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Deep learning method for detection of structural microcracks by Brillouin scattering based distributed optical fiber sensors
摘要： Brillouin scattering (BS)–based distributed optical fiber sensors (DOFS) provide distributed sensing capabilities by monitoring the strain along entire segments of structures. Large cracks, such as those with large crack opening displacements (COD) can be detected by strain peaks or singularities along the measurement length of distributed sensors. Microcracks do not provide visible pronounced local peaks along the length of measured distributed strains. The peaks corresponding to microcracks are submerged within the measurement noise due to low signal-to-noise ratio (SNR) of BS systems. Deep learning (DL) methods have the potential to automatically extract feature representations from data exhibiting lower SNRs, and improve the crack detection sensitivity of the BS-based DOFS. Development of the proposed DL method includes construction of model architecture, design of a training algorithm and the detection process. A 15-m-long wide-flange steel beam with artificial defects is built and employed in this study. A comprehensive experimental program is undertaken in order to train, validate and test the generality of the proposed DL method. Experimental results demonstrate that the DL method is capable of extracting highly discernable microcrack features from the distributed strains, and distinguish the crack-induced local peaks from the noise. Microcracks with CODs as small as 23 microns are accurately detected in the present work.
关键词： Structural health monitoring,optical fiber sensors,Brillouin Scattering,crack detection,deep learning
更新于2025-09-19 17:13:59
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Non-Contact Damage Detection under Operational Conditions with Multipoint Laservibrometry
摘要： Scanning laser–Doppler vibrometry (SLDV) can localize and visualize damages in mechanical structures. In order to enable scanning, it is necessary to repeat the vibration. Therefore, this technique is not suited to detect emerging hazards in working machinery that change the vibration behavior. A common technique for such cases is monitoring the vibration excited by machine operation with accelerometers. This technique requires mechanical coupling between sensors and the measurement object, which in?uences the high-frequency vibration responses. However, in the low-frequency range, local damages do not shift resonances or distort operational de?ection shapes (ODS) signi?cantly. These alterations in the vibration behavior are tiny and hard to detect. This paper shows that multipoint laservibrometry (MPV) with laser excitation can measure these e?ects e?ciently, and it further demonstrates that damages in?uence ODSs at frequencies above 20 kHz much stronger than at frequencies below 20 kHz. In addition, ODS-based damage indices are discussed; these are highly sensitive to minute visible changes of the ODSs. In order to enhance the sensitivity of hazard detection, the response vector assurance criterion value is computed and evaluated during operation. The capabilities and limitations of the methodology on the example of a cantilever with manually emerging damage are demonstrated.
关键词： structural health monitoring,multipoint laser-Doppler vibrometer,operational de?ection shape,operational condition,damage detection,laser–Doppler vibrometry,non-destructive testing,laser ablation
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Understanding CdTe Performance with Engineered Front and Back Interfaces
摘要： Recently, structural health monitoring (SHM) using radio frequency identification (RFID) tag antenna-based sensing (TABS) has received increasing attention because of its wireless, passive, and low-cost characteristics. However, a great challenge in the SHM using RFID TABS is multiple influences in the measurement. This paper presents an ultrahigh frequency RFID sensor system for corrosion detection and characterization. In this paper, a 3-D antenna sensor is designed to work on the surface of a protective coated steel sample. Sweep-frequency measurements are applied for analog identifier with principal component analysis (PCA) to overcome the multiple influences from reader-tag orientation, distance, and environment. Feature extraction and selection though PCA can get robust and sensitive defect information by projecting the test data into an orthogonal feature space. The test results demonstrate that the proposed method can be applied to detect and characterize early-stage corrosion in metals.
