代表性著作
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[2] Sun Y, Zhou J, Chen J, et al. Digital twin-based methodology for schedule execution in hot strip rolling[J]. Ironmaking & Steelmaking, 2025: 03019233241310713.
[3] Li J, Sun Y, Wang X, et al. Explainable machine learning for predicting mechanical properties of hot-rolled steel pipe[J]. Journal of Iron and Steel Research International, 2025: 1-16.
[4] Li J, Sun Y, Wang X, et al. Application of novel interpretable machine learning framework for strip flatness prediction during tandem cold rolling[J]. Measurement, 2025, 244: 116516.
[5] Li J, Zhou J, Sun Y, et al. Interpretable machine learning-based rolling force prediction using multivariate industrial data during tandem cold rolling[J]. Ironmaking & Steelmaking, 2025: 03019233241310711.
[6] Sun Y, Li J, Sun Y, et al. Modeling and Simulation of Shape Control Based on Digital Twin Technology in Hot Strip Rolling[J]. Sensors, 2024, 24(02): 614.
[7] Sun Y, Li J, Li H, et al. Industrial IoT–enabled real-time prediction of strip cross-section shape for hot-rolling steel[J]. The International Journal of Advanced Manufacturing Technology, 2024, 130(01): 961-972.
[8] Chen J, Sun Y, Wang X, et al. Rolling theory-guided prediction of PQF mill rolling force based on DE-GWO-BP[J]. Ironmaking & Steelmaking, 2024: 03019233241282928.
[9] Chen J, Sun Y, Zhou J, et al. A novel framework of process monitoring and fault diagnosis for steel pipe hot rolling[J]. Ironmaking & Steelmaking, 2024: 03019233251349862.
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[11] 孙友昭, 王晓晨, 杨荃, 徐言东, 徐冬, 何海楠, 刘洋, 肖雄, 吴坤鹏, 樊怡冰. 轧钢产线智能装备的研发与应用[J]. 轧钢, 2024, 41(4): 1-8.
[12] 孙友昭, 彭尊, 冯根生, 等. 钢中非金属夹杂物金相鉴定虚拟实验设计与开发[J]. 实验技术与管理, 2021, 38(04): 161-164.
[13] 孙友昭, 杨荃. 热连轧飞剪自动化控制仿真实践教学平台开发[J].实验技术与管理, 2020, 37(11): 147-150+155.
[14] 孙友昭, 杨荃, 王晓晨, 等. 基于激光超声的金属板带晶粒尺寸检测实验平台[J]. 实验室研究与探索, 2020, 39(10): 65-67+82.
[15] 孙友昭, 杨荃, 王晓晨, 等. 轧制原理虚拟仿真实验系统设计与开发[J]. 实验技术与管理, 2020, 37(08): 133-136.