CASIA OpenIR  > 复杂系统认知与决策实验室  > 水下机器人
Fault Diagnosis for Robotic Fish Sensors based on Spatial Domain Image Fusion and Convolution Neural Network
Xuqing Fan1,2; Sai Deng1,2; Junfeng Fan1,2; Chao Zhou1,2; Zhengxing Wu1,2; Yaming Ou1,2; Bin Zhang1,2
2023
Conference Namethe 42nd Chinese Control Conference
Conference Date2023-7
Conference PlaceTianjin, China
Abstract

The accurate detection of faults in robotic fish allows for improving the safety and reliability of its operations. This paper proposes a depth sensor fault diagnosis method based on Gramian Angular Field Fusion and Convolutional Neural Network (GAFF-CNN). Firstly, the depth sensor signals are augmented by a sliding window with overlapping data. Secondly, the one-dimensional time series sensor signals are converted into two-dimensional images by using Gramian Angular Field (GAF). To improve fault diagnosis accuracy and accelerate the training speed, using a weighted fusion method to fuse Gramian Angular Summation Field (GASF) and Gramian Angular Difference Field (GADF). After that, the model of CNN is established to train and test fused images for fault diagnosis. The result shows that the fault diagnosis accuracy is the highest at 97.22% when using a weighted coefficient of 0.3, and when the weighted coefficient is 0.4, the training speed is the fastest.

KeywordFault Diagnosis GAF Fusion CNN Robotic Fish
Language英语
Sub direction classification智能机器人
planning direction of the national heavy laboratory水下仿生机器人
Paper associated data
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57232
Collection复杂系统认知与决策实验室_水下机器人
Corresponding AuthorSai Deng
Affiliation1.The Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Xuqing Fan,Sai Deng,Junfeng Fan,et al. Fault Diagnosis for Robotic Fish Sensors based on Spatial Domain Image Fusion and Convolution Neural Network[C],2023.
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