scholarly journals Lateral Shift Error due to Graduation Anomalies and Line-Detection Algorithm in Line Scale Measurement

2012 ◽  
Vol 6 (1) ◽  
pp. 84-91
Author(s):  
Akira Takahashi ◽  
◽  
Yuji Kokumai ◽  
Yuichi Takigawa ◽  
Keyword(s):  
Signal Processing ◽  
Detection Algorithm ◽  
Lateral Shift ◽  
Signal Processing Algorithm ◽  
Filter Width ◽  
Line Scale ◽  
Scale Calibration ◽  
On Line ◽  
Ordinary Line ◽  
Lateral Error

The measurement error resulting from graduation anomalies and the signal processing algorithm used for determining the positions of graduations on line scales was investigated by simulation and experiment. Optical image-forming simulations were carried out on models of 6-µm-wide graduations with three sizes of defects (0.5, 1.0 and 1.5 µm) at one edge. A digital filter was used in signal processing to obtain the first differential to determine the positions of the graduations. The minimum values of the lateral shift of the determined graduation positions were observed for the three defect sizes when using a 9-µm-wide differential filter. An experiment was also carried out on an ordinary line scale with 6-µm-wide graduations using a high-precision laser-interferometric line scale calibration system by measuring seven positions on the scale in the direction perpendicular to the measurement axis. The root mean square of the standard deviations from the linear fitting lines constructed using the measured positions over a 300-mm-long line scale was 2.8 nmwhen the differential filter width was 9 µm. It was demonstrated that a differential filter was effective in reducing the lateral error due to graduation anomalies.

Analysis of Dynamic Method of Line Scales Detection

2009 ◽  
Vol 147-149 ◽  
pp. 576-581
Author(s):  
A. Barakauskas ◽  
Albinas Kasparaitis ◽  
Saulius Kausinis ◽  
R. Lazdinas
Keyword(s):  
Error Detection ◽  
Dynamic Method ◽  
Optical Microscope ◽  
Detection Algorithm ◽  
Uncertainty In Measurement ◽  
Line Scale ◽  
Scale Calibration ◽  
Calibration Program ◽  
Long Stroke ◽  
Scale Detection

The main causes of uncertainty in measurement regarding long-stroke line scales are line detection errors and external factors, especially temperature effects. The number of calibration errors of this sort increases with the extension of calibration time. Therefore, a dynamic method of line scale detection for modern long-stroke line scale comparators is used [1, 2, 3]. The article discusses the dynamic method of line scale detection by means of an optical microscope equipped with a photosensitive cell matrix and a line scale detection algorithm. Advantages of the dynamic method of scale calibration in terms of rate, accuracy and throughput are presented. The method’s error (detection parameters) correlations with detection rate, number of nominal lines, measuring rate, exposition delay are analyzed and mathematical models are described. The optimal values of these parameters are estimated. We are particularly interested in the improvement of the dynamic calibration program algorithm and minimization of uncertainty in measurement. The method was implemented and tested on the long-stroke line scale comparator, which has been developed and realized by JSC Precizika Metrology [3, 4, 5] in cooperation with VGTU and KUT.

scholarly journals ANALYSIS OF AIRY POINT APPLICATION ON LINE SCALE CALIBRATION IN RCM LIPI

2019 ◽  
Vol 20 (3) ◽  
pp. 189 ◽  
Author(s):  
Nadya Larasati Kartika ◽  
Nurul Alfiyati
Keyword(s):  
Research Center ◽  
One Dimensional ◽  
Supporting Point ◽  
Line Scale ◽  
Two Systems ◽  
Scale Calibration ◽  
On Line ◽  
Measuring Machine

<p>Calibration of line scale in the Research Center for Metrology LIPI Indonesia (RCM-LIPI) is traceable to one dimensional measuring machine (SIP machine). Capability of the SIP machine table used as the base of line scale, however, covers only up to 400 mm and can be extended to 1000 mm using shifting methods. Supporting point as a method to maintain line scale still straight during measurement should be applied on machine table. For line scale ranged 400 mm, supporting point can be attached because the whole artefact is on the table, while some of the industrial instruments have scales above 400 mm, this mean slightly difficult to attach supporting point. This paper described an appropriate supporting points setting and their influence in line scale calibration ranged 500 mm by designed two systems supporting point attachment, they are L = 500 mm and L = 350 mm.  As for the supporting points, airy points were used, because they were the most suitable for line scales with the pattern at the top plane. Each design is analysed using error graph and E<sub>n </sub>score to determine the most suitable design for 500 mm line scale calibration<em>.</em></p>

On-Line Signal Processing Using J-DSP

2004 ◽  
Vol 11 (10) ◽  
pp. 821-825 ◽  
Author(s):  
A. Spanias ◽  
V. Atti ◽  
A. Papandreou-Suppappola ◽  
K. Ahmed ◽  
M. Zaman ◽  
...  
Keyword(s):  
Signal Processing ◽  
On Line

A novel intrinsic time–scale decomposition–graph signal processing–based characteristic extraction method for rotor–stator rubbing of aeroengine

2021 ◽  
pp. 107754632098596
Author(s):  
Mingyue Yu
Keyword(s):  
Signal Processing ◽  
Autocorrelation Function ◽  
Time Scale ◽  
Energy Index ◽  
Signal Processing Algorithm ◽  
Intrinsic Time ◽  
Graph Signal Processing ◽  
Laplacian Energy ◽  
Rotational Components ◽  
Time Scale Decomposition

Intrinsic time-scale decomposition and graph signal processing are combined to effectively identify a rotor–stator rubbing fault. The vibration signal is decomposed into mutually independent rotational components, and then, the Laplacian energy index is obtained by the graph signal of the autocorrelation function of rotational components, and the signal is reconstructed by an autocorrelation function of each proper rotation (PR) component relative to smaller Laplacian energy index (less complexity). Finally, characteristics are extracted from rotor–stator rubbing faults in an aeroengine according to square demodulation spectrum of a reconstructed signal. To validate the effectiveness of the algorithm, a comparative analysis is made among traditional intrinsic time-scale decomposition algorithm, combination of intrinsic time-scale decomposition and autocorrelation function, and the proposed intrinsic time-scale decomposition–graph signal processing algorithm. Comparative result shows that the proposed intrinsic time-scale decomposition–graph signal processing algorithm is more precise and effective than the traditional intrinsic time-scale decomposition and intrinsic time-scale decomposition and autocorrelation function algorithms in extracting characteristic frequency and frequency multiplication of rotor–stator rubbing faults and can greatly reduce the number of noise components irrelevant to faults.

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