's latest patents include a "1D-CNN-based distributed optical fiber sensing signal feature learning and classification method." This innovative method addresses the limitations of existing systems that struggle with adaptability and efficiency. It involves segmenting time sequences of acoustic and vibration signals, constructing a 1D-CNN model, and training it to extract distinguishable features for various event types.

Another significant patent is the "distributed optical fiber sensing signal processing method for safety monitoring of underground pipe networks." This invention aims to improve the detection and identification capabilities of existing systems under complex conditions. It utilizes a distributed optical fiber sensing system to capture sound or vibration signals along a detection cable, enhancing infrastructure safety monitoring.

Career Highlights

Xiangrong Liu is affiliated with the University of Electronic Science and Technology of China. His academic and research endeavors have positioned him as a key figure in the development of advanced sensing technologies. His work not only contributes to academic knowledge but also has practical applications in safety monitoring and environmental adaptability.

Collaborations

Xiangrong Liu collaborates with esteemed colleagues such as Huijuan Wu and Yunjiang Rao. Their combined expertise fosters innovation and drives advancements in optical fiber sensing technologies.

Conclusion

Xiangrong Liu's contributions to optical fiber sensing technology through his patents demonstrate his commitment to addressing real-world challenges. His innovative methods enhance the capabilities of sensing systems, paving the way for safer and more efficient monitoring solutions.