山东科学

• 海洋科技与装备 •    下一篇

基于BP神经网络模型的ADCP倾斜条件下的修正算法研究

郑威, 杨英,惠力, 鲁成杰,赵彬,杨立   

  1. 齐鲁工业大学(山东省科学院),山东省科学院海洋仪器仪表研究所,山东省海洋环境监测技术重点实验室,国家海洋监测设备工程技术研究中心,山东 青岛 266001
  • 收稿日期:2017-08-30 出版日期:2018-06-20 发布日期:2018-06-20
  • 作者简介:郑威(1983—),男,博士,副研究员, 研究方向为ADCP波流测量。E-mail:honestzheng123@163.com
  • 基金资助:

    山东省自然科学基金(ZR2015YL022);国家重点研发计划(2016YFC1400403);海洋公益性行业科研专项(201505007-3);山东省重点研发计划(2016GGH4501);山东省科学院青年基金(2014QN037)

The analysis between wave estimation error and influencing factors based on BP model when ADCP tilts

ZHENG Wei,YANG Ying,HUI Li, LU Cheng-jie,ZHAO Bin,YANG Li   

  1. Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Techno1ogy,National Engineering and Technological Research Center of Marine Monitoring Equipment, Institute of Oceanographic Instrumentation,Qilu University of Technology (Shandong Academy of Sciences),Qingdao 266001, China
  • Received:2017-08-30 Online:2018-06-20 Published:2018-06-20

摘要:

针对现有ADCP倾斜条件下修正算法不准确的问题,将BP神经网络模型应用于分析倾斜条件下波浪估计误差与影响因素ADCP俯仰角、横滚角以及安放深度之间的非线性关系。结果表明,BP神经网络模型的预测值和实测值吻合较好,能够提升波浪估计的准确性。

关键词: 声学多普勒流速剖面仪, 倾斜修正, 海洋表面波浪测量, 波浪估计, BP神经网络模型

Abstract:

Considering that the existing tilt correction is not accurate when ADCP is tilted, the BP neural network model is used to analyze the nonlinear relationship between wave estimation error and various influencing factors such as ADCP pitching angle, roll angle and setting depth. The result shows that real wave directional spectrum and wave directional spectrum that BP neural network predicts are in good agreement. BP neural network model can improve wave estimation accuracy.

Key words: ADCP, tilt correction, wave estimation, BP neural network model, ocean surface wave measurement

中图分类号: 

  • TB556