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学者姓名：罗伟林
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Abstract ：
Based on deep learning, an underwater image instance segmentation method is proposed. Firstly, in view of the scarcity of underwater related data sets, the size of the data set is expanded by measures including image rotation and flipping, and image generation by a generative adversarial network (GAN). Next, the underwater image data set is finally constructed by manual labeling. Then, in order to solve the problems of color shift, blur and the poor contrast of optical images caused by the complex underwater environment and the attenuation and scattering of light, an underwater image enhancement algorithm is used to first preprocess the data set, and several algorithms are discussed, including multi-scale Retinex (MSRCR) with color recovery, integrated color model (ICM), relative global histogram stretching (RGHS) and unsupervised color correction (UCM), as well as the color shift removal proposed in this work. Specifically, the results indicate that the proposed method can largely increase the segmentation mAP (mean average precision) by 85.7% compared with without the pretreatment method. In addition, based on the characteristics of the constructed underwater dataset, the feature pyramid network (FPN) is improved to some extent, and the preprocessing method is further combined with the improved network for experiments and compared with other neural networks to verify the effectiveness of the proposed method, thus achieving the effect and purpose of improving underwater image instance segmentation and target recognition. The experimental analysis results show that the proposed model can achieve a mAP of 0.245, which is about 1.1 times higher than other target recognition models.
Keyword ：
data augmentation data augmentation deep learning deep learning image enhancement image enhancement instance segmentation instance segmentation underwater image underwater image
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| GB/T 7714 | Chen, Jianfeng , Zhu, Shidong , Luo, Weilin . Instance Segmentation of Underwater Images by Using Deep Learning [J]. | ELECTRONICS , 2024 , 13 (2) . |
| MLA | Chen, Jianfeng 等. "Instance Segmentation of Underwater Images by Using Deep Learning" . | ELECTRONICS 13 . 2 (2024) . |
| APA | Chen, Jianfeng , Zhu, Shidong , Luo, Weilin . Instance Segmentation of Underwater Images by Using Deep Learning . | ELECTRONICS , 2024 , 13 (2) . |
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Abstract ：
A model of a submerged angular cavitation nozzle is established, which consists of a contraction part, parallel middle part, and expansion part. Based on the CFD technique, a numerical simulation of the flow field of the submerged cavitation nozzle is carried out, in which a multiphase mixture model, cavitation model, and renormalization group (RNG) k-epsilon turbulence model are applied. Considering the influence of mixture density on cavitation, the effects of the inlet contraction part, parallel middle part, and outlet expansion part on the velocity and vapor volume fraction are studied. The numerical simulation results show that the mixture density is essential in the cavitation jet. When the nozzle diameter d is fixed, the designed angular cavitation nozzle with contraction angle alpha = 13.5 degrees, parallel middle part length Ld = 3d, expansion part length Le = 4d, and expansion angle beta = 60 degrees can effectively bring out cavitation. A cavitation cloud is produced near the rigid wall of the outlet expansion section and diffuses in a vortex ring shape. Optimizing the nozzle structure can improve the cavitation effect of the nozzle. The feasibility of this model is verified by relevant experimental data.
