High resolution method for measuring Brillouin spectrum scattering in special optical fibers

An experimental setup and a method to obtain the Brillouin scattering spectrum (BSS) out of optical fibers are proposed. The setup is described and experimentally validated by developing the measurement of the Brillouin spectral distribution of a birefringent microstructuted optical fiber. The setup here proposed is based on a Brillouin ring cavity that uses the fiber under test as the active medium. The measurements are obtained in base band by beating the Stokes wave with a reference wave that is taken from the optical pump. The data can be obtained with high resolution frequency

Measuring the water content in wood using step-heating thermography and speckle patterns-preliminary results

The relationship between wood and its degree of humidity is one of the most important aspects of its use in construction and restoration. The wood presents a behavior similar to a sponge, therefore, moisture is related to its expansion and contraction. The nondestructive evaluation (NDE) of the amount of moisture in wood materials allows to define, e.g., the restoration procedures of buildings or artworks. In this work, an integrated study of two non-contact techniques is presented. Infrared thermography (IRT) was able to retrieve thermal parameters of the wood related to the amount of water added to the samples, while the interference pattern generated by speckles was used to quantify the expansion and contraction of wood that can be related to the amount of water. In twenty-seven wooded samples, a known quantity of water was added in a controlled manner. By applying advanced image processing to thermograms and specklegrams, it was possible to determine fundamental values controlling both the absorption of water and the main thermophysical parameters that link the samples. On the one hand, results here shown should be considered preliminary because the experimental values obtained by IRT need to be optimized for low water contents introduced into the samples. On the other hand, speckle interferometry by applying an innovative procedure provided robust results for both high and low water contents.This work was supported in part by the Spanish Economy and Competitiveness Minister under project TEC2016-76021-C2-2-R; Jose Castillejo Grant CAS17-00216 by the Spanish Minister of Education, Culture and Sports

Identification of carbon black in military textiles using infrared imaging techniques

The carbon black has been used in military fabrics to comply with the color requirements and infrared radiation lessen- ing criteria. Currently, military industries don’t distinguish between fabrics with carbon black fibers or with carbon black into dyes or prints. The latter initially allows us to comply with the color specifications in the visible and infrared, but fabrics are degraded with use losing that initial capacity. The inclusion of carbon black in the fiber gets that the fab- ric doesn’t degrade with the wear, washed and dried, ensuring the accomplishment of the specifications all the time. The use of infrared imaging will allow us to define a method to discriminate those textiles with carbon black in their fibers from those which are dyed or printed

Multi-zone temperature sensor using a multi-wavelength Brillouin fiber ring laser

A simple system for sensing temperature in multiple zones based on a multi-wavelength Brillouin fiber laser ring is presented. Optical fiber reels are serially concatenated and divided in zones (one per sensing area). Setting the Brillouin lasing in each spool of fiber generates a characteristic wavelength that depends on the fiber properties and the temperature in the zone. Thus, it is possible to measure temperature independently and accurately through heterodyne detection between two narrow laser signals. The proposed sensor integrates the temperature along the whole spool of fiber in each zone. These real time measurements were successfully checked in our laboratory

Quality control on radiant heaters manufacture

An inspection process of radiant heaters is presented in this paper. The proposed non destructive testing and evaluation (NDT and E) technique for defect assessment of radiant heaters is based on infrared thermography images properly acquired and processed. The technique can be used in on-line fabrication quality control radiant heaters manufacturing processes. By exciting the heater with a very short electrical pulse, a sequence of thermographic images is captured by an infrared camera and then analyzed. Regardless of the electrical excitation applied to the heating element of the heater, the electrical power supplied will dissipate at the resistor. Provided enough spatial resolution, the heaters could be tested with an infrared camera capturing the radiated heat. The analysis of the heating wire during the heating flank shows differences among pixels corresponding to defective points and pixels belonging to non-defective areas of the wire. The automation is provided by the development of an algorithm that looks for the slope of the heating evolution of each pixel. A Radon Transform based algorithm is here proposed to reduce human intervention providing just one image where an operator could quickly locate possible defects

Pulse shape effects on the measurement of temperature using a Brillouin-based optical fiber sensor

Distributed fiber sensing based on Brillouin gain scattering (BGS) principle is a useful way to develop devices capable to measure temperature or/and strain in optical fibers. New effects or technologies that could achieve a larger distance and/or a better spatial resolution are a topic of special interest in this fiber sensing area. The influence of the probe-pulse shape in the interaction between the pulsed light and the continuous wave laser in a pump-probe system is presented. The purpose of this study is to improve the spatial resolution of the measurement without losing stability in the BGS. Also it is showed how the backscattering Brillouin gain is affected by inducing variations on the final value of the BGS intensity; this effect is illustrated by using an experimental set up based on the Brillouin optical time-domain analysis (BOTDA). Theoretical analysis of the probe pulse in the Brillouin shift and intensity value using triangular, sinc and saw tooth shapes around the medium phonon life time (~10ns) are presented; as well as the experimental results and possible applications are explained

