Chongqing, China

Zhen Kang


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2024

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2 patents (USPTO):Explore Patents

Title: Zhen Kang: Innovator in Numerical Control Machine Tool Technology

Introduction

Zhen Kang is a prominent inventor based in Chongqing, China. He has made significant contributions to the field of numerical control machine tools, particularly in the area of predicting tool life. With a total of 2 patents to his name, his work is paving the way for advancements in manufacturing technology.

Latest Patents

Zhen Kang's latest patents include a "Prediction method for tool remaining life of numerical control machine tool based on hybrid neural model." This innovative method involves constructing a hybrid neural network model that utilizes convolutional neural networks and long short-term memory networks to predict tool life. The process includes generating feature vectors and inputting them into a multi-layer perceptron for accurate predictions. Another notable patent is the "Method for predicting remaining life of numerical control machine tool," which establishes a prediction model based on data de-noising and feature extraction using a multi-kernel W-LSSVM algorithm. These patents demonstrate his expertise in integrating advanced computational techniques with practical applications in manufacturing.

Career Highlights

Zhen Kang has worked at the Chongqing University of Posts and Telecommunications and the Institute of Industrial Internet at the same university. His academic and research roles have allowed him to explore innovative solutions in the field of industrial technology.

Collaborations

Zhen has collaborated with notable colleagues such as Qingqing Huang and Yan Zhang. Their joint efforts have contributed to the development of cutting-edge technologies in numerical control systems.

Conclusion

Zhen Kang's contributions to the field of numerical control machine tools highlight his innovative spirit and dedication to advancing technology. His patents reflect a deep understanding of both theoretical and practical aspects of tool life prediction, making him a valuable asset to the engineering community.

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