Keyword ：
angular cavitation nozzle angular cavitation nozzle cavitation jet cavitation jet numerical simulation numerical simulation submerged environment submerged environment
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| GB/T 7714 | Dong, Wenqiang , Yao, Ligang , Luo, Weilin . Numerical Simulation of Flow Field of Submerged Angular Cavitation Nozzle [J]. | APPLIED SCIENCES-BASEL , 2023 , 13 (1) . |
| MLA | Dong, Wenqiang 等. "Numerical Simulation of Flow Field of Submerged Angular Cavitation Nozzle" . | APPLIED SCIENCES-BASEL 13 . 1 (2023) . |
| APA | Dong, Wenqiang , Yao, Ligang , Luo, Weilin . Numerical Simulation of Flow Field of Submerged Angular Cavitation Nozzle . | APPLIED SCIENCES-BASEL , 2023 , 13 (1) . |
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提出了一种基于输入饱和抑制和神经网络的欠驱动AUV非奇异快速积分终端滑模控制器。用视线制导法定义期望跟踪速度，针对速度跟踪误差用非奇异快速积分终端滑模控制方法设计动力学控制器。用自适应RBF神经网络逼近时变干扰和计算难以获得的期望速度微分项，设计了抗饱和控制器解决执行器饱和问题。通过数值仿真，验证了提出的控制器对外界干扰具有鲁棒性，并能较好地处理输入饱和的影响。
Keyword ：
欠驱动自主水下机器人 欠驱动自主水下机器人 自适应RBF神经网络 自适应RBF神经网络 轨迹跟踪控制 轨迹跟踪控制 输入饱和 输入饱和 非奇异快速终端滑模控制 非奇异快速终端滑模控制
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| GB/T 7714 | 刘帅 , 罗伟林 . 基于输入饱和抑制和神经网络的欠驱动AUV轨迹跟踪滑模控制 [J]. | 中国造船 , 2023 , 64 (06) : 240-249 . |
| MLA | 刘帅 等. "基于输入饱和抑制和神经网络的欠驱动AUV轨迹跟踪滑模控制" . | 中国造船 64 . 06 (2023) : 240-249 . |
| APA | 刘帅 , 罗伟林 . 基于输入饱和抑制和神经网络的欠驱动AUV轨迹跟踪滑模控制 . | 中国造船 , 2023 , 64 (06) , 240-249 . |
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Abstract ：
利用最优拉丁超立方试验进行初始采样，建立基于自适应最小化置信下限和SMOTE算法的动态径向基函数代理模型.将自适应平衡常数引入到最小化置信下限准则中，通过多岛遗传算法对置信下限进行寻优.根据代理模型精度，在最优解处运用SMOTE算法动态地新增样本点，进而更新代理模型，直至收敛.经过数学算例测试后，将该优化策略应用于深潜器耐压舱的优化中，与其他动态代理模型相比，该策略的优化效率和精度显著提高.
Keyword ：
SMOTE算法 SMOTE算法 动态代理模型 动态代理模型 径向基函数 径向基函数 最小化置信下限 最小化置信下限 深潜器 深潜器 耐压舱 耐压舱
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| GB/T 7714 | 戚林辉 , 潘伟锋 , 罗伟林 . 采用自适应最小化置信下限和SMOTE算法的动态代理模型 [J]. | 福州大学学报(自然科学版) , 2023 , 51 (06) : 811-818 . |
| MLA | 戚林辉 等. "采用自适应最小化置信下限和SMOTE算法的动态代理模型" . | 福州大学学报(自然科学版) 51 . 06 (2023) : 811-818 . |
| APA | 戚林辉 , 潘伟锋 , 罗伟林 . 采用自适应最小化置信下限和SMOTE算法的动态代理模型 . | 福州大学学报(自然科学版) , 2023 , 51 (06) , 811-818 . |
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In this paper, a disturbance observer based nonsingular fast terminal sliding mode control (NFTSMC) scheme is proposed for the trajectory tracking control of an underactuated autonomous underwater vehicle (AUV). A nonlinear disturbance observer (DO) is designed to estimate complex external disturbances and incorporated into a NFTSMC. In constructing sliding surfaces, the parameter selection in the exponential terms in NFTSMC is expanded. Lyapunov's second method proves the uniformly ultimately bounded stability of the proposed DO based NFTSMC. Simulation is performed to demonstrate the effectiveness of the proposed controller. Compared with the existing NTSMC methods, the convergence rate is improved by the proposed NFTSMC. Moreover, the proposed controller has good robustness to smooth external disturbances. For random disturbances along with an impulse at some time, the proposed controller can also track the disturbance well and achieve good robustness.
