A Novel Critical Point Detection Method for Mechanical Deformation in Tightening Processes

Abstract

The mechanical deformation of workpieces due to tightening is a common phenomenon in assembly processes. This paper presents a novel method for critical point detection using a state space model and a new particle filter algorithm, significantly improving detection performance and computational efficiency.

Juan Du

Assistant Professor

My research interests include knowledge-infused data science for quality improvement, industrial data analytics and machine learning, and system informatics and control for manufacturing applications.