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In-line laser thermography for crack detection at elevated temperature: A Numerical modeling study
(2016)
The detection and characterization of cracks prior to damage is a technologically and economically highly significant task and is of very importance when it comes to safety-relevant structures. The evaluation of a components life is closely related to the presence of cracks in it. Laser thermography has already high capability for the detection of surface cracks and for the characterization of the geometry of artificial surface flaws in metallic samples. Crack detection in metallic samples at high temperature is highly significant in present manufacturing scenario. During the casting process of billets, surface cracks form, due to the suboptimal cooling rates. These cracks reduce value of the billet and must be removed using machining process after cooling. This secondary process increases cost of manufacturing. In this work we developed a heat transfer model for laser thermography to study the thermal contrast variation with increase in surface temperature using finite element method (FEM). Here we are mainly concentrating the capability of the scanning laser thermography in crack detection which are in elevated temperature and numerical modeling study of thermal contrast variation of crack with respect increase in metal surface temperature. This study is important to prove the capability of laser thermography for crack detection in elevated temperature. Since we are using High power CW Laser to local heating of the metal surface which can give relatively high thermal contrast even at elevated temperature compare to other heating source. Here we are modeled and simulated 2D laser scanning across a surface breaking crack and developed an algorithm to produce the vicinity of crack. The algorithm we developed applied for various surface temperature data. And validated the credibility of the algorithm with experimental data.
Crack detection in metallic samples at high surface temperature, hostile and hazardous environments, etc. is challenging situation in any manufacturing industries. Most of the present NDE methods are suitable only for lower surface temperatures, especially room temperature. In this situation, we need a fast and non-contact NDT method which can be applied even in high sample surface temperature. Laser thermography is one of the techniques having a high potential in non-contact inspection. As a preliminary investigation, in this article, we have studied the potentiality of laser line thermography in crack detection at room temperature. In laser line thermography, a continuous wave (CW) laser is used to generate a laser line, which in turn is used to scan the metal surface. The heat distribution over the sample surface is recorded by an infrared thermal (IR) camera. Two different approaches are reported in this work. Firstly, a stationary laser line source and its interaction with cracks; secondly, moving laser line source scanning over a surface with crack. When the distance between crack centre to laser line centre increases, crack detectability will decrease; and when laser power increases, crack detectability will increase. A dedicated image processing algorithm was developed to improve the detectability of the cracks. To understand the heat transfer phenomenon, a simplified 3D model for laser thermography was developed for the heat distribution during laser heating and was validated with experimental results. Defects were incorporated as a thermally thin resistive layer (TTRL) in numerical modeling, and the effect of TTRL in heat conduction is compared with experimental results.
The aim of this work is to illustrate the contribution of signal processing techniques in the field of Non-Destructive Evaluation. A component’s life evaluation is inevitably related to the presence of flaws in it. The detection and characterization of cracks prior to damage is a technologically and economically significant task and is of very importance when it comes to safety-relevant measures. The Laser Thermography is the most effective and advanced thermography method for Non-Destructive Evaluation. High capability for the detection of surface cracks and for the characterization of the geometry of artificial surface flaws in metallic samples of laser thermography is particularly encouraging. This is one of the non- contacting, fast and real time detection method. The presence of a vertical surface breaking crack will disturb the thermal footprint. The data processing method plays vital role in fast detection of the surface and sub-surface cracks.
Currently in laser thermographic inspection lacks a compromising data processing algorithm which is necessary for the fast crack detection and also the analysis of data is done as part of post processing. In this work we introduced a raw data based image processing algorithm which results precise, better and fast crack detection. The algorithm we developed gives better results in both experimental and modeling data. By applying this algorithm we carried out a detailed investigation Variation of thermal contrast with crack parameters like depth and width. The algorithm we developed is applied for various surface temperature data from the 2D scanning model and also validated credibility of algorithm with experimental data.