Data-Driven Fault Diagnosis for Complex Industrial Processes

Discover the cutting-edge insights in "Data-Driven Fault Diagnosis for Complex Industrial Processes" by Hongpeng Yin, published by Springer Nature Switzerland AG in 2025. This comprehensive hardback edition spans 208 pages, providing a thorough exploration of advanced techniques in fault prediction, detection, and identification tailored for industrial processes. The book uniquely combines the fields of data science and machine learning with domain-specific expertise, making it an essential resource for professionals seeking to enhance their understanding of data-driven fault diagnosis. Whether you are a researcher, engineer, or industry practitioner, this book will equip you with the knowledge to effectively address the complexities of fault diagnosis in modern industrial settings. Don't miss the opportunity to elevate your expertise with this invaluable guide.