Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The adequate assessment of key apparatus conditions is a hot topic in all branches of industry. Various online and offline diagnostic methods are widely applied to provide early detections of any abnormality in exploitation. Furthermore, different sensors may also be applied to capture selected physical quantities that may be used to indicate the type of potential fault. The essential steps of the signal analysis regarding the technical condition assessment process may be listed as: signal measurement (using relevant sensors), processing, modelling, and classification. In the Special Issue entitled “Advances in Sensors and Sensing for Technical Condition Assessment and NDT”, we present the latest research in various areas of technology.

Technology: general issues --- pulse compression --- scattering --- attenuation --- insulation --- ultrasonic testing --- OLTC --- AE sensor --- acoustic emission --- feature extraction --- supervised classification --- machine learning --- contrast-enhanced ultrasound --- muscle perfusion --- Nakagami parameter --- compounding Nakagami imaging --- low-frequency sensor --- power transformer --- low-frequency noise --- genetic algorithm --- geometric layout of railway track --- track axis identification --- tramway loop --- route's polygon --- GNSS mobile measurements --- vibroarthography --- VAG --- knee joint --- spectral features --- frequency analysis --- non-invasive examination --- lateral temperature gradient --- temperature field --- boundary conditions --- solar radiation intensity --- temperature monitoring --- non-destructive evaluation --- eddy current --- 3D sensing --- inverse problem --- wavelet transform --- principal component analysis --- neural network --- incubation --- spectrum --- image processing --- ROC curve --- infrasound measurement system --- wind turbine --- infrasound correlation analysis --- measuring scale --- thermoelastic deformation --- coefficient of thermal expansion --- elastic waves --- laser ultrasound --- Fizeau fiber interferometer --- defect identification --- high-current pulses --- current measurement --- high-current shunts --- circuit modeling --- Rogowski coil --- electrodynamic accelerators --- pulse compression --- scattering --- attenuation --- insulation --- ultrasonic testing --- OLTC --- AE sensor --- acoustic emission --- feature extraction --- supervised classification --- machine learning --- contrast-enhanced ultrasound --- muscle perfusion --- Nakagami parameter --- compounding Nakagami imaging --- low-frequency sensor --- power transformer --- low-frequency noise --- genetic algorithm --- geometric layout of railway track --- track axis identification --- tramway loop --- route's polygon --- GNSS mobile measurements --- vibroarthography --- VAG --- knee joint --- spectral features --- frequency analysis --- non-invasive examination --- lateral temperature gradient --- temperature field --- boundary conditions --- solar radiation intensity --- temperature monitoring --- non-destructive evaluation --- eddy current --- 3D sensing --- inverse problem --- wavelet transform --- principal component analysis --- neural network --- incubation --- spectrum --- image processing --- ROC curve --- infrasound measurement system --- wind turbine --- infrasound correlation analysis --- measuring scale --- thermoelastic deformation --- coefficient of thermal expansion --- elastic waves --- laser ultrasound --- Fizeau fiber interferometer --- defect identification --- high-current pulses --- current measurement --- high-current shunts --- circuit modeling --- Rogowski coil --- electrodynamic accelerators

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Remote sensing data and methods are increasingly being implemented in assessments of volcanic processes and risk. This happens thanks to their capability to provide a spectrum of observation and measurement opportunities to accurately sense the dynamics, magnitude, frequency, and impacts of volcanic activity. This book includes research papers on the use of satellite, aerial, and ground-based remote sensing to detect thermal features and anomalies, investigate lava and pyroclastic flows, predict the flow path of lahars, measure gas emissions and plumes, and estimate ground deformation. The multi-disciplinary character of the approaches employed for volcano monitoring and the combination of a variety of sensor types, platforms, and methods that come out from the papers testify to the current scientific and technology trends toward multi-data and multi-sensor monitoring solutions. The added value of the papers lies in the demonstration of how remote sensing can improve our knowledge of volcanoes that pose a threat to local communities; back-analysis and critical revision of recent volcanic eruptions and unrest periods; and improvement of modeling and prediction methods. Therefore, the selected case studies also demonstrate the societal impact that this scientific discipline can potentially have on volcanic hazard and risk management.

