基于改进小波阈值算法的遥测数据去噪研究
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西安工业大学

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TP399

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工程实验室项目基金资助


Denoising of Telemetry Data Based on Improved Wavelet Threshold Algorithm
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Xi’an Technological University

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Engineering Laboratory Project Fund

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    摘要:

    为改善目前遥测数据检测系统硬件体积较大、数据测量误差大、去噪算法适用性弱等缺陷,利用改进小波阈值的遥测参数去噪算法实现了遥测监测系统软件化设计,通过对遥测空速、发动机转速等参数进行小波去噪效果实验分析,结果表明,该算法对于空速数据去噪效果显著提升,将测量误差平方和降低为2199.6,去噪拟合曲线与原始数据曲线相似度高达0.9889,且对其它遥测数据噪声处理具有较好的通用性。

    Abstract:

    In order to improve the shortcomings of large hardware volume, large data measurement error, weak applicability of de-noising algorithm in the current telemetry data detection system. The paper realize the software design of telemetry monitoring system based on the improved wavelet threshold de-noising algorithm for telemetry parameters. In order to confirm the algorithm’s effectiveness, there are many de-noising experiments for telemetry data of airspeed and engine speed based on improved wavelet threshold algorithm. It shows that the algorithm’s de-noising effect for telemetry airspeed data is significantly improved, the square sum of measurement errors is reduced to 2199.6 and the similarity between the de-noising fitting curve and the original data curve is as high as 0.9889, and it has good generality in data de-noise for other telemetry parameters.

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引用本文

苏小会,王钦钦,王贵鸿. 基于改进小波阈值算法的遥测数据去噪研究[J]. 科学技术与工程, 2019, 19(22): 254-258.
Suxiaohui, Wangqinqin, Wangguihong. Denoising of Telemetry Data Based on Improved Wavelet Threshold Algorithm[J]. Science Technology and Engineering,2019,19(22):254-258.

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  • 收稿日期:2019-01-23
  • 最后修改日期:2019-04-10
  • 录用日期:2019-04-17
  • 在线发布日期: 2019-08-28
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