scholarly journals Measurement Point Selection and Modal Damping Identification for Bladed Disks

2011 ◽  
Author(s):  
Darren Holland ◽  
Jason Rodgers ◽  
Bogdan Epureanu
Keyword(s):  
Measurement Point ◽  
Point Selection ◽  
Bladed Disks ◽  
Modal Damping ◽  
Measurement Point Selection

Measurement point selection and compensation of geometric error of NC machine tools

2020 ◽  
Vol 108 (11-12) ◽  
pp. 3537-3546
Author(s):  
Hongwei Liu ◽  
Rui Yang ◽  
Pingjiang Wang ◽  
Jihong Chen ◽  
Hua Xiang ◽  
...  
Keyword(s):  
Machine Tools ◽  
Geometric Error ◽  
Measurement Point ◽  
Point Selection ◽  
Nc Machine ◽  
Nc Machine Tools ◽  
Measurement Point Selection

SELECTING MEASUREMENT LOCATIONS TO MINIMIZE RECONSTRUCTION ERROR USING THE INVERSE BOUNDARY ELEMENT METHOD

2007 ◽  
Vol 15 (04) ◽  
pp. 531-555 ◽  
Author(s):  
FERDY MARTINUS ◽  
DAVID W. HERRIN ◽  
ANDREW F. SEYBERT
Keyword(s):  
Boundary Element Method ◽  
Boundary Element ◽  
Transfer Matrix ◽  
Reconstruction Error ◽  
Measurement Point ◽  
Point Selection ◽  
Inverse Boundary ◽  
Point Density ◽  
Measurement Point Selection ◽  
Element Method

This paper details an approach to select measurement point locations for the inverse boundary element method. An accurate reconstruction of the vibration requires a well conditioned acoustic transfer matrix, which depends on measurement point selection. Matrix techniques can be used to regularize the solution though they often lead to poor reconstruction rank. A technique to determine the number of measurement points required, and their placement, prior to measurement has been developed using three criteria: uniqueness, completeness, and measurement point density. With this technique, the reconstruction error and the number of measurements can be minimized.

scholarly journals The precision of gingival recession measurements is increased by an automated curvature analysis method

2021 ◽  
Author(s):  
Marko Kuralt ◽  
Rok Gašperšič ◽  
Aleš Fidler
Keyword(s):  
Cross Sections ◽  
Gingival Recession ◽  
Outcome Evaluation ◽  
Measurement Point ◽  
Limits Of Agreement ◽  
Point Selection ◽  
Curvature Analysis ◽  
Scatter Plots ◽  
Point Distance ◽  
Measurement Point Selection

Abstract Background The extent of gingival recession represents one of the most important measures determining outcome of periodontal plastic surgery. The accurate measurements are, thus, critical for optimal treatment planning and outcome evaluation. Present study aimed to introduce automated curvature-based digital gingival recession measurements, evaluate the agreement and reliability of manual measurements, and identify sources of manual variability. Methods Measurement of gingival recessions was performed manually by three examiners and automatically using curvature analysis on representative cross-sections (n = 60). Cemento-enamel junction (CEJ) and gingival margin (GM) measurement points selection was the only variable. Agreement and reliability of measurements were analysed using intra- and inter-examiner correlations and Bland-Altman plots. Measurement point selection variability was evaluated with manual point distance deviation from an automatic point. The effect of curvature on manual point selection was evaluated with scatter plots. Results Bland-Altman plots revealed a high variability of examiner's recession measurements indicated by high 95% limits of agreement range of approximately 1mm and several outliers beyond the limits of agreement. CEJ point selection was the main source of examiner's variability due to smaller curvature values than GM, i.e., median values of -0.98mm− 1 and − 4.39mm− 1, respectively, indicating straighter profile for CEJ point. Scatter plots revealed inverse relationship between curvature and examiner deviation for CEJ point, indicating a threshold curvature value around 1mm− 1. Conclusions Automated curvature-based approach increases the precision of recession measurements by reproducible measurement point selection. Proposed approach allows evaluation of teeth with indistinguishable CEJ that could be not be included in the previous studies.

scholarly journals The precision of gingival recession measurements is increased by an automated curvature analysis method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Marko Kuralt ◽  
Rok Gašperšič ◽  
Aleš Fidler
Keyword(s):  
Cross Sections ◽  
Gingival Recession ◽  
Outcome Evaluation ◽  
Measurement Point ◽  
Limits Of Agreement ◽  
Point Selection ◽  
Curvature Analysis ◽  
Scatter Plots ◽  
Point Distance ◽  
Measurement Point Selection

Abstract Background The extent of gingival recession represents one of the most important measures determining outcome of periodontal plastic surgery. The accurate measurements are, thus, critical for optimal treatment planning and outcome evaluation. Present study aimed to introduce automated curvature-based digital gingival recession measurements, evaluate the agreement and reliability of manual measurements, and identify sources of manual variability. Methods Measurement of gingival recessions was performed manually by three examiners and automatically using curvature analysis on representative cross-sections (n = 60). Cemento-enamel junction (CEJ) and gingival margin (GM) measurement points selection was the only variable. Agreement and reliability of measurements were analysed using intra- and inter-examiner correlations and Bland–Altman plots. Measurement point selection variability was evaluated with manual point distance deviation from an automatic point. The effect of curvature on manual point selection was evaluated with scatter plots. Results Bland–Altman plots revealed a high variability of examiner’s recession measurements indicated by high 95% limits of agreement range of approximately 1 mm and several outliers beyond the limits of agreement. CEJ point selection was the main source of examiner’s variability due to smaller curvature values than GM, i.e., median values of − 0.98 mm− 1 and − 4.39 mm− 1, respectively, indicating straighter profile for CEJ point. Scatter plots revealed inverse relationship between curvature and examiner deviation for CEJ point, indicating a threshold curvature value around 1 mm− 1. Conclusions Automated curvature-based approach increases the precision of recession measurements by reproducible measurement point selection. Proposed approach allows evaluation of teeth with indistinguishable CEJ that could be not be included in the previous studies.

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