基于自适应阈值优化算法的Golay编码RDTS研究
Research on Golay Code RDTS Based on Adaptive Threshold Optimization Algorithm
赵宇 1高妍 1张红娟 1靳宝全2
作者信息
- 1. 太原理工大学电气与动力工程学院
- 2. 太原理工大学,新型传感器与智能控制教育部重点实验室
- 折叠
摘要
Golay编码可有效提升拉曼分布式光纤测温(RDTS)系统的信号强度,但数据处理量增加了 4倍,大量数据的累加平均影响了信噪比和测量速度.文中提出了基于Golay编码的自适应阈值优化算法,旨在提升RDTS的信噪比和数据处理速率.分析了Golay编码RDTS的信号特征,设计了粒子群优化的自适应阈值算法,动态调整小波阈值,实现最优降噪.实验证明:与仅用Golay编码相比,在 45 km长的传感光纤测试中,末端信噪比从 14.5 dB提升至 21.7 dB,末端最大温度不确定度从±7℃降低至±2.5℃,同样精度下,累加平均次数从30 万次降至3 万次.
Abstract
The Golay coding effectively enhances the signal strength of the Raman distributed temperature sensing(RDTS)system,however,it results in a quadrupling of the data processing volume.Moreover,the accumulation and averaging of a substan-tial amount of data have an impact on both the signal-to-noise ratio and measurement speed.The proposed algorithm based on Go-lay coding aimed to enhance the signal-to-noise ratio and data processing rate of RDTS through adaptive threshold optimization.The signal characteristics of Golay-coded RDTS were analyzed,and an adaptive threshold algorithm optimized by particle swarm optimization was devised to dynamically adjust the wavelet threshold for achieving optimal noise reduction.The experimental re-sults demonstrate that,when compared to the utilization of solely Golay coding,in a 45 km long sensor fiber test,the signal-to-noise ratio at the end exhibited an increase from 14.5 dB to 21.7 dB,while concurrently reducing the maximum temperature un-certainty at the end from±8℃to±2.5℃.Furthermore,with equivalent precision,there was a reduction in the number of accu-mulation averages required from 300,000 to 30,000 times.
关键词
Golay编码/拉曼分布式光纤测温系统/粒子群优化/小波阈值降噪/信噪比/测量时间Key words
Golay coding/Raman distributed temperature sensing(RDTS)system/particle swarm optimization/wavelet threshold denoising/signal-to-noise ratio/measurement time引用本文复制引用
基金项目
山西省重点研发计划项目(202102130501021)
中央引导地方科技发展资金项目(YDZJSX20231B004)
山西省科技创新团队项目(201805D131003)
出版年
2024
NETL
NSTL
万方数据