Research & information: general --- volcanic thermal anomalies --- change detection --- Villarrica Volcano --- small satellites --- FireBIRD --- TET-1 --- gas emission monitoring --- X-band InSAR --- scanning Mini-DOAS --- Multi-GAS --- volcanic gases --- precipitable water vapor --- radar path delay --- Láscar volcano --- Mt. Etna --- multi-platform satellite observations --- RSTVOLC --- Stromboli volcano --- landslides --- effusive activity --- Ground-Based InSAR --- infrared live cam --- seismic monitoring --- PLEIADES --- Digital Elevation Models --- optical sensors --- volcano remote sensing --- volcano deformation --- SAR interferometry --- post-unrest deflation --- inversion modelling --- Santorini --- hyperspectral --- FENIX --- lava field --- SMACC --- LSMA --- volcano monitoring --- thermal imaging --- time series --- Seasonal-Trend Decomposition --- heat flux --- emissivity --- lava flow modeling --- remote sensing --- volcanic eruption interpretation --- eruption forecasting --- MSG SEVIRI --- wavelet --- thermal measurements --- lava fountain --- lava flow --- Mt.Etna --- eruptive style --- Timanfaya volcanic area --- HDR geothermal systems --- GPR --- EMI --- magnetic anomalies --- seasonality --- lahars hazard --- magma accumulation --- pyroclastic flows --- ash plumes --- volcanic cloud --- Landsat 8 --- elevation model --- Volcán de Colima --- lava flow volume estimation --- SPOT --- EO-1 ALI --- MODIS data --- SENTINEL-2 images --- infrasonic activity --- open-vent activity --- fissural eruption --- long- and short-term precursors --- SO2 fluxes --- UV Camera --- Etna Volcano --- explosive basaltic volcanism --- Bezymianny --- monitoring --- lava dome --- inflation --- SAR imaging --- radar pixel offsets --- acoustic infrasound --- volcanic emissions --- ground-based remote sensing --- Sentinel missions --- Convolutional Neural Network (CNN) --- Synthetic Aperture Radar (SAR) imaging --- InSAR processing --- infrared remote sensing --- SO2 gas emission --- satellite remote sensing --- ash fall --- lava flows --- pyroclastic density currents --- mapping --- volcanic hazard --- gas emissions --- edifice growth and collapse --- volcanic unrest --- thermal anomalies --- volcanic thermal anomalies --- change detection --- Villarrica Volcano --- small satellites --- FireBIRD --- TET-1 --- gas emission monitoring --- X-band InSAR --- scanning Mini-DOAS --- Multi-GAS --- volcanic gases --- precipitable water vapor --- radar path delay --- Láscar volcano --- Mt. Etna --- multi-platform satellite observations --- RSTVOLC --- Stromboli volcano --- landslides --- effusive activity --- Ground-Based InSAR --- infrared live cam --- seismic monitoring --- PLEIADES --- Digital Elevation Models --- optical sensors --- volcano remote sensing --- volcano deformation --- SAR interferometry --- post-unrest deflation --- inversion modelling --- Santorini --- hyperspectral --- FENIX --- lava field --- SMACC --- LSMA --- volcano monitoring --- thermal imaging --- time series --- Seasonal-Trend Decomposition --- heat flux --- emissivity --- lava flow modeling --- remote sensing --- volcanic eruption interpretation --- eruption forecasting --- MSG SEVIRI --- wavelet --- thermal measurements --- lava fountain --- lava flow --- Mt.Etna --- eruptive style --- Timanfaya volcanic area --- HDR geothermal systems --- GPR --- EMI --- magnetic anomalies --- seasonality --- lahars hazard --- magma accumulation --- pyroclastic flows --- ash plumes --- volcanic cloud --- Landsat 8 --- elevation model --- Volcán de Colima --- lava flow volume estimation --- SPOT --- EO-1 ALI --- MODIS data --- SENTINEL-2 images --- infrasonic activity --- open-vent activity --- fissural eruption --- long- and short-term precursors --- SO2 fluxes --- UV Camera --- Etna Volcano --- explosive basaltic volcanism --- Bezymianny --- monitoring --- lava dome --- inflation --- SAR imaging --- radar pixel offsets --- acoustic infrasound --- volcanic emissions --- ground-based remote sensing --- Sentinel missions --- Convolutional Neural Network (CNN) --- Synthetic Aperture Radar (SAR) imaging --- InSAR processing --- infrared remote sensing --- SO2 gas emission --- satellite remote sensing --- ash fall --- lava flows --- pyroclastic density currents --- mapping --- volcanic hazard --- gas emissions --- edifice growth and collapse --- volcanic unrest --- thermal anomalies