Monitoring multimode continuous processes: a data-driven approach
This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.
Read More ↓Title Statements
- Full title :Monitoring multimode continuous processes : a data-driven approach / Marcos Quiñones-Grueiro, Orestes Llanes-Santiago, Antônio José Silva Neto.
Summary
This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.
Read More ↓Edition Statements
- Publication Date:2021.
Publication Statements
- Publisher(s):Springer
- Place of Publication:Cham, Switzerland
- Language:eng
- Publication Date:2021.
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9783030547387, 3030547388, 9783030547394, 3030547396, 9783030547400, 303054740X
- DOI:10.1007/978-3-030-54738-7
- oclc:on1182839920
- LC Classification:TA169.6
- Dewey Decimal:620/.0044
Table of Contents
Data-driven Fault Diagnosis -- Multimode Continuous Processes -- Multimode Continuous Processes Clustering -- Multimode Continuous Processes Monitoring.
Read More ↓Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Related Works
more →
Monitoring Multimode Continuous Processes: A Data-Driven Approach
Quiñones-Grueiro, Marcos
Network science with Python and networkX quick start guide: explore and visualize network data effe…
Platt, Edward L.
Become a Python data analyst: perform exploratory data analysis and g…
Fuentes, Alvaro
Proceedings of a Workshop on Statistics on Networks
Rate & Review