دانلود کتاب تشخیص هوشمند و نگهداری پیش‌بینانه

This volume, titled Smart Diagnostics and Predictive Maintenance, presents a comprehensive collection of advanced research that integrates intelligent control strategies, artificial intelligence, and data driven methods across energy systems and industrial maintenance. The book begins with a state-of-the-art approach to optimizing grid connected hybrid PV-battery-supercapacitor systems using machine learning, addressing the growing demand for sustainable and efficient renewable energy solutions. Subsequent chapters explore diagnostic and predictive maintenance methodologies applied to critical industrial components, including reciprocating compressors, electrical submersible pumps, vehicle cylinder heads, and centrifugal pumps. By combining energy optimization with AI-based condition monitoring and predictive analytics, the chapters in this volume offer both theoretical insights and practical implementations. These contributions aim to bridge the gap between academic research and industrial application, ensuring that solutions are not only innovative but also viable for real-world deployment. This work will be of interest to researchers, engineers, and professionals working in renewable energy, mechanical systems, process engineering, and artificial intelligence, providing both foundational knowledge and cutting-edge developments.