测量不确定度是表征测量结果量值可信程度的参数,正确评定测量不确定度对于精密零件生产的质量保证具有重要意义。以动压马达半球零件球径测量为例,进行了典型精密零件坐标测量不确定度的评定。针对示值误差过量估计导致不确定度评定结...测量不确定度是表征测量结果量值可信程度的参数,正确评定测量不确定度对于精密零件生产的质量保证具有重要意义。以动压马达半球零件球径测量为例,进行了典型精密零件坐标测量不确定度的评定。针对示值误差过量估计导致不确定度评定结果偏大乃至失准的问题,研究了采用标准工件进行测量标定获得实际示值误差的不确定度优化评定方法。实验结果表明,采用优化评定后,不确定度合理地减小了54.5%。研究了采用蒙特卡洛法(Monte Carlo Method,MCM)对常规的测量不确定度表示指南(Guide to the Expression of Uncertainty in Measurement,GUM)法评定结果进行验证的方法,通过软件编程实现了MCM仿真验证。MCM验证可以发现被测量偏离正态分布时GUM法的假设偏差,典型零件MCM验证的结果表明,GUM法评定的不确定度比实际情况扩大了10.2%。示值误差的过量估计会使被测量偏离正态分布,对此MCM验证是敏感的,故MCM验证可以作为示值误差过量估计的检验手段。展开更多
A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems a...A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems.展开更多
文摘测量不确定度是表征测量结果量值可信程度的参数,正确评定测量不确定度对于精密零件生产的质量保证具有重要意义。以动压马达半球零件球径测量为例,进行了典型精密零件坐标测量不确定度的评定。针对示值误差过量估计导致不确定度评定结果偏大乃至失准的问题,研究了采用标准工件进行测量标定获得实际示值误差的不确定度优化评定方法。实验结果表明,采用优化评定后,不确定度合理地减小了54.5%。研究了采用蒙特卡洛法(Monte Carlo Method,MCM)对常规的测量不确定度表示指南(Guide to the Expression of Uncertainty in Measurement,GUM)法评定结果进行验证的方法,通过软件编程实现了MCM仿真验证。MCM验证可以发现被测量偏离正态分布时GUM法的假设偏差,典型零件MCM验证的结果表明,GUM法评定的不确定度比实际情况扩大了10.2%。示值误差的过量估计会使被测量偏离正态分布,对此MCM验证是敏感的,故MCM验证可以作为示值误差过量估计的检验手段。
文摘A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems.
