Laser-induced breakdown spectroscopy: fundamentals, applications, and challenges

Laser-induced breakdown spectroscopy (LIBS) is a technique that provides an accurate in situ quantitative chemical analysis and, thanks to the developments in new spectral processing algorithms in the last decade, has achieved a promising performance as a quantitative chemical analyzer at the atomic level. These possibilities along with the fact that little or no sample preparation is necessary have expanded the application fields of LIBS. In this paper, we review the state of the art of this technique, its fundamentals, algorithms for quantitative analysis or sample classification, future challenges, and new application fields where LIBS can solve real problems

Focal beam position detection in a laser induced breakdown spectroscopy system by using a fiber Bragg grating sensor

Chemical analysis of dangerous materials entails a safety issue for the researchers. Laser Induced Breakdown Spectroscopy offers the possibility to analyze these materials away from them using Stand-Off Set-ups. To optimize the plasma induction, the remote focalization of the laser beam is of paramount importance. A custom Fiber Bragg Grating sensor system able to correct the laser beam focalization errors is proposed and experimentally checked. The optical transducer architecture and the preliminary obtained results are reported in this paper.This work has been co-supported by the Spanish Government through the project TEC2010-20224-C02- 02 and the grant AP2007-02230

Acoustic detection of laser-induced plasma emission by means of a fiber-Bragg grating sensor

Laser-induced breakdown spectroscopy (LIBS) is an analytical tool able to estimate the atomic composition of materials, without sample preparation and in a short time. One drawback of this technique is that the quantitative analysis is not as precise as other established methods, in part because of the pulse-to-pulse fluctuations of the energy delivered to the sample. These fluctuations can be compensated by monitoring the acoustic wave emitted by the plasma, which is related to the ablated mass. In this paper, we propose the use of a fiber-Bragg grating sensor to detect and measure the acoustic shockwave. A processing scheme is proposed to derive the acoustic energy from the sensor waveform. The experiments show that there is a correlation between the sensor’s response and the laser pulse energy, so it can be used as a monitoring signal of the ablation process

Integral temperature hybrid laser sensor

An integral temperature sensor based on Brillouin laser ring that is feed by a Fourier Domain mode-locking (FDML) laser is here proposed. The source FDML laser ring emits at 1532 nm within a range of 5 nm. The working wavelength is given by tuning the offset voltage applied to a Fabry-Perot tunable filter (FFP-TF). In the present work, the FDML laser linewidth is set at 0.136 nm. This linewidth allows a more efficient Brillouin response in the optical fiber without increasing the Brillouin threshold. The FDML laser linewidth is controlled by setting the amplitude modulation of the drive signal offset applied on the FFP-TF

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

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

Spectral marks for qualitative discriminant analysis

In this paper, a method for the automatic qualitative discrimination of liquid samples based on their absorption spectrum in the ultraviolet, visible and near-infrared regions is presented. An alternative implementation of conventional spectrum matching methodologies is proposed working towards the improvement of the response time of the discrimination system. The method takes advantage of not making assumptions on the probability density function of the data and it is also capable of automatic outlier removal. Preliminary discrimination results have been evaluated on the classification of different oil samples from seeds and olives. The system here proposed could be easily and efficiently implemented in hardware platforms, improving in this way the system performance

Tunable fiber laser using concatenated non-adiabatic single-mode fiber tapers

An erbium doped fiber ring laser (EDFRL) that incorporates four non-adiabatic concatenated single-mode fiber tapers (acting as tunable filter in the laser cavity) is presented. These concatenated fiber tapers integrates a filter with a narrower band-pass and a higher modulation depth than a single taper. The tuning of this filter was implemented applying a controlled perturbation in the fiber taper. The proposed laser architecture was successfully demonstrated in the laboratory in which a tuning range of 20.8nm (1544.5nm-1565.3nm) were measured

POF-based specklegram sensor post processing comparative: methods for extracting breath and heart rate

Continuous patient monitoring has been evidenced as very beneficious for reducing degeneration1. Due to this, a POF specklegram sensor has been developed based on a previous work2. This work presents a comparative between analysis methods of the specklegram signal for achieving a precise and robust non-contact monitor system. Two different techniques have been used: one based on the Fast Fourier Transform (FFT) and the other based on the Hilbert Transform (HT). Each technique has been employed with two different methods, for heart rate and breath rhythm. The different algorithms are tested on 10 volunteers of different ages and sex.This work has been sponsored by the Spanish Ministry of Science, Innovation and Universities and European Regional Development Fund (ERDF) across projects RTC-2017-6321-1 AEI/FEDER,UE and TEC2016-76021-C2-2-R AEI/FEDER, UE

Automatic classification of steel plates based on laser induced breakdown spectroscopy and support vector machines

Welding processes are one of the most widely spread industrial activities, and their quality control is an important area of research. The presence of residual traces from the protective antioxidant coating, is a problematic issue since it causes a significant reduction in the welding seam strength. In this work, a solution based on a Laser Induced Breakdown Spectroscopy (LIBS) setup and a Support Vector Machines (SVMs) classifier to detect and discriminate antioxidant coating residues in the welding area without destroying the sample before the welding procedure is proposed. This system could be an interesting and fast tool to detect aluminium impurities