A simple approach to fine wire diameter measurement using a high-resolution flatbed scanner

Kee, C. W.; Ratnam, Mani Maran

doi:10.1007/s00170-008-1405-9

Cited by 11 publications

(9 citation statements)

References 10 publications

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“…Elsewhere 100x100 mm plates of air entrained concrete were scanned [14] and the longitudinal and lateral distortion of a scanned image across large dimensions was examined [15]. Two particularly relevant and recent FBS applications are notable; in one paper section lengths of injection moulded test spirals were measured [16], and in another automatic wire diameter measurements were made using a Matlab image processing toolkit [17]. The main disadvantage of these systems is that they were developed for measurements that were almost 2D.…”

Section: Previous Applications Of Flatbed Scannersmentioning

confidence: 99%

Desktop Scanner Metrology

Divis

Mair

Corney

2015

Machine Vision and Mechatronics in Practice

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An investigation is presented of a low cost approach to the measurement of two and three dimensional objects using a flatbed scanner and image analysis software. Conventional measurement using relatively low cost instruments such as micrometers and vernier callipers can be time consuming and requires operator skills which result in higher overall costs. The increasing resolution and decreasing prices of flatbed scanners introduces the possibility of their use as a low cost alternative to traditional manual measuring. To investigate this, a simple dimensional measurement technique was developed using an unmodified, then a modified, flatbed scanner, a standard PC, and software. A dimensional accuracy of ±0.05 mm was achieved with a modified flatbed scanner system for slip gauge samples of nominal thickness 10mm and 5mm

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Section: Previous Applications Of Flatbed Scannersmentioning

confidence: 99%

Desktop Scanner Metrology

Divis

Mair

Corney

2015

Machine Vision and Mechatronics in Practice

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“…Applications include the measurement of crystal sizes [11] and adaptive direct slicing techniques in rapid prototyping [12]. Specifically, the MATLAB Image Processing Toolbox has been implemented for various advanced manufacturing purposes [13], [14], [15], [16].…”

Section: Image Processingmentioning

confidence: 99%

Cogging torque prediction for mass-produced axial flux PMSM stators

Brown

Heins

Hobbs

et al. 2011

2011 IEEE International Electric Machines &Amp; Drives Conference (IEMDC)

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Stator manufacturing processes for axial flux permanent magnet synchronous motors (AFPMSM) are susceptible to variation leading to cogging torque. To date, there are no methods which synthesize cogging torque based on stator manufacturing errors. This paper presents a superposition method based on stator geometry to predict critical cogging harmonics for AFPMSM stators. Geometry is obtained using image processing techniques on a scanned image of the stator. The proposed method has been validated by comparison with experimental cogging torque data. A correlation of 0.82 linear regression was found using the method proposed in this paper. Process capability was tested by measuring slot widths and checking deviation.

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“…Some recent applications of the scanner include rock and sediment color measurement, 1 measurement of effective optical reflectivity of silicon wafers, 2 assessment of quality parameters of coated metallic surfaces and monitoring of electrochemical coating bath lives, 3 assessment of occlusal tooth wear, 4 quantification of infected cell population and plaque formation, 5 monitoring and quantification of oil migration in cocoa butter, 6 determination of size distribution in rice kernels, 7 measurement of nose radii of cutting inserts, 8 determination of size and distribution of airborne dust particles, 9 and wire diameter measurement. 10 Although the flatbed scanner has been used in numerous sensing and measurement applications, literature on the application of the scanner in roughness assessment and measurement is very limited. In the work carried out by Gutierrez-Padilla et al 11 a charge-coupled device (CCD) flatbed scanner was used to scan the image of a concrete specimen subjected to various levels of corrosion.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Areal (Three-Dimensional) Roughness Parameters of Milled Surface Using Charge-Coupled Device Flatbed Scanner and Image Processing

Goh

Ratnam

2015

Exp Techniques

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A new application of the charge-coupled device (CCD) flatbed scanner for the noncontact assessment of areal three-dimensional (3D) roughness parameters of milled surfaces is proposed in this work. The surfaces were prepared by milling a block of aluminum at five different feed rates using a CNC milling cutter. The specimen was placed on the flatbed scanner with the milled surface facing the scanner array. The scanned images were analyzed using image processing to extract the average pixel intensity, root-mean-square pixel intensity, variance, black-to-white ratio, and bright region average area intensity within a region-of-interest. These parameters were correlated with the 3D areal parameters obtained using a state-of-the-art focus variation 3D metrology system. The highest correlation of 0.9931 was obtained between the average pixel intensity from the scanned image and average areal roughness S a at a scanning height of 7.2 mm from the scanner surface. Compared with the costly 3D metrology system, the flatbed scanner combined with the proposed image processing algorithm has significant potential for roughness assessment due to the high correlation between the image parameters and roughness parameters.

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A simple approach to fine wire diameter measurement using a high-resolution flatbed scanner

Cited by 11 publications

References 10 publications

Desktop Scanner Metrology

Desktop Scanner Metrology

Cogging torque prediction for mass-produced axial flux PMSM stators

Assessment of Areal (Three-Dimensional) Roughness Parameters of Milled Surface Using Charge-Coupled Device Flatbed Scanner and Image Processing

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