Evaluation of touch trigger probe measurement uncertainty using FEA

Evaluation of measurement uncertainty is an essential subject in dimensional measurement. It has also become a dominant issue in coordinate measuring machine (CMM) even though its machine performance has been well accepted by many users. CMM probes, especially touch trigger probes which are commonly used, have been acknowledged as a key error source, largely due to pre-travel variations. The probe errors result in large measurement uncertainty in CMM measurement. Various methods have been introduced to estimate measurement uncertainty, but they tend to be time consuming and necessarily require a large amount of experimental data for analyzing the uncertainty. This paper presents the method of evaluation of CMM probe uncertainty using FEA modeling. It is started with the investigation of the behavior of probe by recording stylus displacement with vary triggering force. Then, those displacement results will be analyzed with sensitivity analysis technique to estimate the uncertainty of recorded results

Finite elements modeling and simulation of probe system

Coordinate measuring machines (CMMs) have been widely used for enhancing product quality, productivity and reliability. This powerful instrument assists the user by providing them with highly accurate and reliable measurement results. Many studies involving the application of various different methods have been carried out to enhance the performance of CMM. This paper discusses the application of finite element analysis (FEA) to study the probe system of CMM. Finite element modeling is utilized to investigate the displacement of the probe stylus, pre-travel variation (lobing effects) and the associated measurement uncertainty. Different characteristics of styli have been considered and the corresponding effects on the probe operation are reported

Strain and temperature sensors using multimode optical fiber Bragg gratings and correlation signal processing

Multimode fiber optic Bragg grating sensors for strain and temperature measurements using correlation signal processing methods have been developed. Two multimode Bragg grating sensors were fabricated in 62/125 m graded-index silica multimode fiber; the first sensor was produced by the holographic method and the second sensor by the phase mask technique. The sensors have signal reflectivity of approximately 35% at peak wavelengths of 835 nm and 859 nm, respectively. Strain testing of both sensors has been done from 0 to 1000 με and the temperature testing from 40 to 80°C. Strain and temperature sensitivity values are 0.55 pm/με and 6 pm/°C, respectively. The sensors are being applied in a power-by-light hydraulic valve monitoring system

Experimental validation of FEA modelling of touch trigger probes

The authors have previously proposed the use of finite element method (FEM) for the modeling of coordinate measuring machine probes. Whilst the modeling results have been published previously, this paper presents the detailed experimental validation to compare the FEM and experimental results. The comparison shows that the agreement is generally good with probing contacts at lower latitudes near the equator of the reference sphere. The differences between the modeling and experimental results become large at higher latitudes. This is believed to be mainly caused by the sliding effects which occur during probing contact in the experiments

Symbolic computation for evaluation of measurement uncertainty

In recent years, with the rapid development of symbolic computation, the integration of symbolic and numeric methods is increasingly applied in various applications. This paper proposed the use of symbolic computation for the evaluation of measurement uncertainty. The general method and procedure are discussed, and its great potential and powerful features for measurement uncertainty evaluation has been demonstrated through examples

Theoretical and experimental studies of a novel cone-jet sensor

Modeling of a novel cone-jet sensor using two-dimensional (2-D) finite element analysis was investigated for dimensional measurement. Theoretical and experimental studies demonstrated that a cone-jet sensor supplied with air can be used to accurately measure displacement, and its work range of 1.5 to 4.2 mm is some ten times greater than a simple back-pressure sensor. It is anticipated that this type of sensor will find wide applications in manufacturing industry due to its wider working range, high precision, and other features

Effects of the size of the measured surface on the performance of an air cone-jet sensor for in-process inspection

This paper investigates the effects of the size of the measured surface on the performance of an air-jet sensor using 2-D finite element method. The modeling and experimental results have shown that in the measuring range of 1.5 mm to 4.5 mm with a nozzle of diameter of 6 mm, the output of the cone-jet is not significantly affected by the size change from 10 mm to 14 mm. It also proved that this particular sensor is not suitable for measuring an object with a size less than 9 mm

Uncertainty Principle Enhanced Pairing Correlations in Projected Fermi Systems Near Half Filling

We point out the curious phenomenon of order by projection in a class of lattice Fermi systems near half filling. Enhanced pairing correlations of extended s-wave Cooper pairs result from the process of projecting out s-wave Cooper pairs, with negligible effect on the ground state energy. The Hubbard model is a particularly nice example of the above phenomenon, which is revealed with the use of rigorous inequalities including the Uncertainty Principle Inequality. In addition, we present numerical evidence that at half filling, a related but simplified model shows ODLRO of extended s-wave Cooper pairs.Comment: RevTex 11 pages + 1 ps figure. Date 19 September 1996, Ver.

Enrichment analysis of genetic association in genes and pathways by aggregating signals from both rare and common variants

New high-throughput sequencing technologies have brought forth opportunities for unbiased analysis of thousands of rare genomic variants in genome-wide association studies of complex diseases. Because it is hard to detect single rare variants with appreciable effect sizes at the population level, existing methods mostly aggregate effects of multiple markers by collapsing the rare variants in genes (or genomic regions). We hypothesize that a higher level of aggregation can further improve association signal strength. Using the Genetic Analysis Workshop 17 simulated data, we test a two-step strategy that first applies a collapsing method in a gene-level analysis and then aggregates the gene-level test results by performing an enrichment analysis in gene sets. We find that the gene set approach which combines signals across multiple genes outperforms testing individual genes separately and that the power of the gene set enrichment test is further improved by proper adjustment of statistics to account for gene-wise differences