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Optical Surface Roughness Measuremen...

Direito, Frederico Preto,

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Optical Surface Roughness Measurement Techniques for Industrial Applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optical Surface Roughness Measurement Techniques for Industrial Applications // Frederico Preto Direito.
作者:	Direito, Frederico Preto,
面頁冊數:	1 electronic resource (184 pages)
附註:	Source: Masters Abstracts International, Volume: 84-01.
Contained By:	Masters Abstracts International84-01.
標題:	Microscopy. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29139470
ISBN:	9798835533640

Optical Surface Roughness Measurement Techniques for Industrial Applications /
Direito, Frederico Preto,

Optical Surface Roughness Measurement Techniques for Industrial Applications /Frederico Preto Direito. - 1 electronic resource (184 pages)

Source: Masters Abstracts International, Volume: 84-01.

Surface roughness is a material surface's property that affects the component behavior, internally, affecting mechanical properties, and externally, possibly affecting the performance of the system in which the component is included. The most common surface roughness methods require contact with the material, damaging the surface, if the material is softer than the contacting instrument, and are restricted to a single line profile. As such, it is necessary for supplementary methods to be developed, in order to measure surface roughness without damaging the material's surface, and acquire information from the whole surface. Optical techniques for surface roughness measurements are a subject on the rise, as they don't need any contact to perform the measurements, while measuring the whole surface, not merely a single line profile. These techniques also remain affordable, compared to other common non-contact methods such as Scanning Probe Microscopy and Electron Microscopy methods, which require expensive hardware and software.The referred optical techniques contain one fundamental shortcoming: as these usually require multiple captures of the same reflection pattern, and the minimal displacement causes this pattern to change, any vibration may render the measurement inaccurate. There are special methods to eliminate vibration influence, but these usually come at a price.The present work aims to develop an affordable and effective optical surface roughness measurement technique that is to be employed in an industrial environment. As such, a single capture method is picked, speckle pattern analysis. Speckle pattern analysis is originally a technique that also required multiple captures but, with some adaptation, transforming it to a single capture method was feasible. Allied to Haralick's parameters, that translate image information into statistical properties, it is possible to accurately obtain the surface roughness value. Maintaining the economic factor in mind, a method has been developed.Two different software packages were experimented with, Matlab and MVTec's Halcon, in order to obtain a more diverse set of results. The system components were usual optical paraphernalia, such as a laser beam, a collimator with an integrated pin hole, and an optical lens, with a monochromatic camera to capture the images. Algebraic manipulation of the image information on the softwares was performed in order to transform a black and white image into statistical properties, which received further treatment. The chosen method to ascertain the quality of the measurements was a linear regression with the different values obtained.In the end, with the proper calibration, measurements with a negligible error ratio were achieved, with an R-squared value of almost 1 in some cases. The value range in which the measurement is possible was approximately between the dozens of nanometers to roughly one hundred micrometers. It is then concluded that, as long as the surface that is to be examined possesses a surface roughness value inside of the range set in calibration, an accurate and precise estimation of its surface roughness will be obtained.

English

ISBN: 9798835533640Subjects--Topical Terms:

540544
Microscopy.

Optical Surface Roughness Measurement Techniques for Industrial Applications /
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520 $a Surface roughness is a material surface's property that affects the component behavior, internally, affecting mechanical properties, and externally, possibly affecting the performance of the system in which the component is included. The most common surface roughness methods require contact with the material, damaging the surface, if the material is softer than the contacting instrument, and are restricted to a single line profile. As such, it is necessary for supplementary methods to be developed, in order to measure surface roughness without damaging the material's surface, and acquire information from the whole surface. Optical techniques for surface roughness measurements are a subject on the rise, as they don't need any contact to perform the measurements, while measuring the whole surface, not merely a single line profile. These techniques also remain affordable, compared to other common non-contact methods such as Scanning Probe Microscopy and Electron Microscopy methods, which require expensive hardware and software.The referred optical techniques contain one fundamental shortcoming: as these usually require multiple captures of the same reflection pattern, and the minimal displacement causes this pattern to change, any vibration may render the measurement inaccurate. There are special methods to eliminate vibration influence, but these usually come at a price.The present work aims to develop an affordable and effective optical surface roughness measurement technique that is to be employed in an industrial environment. As such, a single capture method is picked, speckle pattern analysis. Speckle pattern analysis is originally a technique that also required multiple captures but, with some adaptation, transforming it to a single capture method was feasible. Allied to Haralick's parameters, that translate image information into statistical properties, it is possible to accurately obtain the surface roughness value. Maintaining the economic factor in mind, a method has been developed.Two different software packages were experimented with, Matlab and MVTec's Halcon, in order to obtain a more diverse set of results. The system components were usual optical paraphernalia, such as a laser beam, a collimator with an integrated pin hole, and an optical lens, with a monochromatic camera to capture the images. Algebraic manipulation of the image information on the softwares was performed in order to transform a black and white image into statistical properties, which received further treatment. The chosen method to ascertain the quality of the measurements was a linear regression with the different values obtained.In the end, with the proper calibration, measurements with a negligible error ratio were achieved, with an R-squared value of almost 1 in some cases. The value range in which the measurement is possible was approximately between the dozens of nanometers to roughly one hundred micrometers. It is then concluded that, as long as the surface that is to be examined possesses a surface roughness value inside of the range set in calibration, an accurate and precise estimation of its surface roughness will be obtained.
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