Keyword ：
AUV AUV Disturbance observer Disturbance observer Nonsingular fast terminal sliding mode control Nonsingular fast terminal sliding mode control Trajectory tracking control Trajectory tracking control
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| GB/T 7714 | Luo, Weilin , Liu, Shuai . Disturbance observer based nonsingular fast terminal sliding mode control of underactuated AUV [J]. | OCEAN ENGINEERING , 2023 , 279 . |
| MLA | Luo, Weilin 等. "Disturbance observer based nonsingular fast terminal sliding mode control of underactuated AUV" . | OCEAN ENGINEERING 279 (2023) . |
| APA | Luo, Weilin , Liu, Shuai . Disturbance observer based nonsingular fast terminal sliding mode control of underactuated AUV . | OCEAN ENGINEERING , 2023 , 279 . |
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Abstract ：
For the trajectory tracking of underactuated autonomous underwater vehicle (AUV) subject to disturbances, a disturbance suppression and neural network (NN) compensation based control strategy is proposed. Lyapunov method is used to guide the overall design of control system. To deal with the underactuation, Light of sight (LOS) guidance is used to establish the relationship between heading angle and cross-track error. To suppress the external disturbance, L2-gain design is employed to guarantee the controller robustness. To improve the tracking accuracy, on-line neural networks with guaranteed stability are designed to identify unknown dynamics including the derivatives of virtual controls and errors induced by input saturation. Numerical simulation is performed to verify the effectiveness of the proposed control strategy. Compared with sliding mode controller (SMC) and disturbance observer approaches, the proposed controller performs better in terms of robustness and the input saturation is alleviated.
Keyword ：
Disturbances Disturbances L2-gain L2-gain Light of sight guidance Light of sight guidance Neural networks Neural networks Underactuated underwater robot Underactuated underwater robot
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| GB/T 7714 | Luo, Weilin , Cheng, Bo . Disturbance suppression and NN compensation based trajectory tracking of underactuated AUV [J]. | OCEAN ENGINEERING , 2023 , 288 . |
| MLA | Luo, Weilin 等. "Disturbance suppression and NN compensation based trajectory tracking of underactuated AUV" . | OCEAN ENGINEERING 288 (2023) . |
| APA | Luo, Weilin , Cheng, Bo . Disturbance suppression and NN compensation based trajectory tracking of underactuated AUV . | OCEAN ENGINEERING , 2023 , 288 . |
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Abstract ：
An underactuated AUV non-singular fast integrating terminal sliding mode controller with input saturation constraint and external disturbance is proposed. Firstly, the desired longitudinal velocity and expected yaw rate are obtained by the line-of-sight guidance method. Aiming at the velocity tracking errors and angular velocity tracking errors, a trajectory tracking controller is designed by using the non-singular fast integrating terminal sliding mode control method. The adaptive RBF neural network is used to approximate unknown time-varying disturbances and the time derivatives of desired velocity. A kind of anti-windup controller is designed to solve the actuator saturation problem. Numerical simulation shows that the proposed controller is robust to external disturbance and can handle the input saturation effect well. © 2023 Editorial office of Ship Building of China. All rights reserved.
Keyword ：
Adaptive control systems Adaptive control systems Autonomous underwater vehicles Autonomous underwater vehicles Controllers Controllers Radial basis function networks Radial basis function networks Sliding mode control Sliding mode control
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| GB/T 7714 | Liu, Shuai , Luo, Weilin . Anti-windup and Neural Networks-Based Sliding Mode Control of Trajectory Tracking for Underactuated AUV [J]. | Ship Building of China , 2023 , 64 (6) : 240-249 . |
| MLA | Liu, Shuai 等. "Anti-windup and Neural Networks-Based Sliding Mode Control of Trajectory Tracking for Underactuated AUV" . | Ship Building of China 64 . 6 (2023) : 240-249 . |
| APA | Liu, Shuai , Luo, Weilin . Anti-windup and Neural Networks-Based Sliding Mode Control of Trajectory Tracking for Underactuated AUV . | Ship Building of China , 2023 , 64 (6) , 240-249 . |
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Abstract ：
In this paper, a nonsingular terminal sliding mode control (NTSMC) combined with neural network and disturbance observer is proposed for the trajectory tracking of an underactuated AUV. An adaptive neural network (NN) is designed to compensate the complicated uncertain nonlinearity in the dynamics of AUV. Disturbance observer is employed to estimate the external disturbances. Lyapunov method proves the stability of the proposed controller. Simulation results show that the designed controller has good performance. © 2023 IEEE.