Support vector machines in hyperspectral imaging spectroscopy with application to material identification

A processing methodology based on Support Vector Machines is presented in this paper for the classification of hyperspectral spectroscopic images. The accurate classification of the images is used to perform on-line material identification in industrial environments. Each hyperspectral image consists of the diffuse reflectance of the material under study along all the points of a line of vision. These images are measured through the employment of two imaging spectrographs operating at Vis-NIR, from 400 to 1000 nm, and NIR, from 1000 to 2400 nm, ranges of the spectrum, respectively. The aim of this work is to demonstrate the robustness of Support Vector Machines to recognise certain spectral features of the target. Furthermore, research has been made to find the adequate SVM configuration for this hyperspectral application. In this way, anomaly detection and material identification can be efficiently performed. A classifier with a combination of a Gaussian Kernel and a non linear Principal Component Analysis, namely k-PCA is concluded as the best option in this particular case. Finally, experimental tests have been carried out with materials typical of the tobacco industry (tobacco leaves mixed with unwanted spurious materials, such as leathers, plastics, etc.) to demonstrate the suitability of the proposed technique

Predictive models for the characterization of internal defects in additive materials from active thermography sequences supported by machine learning methods

The present article addresses a generation of predictive models that assesses the thickness and length of internal defects in additive manufacturing materials. These modes use data from the application of active transient thermography numerical simulation. In this manner, the raised procedure is an ad-hoc hybrid method that integrates finite element simulation and machine learning models using different predictive feature sets and characteristics (i.e., regression, Gaussian regression, support vector machines, multilayer perceptron, and random forest). The performance results for each model were statistically analyzed, evaluated, and compared in terms of predictive performance, processing time, and outlier sensibility to facilitate the choice of a predictive method to obtain the thickness and length of an internal defect from thermographic monitoring. The best model to predictdefect thickness with six thermal features was interaction linear regression. To make predictive models for defect length and thickness, the best model was Gaussian process regression. However, models such as support vector machines also had significative advantages in terms of processing time and adequate performance for certain feature sets. In this way, the results showed that the predictive capability of some types of algorithms could allow for the detection and measurement of internal defects in materials produced by additive manufacturing using active thermography as a non-destructive test.This research was funded by Ministry of Science and Innovation, Government of Spain, through the research project titled Fusion of non-destructive technologies and numerical simulation methods for the inspection and monitoring of joints in new materials and additive manufacturing processes (FaTIMA) with code RTI2018-099850-B-I00. The authors are grateful to the Fundación Universidad de Salamanca for the indirect support provided by the ITACA proof-of-concept project (PC_TCUE_18-20_047), being this helpful for some of the purposes of this article

Infrared imaging spectroscopic system based on a PGP spectrograph and a monochrome infrared camera

Hyperspectral imaging spectroscopy has been widely used in remote sensing. However, its potential for applications in industrial and biological fields is enormous. Observation line spectrographs, based on the reflectance of the material under study in each field, can be obtained by means of an imaging spectrometer. In this way, imaging spectroscopy allows the simultaneous determination of the optical spectrum components and the spatial location of an object in a surface. A simple, small and low-cost spectrometer, such as those ones based on passive Prism-Grating-Prism (PGP) devices, is required for the abovementioned application fields. In this paper a non-intrusive and non-contact near infrared acquisition system based on a PGP spectrometer is presented. An extension to the whole near infrared range of the spectrum of a previously designed system in the Vis-NIR range has been performed. The reason under this investigation is to improve material characterization. To our knowledge, no imaging spectroscopic system based on a PGP device working in this range has been previously reported. The components of the system, its assembling, alignment and calibration procedures will be described in detail. This system can be generalized for a wide variety of applications employing a specific and adequate data processing

Enhanced contrast detection of subsurface defects by pulsed infrared thermography based on the fourth order statistic moment, kurtosis

The automatic detection of subsurface defects has become a desired goal in the application of non-destructive testing and evaluation techniques. In this paper, an algorithm based on the fourth order standardised statistic moment, i.e. kurtosis, is proposed for detection and/or characterization of subsurface defects having a thermal diffusivity either higher or lower than the host material. The analysis of thermographic data for the detection of defects can be reduced to the temporal statistics of the thermographic sequence. The final result provided by this algorithm is an image showing the different defects without the necessity of establishing other evaluating parameters such as the delayed time of the first image or the acquisition frequency in the analysis, which are required in other processing techniques. All the information is contained in a single image allowing to discriminate between the defect types (high o low thermal diffusivity). Synthetic data from Thermocalcà ® and experimental works using a PlexiglasTM specimen were performed showing good agreement. Processed results using synthetic and experimental data with other methods used in the field of thermography for defect detection and/or characterization are provided as well for comparison