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Multi-UUV/USV Adaptive Cooperative Search Using Online State Information 1

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Li, Wenjie Gao, Jian Chen, Yimin Cui, Pei Lv, Junjun Pan, Guang School of Marine Science and Technology Northwestern Polytechnical University Xi’an710072 China Science and Technology on Underwater Test and Control Laboratory Dalian116013 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Unmanned Surface Vessel (USV) and Unmanned underwater Vehicle (UUV) detect the same task plane while located in different planes, and have to avoid obstacles autonomously in cooperative search in unknown environments. This paper proposes an adaptive cooperative search method for a USV/UUV heterogeneous cross-domain swarm based on online state information. Considering the different planes of USV/UUV detection, we establish a USV/UUV detection model with a forward-looking sonar according to the cross-sectional view. In order to guarantee the safety of USV/UUV, an obstacle avoidance algorithm based on predictive guidance is designed. Finally, the task environment is rasterized to establish the state information structure of grids and USV/UUV. On this basis, USV/UUV adaptively plans the search path according to its own motion state. The state information of each grid is updated online until USV/UUV swarm completes the search task. Simulation results show that USV/UUV can accomplish cooperative search safely in an unknown environment. Compared with a UUV homogeneous swarm, the USV/UUV swarm shortens the search time and improves the cooperative search efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Unmanned surface vehicles

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Feasibility of low-intensity ultrasound treatment with hydroxylamine to accelerate the initiation of partial nitrification and allow operation under intermittent aeration

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Journal of Environmental sciences 2024年第5期139卷 446-459页

作者： Jianxiong Jian Xiaojian Liao Zhihua Mo Shoupeng Li Lei Li Shaojin Chen Zhenhua Huang Junhao Chen Wencan Dai Shuiyu Sun Guangzhou Key Laboratory Environmental Catalysis and Pollution Control Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Guangdong Province Solid Waste Recycling and Heavy Metal Pollution Control Engineering Technology Research Center Guangdong Polytechnic of Environmental Protection EngineeringFoshan 528216China Analysis and Test Center Guangdong University of TechnologyGuangzhou 510006China

Partial nitrification is a key aspect of efficient nitrogen removal,although practically it suf-fers from long start-up cycles and unstable long-term operational *** address these drawbacks,this study investigated the effect of low intensity ultrasound treatment combined with hydroxylamine(NH2OH)on the performance of partial *** showthat compared with the control group,low-intensity ultrasound treatment(0.10W/mL,15 min)combined with NH2OH(5 mg/L)reduced the time required for partial nitrification initiation by 6 days,increasing the nitrite accumulation rate(NAR)and ammonia nitro-gen removal rate(NRR)by 20.4% and 6.7%,respectively,achieving 96.48% ***-tic analysis showed that NH2OH enhanced ammonia oxidation,inhibited nitrite-oxidizing bacteria(NOB)activity and shortened the time required for partial nitrification ***,ultrasonication combined with NH2OH dosing stimulated EPS(extracellular polymeric substances)secretion,increased carbonyl,hydroxyl and amine functional group abundances and enhanced mass *** addition,16S rRNA gene sequencing results showed that ultrasonication-sensitive Nitrospira disappeared from the ultrasound+NH_(2)OH system,while Nitrosomonas gradually became the dominant ***,the results of this study provide valuable insight into the enhancement of partial nitrification start-up during the process of wastewater nitrogen removal.

关键词： Partial nitrification Low-intensity ultrasound Hydroxylamine Ammonia oxidizing bacteria Nitrite oxidizing bacteria

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The polarization filtering line spectrum extraction algorithm of underwater target signal

The polarization filtering line spectrum extraction algorith...

