Jijin Xu
Papers
6
Total Citations
235
H-Index
5
About
Jijin Xu is a researcher specializing in robotic belt grinding, tool condition monitoring, and the surface integrity of advanced aerospace materials. His work has made significant contributions to the intelligent automation of precision manufacturing processes, particularly in the grinding of nickel-based superalloys such as Inconel 718. Xu has pioneered the use of acoustic and sound-based sensing techniques to monitor abrasive belt conditions in real time, developing novel machine learning approaches — including optimally pruned extreme learning machines and random forest classifiers — to improve process reliability and efficiency. His most cited work (88 citations) introduced a sound-based belt condition monitoring method that set a new benchmark in robotic grinding intelligence. Beyond monitoring, Xu has conducted comprehensive investigations into how robotic belt grinding affects surface roughness, residual stress, microstructural integrity, and corrosion resistance of high-performance superalloys, directly addressing quality and durability concerns critical to aerospace applications. His 2020 work on dynamic heat input monitoring further demonstrates his commitment to bridging sensing, data analytics, and manufacturing science. With a cumulative citation count exceeding 230, Xu's research offers valuable insights for engineers and scientists advancing smart, high-precision manufacturing systems.
Research Focus
Key Achievements
Top Papers
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