Liaoning, China

Honghui Wang

This inventor holds 1 USPTO granted patent. Top assignee: Dalian University of Technology. Active years: 2023.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Honghui Wang. Retrieved from https://idiyas.com/inventor/honghui-wang-i6qwrfv6

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Innovations by Honghui Wang

Introduction

Honghui Wang is a notable inventor based in Liaoning, China. He has made significant contributions to the field of machining technology, particularly through his innovative approaches to predicting part surface roughness and tool wear.

Latest Patents

Honghui Wang holds a patent for a "Prediction method of part surface roughness and tool wear based on multi-task learning." This method involves collecting vibration signals during the machining process and measuring the corresponding part surface roughness and tool wear. The process includes expanding samples, extracting and normalizing features, and constructing a multi-task prediction model based on deep belief networks (DBN). The model predicts surface roughness and tool wear by inputting vibration signals, showcasing a sophisticated approach to enhancing machining efficiency.

Career Highlights

Honghui Wang is affiliated with Dalian University of Technology, where he continues to advance research in machining technology. His work has garnered attention for its practical applications in improving manufacturing processes.

Collaborations

Honghui Wang has collaborated with colleagues such as Yongqing Wang and Bo Qin, contributing to a dynamic research environment that fosters innovation and development in their field.

Conclusion

Honghui Wang's contributions to machining technology through his innovative patent demonstrate his expertise and commitment to advancing the industry. His work not only enhances understanding but also improves practical applications in manufacturing processes.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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