关键词： principal component analysis (PCA),radio frequency identification (RFID),structural health monitoring (SHM),Antenna sensor,corrosion detection
更新于2025-09-19 17:13:59
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Robust and automatic modeling of tunnel structures based on terrestrial laser scanning measurement
摘要： The terrestrial laser scanning technology is increasingly applied in the deformation monitoring of tunnel structures. However, outliers and data gaps in the terrestrial laser scanning point cloud data have a deteriorating effect on the model reconstruction. A traditional remedy is to delete the outliers in advance of the approximation, which could be time- and labor-consuming for large-scale structures. This research focuses on an outlier-resistant and intelligent method for B-spline approximation with a rank (R)-based estimator, and applies to tunnel measurements. The control points of the B-spline model are estimated specifically by means of the R-estimator based on Wilcoxon scores. A comparative study is carried out on rank-based and ordinary least squares methods, where the Hausdorff distance is adopted to analyze quantitatively for the different settings of control point number of B-spline approximation. It is concluded that the proposed method for tunnel profile modeling is robust against outliers and data gaps, computationally convenient, and it does not need to determine extra tuning constants.
关键词： Terrestrial laser scanning,health monitoring,rank-based estimator,B-spline approximation,robust modeling
更新于2025-09-16 10:30:52
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Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification
摘要： In this paper, photovoltaic (PV) string failure analysis and health monitoring of PV modules based on a low-cost self-powered wireless sensor network (WSN) are presented. Simple and effective fault detection and diagnosis method based on the real-time operating voltage of PV modules is proposed. The proposed method is verified using the developed health monitoring system which is installed in a grid-connected PV system. Each of the PV modules is monitored via WSN to detect any individual faulty module. The analysis of PV string failure includes several electrical fault scenarios and their impact on the PV string characteristics. The results show that a degraded or faulty module exhibits low operating voltage as compared to the normal module. The developed health monitoring system also includes a graphical user interface (GUI) program which graphically displays the real-time operating voltage of each module with colors and thus helping users to identify the faulty modules easily. The faulty modules identification approach is further validated using the PV module electroluminescence (EL) imaging system.
关键词： photovoltaic module fault detection,health monitoring,Internet of Things,photovoltaic string,graphical user interface,self-powered wireless sensor network
更新于2025-09-16 10:30:52
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Near-infrared tunable diode laser absorption spectroscopy-based determination of carbon dioxide in human exhaled breath
摘要： A spectroscopic detection system for the accurate monitoring of carbon dioxide (CO2) in exhaled breath was realized by tunable diode laser absorption spectroscopy (TDLAS) in conjunction with a vertical-cavity surface-emitting laser (VCSEL) and a multipass cell with an effective optical path-length of 20 m. The VCSEL diode emitting light with an output power of 0.8 mW, covered the strong absorption line of CO2 at 6330.82 cm?1 by drive-current tuning. The minimum detectable concentration of 0.769% for CO2 detection was obtained, and a measurement precision of approximately 100 ppm was achieved with an integration time of 168 s. Real-time online measurements were carried out for the detection of CO2 expirograms from healthy subjects, different concentrations were obtained in dead space and alveolar gas. The exhaled CO2 increased significantly with the increasing physical activity, reaches its maximal value at the beginning of respiratory compensation and then decreased slightly until maximal exercise. The developed measurement system has a great potential to be applied in practice for the detection of pulmonary diseases associated with CO2 retention.
关键词： CO2,human health monitoring,Tunable diode laser absorption spectroscopy,carbon dioxide,VCSEL,exhaled breath,TDLAS,vertical-cavity surface-emitting laser
更新于2025-09-16 10:30:52
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Do Infrared Molecular Fingerprints of Individuals Exist? Lessons from Spectroscopic Analysis of Human Blood
摘要： Genetic, lifestyle and environmental factors, along with development and aging impact molecular composition of human blood. Although many diseases leave their trace in blood, the question is whether this trace can be robustly and reproducibly measured and used for health monitoring of a given adult population. Infrared molecular spectra of blood serum can be obtained in a non-invasive, time- and cost-efficient manner, delivering molecular information from all molecular species within the highly complex samples. We demonstrate that broadband infrared spectroscopy can be used for reproducible molecular fingerprinting of human blood. To evaluate whether certain medium is sufficiently robust to facilitate detection of disease onset, the quantitative extent of variability of a person as well as a reference population needs to be evaluated. If within-person variability would exceed that of the between-personal variability in a reference population, the approach would not be suited for disease detection. To assess the extent of uniqueness of infrared molecular fingerprints as well as their biological variability, we performed a comprehensive prospective longitudinal study collecting blood samples of 27 healthy individuals donating blood at 8 consequent intervals. We apply broadband infrared molecular fingerprinting by Fourier transform infrared spectroscopy (FTIR) and analyse between-person and within-person variability based on all different molecular classes in the blood simultaneously. We report experimental evidence of the feasibility of identifying a person within a group of individuals based on her/his infrared molecular fingerprint, similarly to metabolic fingerprints [1]. In a first step, using standard methods for descriptive analysis we observe that the between-person variability is larger than the within-person variability by a factor of 3 (Fig.1 Left). This observation opens up the possibility for disease detection. In a second step, we combine standard dimensionality-reduction methods, such as principal component analysis (PCA), and several high-accuracy machine-learning algorithms [1] (random forests, extreme gradient boosting, k nearest neighbours) for deriving classification rules, which we then use for making predictions on test sets of unseen data. For a group of 7 donations that span a period of 6 weeks, we reach peak classification accuracy of above 95% (Fig.1 Right), while the accuracy of a classifier predicting in random would have been as low as 3.7%. In addition, we evaluate the underlying spectral features with respect to their importance on signalling separation and in this way identifying the human blood serum constituents associated with between-person variation. Observed robustness of infrared molecular fingerprints suggests their applicability for health and treatment monitoring.
