Jesús María Mirapeix Serrano

Structural Damage Identification in an Aluminum Composite Plate by Brillouin Sensing

We report the results of an experimental modal analysis aimed to estimate the location of mechanical changes in an aluminum composite panel. A distributed Brillouin optical fiber sensor was used to retrieve the mode shapes of the first two bending modes of the plate. We show that the position of the defect is retrieved from the strain mode shapes, with a resolution determined by the disposition of the fiber across the structure, as well as by the spatial resolution of the interrogation unit.

Experimental demonstration of a leakage monitoring system for large diameter water pipes using a fiber optic distributed sensor system

In this paper an experimental demonstration of a leakage monitoring system designed for large diameter water pipes is discussed. The proposed solution is a distributed optical fiber sensor system based on Brillouin scattering. The design and implementation of a specific infrastructure simulating the conditions to be found in field tests have allowed to carry out a comprehensive set of experiments that will show the feasibility of the proposed approach.

Hyperspectral imaging sustains production-process competitiveness

Because of increased worldwide competition, efficiency improvements and establishing processes that are suitable for manufacturing high-end, high-quality products are primary commercial aims. In the agri-food industry, raw-material online characterization during the input stages of processing chains is of key importance for quality control. Classification into different quality categories and separation of unwanted spurious materials are traditionally done based on time-consuming machine-vision techniques. In industrial settings, however, welding-quality monitoring plays a major role, particularly in aeronautics and the nuclear industry, and the appearance of flaws (such as porosities or inclusions) must be prevented. Using x-rays, ultrasound, or other offline nondestructive evaluation techniques is associated with both economic and productivity costs, however. Optical spectroscopy (OS)1 has been widely used in process manufacturing, since each substance is uniquely identifiable from its spectral properties. However, traditional OS techniques generate information about the bulk properties of (or part of) a sample,2 and, in commonly used applications, many aspects of the derived sample properties result from composition heterogeneity. Imaging spectroscopy simultaneously determines the optical spectral components of a particular light-matter interaction (such as absorption) and its spatial location. It can successfully monitor sample heterogeneity. Hyperspectral imagers allow data collection in hundreds or even thousands of spectral bands. Thus, multicomponent information and high sensitivity to minor components are achieved, thus allowing enhanced quality control. Of the different types of imaging spectrometers,3 Figure 1. Global block diagram of our hyperspectral-imaging system for agri-food and industrial applications. LOS: Line of sight. a.u.: Arbitrary units. : Wavelength.

Colorimetric Analysis for On-Line Arc-Welding Diagnostics by Means of Plasma Optical Spectroscopy

In this paper, an analysis on the suitability of employing a colorimetric analysis of the acquired plasma spectra to perform on-line arc-welding quality monitoring will be discussed. Different colorimetric parameters like the color temperature or the parameters associated with the hue, saturation, luminance color space will be evaluated in comparison with the standard approach based on the estimation of the plasma electronic temperature. This approach does not require the identification of the emission lines involved in the analysis, thus giving rise to a more efficient solution in terms of computational efficiency, and avoiding unambiguous identifications that may give rise to incorrect results. In particular, experimental tests performed with a tungsten inert gas arc-welding process will show the feasibility of using the proposed solution and its ability to perform an online detection of different welding perturbations.

Automatic strain detection in a Brillouin Optical Time Domain sensor using Principal Component Analysis and Artificial Neural Networks

In this paper the performance of a distributed optical fiber sensor based on the Stimulated Brillouin Scattering (SBS) for dynamic strain detection is analyzed. The proposed scheme is based on the employment of Principal Component Analysis (PCA) to help in the detection and localization of the dynamic events employing the signal offered by a Slope-assisted Brillouin Optical Time Domain Analysis (BOTDA) sensor system. Results will demonstrate that the selection of the proposed processing scheme might prove useful, allowing identification of these events using the first PCA components. Additionally, an Artificial Neural Network (ANN) has been designed to be fed by the outputs of the PCA stage to perform the required classification.

Colorimetric analysis for on-line arc-welding diagnostics by means of plasma optical spectroscopy

In this paper an analysis on the suitability of employing a colorimetric analysis of the acquired plasma spectra to perform online arc-welding quality monitoring will be discussed. Different colorimetric parameters like the color temperature will be evaluated in comparison to the standard approach based on the estimation of the plasma electronic temperature. In particular, experimental tests performed with a TIG arc-welding process will show that some colorimetric parameters exhibit a better response in terms of detection and correlation to some defects than the traditional spectroscopic approach.

In-process automatic wavelength calibration for CCD-spectrometers

In CCD-spectrometers, the relation between the CCD-pixel number and the associated wavelength is established by means of a calibration polynomial, whose coefficients are typically obtained using a calibration lamp with known emission line wavelengths and a regression procedure. A recalculation of this polynomial has to be performed periodically, as the pixel number versus wavelength relation can change with ambient temperature variations or modifications in the optics attached to the spectrometer connector. Given that this calibration procedure has to be performed off-line, it implies a disturbance for industrial scenarios, where the monitoring setup must be altered. In this paper an automatic wavelength calibration procedure for CCD-spectrometers is proposed. It is based on a processing scheme designed for the in-process estimation of the plasma electronic temperature, where several plasma emission lines are identified for each spectral capture. This identification stage involves the determination, by means of a sub-pixel algorithm, of the central wavelength of those lines, thus allowing an on-line wavelength calibration for each single acquired spectrum. The proposed technique will be demonstrated by means of several experimental arc-welding tests.

Efficient processing technique based on plasma optical spectroscopy for on-line welding quality monitoring

In this paper a new spectroscopic analysis technique is proposed for on-line welding quality monitoring. This approach is based on the estimation of the wavelength associated with the maximum intensity of the background signal (continuum) of the welding plasma spectra. It will be demonstrated that this parameter exhibits a clear correlation with the welding quality of the seams, as it also happens with the traditional spectroscopic approach based on the determination of the plasma electronic temperature, thus allowing an identification of the appearance of weld defects. This technique offers a relevant improvement in terms of computational performance, what enables to detect smaller defects within the seam.