Zaiquan Wang

Title: Zaiquan Wang and Collaborative Project Disaster Warning

Introduction

Zaiquan Wang is an inventor associated with Qingdao University of Technology in Qingdao, China. His patent work addresses project safety through the analysis and fusion of monitoring data from multiple physical fields.

Latest Patents

Wang is named on one patent, Project Disaster Warning Method and System Based on Collaborative Fusion of Multi-Physics Monitoring Data. The invention describes collecting and preprocessing real-time data from multiple sensors monitoring potentially dangerous parts of a project structure. It normalizes time-series data from different physical fields into a sample matrix and uses multivariate statistical analysis to assess how monitoring indicators relate to structural safety.

The method uses those sensitivity results to guide the initial training of a long short-term memory (LSTM) network. It then combines the network’s outputs using an improved Dempster–Shafer evidence theory based on Chebyshev distance, producing probability assignments for different warning levels. A decision method based on those assignments determines the danger level of potentially hazardous structural areas.

Career Highlights

Wang’s listed patent focuses on integrating sensor data, statistical analysis, machine learning, and evidence-based decision-making for project disaster warnings. The approach is intended to support the identification and assessment of risks in potentially dangerous parts of project structures. His listed patent count is 1 patent.

Collaborations

Wang’s listed coworkers include Liming Zhang and Zhongyuan Liu. His patent is associated with Qingdao University of Technology.

Conclusion

Zaiquan Wang’s patent presents a collaborative data-fusion approach to project disaster warning, combining multi-physics monitoring with statistical analysis and LSTM-based assessment to determine structural danger levels.