{"product_id":"datadriven-fault-detection-and-reasoning-for-industrial-monitoring-9789811680434","title":"Data-Driven Fault Detection and Reasoning for Industrial Monitoring","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e This book evaluates the potential of data-driven methods in industrial process monitoring engineering, focusing on process modeling, fault detection, classification, isolation, and reasoning. It provides a framework for fault diagnosis and implements statistical analysis methods for process monitoring, catering to senior undergraduate and graduate students, researchers, practitioners, and engineers. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 264 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 04 January 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Verlag, Singapore\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eIt evaluates the potential of data-driven approaches in industrial process monitoring engineering, delving into detailed process modeling, fault detection, classification, isolation, and reasoning. These methods hold immense potential for enhancing the safety and reliability of industrial processes. Fault diagnosis, encompassing fault detection and reasoning, has garnered the attention of engineers and scientists from diverse fields such as control, machinery, mathematics, and automation engineering. By integrating diagnosis algorithms and real-world application cases, this book establishes a foundational framework for this domain and employs various statistical analysis methods for process monitoring. This book is specifically designed for senior undergraduate and graduate students with a keen interest in fault diagnosis technology, researchers exploring automation and industrial security, professional practitioners, and engineers engaged in engineering modeling and data processing applications.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 564g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 162 x 241 x 25 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9789811680434\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Jing Wang,Jinglin Zhou,Xiaolu Chen","offers":[{"title":"Hardback","offer_id":44102905823482,"sku":"9789811680434","price":37.47,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1646374846821_book.jpg?v=1646983667","url":"https:\/\/shulphink.com\/products\/datadriven-fault-detection-and-reasoning-for-industrial-monitoring-9789811680434","provider":"Shulph Ink","version":"1.0","type":"link"}