Optically and non-optically excited thermography for composites: A review

E n los últimos años nos hemos acostumbrado a ver soluciones de automatización y control en que la utilización de técnicas de inteligencia artificial aporta beneficios contrastables. Varias marcas comercializan reguladores borrosos o combinados (por ejemplo, PID con control anticipativo borroso), o incluyen mecanismos de ajuste fino de parámetros basados en lógica borrosa. Ocasionalmente, las redes neuronales se han utilizado en el modelado y control de sistemas no lineales. La implantación masiva de sistemas de adquisición y registro de datos (en ocasiones impuestos por requisitos de trazabilidad y calidad) ha permitido un mejor conocimiento de las plantas, que se ha reflejado en las tareas de ingeniería y gestión. Se persigue, por tanto, la reutilización de este conocimiento directamente en planta para detectar y diagnosticar en línea. El beneficio recaerá tanto en la mejora de planes de mantenimiento (ajuste de tiempos, predicción de fallos, asignación de recursos, planificación, etc.) como en la toma de decisiones por parte del supervisor (reducción del tiempo para conocer las causas) para evitar situaciones catastróficas.

A.I. (Inteligencia Artificial)

A review of state-of-the-art techniques for abnormal human activity recognition

An overview of corrosion defect characterization using active infrared thermography

After defining a good usage of pulse thermograms, in particular their ‘rectification’ thanks to log-log plot, and fitting by the TSR (thermographic signal reconstruction) technique, it is demonstrated that a simple and efficient normalisation is possible. The optimisation of pulse thermography is proposed based on two complementary approaches: the early detection of contrasts and the use of the TSR technique with logarithmic derivation. It is shown that in these conditions the quality of thermal images is greatly enhanced (reduction of blurring) and the accuracy of the identified defect parameters (depth and thermal resistance) is better. Based on experimental and simulated results it is shown that to optimise pulse stimulated thermography it is necessary to consider two parameters: the signal-to-noise ratio of the defect contrast and the precociousness of its exploitation. It is shown that this second parameter, which has been neglected by most of the users of pulse thermography who identified the defect...

Defense and illustration of time-resolved pulsed thermography for NDE

Definition of a new thermal contrast and pulse correction for defect quantification in pulsed thermography

Infrared thermography is a nondestructive evaluation technique in which the specimen surface is thermally stimulated to produce a temperature difference between "sound" (free of defects) areas and eventual defective regions. It is well known that the thermographic methods based on the thermal contrast are strongly affected by non-uniform heating at the surface. Hence, thermal contrast-based results considerably depend on the chosen reference point. The differential absolute contrast (DAC) method was developed to eliminate the need of determining a reference point by defining the thermal contrast with respect to an "ideal" sound area. The DAC technique is based on the 1D solution of the Fourier diffusion equation for homogeneous and semi-infinite materials stimulated with a Dirac heat pulse. Although very useful at early times, this assumption considerably decreases DAC accuracy when the heat front approaches the sample rear face. We propose a modified DAC version by explicitly introducing the sample thickness using the thermal quadrupoles theory. We demonstrate that taking into account the sample thickness, the DAC validity range considerably extends for long times after excitation while preserving its performance for short times.

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Modified Differential Absolute Contrast using Thermal Quadrupoles for the Nondestructive Testing of Finite Thickness Specimens by Infrared Thermography

It is well known that thermal contrast-based quantification methods are strongly affected by the non-uniform heating, the sample shape and the chosen sound area In this work we propose a reference-free thermal contrast by using the thermal quadrupoles theory and evaluate the limits of defect detection in composite samples by using dynamic principal components analysis (DPCA) and k-nearest neighbor algorithm Additionally, we propose and validate the radial basis functions (RBF) networks and support vector machines (SVM) for the detection and quantification of defect depth in composite material samples affected by non-uniform heating and with complex shapes

Defect characterization in infrared non-destructive testing with learning machines

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.

http://cic.javerianacali.edu.co/~hbenitez/Publications_files/QIRT06PhaseCtrs.pdf

Phase contrast using a differentiated absolute contrast method

We have shown that it's possible to realize a stereoscopic sensor with poor cameras. We developed image processing that is robust and allows us to quickly obtain results for the matching algorithm. We computed an important number of features on each segment, and with these features, we built 16-component vector used in the classification step. After an exhaustive study, we decided to combine two methods, Bayesian and neural, to construct an efficient classifier. The tests for indoor images had better than 90% good matching. With segment couples, it is possible to compute the 3D coordinates of the objects. Therefore, the mobile robot is able to localize and move about in the environment.

Humberto Loaiza

Papers

Definition of a new thermal contrast and pulse correction for defect quantification in pulsed thermography

Modified Differential Absolute Contrast using Thermal Quadrupoles for the Nondestructive Testing of Finite Thickness Specimens by Infrared Thermography

Defect characterization in infrared non-destructive testing with learning machines

Phase contrast using a differentiated absolute contrast method

Matching segments in stereoscopic vision