Hernán D. Benítez

Phase contrast using a differentiated absolute contrast method

A depth retrieval technique based on phase contrast calculations by pulsed phase thermography (PPT) has been previously reported. The phase contrast requires an appropriate selection of the sound area. This is rarely an easy task primarily because a non-defective zone is not always a priori known and even when it is, some variability is typically observed in the results due to changes in the sound phase. This article proposes implementing the differentiated absolute contrast (DAC) method to eliminate the need of defining a sound area. The proposed PPT-DAC approach, allows computation of the phase contrast by subtracting the ideal phase value of a pixel from its measured phase.

Defect quantification with reference-free thermal contrast and artificial neural networks

The Infrared Nondestructive Testing (IRNT) methods based on thermal contrast are strongly affected by non-uniform heating at the surface. Hence, the results obtained from these methods considerably depend on the chosen reference point. One of these methods is Artificial Neural Networks (ANN) that uses thermal contrast curves as input data for training and test in order to detect and estimate defect depth. The Differential Absolute Contrast (DAC) has been successfully used as an alternative thermal contrast to eliminate the need of a reference point by defining the thermal contrast with respect to an ideal sound area. The DAC technique has been proven effective to inspect materials at early times since it is based on the 1D solution of the Fourier equation. A modified DAC version using thermal quadrupoles explicitly includes the sample thickness in the solution, extending in this way the range of validity when the heat front approaches the sample rear face. We propose to use ANN to detect and quantify defects in composite materials using data extracted from the modified DAC with thermal quadrupoles in order to decrease the non-uniform heating and plate shape impact on the inspection.

Design and implementation of a protocol for acquisition and processing of infrared images obtained from hands

Disorders associated with repeated trauma account for about 60% of all occupational illnesses, being Carpal Tunnel Syndrome (CTS), the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine, where diseases are detected by temperature variations. In this paper we present the extraction of temperature variations in space and time from hands of healthy and ill subjects with CTS. These features are expected to give support to the analysis of CTS using IT. The paper presents a theoretical framework of CTS, a protocol to acquire infrared images and create a standardized collection. The techniques used for image registration and feature extraction are included. Finally, the results obtained with representative features in images of healthy subjects are presented and compared against features extracted from patientss with CTS.

Spatial pattern recognition of seismic events in South West Colombia

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

Disorders associated with repeated trauma account for about 60% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.

a new thermal contrast for non-destructive thermographic testing of materials

It is known that methods of thermographic non destructive testing (TNDT) based on thermal contrast are strongly affected by non-uniform heating at the surface. Hence, the results obtained from these methods considerably depend on the chosen reference point. The differential absolute contrast (DAC) method was developed to eliminate the need of determining a reference point that defines the thermal contrast with respect to an ideal (sound) area. Although DAC is very useful at early times, the DAC accuracy decreases at later times when the heat front approaches the sample rear face. In this article, a new DAC version is proposed by explicitly introducing the sample thickness and using the thermal quadrupoles theory. It is shown that the validity of the new DAC version increases for long times while being preserved at short times.

Content based thermal images retrieval

INDT (Infrared Nondestructive Testing) inspections produce large sets of thermal images. The thermal images obtained must be stored to do comparisons with the results of previous and future inspections generating considerable amounts of data to be analyzed. In this paper, we present a CBIR system based on thermal features and spatial relations among defects in the thermal image to measure the similarity between query and database images affected by non uniform heating and taken from anisotropic material samples.

Heat-stimulus correction for pulsed-infrared thermography

The modified DAC version with thermal quadrupoles can be considered an interesting alternative to thermal contrast computations since it provides an automated tool for depth retrieval and eliminates the need of selecting a non-defective area. In practice it is important to have heat stimulus with complex shapes and long durations (several seconds) in order to cover larger inspection areas, enhance thermal contrast between defective and sound areas and increase the depth of inspection inside the material. In this work we present a heat stimulus correction by using the thermal quadrupoles theory and its validation with several heat stimulus shapes and durations.

Images processing and flow measurement applied to the thermographic analysis of heat-losses in boilers’ isolation

Infrared thermography is a non-contact evaluation technique which allows not only the registration of the temperature distribution on a surface, but also the calculation of the amount of heat flowing through it. Boilers are important for industry and the quantification of the heat losses is beneficial to avoid fuel waste. The present work suggests a methodology to calculate the thermic flow through boilers isolation surfaces, using thermic images. With this, it is possible to find the flow by using a thermogram taking into consideration: the thermograms range, knowing the cameras FOV, surfaces emmisivity and characteristic length, object-to-camera distance, environmental temperature, and the assigned grey-level calibration curve to determined temperature range. A software tool to upload and process the information was developed. This tool can calculate the surfaces average convection coefficient hc by using empiric correlations developed for common geometries and heat transfer equations to calculate the thermic flow. To test the technique functioning, the information given by the software tool was compared to the data given by the heat flow measurement thermal sensor. This comparison showed a 3% error range of relative error. The final validation was made on a waterwall-boilers home isolated walls and the highest error obtained was close to 15%. Regardless the calibration curve was found under laboratory conditions and the empiric correlations to calculate hc are for isometric surfaces, the methodology presented a good performance. This then is a first step to quantify the global heat losses on boilers isolation surfaces.