华中科技大学学报（自然科学版）Issue(6)：22-26,54,6.DOI:10.13245/j.hust.150605
随机干扰下 AUV 推进器故障特征提取与融合
Feature extraction and fusion for thruster faults of AUV with random disturbance
摘要
Abstract
The correctness of fault diagnosis results for thrusters of AUV (autonomous underwater vehicle) was frequently influenced by random disturbance ,which was caused by the internal noise of underwater sensors .To decrease the influence ,two feature extraction methods that extracting fault feature from the wavelet approximate component of longitudinal velocity and from the changing rate of control voltage ,and a feature fusion method with normalization were proposed .After the wavelet re‐construction of scale coefficients for wavelet decomposition of longitudinal velocity ,the wavelet ap‐proximate component was obtained .After the derivation of control voltage ,the changing rate was ac‐quired .Two kinds of fault feature were extracted from the wavelet approximate component and the changing rate based on modified Bayes′classification algorithm separately .Following the feature fu‐sion of the two kinds of fault feature based on evidence theory ,the fusion result were normalized .The effectiveness of the proposed methods was verified by the experiments of AUV ,which were carried out in the pool .关键词
水下机器人/随机干扰/推进器故障检测/故障特征提取/特征融合Key words
autonomous underwater vehicle (AUV )/random disturbance/thruster fault detection/fault feature extraction/feature fusion分类
信息技术与安全科学引用本文复制引用
张铭钧,殷宝吉,刘维新,王玉甲..随机干扰下 AUV 推进器故障特征提取与融合[J].华中科技大学学报（自然科学版）,2015,(6):22-26,54,6.基金项目
国家自然科学基金资助项目（51279040）；工业和信息化部基础科研资助项目（B2420133003）． （）