关键词： infrared molecular fingerprints,FTIR,health monitoring,human blood,spectroscopic analysis
更新于2025-09-12 10:27:22
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Integrated Optical Fibre — Investigating the Vibrational Response using Optical Frequency Domain Reflectometry
摘要： Integrated Optical Fibre (IOF) is a new technology in integrated optics using flame hydrolysis deposition to permanently attach an optical fibre onto a silicon substrate. This approach combines the low losses of optical fibre with the mechanical integrity of an integrated planar platform. By attaching the fibre with high quality optical glass we create devices that transform the packaging of fibres for sensing applications removing any use of glues, epoxies, adhesives and making it suitable for harsh environments such as aerospace. The binding medium itself can also be used for its optical properties. Aerospace environments are demanding, both for temperature range (-50 to +120 °C), but also for vibration and shock. In this work we are investigating a technique for monitoring the vibration sensitivity and damage points of the IOF under typical structural vibration conditions. In particular, here we report the use of Optical Frequency Domain Reflectometry (OFDR), which can reveal spectral and spatial information of features within a fibre such as Fibre Bragg Gratings (FBGs). This is of particular interest when applied to structural health monitoring, distributed strain and temperature sensing.
关键词： Optical Frequency Domain Reflectometry,vibration sensitivity,structural health monitoring,Integrated Optical Fibre,Fibre Bragg Gratings
更新于2025-09-12 10:27:22
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[IEEE 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC) - Fukuoka, Japan (2019.7.7-2019.7.11)] 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC) - Infrared- Thermometer-Based Detection of Optical Fiber Breakage in Structure
摘要： We show that infrared thermometry can be exploited to detect breakage points of optical fibers embedded in structures. This method has such advantages as real-time operation, cost efficiency, and visual display on site.
关键词： infrared thermometry,carbon fiber-reinforced plastics,structural health monitoring
更新于2025-09-11 14:15:04
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Nanomaterial‐Enabled Flexible and Stretchable Sensing Systems: Processing, Integration, and Applications
摘要： Nanomaterial-enabled flexible and stretchable electronics have seen tremendous progress in recent years, evolving from single sensors to integrated sensing systems. Compared with nanomaterial-enabled sensors with a single function, integration of multiple sensors is conducive to comprehensive monitoring of personal health and environment, intelligent human–machine interfaces, and realistic imitation of human skin in robotics and prosthetics. Integration of sensors with other functional components promotes real-world applications of the sensing systems. Here, an overview of the design and integration strategies and manufacturing techniques for such sensing systems is given. Then, representative nanomaterial-enabled flexible and stretchable sensing systems are presented. Following that, representative applications in personal health, fitness tracking, electronic skins, artificial nervous systems, and human–machine interactions are provided. To conclude, perspectives on the challenges and opportunities in this burgeoning field are considered.
关键词： sensing systems,human-machine interfaces,nanomaterials,Flexible electronics,health monitoring,stretchable electronics
更新于2025-09-11 14:15:04