Smart Sensors for Structural Health Monitoring
Laflamme, Simon
Smart Sensors for Structural Health Monitoring - MDPI - Multidisciplinary Digital Publishing Institute 2019 - 1 electronic resource (342 p.)
Open Access
Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).
Creative Commons
English
books978-3-03921-759-5 9783039217595 9783039217588
10.3390/books978-3-03921-759-5 doi
NSGA-II wind force wavelet packet decomposition structural health monitoring amplitude spectrum environmental noise patch antenna damage identification event-triggered sensing Particle Swarm Optimization (PSO) algorithm high-speed train low-velocity impacts concrete structures sensors distribution optimization acceleration digital sampling moiré crack displacement sensor length effect FBG sensor array SHM space window Bayesian blind source separation feature selection stress detection wheel minor defect strain uniaxial stress measurement turbine impact identification helical antenna energy analysis of wavelet band strain wave time window structural steel members steel frame acoustoelastic effect demand-based nodes online wayside detection sensor bridge sensitivity acoustic emission bending stiffness wireless smart sensors distributed dense sensor network mapping construction data fusion fuzzy classification shear-wave birefringence normal mode piezoelectric wafer active sensors resonant frequency electromagnetic oscillation settlement sensor optimization modal frequencies perturbation theory feature extraction Virtual Distortion Method (VDM) reflective optical sensor fibre bundle smartphones crack identification active sensing test vehicle calibration stretching method model updating rotary ultrasonic array 2D crack growth data processing damage detection impactor stiffness tip clearance transmission tower phase spectrum concrete crack structural impact monitoring shaking table tests optical crack growth sensor steel strand passive sensing sudden event monitoring aero engine principal component analysis
Smart Sensors for Structural Health Monitoring - MDPI - Multidisciplinary Digital Publishing Institute 2019 - 1 electronic resource (342 p.)
Open Access
Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).
Creative Commons
English
books978-3-03921-759-5 9783039217595 9783039217588
10.3390/books978-3-03921-759-5 doi
NSGA-II wind force wavelet packet decomposition structural health monitoring amplitude spectrum environmental noise patch antenna damage identification event-triggered sensing Particle Swarm Optimization (PSO) algorithm high-speed train low-velocity impacts concrete structures sensors distribution optimization acceleration digital sampling moiré crack displacement sensor length effect FBG sensor array SHM space window Bayesian blind source separation feature selection stress detection wheel minor defect strain uniaxial stress measurement turbine impact identification helical antenna energy analysis of wavelet band strain wave time window structural steel members steel frame acoustoelastic effect demand-based nodes online wayside detection sensor bridge sensitivity acoustic emission bending stiffness wireless smart sensors distributed dense sensor network mapping construction data fusion fuzzy classification shear-wave birefringence normal mode piezoelectric wafer active sensors resonant frequency electromagnetic oscillation settlement sensor optimization modal frequencies perturbation theory feature extraction Virtual Distortion Method (VDM) reflective optical sensor fibre bundle smartphones crack identification active sensing test vehicle calibration stretching method model updating rotary ultrasonic array 2D crack growth data processing damage detection impactor stiffness tip clearance transmission tower phase spectrum concrete crack structural impact monitoring shaking table tests optical crack growth sensor steel strand passive sensing sudden event monitoring aero engine principal component analysis