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[null,"1.","Record Nr.",null,"UNINA9910141509303321"]
[null,null,"Autore",null,"Farrar C. R (Charles R.)"]
[null,null,"Titolo",null,"Structural health monitoring [[electronic resource] ] : a machine learning perspective / / Charles R. Farrar, Keith Worden"]
[null,null,"Pubbl/distr/stampa",null,"Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, 2013"]
[null,null,"ISBN",null,"1-118-44311-X"]
[{"$nulls":4},"1-299-18678-5"]
[{"$nulls":4},"1-118-44320-9"]
[{"$nulls":4},"1-118-44321-7"]
[null,null,"Descrizione fisica",null,"1 online resource (655 p.)"]
[null,null,"Disciplina",null,"624.1/71"]
[{"$nulls":4},"624.171"]
[null,null,"Soggetti",null,"Structural health monitoring"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"STRUCTURAL HEALTH MONITORING; Contents; Preface; Acknowledgements; 1 Introduction; 1.1 How Engineers and Scientists Study Damage; 1.2 Motivation for Developing SHM Technology; 1.3 Definition of Damage; 1.4 A Statistical Pattern Recognition Paradigm for SHM; 1.4.1 Operational Evaluation; 1.4.2 Data Acquisition; 1.4.3 Data Normalisation; 1.4.4 Data Cleansing; 1.4.5 Data Compression; 1.4.6 Data Fusion; 1.4.7 Feature Extraction; 1.4.8 Statistical Modelling for Feature Discrimination; 1.5 Local versus Global Damage Detection; 1.6 Fundamental Axioms of Structural Health Monitoring"]
[{"$nulls":4},"1.7 The Approach Taken in This BookReferences; 2 Historical Overview; 2.1 Rotating Machinery Applications; 2.1.1 Operational Evaluation for Rotating Machinery; 2.1.2 Data Acquisition for Rotating Machinery; 2.1.3 Feature Extraction for Rotating Machinery; 2.1.4 Statistical Modelling for Damage Detection in Rotating Machinery; 2.1.5 Concluding Comments about Condition Monitoring of Rotating Machinery; 2.2 Offshore Oil Platforms; 2.2.1 Operational Evaluation for Offshore Platforms; 2.2.2 Data Acquisition for Offshore Platforms; 2.2.3 Feature Extraction for Offshore Platforms"]
[{"$nulls":4},"2.2.4 Statistical Modelling for Offshore Platforms2.2.5 Lessons Learned from Offshore Oil Platform Structural Health Monitoring Studies; 2.3 Aerospace Structures; 2.3.1 Operational Evaluation for Aerospace "]
[{"$nulls":4},"Structures; 2.3.2 Data Acquisition for Aerospace Structures; 2.3.3 Feature Extraction and Statistical Modelling for Aerospace Structures; 2.3.4 Statistical Models Used for Aerospace SHM Applications; 2.3.5 Concluding Comments about Aerospace SHM Applications; 2.4 Civil Engineering Infrastructure; 2.4.1 Operational Evaluation for Bridge Structures"]
[{"$nulls":4},"2.4.2 Data Acquisition for Bridge Structures2.4.3 Features Based on Modal Properties; 2.4.4 Statistical Classification of Features for Civil Engineering Infrastructure; 2.4.5 Applications to Bridge Structures; 2.5 Summary; References; 3 Operational Evaluation; 3.1 Economic and Life-Safety Justifications for Structural Health Monitoring; 3.2 Defining the Damage to Be Detected; 3.3 The Operational and Environmental Conditions; 3.4 Data Acquisition Limitations; 3.5 Operational Evaluation Example: Bridge Monitoring; 3.6 Operational Evaluation Example: Wind Turbines"]
[{"$nulls":4},"3.7 Concluding Comment on Operational EvaluationReferences; 4 Sensing and Data Acquisition; 4.1 Introduction; 4.2 Sensing and Data Acquisition Strategies for SHM; 4.2.1 Strategy I; 4.2.2 Strategy II; 4.3 Conceptual Challenges for Sensing and Data Acquisition Systems; 4.4 What Types of Data Should Be Acquired?; 4.4.1 Dynamic Input and Response Quantities; 4.4.2 Other Damage-Sensitive Physical Quantities; 4.4.3 Environmental Quantities; 4.4.4 Operational Quantities; 4.5 Current SHM Sensing Systems; 4.5.1 Wired Systems; 4.5.2 Wireless Systems; 4.6 Sensor Network Paradigms"]
[{"$nulls":4},"4.6.1 Sensor Arrays Directly Connected to Central Processing Hardware"]
[null,null,null,"Sommario/riassunto","Written by global leaders and pioneers in the field, this book is a must-have read for researchers,  practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process"]