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gautiercap last won the day on June 3 2015

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  1. Tom, The software I used is called PTMconvert, it's available here: http://blog.tobias-franke.eu/ptmconvert/ I asked for help to compile it and it runs smoothly. It actually gives me everything I need for my study, including coefficients! Gautier
  2. Tom, Thank you for your answer! I managed to actually find a software that converts any .ptm file into three pictures highlighting coefficients. By splitting the color channels I can compare the 6 pictures and see which coefficients change when there are cracks, holes, etc... That said, I'd still like to see these coefficient values in the text file but I have zero knowledge in programming. Do I need to use a specific software to convert the text characters in numerical values? I can't find how to do so. Thank you for your time and expertise, Gautier
  3. Hello, I read with attention Mr. Malzbender's document about PTM Format as well as some other posts here but I haven't found a solution to my problem. I would like -using the .ptm text file- to find the coefficients used to recreate the dynamic visualization. Basically a0, a1, a2, a3, a4 and a5 in the equation that gives the luminance for each pixel (C = a0Lu² + a1Lv² + a2LuLv + a3Lu + a4Lv + a5). I'm studying RGB and LRGB formats. The paper gives for both of these formats the following explanations: When I open any .ptm text file, I can easily find the header (type, image size, scale and bias) but then it's a random succession of characters. Are the coefficients accessible by any means? Would it also be possible to visualize them in 6 separate pictures? To see which ones have influence on some aspects of the surface (defects, indications, etc)? Thanks a lot in advance, Gautier
  4. I contacted Serge since it seems like his expertise could be of a great help with my issues. I'd also appreciate it a lot if you could share your work with us, and give some insights on what you've done so far on the project. Thanks, Gautier
  5. Hello Taylor, Thanks for these very complete precisions. Turns out we won't actually buy a camera, I will have to use some that the lab downstairs already has. I need to receive my Personal Protective Equipment before going there so I'll keep you updated on which camera we have and the kind of lense we can use. The dome should be done by the middle/end of next week. Hopefully I will be able to present proper results by the middle of June. I'll make sure to share my progress with you guys. To refocus my objectives on this project, I need to find detection criteria for surface defects. The dome is just the tool to help us visualize the surface. I need to find the proper parameters to vary to detect each types of defects. I'm looking for 7 types of defects: Discontinuities (cracks) Cavities (holes and porosity) Excrescences of matter (too much metal) Surface impurities (mostly oxides) Surface defects (scratches, scales, etc) Shape defects (mostly due to bad welding) Chemical defects The minimal dimension we're looking for is 5µm in opening and 1 to 2mm in lenght. Besides changing the light orientation and adding filters to the camera (both color and polarizing), is there anything else I should consider to highlight these defects? Gautier
  6. Taylor, Thank you very much for your input on this. I must admit I’m very new to the RTI method and my limited time on the project makes it harder to digest and take all parameters into account. That said, you highlighted some points that make a lot of sense and I had further questioning about the project. I’ll answer your questions as well. I wasn’t the one who ordered most of the components so I’ll be using LEDs that are cold white (color temperature: 10000°K and luminous flux: 370 lumens). I’m going to follow your advice and use only 48 LEDs from angles that range from 15° to 55°. I have not ordered the camera yet; I need to check with my supervisor about the price range we can afford. Would you recommend any model in particular? The dome will be about 450mm in diameter. I think we should be able to afford expensive equipment. I didn’t realize the spheres could be that small. That might work then! Is that method extremely precise to find the light direction though? And will it give me sufficient information on the LEDs positions? I have started experimenting with the three algorithms you mentioned (diffuse gain, specular enhancement and unsharp masking). They do seem to show great promise. I’ll definitely keep you updated on that. I will have access to smaller scale models of nuclear plants components with known defects (usually cracks) created by electrical discharge machining. I firstly want to optimize the method of visualization (reduce the number of LEDs, find the right light orientations, etc...) and then find a way to process the data in order to not only detect all defects but also possibly to proportion them. That way we could separate easily the defects that are critical from the ones that aren’t. Regarding the latter issue, when using the HP Labs PTMViewer software I noticed a button named ‘Output Depth Values’ but it didn’t work. The error message read ‘Unable to open .cam file, aborting depth calculation’. That feature seemed extremely interesting especially for this project so I was also wondering if someone knew anything about this. Thank you again for reading and helping me on this, I genuinely appreciate it. Gautier
  7. Hello, I’m currently working as an intern in AREVA (France) on a project that involves inspecting surfaces of nuclear plants primary components (mostly the reactor vessel and the lid) to look for defects and try to automatize the procedure. It’s currently done by watching hour long videos and the procedure, besides being both tiring and time consuming, leads to a high variability in judgments. I thought about using the PTM/RTI method and my supervisor agreed to let me buy the tools required to build a dome. Its diameter will be 450 mm and I’ll be using 96 white LEDs as light sources. I’ve been strongly inspired by the work of G. Le Goïc and S. Samper (2011) who used the PTM technique for detection of appearance anomalies in high-value products requiring a perfect surface quality (watches, automotive, medical, automation). I had some questions regarding this project and thought this forum could be of great help. Firstly, I have some apprehension concerning the position of the 96 holes in the dome. I don’t really know how to go with the drilling procedure and how to be sure their orientation is rigorous. I included a scheme of said dome in the message. Then, is it absolutely necessary to use reflecting spheres or can the light position coordinates be calculated using another method? I don’t really see how I could include spheres in the dome without obscuring the lowermost part of it. I’m also guessing it’s really important to make sure the inside of the dome is kept in the complete dark when all LEDs are turned off, right? Lastly, the goal would be to automatize the process of finding defects. These defects are usually cracks, gutters, porosities, metal grindings, etc… I was wondering how the processed data could be treated using PTM/RTI to highlight such anomalies? Is it even possible with proper software or with different equipment? Thank you so much in advance, I’ll make sure to update the post from time to time if I have further issues or if you guys are simply interested in the project. Gautier
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