Shengqiang Zhao
According to our database1,
Shengqiang Zhao
authored at least 13 papers
between 2021 and 2025.
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Bibliography
2025
Extremely constrained robotic milling posture active adjustment on curved surface: Divide and conquer strategy with index of generalized accumulative work.
Robotics Comput. Integr. Manuf., 2025
Spatial-temporal feature fusion for intelligent foreknowledge of robotic machining errors.
Robotics Comput. Integr. Manuf., 2025
2024
Robotic milling posture adjustment under composite constraints: A weight-sequence identification and optimization strategy.
Robotics Comput. Integr. Manuf., February, 2024
In-situ prediction of machining errors of thin-walled parts: an engineering knowledge based sparse Bayesian learning approach.
J. Intell. Manuf., January, 2024
A sparse knowledge embedded configuration optimization method for robotic machining system toward improving machining quality.
Robotics Comput. Integr. Manuf., 2024
Sparse Representation of Robotic Machining Deformation Based on Key Points Determination.
Proceedings of the Intelligent Robotics and Applications - 17th International Conference, 2024
2022
A deep transfer regression method based on seed replacement considering balanced domain adaptation.
Eng. Appl. Artif. Intell., 2022
A Knowledge-Embedded End-to-End Intelligent Reasoning Method for Processing Quality of Shaft Parts.
Proceedings of the Intelligent Robotics and Applications - 15th International Conference, 2022
A foreknowledge perception method of multi-stages machining accuracy in aviation turbine shafts based on hidden Markov model and Neural networks<sup>*</sup>.
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2022
Analysis and inference of stream of dimensional errors in multistage machining process based on an improved semiparametric model.
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2022
2021
Tool wear parameters identification in precision milling using a hybrid model combining cutting forces analytical model and Gaussian process regression method.
Proceedings of the 27th International Conference on Mechatronics and Machine Vision in Practice, 2021
A transfer learning based geometric position-driven machining error prediction method for different working conditions.
Proceedings of the 27th International Conference on Mechatronics and Machine Vision in Practice, 2021
A hybrid mechanism-based and data-driven approach for the calibration of physical properties of Ni-based superalloy GH3128.
Proceedings of the 27th International Conference on Mechatronics and Machine Vision in Practice, 2021