This inventor holds 1 USPTO granted patent. Top assignee: Northeastern University. Active years: 2017.
Company Filing History:
Years Active: 2017
Title: Innovations of Zhenning Wu in Oil Pipeline Monitoring
Introduction
Zhenning Wu is a notable inventor based in Shenyang, China. He has made significant contributions to the field of oil pipeline monitoring through his innovative approaches. His work focuses on utilizing big data to enhance the safety and efficiency of pipeline networks.
Latest Patents
Zhenning Wu holds a patent for an "Intelligent adaptive system and method for monitoring leakage of oil pipeline networks based on big data." This invention effectively analyzes large amounts of data collected on-site within a reasonable time frame. It employs an intelligent adaptive method to determine the state of a pipeline network, thereby establishing its topological structure. The invention utilizes a flow balance method combined with information conformance theory to detect leaks in the pipeline network. It can accurately alarm for small and slow leaks, enhancing the reliability of the monitoring process. By adopting a generalized regression neural network, the accuracy of leak location is significantly improved. This innovative approach addresses the critical issues of detecting and locating leaks in oil pipeline networks.
Career Highlights
Zhenning Wu is affiliated with Northeastern University, where he continues to advance his research and development efforts. His work has garnered attention for its practical applications in the oil and gas industry.
Collaborations
Zhenning Wu has collaborated with notable colleagues, including Huaguang Zhang and Dazhong Ma. Their combined expertise contributes to the advancement of innovative solutions in pipeline monitoring.
Conclusion
Zhenning Wu's contributions to the field of oil pipeline monitoring through his innovative patent demonstrate the potential of big data in enhancing safety and efficiency. His work is a testament to the importance of innovation in addressing real-world challenges.
