作者：宋大雷1, 孙兆阳1, 孙康康2, 张家乐1, 贺同福1
作者单位：1. 中国海洋大学工程学院，山东 青岛 266000;
2. 中石化胜利石油工程有限公司钻井工艺研究院，山东 东营 257017
关键词：多普勒海流计;频率信号估计;鲸鱼优化算法;匹配追踪
摘要：
受海洋环境复杂干扰影响，多普勒式海流计的超声波回波信号易受干扰影响，包含多种频率成分，这给海流流速信息的解算带来困难。为解决多普勒海流计回波信号频率估计精度较差的问题，提出一种基于信号匹配追踪（mp）的频率估计方法，并融合改进型鲸鱼优化算法（mwoa）提高估计过程的效率。该方法利用混沌映射提升初始种群多样性，并引入自适应权重和非线性收敛因子提高算法局部寻优能力、搜索速度和求解精度。而后，对改进算法与其他优化算法进行对比测试，结果显示所设计改进算法在收敛速度和寻优能力上具有有效性和优越性。此外，通过对多普勒回波信号进行特征重构，开展mwoa-mp算法在噪声环境下的频率估计精度性能测试。在回波信号信噪比为–10 db条件下，mwoa-mp算法相对传统方法抗噪声能力提高30%。与其他智能方法融合mp后的频率估计算法相比，mwoa-mp算法的估计误差在10 hz以内，可满足多普勒海流计频率测量精度要求。
research on frequency estimation of doppler current meter echo signal based on optimization woa-mp algorithm
song dalei1, sun zhaoyang1, sun kangkang2, zhang jiale1, he tongfu1
1. school of engineering, ocean university of china, qingdao 266000, china;
2. drilling technology research institute, sinopec shengli petroleum engineering co., ltd., dongying 257017, china
abstract: due to the complex interference of the marine environment, the ultrasonic echo signal of the doppler current meter is easily affected by interference and contains multiple frequency components, which makes it difficult to calculate the current velocity information. to tackle the issue of reducing frequency estimation accuracy of the echo signal, a frequency estimation method based on signal matching pursuit is proposed, improving the estimation process’s efficiency with a modified whale optimization algorithm. the modified method uses chaotic mapping to enhance the diversity of the initial population, and introduces adaptive weights and nonlinear convergence factors to improve the algorithm's local optimization capability, search speed, and solution accuracy. subsequently, the improved algorithm was compared with other optimization algorithms in a test, and the results showed that the designed improved algorithm was effective and superior in terms of convergence speed and optimization ability. in addition, by reconstructing the characteristics of doppler echo signals, the frequency estimation accuracy performance of the mwoa-mp algorithm in noisy environments was tested. under the condition of an echo signal-to-noise ratio of -10 db, the mwoa-mp algorithm has a 30% improvement in noise immunity compared to traditional methods. compared with other intelligent methods that fuse mp with frequency estimation algorithms, the mwoa-mp algorithm has an estimation error within 10 hz, which meets the frequency measurement accuracy requirements of doppler current meters.
keywords: doppler current meter;frequency signal estimation;whale optimization algorithm;matching pursuit
2024, 50(8):1-10 收稿日期: 2024-03-28;收到修改稿日期: 2024-05-20
基金项目: 国家自然科学基金(52301390)；山东省自然科学基金(zr2022qe072）；中央高校基本科研业务费专项资金(202213029)
作者简介: 宋大雷（1972-），男，黑龙江哈尔滨市人，教授，博士，研究方向为智能感知与控制、检测技术与自动化装置。
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