The Research Of Measurement Data Error Process And Uncertainty Evaluation Of Special Objects

Measurement error and uncertainty play an important role in the production practice and scientific research, smaller uncertainty values generally are of higher value and of higher cost. Form error is an important index to assess the quality of the products in machinery industry. Accurate measurement and evaluation of parts form error, not only can be used as the basis for the acceptance of parts, and to provide reliable data to improve the precision parts processing and assembly accuracy. Chang’E-1 lunar orbiter is the first detection of the Earth-Moon space about 400,000 km away from the earth, Chang’E-1 lunar orbiter working in the harsh space environment. some uncertain factors, such as thermal environment, electromagnetic environment and the space bombardment of high energy particles and so on, will not only affect the lunar satellite control accuracy, but also bring apparent measurement error to various effective load (the moon observation instrument) carried on the lunar orbiter, and reduce the measurement of the reliability and the measurement precision. Therefore it is necessary to research error and uncertainty of the moon exploration data. The research object of this paper is the error process and uncertainty analysis of two special objects, form error parameter measurement data and Chang’E-1 laser altimeter detection data.Differential evolution (DE) Optimization algorithm is presented to evaluate the circularity error and flatness error. Ten typical examples in the literatures have been calculated by differential evolution algorithm, and compared with the other algorithms. It is verified that differential evolution is efficient and reliable in evaluating the circularity and flatness error.Quasi particle swarm optimization (QPSO) is proposed to evaluate the freeform curve profile error and freeform surface profile errors. Freeform curve is expressed by non-uniform rational B-spline (NURBS) and QPSO algorithm is proposed to reconstruct freeform curve. Then, the shortest distance from point to reconstructed curve is calculated based on parameter values uniformly generated by quasi random sequence. The detailed steps are established for reconstructing it and computing the shortest distance from point to curve based on QPSO and quasi random sequence. Finally, by calculating the curve profile errors of simulation example and practical measured parts the results verify that the proposed method has the advantages of simple algorithm, rapid computation speed and high accuracy. It is easy to be applied in engineering metrology. In order to evaluate freeform surface profile errors which are inspected by Computer Aided Design (CAD) model-directed measured, firstly, quasi particle swarm optimization (QPSO) is proposed to realize the precise localization between measured surface and designed surface in order to solve the un-repetitive problem between design coordinate system and measurement coordinate system when using coordinate measurement machine (CMM) to inspect parts. Then, according to the features of freeform surface form, the peak-valley error and root mean square error are proposed to evaluate freeform surface form together. Finally, by calculating the surface profile errors of simulation example and many practical measured parts, the results verify that the proposed method has high evaluation precision of freeform surface profile errors and it is suitable for the form error evaluation of high precise freeform surface parts.Measurement uncertainty (MU) of circularity error is researched by three aspects. Firstly, many experiments of sampling strategy are made to achieve the appropriate the number of sampling points. Then, the minimum zone resolution is obtained by DE algorithm. Finally, MU of circularity error is calculated with Monte Carlo method and Guide to the Expression of Uncertainty in Measurement, the results from two methods are in agreement. Adaptive Monte Carlo method (AMCM) is presented based on the QPSO to evaluate the MU of complicated conicity error. The mathematical model of the minimum zone conicity error (MZCE) is established and QPSO method is proposed to search the conicity error. Because the mathematical model of conicity error is strong nonlinear and it is difficult to use Guide to the Expression of Uncertainty in Measurement (GUM) method to evaluate MU. AMCM is proposed to estimate MU in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. Experiments are conducted and the results confirm that the proposed method not only can search the MZCE rapidly and precisely, but also can evaluate MU and give control variables with an expected numerical tolerance.As Chang’E-1 lunar orbiter ran in a near-polar and near-circular orbit, the probability of laser altimeter detecting the polar area is high and the detection data are more than the other area of moon. So the lunar elevation detection data from polar area are selected for studing the detecting error of lunar elevation and the analysis results are showed in this paper. As one of the lunar terrain, lunar maria is large flat plain on the surface of the moon. The detection data of lunar maria area are selected to evaluate the uncertainty of elevation detection data. Because the flat terrain in maria region can reduce the elevation detecting error from the impact of topographical variation. The error process and uncertainty evaluation results the lunar detection data are given in this paper. The evaluation results can give the reference for making the high precision moon digital elevation graph and the accuracy of design of payload on lunar orbiter.