张铭钧, 吴娟, 王玉甲. 水下机器人多传感器并发故障检测方法[J]. 机器人, 2010, 32(3): 298-305.
引用本文: 张铭钧, 吴娟, 王玉甲. 水下机器人多传感器并发故障检测方法[J]. 机器人, 2010, 32(3): 298-305.
ZHANG Mingjun, WU Juan, WANG Yujia. A Method of Multi-sensor Simultaneous Faults Detection for Autonomous Underwater Vehicle[J]. ROBOT, 2010, 32(3): 298-305.
Citation: ZHANG Mingjun, WU Juan, WANG Yujia. A Method of Multi-sensor Simultaneous Faults Detection for Autonomous Underwater Vehicle[J]. ROBOT, 2010, 32(3): 298-305.

水下机器人多传感器并发故障检测方法

A Method of Multi-sensor Simultaneous Faults Detection for Autonomous Underwater Vehicle

  • 摘要: 针对水下机器人多传感器并发故障检测问题,提出了一种小波分析和神经网络相结合的故障特征提取方法,将小波多分辨率分解后的细节系数进行小波重构,对重构后的细节系数进行融合得到整体高频细节信息量作为一类故障特征值;同时,基于改进的Elman网络建立水下机器人的全阶状态观测器模型,模型输出与传感器测量值之间的差值作为另一类故障特征值.为进行水下机器人多传感器并发故障定位,提出了一种模糊加权属性信息融合方法,将两类故障特征值的重要度与可信度进行模糊合成转换,基于转换结果将各故障特征值加权融合,进行水下机器人多传感器并发故障定位.水下机器人实验样机的水池实验结果验证了本文所提方法的可行性和有效性.

     

    Abstract: To solve the problem of multi-sensor simultaneous faults detection for autonomous underwater vehicle(AUV),a fault feature extraction method is proposed by combining wavelet analysis technology with neural network technology.After the wavelet reconstruction of detail coefficients for multi-resolution wavelet decomposition,the reconstructed detail coefficients are fused to obtain the overall high-frequency detail information,which is taken as a type of fault feature.At the same time,a full-order state observer model for AUV is built based on the improved Elman network.The difference between the model output value and actual measurement value of sensors is taken as another fault feature.In order to locate the simultaneous faults of multiple sensors for AUV,a method of fuzzy weighted attribute information fusion is proposed.The importance degree and confidence degree of the two fault feature values are transformed by the method of fuzzy synthetic conversion.Based on the results of conversion,the weighted fusion of every fault feature is made,and the simultaneous faults location of multiple sensors for AUV is realized.The results of pool experiment for AUV show that the method is feasible and effective.

     

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