Mingrui Shen

Title: Innovations of Mingrui Shen in Surface Roughness Prediction

Introduction

Mingrui Shen is a prominent inventor based in Dalian, China. He has made significant contributions to the field of machining technology, particularly in the prediction of surface roughness and tool wear. With a total of four patents to his name, Shen's work is at the forefront of innovation in this area.

Latest Patents

Mingrui Shen's latest patents include an "On-line prediction method of surface roughness of parts based on SDAE-DBN algorithm." This method utilizes a tri-axis acceleration sensor to collect vibration signals during the cutting process, while a microphone captures noise signals. The data is processed to eliminate trends and smooth the signals, which are then input into a deep belief network for real-time prediction of surface roughness.

Another notable patent is the "Prediction method of part surface roughness and tool wear based on multi-task learning." This method involves collecting vibration signals and measuring surface roughness and tool wear. A multi-task prediction model is constructed using deep belief networks, allowing for simultaneous predictions of both surface roughness and tool wear based on the input vibration signals.

Career Highlights

Mingrui Shen is affiliated with Dalian University of Technology, where he continues to advance research in machining technology. His innovative approaches have garnered attention in academic and industrial circles alike.

Collaborations

Shen has collaborated with notable colleagues, including Kuo Liu and Yongqing Wang, contributing to the advancement of their shared research interests.

Conclusion

Mingrui Shen's work exemplifies the intersection of innovation and practical application in machining technology. His patents reflect a commitment to enhancing manufacturing processes through advanced predictive methods.