The gases accumulated inside the landfill as result of the fermentation of Municipal Solid Waste (MSW) known as biogas, are taking into consideration all possible uses as direct transformation into electricity. The system for collecting, regulating and controlling the biogas must include all the necessary safety features where the biogas leakage presents a high impact. Infrared thermography can be use to detect gas leakages due to the differences in temperature between the gas and the immediate surroundings. This method is able to monitor a wide area of landfill sites, quickly. This technology will not be effective if the differences in temperature are not better than five degrees. This paper describes a field test conducted to study the limitations of the infrared thermography caused by weather conditions and the moment of day or/and season when the thermal images was captured. Pipelines, borders, cells, covers, slopes and leakage (hot spots) are studied and optimum conditions are defined.
The automatic detection of subsurface defects has become a desired goal in the application of Non Destructive Techniques. In this paper, a new algorithm based on the Radon Transform is proposed to reduce human intervention to a minimum in the field of Thermography for defect detection and/or characterization. The analysis of a thermographic sequence for the detection of subsurface defects can be reduced to the identification of the -0.5 slope in the surface temperature decay for each pixel within the image. Employing techniques commonly used in computer vision, an algorithm can be developed in order to look for the -0.5 slope in the temporal temperature decay profiles of each pixel. In our case, the Radon transform can be used to detect those -0.5 slope lines in the temporal temperature decay profiles. The final result provided by this algorithm is an image showing the different defects avoiding the necessity of evaluating parameters as relevant in other algorithms as the delayed time of the first image or any subjective point of view in the analysis. All the information is contained in only one image and leads to a quantitative estimation of the defect depths. The principal limitation is that the specimens under inspection should be semi-infinite homogeneous samples because this algorithm is supported on a 1-D Fourier diffusion equation approximation. Experimental works using a PlexiglasTM specimen were performed showing a good agreement with other semi-automated techniques.
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.
In this paper, we review some of the discrete signal transforms that are in use in the field of thermography for defect detection and/or characterization. Signal transformation is used with the purpose of finding an alternative domain where data analysis is more straightforward. For instance, it is possible to pass from the time domain to the frequency spectra through the one-dimensional discrete Fourier transform (DFT). The DFT constitutes the basis of pulsed phase thermography (PPT), but other transformations are possible such as the discrete wavelet transform (DWT) with the advantage that, in this case, time information is preserved after the transformation. It is also possible to rearrange data into domains others than frequency. For instance, the Hough transform (HT) allows the detection of regular forms (e.g. lines, curves, etc.) in a parameter space. The HT has been used in two different ways in thermography: for the detection of lines in thermal profiles, with the goal of discriminating between defective and non-defective regions; or it can be used to locate the inflection points in phase profiles obtained by PPT to extract the blind frequencies. The Laplace transform can also be used in the time domain to improve flaws detection and their characterization in the transformed space. Eigenvector-based transforms, such as singular value decomposition (SVD), have also been implemented. Principal component thermography (PCT) uses SVD to decompose thermographic data into a set of orthogonal modes. We discuss all these transforms and provide some comparative results.
Based on infrared thermography, a non-destructive testing and evaluation (NDT&E) procedure is proposed for defects
assessment on radiant heaters. Under a short electrical excitation, an infrared camera captures the cooling process of the
heaters. Breaking the thermographic images down not only makes easiest the location of defects but it also allows their
classification. Several kinds of defects have been taken into account: lack of supporting brackets; defects originated by a
deficiency in the heating material; those from an excess of heating material; and those parts of the heating elements
which are in wrong contact (non-contact or semi-buried) with the substrate. Each kind of analyzed defect has a different
thermal history after the electrical excitation because of its nature. By means of computer vision techniques, the defects
can be spatially located. The "chain code" was employed to follow the pattern of the heating element and so concentrate
the analysis in points belonging to the pattern. A good agreement with analysis made under human's criteria is achieved.
However, using infrared cameras and processing the data with computer vision algorithms allows controlling in-site the
quality of the product without any subjectivity. So, the heaters manufacturing industry could come along with the
implementation of this automatic detection procedure. Experimental results that validate the proposed method will be
presented and discussed in this paper.
Pump power-induced changes in the center wavelength of the attenuation band of the spectrum of long-period fiber gratings (LPG) writing in erbium doped fibers are experimentally checked. The pump tuning of the LPG is demonstrated.
The spectral properties of long period fiber gratings (LPFG) are modified when twisting is applied. Herein, results of applying torsion to UV-induced LPFGs are presented for comparing with others which have already been presented in literature and where the LPFGs are fabricated using different techniques. Both, the resonant wavelength and the peak attenuation of the resonance, have similar behaviors to those obtained by other authors. However, in spite of the fact that the values of sensitivity to twist rate are sensibly lower in the case of UV-LPFGs, its bigger mechanical strength lets them be subjected to higher twist rates, which could be useful in determinate applications.
In this paper a theoretical prediction of a new kind of in-fiber devices is presented. They behave essentially like long-period Bragg gratings except for the fact that they are not permanent but volatile. This is because these devices are not formed by the UV-induced increment of the refractive index but by the twisting of a pristine HiBi fiber. This way, a long period fiber grating whose characteristics can be modified by changing the polarization of the incoming light is obtained.
On the steel production industry, a mixture of selected scrap and pellets of DRI is put into the furnace according to the desired quality of steel. The quality of the iron steel bars, among other, depends on the temperature profile during the cooling and solidifying process. A new multipoint high temperature transducer based on the optical power collected by a group of multimode optical fibers has been developed for measuring the transversal cooling profile. The optic fibers are adequately sheathed by a ceramic mixture in order to achieve its mechanical and thermal protection. Besides in order to use the transducer in pollution environments, the probe is putted inside of a close chamber with a window made with a vitreous ceramic material. The use of silica fiber optic limits the spectral range to analyze, and the measured temperature range. The behavior of the transducer from the angle, the distance and the change of emissivity have been measured, and the transducer has been optimized. The transducer was calibrated in the Photonics Engineering Group laboratory and it was installed in a iron-steel bar manufacturing plant in Spain where it is working high relative humidity and high temperature environment.
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