Development of high-precision micro-roundness measuring machine using a high-sensitivity and compact multi-beam angle sensor

2015 ◽  
Vol 42 ◽  
pp. 276-282 ◽  
Author(s):  
Meiyun Chen ◽  
Satoru Takahashi ◽  
Kiyoshi Takamasu
2011 ◽  
Vol 32 (5) ◽  
pp. 055007 ◽  
Author(s):  
Lichong Sun ◽  
Wenliang Ren ◽  
Na Yan ◽  
Hao Min

2012 ◽  
Vol 184-185 ◽  
pp. 789-792
Author(s):  
Bing Li ◽  
Yu Lan Wei ◽  
Meng Dan Jin ◽  
Ying Ying Fan

Put forward a method that use scatter points which got in different places to measure the involution cylindrical gears, give a mathematical model that use the discrete points to sure the total deviation of gear tooth profile. The experience results show that this way is of high precision in measurement points, measurement an error data processing less intervention, etc.


2019 ◽  
Vol 9 (13) ◽  
pp. 2701 ◽  
Author(s):  
Li ◽  
Yang ◽  
Gao ◽  
Su ◽  
Wei ◽  
...  

Error compensation technology offers a significant means for improving the geometric accuracy of CNC machine tools (MTs) as well as extending their service life. Measurement and identification are important prerequisites for error compensation. In this study, a measurement system, mainly composed of a self-developed micro-angle sensor and an L-shape standard piece, is proposed. Meanwhile, a stepwise identification method, based on an integrated error model, is established. In one measurement, four degrees-of-freedom errors, including two-dimensional displacement and two-dimensional angle of a linear guideway, can be obtained. Furthermore, in accordance with the stepwise identification method, the L-shape standard piece is placed in three different planes, so that the measurement and identification of all 21 geometric errors can be implemented. An experiment is carried out on a coordinate measuring machine (CMM) to verify the system. The residual error of the angle error, translation error and squareness error are 1.5″, 2 μm and 3.37″, respectively, and these are compared to the values detected by a Renishaw laser interferometer.


2020 ◽  
Author(s):  
Randall Parrish ◽  
Robert Haley

Abstract Background: Of the hypothesized causes of Gulf War Illness (GWI), a chronic multi-symptom illness afflicting approximately 25 percent of >700,000 military personnel deployed to the 1991 Gulf War, depleted uranium (DU) and exposure to nerve agents have stimulated the most intense international concern. Past depleted uranium research on Gulf War veterans has measured urinary uranium concentration [U] and uranium isotopic ratios with low precision mass spectrometry primarily in GW veterans with retained shrapnel but has not used high precision mass spectrometry to test for an association of GWI with inhaled DU and we set out to test this potential association. Methods: We applied a standard biokinetic model to predict the urinary total [U] and uranium isotopic ratios in urine 18 years after inhalation exposure. We applied high sensitivity mass spectrometry methods capable of detecting the predicted levels in 154 individuals of a population-representative sample of U.S. veterans in whom Gulf War illness had been determined by standard case definitions and DU inhalation exposures obtained by medical history. Results: Methods used in past studies are capable of detecting only the high urinary uranium excretion levels from retained DU shrapnel but not lower levels predicted from DU inhalation. Using high precision mass spectrometry, we found no difference in the 238U/235U ratio in veterans meeting the standard case definitions of GWI versus control veterans, and no differences by levels of DU inhalation exposure. Our bivariate analysis of 236U/238U by 235U/238U showed only the signature of natural dietary uranium, excluding DU inhalation exposures above 0.4 mg, far below the disease-causing threshold. Conclusion: The findings by high precision mass spectrometry support the conclusion that even the highest levels of DU inhalation played no role in the development of Gulf War illness. Other factors including exposure to aerosolized organophosphate compounds (pesticides and sarin nerve agent) remain as the most likely cause(s) of GWI.


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