The rapid acceleration of technological innovation in the twenty-first century demands a fundamental reimagining of how engineering research addresses complex, interconnected global challenges. Engineering disciplines that once operated in relative isolation must now converge to tackle problems that transcend traditional boundaries—from climate...
Collaborative robots (cobots) are increasingly deployed in industrial environments, necessitating robust fault detection systems to ensure operational safety and efficiency. This study presents a comprehensive machine learning framework for fault detection in UR3 collaborative robots using multimodal sensor data. We analyzed a dataset...
The intermittent and uncertain nature of photovoltaic power generation poses significant challenges to grid stability. To enhance short-term forecasting accuracy and quantify uncertainty, this study proposes a probabilistic forecasting method for photovoltaic power generation that integrates multi-source data with feature engineering. Utilising...
