Structural Health Monitoring & Damage Detection, Volume 7 (eBook, PDF)

Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics 2017
Redaktion: Niezrecki, Christopher

• Format: PDF

Produktbeschreibung

Structural Health Monitoring & Damage Detection, Volume 7: Proceedings of the 35^th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the seventh volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Health Monitoring & Damage Detection, including papers on:

• Structural Health Monitoring
• Damage Detection
• System Identification
• Active Controls

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 97
• Erscheinungstermin: 20. März 2017
• Englisch
• ISBN-13: 9783319541099
• Artikelnr.: 53063924

Autorenporträt

Dr. Christopher Niezreck is a Professor, and Director at the Center for Wind Energy and Co-director of the Structural Dynamics & Acoustic Systems Laboratory at the University of Massachusetts, Lowell.

Inhaltsangabe

Chapter 1.Exploiting Spatial Sparsity in Vibration-based Damage Detection.- Chapter 2.Multi-Source Sensing and Analysis for Machine-Array Condition Monitoring.- Chapter 3.Wavelet Transform-Based Damage Detection in Reinforced Concrete Using an Air-Coupled Impact-Echo Method.- Chapter 4. Damage Detection Based on Strain Transmissibility for Beam Structure by Using Distributed Fiber Optics.- Chapter 5.Modal Parameters Estimation of an Offshore Wind Turbine Using Measured Acceleration Signals from the Drive Train.- Chapter 6.Structural Damage Detection in Real-Time: Implementation of 1D Convolutional Neural Networks for SHM Applications.- Chapter 7.Monitoring the Health of a Cantilever Beam Using Nonlinear Modal Tracking.- Chapter 8.Using Modal Parameters for Structural Health Monitoring.- Chapter 9.Current Challenges with BIGDATA Analytics in Structural Health Monitoring.- Chapter 10.Detection of Cracks in Beams Using Treed Gaussian Processes.