Search

Underwater image processing has always been a very challenging problem. Under the influence of environmental factors, underwater images are prone to some problems, such as colour cast, low visibility, and few edge details. Here, an image enhancement algorithm is proposed to improve image degradation mainly caused by the absorption of light. First, colour compensation and white balance algorithm are used to restore the natural appearance of the image. Then the improved dark channel prior (DCP) is used to improve the visibility and avoid blocking artifacts which appear in traditional DCP. Unsharp masking (USM) is applied to enhance the texture features of the DCP image. Finally, wavelet fusion is used to fuse the DCP image and DCP+USM image. The fusion algorithm not only further improves the visibility and texture features, but also reduces the noise of DCP+USM. Compared with other methods, quantitative analysis results show that the enhanced images have higher visibility, more details and edge information. [ABSTRACT FROM AUTHOR]

A thruster fault tolerant control method based on quantum‐behaved particle swarm optimisation (QPSO) is investigated for 7000 m JIAOLONG manned submarine vehicle (MSV) in this study. First, QPSO is selected for the fast convergence and global search capability. To show the efficiency of QPSO fault tolerant method, PSO is studied as a comparison research. Then, to further apply the proposed method, tracking control problem with thruster fault is taken into consideration. Finally, simulations illustrate the performance of the derived fault tolerant tracking control technique. [ABSTRACT FROM AUTHOR]

A novel thruster fault diagnosis method for open‐frame unmanned underwater vehicle is presented in the study. An credit assignment‐based fuzzy cerebellar model articulation controller (FCA‐CMAC) neural network information fusion model is used to realise the fault identification for thruster continuous and uncertain jammed fault situations. Information inputs for the fusion model are yaw rate and the control signal for the underwater vehicles; the information output of the FCA‐CMAC fusion model is the corresponding jammed fault parameter s, which indicates the degree of the fault. To illustrate the effectiveness of the proposed method, a pool experiment under uncertain continuous fault conditions is presented in this study. [ABSTRACT FROM AUTHOR]