一种遥测缓变参数自动判读的新方法

针对遥测参数中缓变参数的自动判读问题，提出一种基于历史数据统计特性的遥测缓变参数自动判读新方法。首先，设计了一种以参数目标数据时标为基准的时间间隔递推算法和线性插值方法，使历史数据与目标数据的时标得到有效统一。其次，基于方向和距离函数构造了双因子等价权函数，并利用抗差最小二乘估计算法得到了参数的估值和标准差。最后，根据参数的估值和标准差对目标数据进行统计分析，依据目标数据的概率分布判断参数是否存在异常，进而实现参数的自动判读。仿真校验结果表明，该方法能有效辨识缓变参数中的异常参数，且具有较强的抑制随机噪声和抗差自适应能力。与传统以人工为主的判读方式相比，该方法能有效提高遥测参数判读的效率和准确性。

A Novel Method of Automatic Interpretation for Slow Varying Telemetry Parameters

Based on the statistical characteristics of the historical data, a novel method of automatic interpretation for the slow-varying telemetry parameters is proposed. Firstly, a time interval recursion algorithm based on the time scale of the target parameters measurement data and a linear interpolation method are designed to make the time scale of the historical data and the target data be unified effectively. Secondly, a two-factor equivalent weight function is constructed from the direction and distance function, and the estimated value and standard deviation of the parameters are obtained by using a robust least squares estimation algorithm. Finally, according to the estimated value and standard deviation of the parameters, the statistical analysis of the target data is carried out, where the parameters are determined to be abnormal or not according to the analysis result, so as to realize the automatic interpretation function of the parameters. The test results show that the proposed method can effectively identify the anomalous parameters in the slow-varying telemetry parameters and has a strong ability to suppress the random noise and the robustness. Compared with the traditional method of the artificial interpretation, this method can effectively improve the efficiency and accuracy of the telemetry parameter interpretation.