基于现代通信技术的电参数远程校准方法研究
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国网江苏省电力有限公司营销服务中心

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TB971

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国网江苏省电力有限公司科技项目


Research on remote calibration method of electrical parameters based on modern communication technology
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    摘要:

    在现有计量仪器远程校准与溯源实现方式的基础上,提出了一种基于现代通信技术的电参数远程校准方法。该校准方法结合以非实物标准为传递对象的远程校准方法和直流电压源校准的标准源法,将标准器安放在实验室而非传递至现场,解决了传统电参数校准方法的校准周期长和附加误差难以测量等问题。基于卫星共视法对时间频率进行校准的原理,将标准电压源和被校准电参数转换为可靠的数字量进行电参数的远程传递,建立起电参数的传递和溯源链;设计了AD转换模块参考电压远程校准模块,建立了AD转换模块远程自校准模型,研究了基于卫星共视的电参数远程校准算法与A/D模数转换远程自校准算法,对高精度电参数采集模块的转换结果进行修正。经数据分析,其准确度为0.1级。

    Abstract:

    On the basis of existing ways of realizing remote calibration and traceability of measuring instruments, a remote calibration method of electrical parameters based on modern communication technology is proposed. The calibration method combines the remote calibration method with non-physical standards as the transmission object and the standard source method of DC voltage source calibration, which places the standards in the laboratory rather than transmitting them to the field, solving the problems of long calibration period and difficult to measure additional errors of the traditional electrical parameter calibration method. Based on the principle of time-frequency calibration by the satellite co-vision method, the standard voltage source and the calibrated electrical parameters are converted into reliable digital quantities for the remote transmission of the electrical parameters, and the transmission and traceability chain of the electrical parameters is established; the reference voltage remote calibration module of the AD conversion module is designed, and a model of the remote self-calibration of the AD conversion module is established, and the remote calibration algorithm of the electrical parameters based on the satellite co-vision is investigated, and the remote self-calibration algorithm of the A/D conversion is also investigated. The remote self-calibration algorithm of analog-to-digital conversion is studied, and the conversion results of high-precision electric parameter acquisition module are corrected. After data analysis, its accuracy is 0.1 level.

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  • 收稿日期:2024-05-28
  • 最后修改日期:2024-07-16
  • 录用日期:2024-07-17
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