Keyword ：
Controllers Controllers Lyapunov methods Lyapunov methods Sliding mode control Sliding mode control
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| GB/T 7714 | Luo, Weilin , Wang, Yuanjing , Yao, Ligang . Nonsingular terminal sliding mode and NN based control of underactuated AUV [C] . 2023 : 48-53 . |
| MLA | Luo, Weilin 等. "Nonsingular terminal sliding mode and NN based control of underactuated AUV" . (2023) : 48-53 . |
| APA | Luo, Weilin , Wang, Yuanjing , Yao, Ligang . Nonsingular terminal sliding mode and NN based control of underactuated AUV . (2023) : 48-53 . |
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Convolutional neural networks (CNNs) are employed to achieve the color balance and dehazing of degraded underwater images. In the module of color balance, an underwater generative adversarial network (UGAN) is constructed. The mapping relationship between underwater images with color deviation and clean underwater images is learned. In the module of clarity improvement, an all-in-one dehazing model is proposed in which a comprehensive index is introduced and estimated by deep CNN. The third module to enhance underwater images adopts an adaptive contrast improvement method by fusing global and local histogram information. Combined with several underwater image datasets, the proposed enhancement method based on the three modules is evaluated, both by subjective visual effects and quantitative evaluation metrics. To demonstrate the advantages of the proposed method, several commonly used underwater image enhancement algorithms are compared. The comparison results indicate that the proposed method gains better enhancement effects for underwater images in different scenes than the other enhancement algorithms, since it can significantly diminish the color deviation, blur, and low contrast in degraded underwater images.
Keyword ：
color color contrast contrast convolutional neural network convolutional neural network dehazing dehazing underwater image underwater image
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| GB/T 7714 | Zhu, Shidong , Luo, Weilin , Duan, Shunqiang . Enhancement of Underwater Images by CNN-Based Color Balance and Dehazing [J]. | ELECTRONICS , 2022 , 11 (16) . |
| MLA | Zhu, Shidong 等. "Enhancement of Underwater Images by CNN-Based Color Balance and Dehazing" . | ELECTRONICS 11 . 16 (2022) . |
| APA | Zhu, Shidong , Luo, Weilin , Duan, Shunqiang . Enhancement of Underwater Images by CNN-Based Color Balance and Dehazing . | ELECTRONICS , 2022 , 11 (16) . |
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The lines optimisation of an underwater vehicle based on a dynamic surrogate model is studied. Four performances including rapidity, manoeuverability, energy consumption and structure of the underwater vehicle are considered in the optimisation framework constructed by a generalised collaborative optimisation method. Expert knowledge based analytic hierarchy process is conducted to obtain the optimisation object that involves the four performances. Numerical simulation is performed to accurately analyze the rapidity, manoeuverability and structure performances of the underwater vehicle. To reduce the calculation burden, dynamic surrogate models are proposed to replace numerical simulation in the optimisation framework. To guarantee the optimisation efficiency and accuracy, a synthetic minority oversampling technique (SMOTE) and adaptive minimise lower confidence bound (LCB) are combined in constructing the dynamic surrogate models. The proposed optimisation strategy is applied to the SUBOFF model and compared with other dynamic surrogate models. Comparison results prove the advantages of the proposed dynamic surrogate model.
Keyword ：
analytic hierarchy process analytic hierarchy process dynamic surrogate model dynamic surrogate model lower confidence bound lower confidence bound MDO MDO synthetic minority oversampling technique synthetic minority oversampling technique
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| GB/T 7714 | Pan, Weifeng , Luo, Weilin . Lines optimisation of an underwater vehicle using SMOTE and adaptive minimise LCB based dynamic surrogate models [J]. | SHIPS AND OFFSHORE STRUCTURES , 2022 , 19 (1) : 91-108 . |
| MLA | Pan, Weifeng 等. "Lines optimisation of an underwater vehicle using SMOTE and adaptive minimise LCB based dynamic surrogate models" . | SHIPS AND OFFSHORE STRUCTURES 19 . 1 (2022) : 91-108 . |
| APA | Pan, Weifeng , Luo, Weilin . Lines optimisation of an underwater vehicle using SMOTE and adaptive minimise LCB based dynamic surrogate models . | SHIPS AND OFFSHORE STRUCTURES , 2022 , 19 (1) , 91-108 . |
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