This work presents the equations for the components of the volumetric error of a Coordinate Measuring Machine (CMM) considering thermal influences. These equations were applied to a moving bridge CMM and combines homogeneous transformations, regression techniques and least squares algorithm. The magnitudes of both the geometric errors and its thermally induced variations were collected by means of a Laser interferometric system, a mechanical square and an electronic level. Simultaneously, temperature values were monitored using T-type Copper-Constantan thermocouples. From the proposed model, components of the volumetric errors were synthesized. Results are discussed and compared to the ones obtained from measurement sets of a ring gauge. It was verified that the model presented an excellent ability to predict volumetric error of the CMM. Errors of about 10µm in magnitude were reduced by at least 75%, while for errors greater than 10µm, the efficiency of the model was 90%
Measurements of thermal diffusivity and thermal effusivity are critical to developing a complete description of thermal transport within thermal barrier coating systems. Thermal diffusivity and thermal effusivity of coatings can be measured nondestructively using the phase of photothermal emission analysis experimental measurement. However, the complexity of the regression analysis required in this measurement makes determining the uncertainties associated with the best-fit values nontrivial. The aim of this paper is to develop a framework to carry out this uncertainty analysis and to minimize the uncertainties in fitted parameters. It is shown that the physical model can be used as an effective tool for identifying and removing data points afflicted by excessive bias error, which can occur in the limits of the observational data. It is revealed that this reduction in the dataset offers a tradeoff between increasing agreement between the data and the model while reducing the uniqueness of fitted parameter values. The current analysis demonstrates that this situation can be treated as an optimization problem, whereby uncertainties in fitted parameters can be minimized.
Specimens subject to periodic heating must be probed for a calibrated temperature response if standard measurements of thermal diffusivity are to be extended to determine thermal conductivity. A variation on two-color pyrometry is developed to measure both the offset and harmonic amplitudes of temperature fluctuations caused by periodic heating. The requisite pyrometric formulae are derived for low amplitude heating using an expansion of the nonlinear thermal emission. Well-defined uncertainties in the temperature values are determined from experimental uncertainties in radiometric measurements. The accuracy demonstrated in this work is better than 2% for the temperature offset and 3%-8% for the fluctuating temperature amplitude.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.