电能计量器具自动化检定流水线MSA分析研究

    MSA Analysis and Research on Automatic Verification Assembly Lines for Electric Energy Measuring Instruments

    • 摘要: 电能计量器具自动化检定流水线长期在线高负荷运行,会发生性能退化甚至出现故障,导致电能测量误差试验结果出现偏差。为准确掌握电能计量器具自动化检定流水线测量系统波动规律,确定来自测量系统的总变化量以及各变量的差异,提高测量系统的准确性与可靠性,设计了流水线测量系统分析方案。在分析流水线结构特点和工作原理的基础上,提出一种全新的实验设计方案,并制定了测量系统分析计划。以低压电流互感器自动化检定流水线为例,对测量系统重复性和再现性、偏倚和线性、稳定性三个指标进行了分析。分析结果表明,测量系统的变异占合计变异的1.67%,变异指标%GR & R为18.21%,偏倚占比5.4%,线性占比8.7%,可区分的类别数7,测量系统具备所需的测量能力,处于条件接受状态。进一步分析变异的来源,再现性是主要的变异因素,测量系统在不同工位上的一致性存在显著差异。最后,结合测量系统分析结果、生产现场管理和运维经验,对流水线测量系统的改进提出建议。

       

      Abstract: The automatic verification assembly lines for electric energy measuring instruments can experience performance degradation or even malfunctions during long-term online high-load operation, leading to deviations in the test results of electric energy measurement errors. In order to accurately grasp the fluctuation patterns of the automatic verification assembly line measurement system for electric energy measuring instruments, determine the total variation from the measurement system and the differences in each variable, and improve the accuracy and reliability of the measurement system, an analysis plan for the assembly line measurement system was designed. Based on the analysis of the structural characteristics and working principles of the assembly line, a new experimental scheme is proposed, and a measurement system analysis plan is formulated. Taking the automated calibration assembly line of low-voltage current transformers as an example, the repeatability and reproducibility, bias and linearity, and stability of the measurement system were analyzed. The analysis results show that the variation of the measurement system accounts for 1.67% of the total variation, the variation index GR&R is 18.21%, the bias ratio is 5.4%, the linearity ratio is 8.7%, and there are 7 distinguishable categories. The measurement system has the required measurement ability and is in a conditionally acceptable state. Further analysis of the sources of variation reveals that reproducibility is the main factor of variation, and there are significant differences in the consistency of measurement systems at different workstations. Finally, based on the analysis results of the measurement system, production site management, and operation and maintenance experience, suggestions for improving the measurement system are proposed.

       

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