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2022 International Conference on Information Processing in Ocean science and technology, ICIPOST 2022

作者： Han, Xue Wang, Yang College of Intelligent System Science and Engineering Shenyang University Liaoning Shenyang110044 China Science and Technology on Underwater Test and Control Laboratory DaLian China

In order to increase the performance of underwater target line spectrum extraction, an adaptive polarization filtering line spectrum extraction method is researched in the paper. By using of the polarization characteristics of underwater target signals, the polarization characteristics of underwater target line spectrum signal is analyzed via singular value decomposition (SVD) method in frequency domain. Firstly, the line spectrum signal is presented by the eigenimage corresponding to the maximum singular value to increase the signal-to-noise ratio (SNR) of the signal. Then the polarization parameters are extracted according to the polarization characteristics of the line spectrum signals. And the line spectrum signal is filtered by constructing the polarization filtering function. The simulation results show that the output SNR of the proposed method are larger than that of conventional FFT analysis method when the SNR of the signal is larger than -9dB, and the detection probability of the proposed method is 100% when the SNR of the signal is -1 dB, while the detection probability of the conventional FFT analysis method is 27.73%. It shows that the proposed method provides a new approach for underwater line spectrum signal extraction techniques. © Published under licence by IOP Publishing Ltd.

关键词： Signal to noise ratio

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Vertical Array Cable Jitter Noise Suppression Method using Frequency Vertical Wavenumber Spectral Filtering*

Vertical Array Cable Jitter Noise Suppression Method using F...

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IEEE/OES China Ocean Acoustics (COA)

作者： Peng Li Shuwei Che Yu Liu Xingchen Zhao Science and Technology on Underwater Test and Control Laboratory Dalian Scientific Test and Control Technology Institute Dalian China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

The proposed method suppresses low-frequency cable vibration noise in a vertical array acoustic observation system using the frequency vertical wavenumber spectrum. Initially, the frequency wavenumber spectrum is extracted from the data collected from the vertical array via vertical wavenumber-depth transformation. A frequency wavenumber domain filter is designed according to the sound wave speed in the cable, and cable interference is filtered out. The signal is restored via vertical wavenumber-depth inverse transformation. The simulation results show that under the simulation conditions described herein, low-frequency line spectra such as 30 and 60 Hz can achieve a signal-to-noise ratio improvement of $>1.2\text{dB}$ .

关键词： Vibrations Filtering Frequency-domain analysis Simulation Noise reduction Jitter Acoustics Arrays Signal to noise ratio testing

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Unsteady Narrowband Spectrum Enhancement Method of Ship Noise Using PSO and Stochastic Resonance Processing

Unsteady Narrowband Spectrum Enhancement Method of Ship Nois...

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IEEE/OES China Ocean Acoustics (COA)

作者： Wang Yang LIU Yan-sen WU Feng-ming Science and Technology on Underwater Test and Control Laboratory Dalian Scientific Test and Control Technology Institute Dalian China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

To enhance the unsteady narrowband spectrum of ship noise, an unsteady narrowband stochastic resonance processing method based on particle swarm optimization (PSO) was proposed. The method adopts a bistable stochastic resonance model and takes the mean signal-to-noise ratio in the narrowband bandwidth as the fitness function; it can perform adaptive optimal selection of system parameters matching the narrowband spectrum and background noise and can enhance the narrowband spectrum signal. According to the flow of the algorithm, the simulated unsteady narrowband spectrum and the measured ship noise data are processed and analyzed. The results show that this method can easily adapt to the characteristics of the narrowband ship spectrum and enhances a weak narrowband spectrum; it has broad research prospects and good application value.

关键词： Time-frequency analysis Stochastic resonance Oceans Sea measurements Object detection Marine vehicles Particle swarm optimization Time-varying systems Narrowband Signal to noise ratio

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Simulation of Vertical Highlight Distribution of underwater Objects Based on Virtual Extended Arrays *

Simulation of Vertical Highlight Distribution of Underwater ...

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IEEE/OES China Ocean Acoustics (COA)

作者： Yang Zhang Guijuan Li Rui Wang Wenhao Liu Jingying Wang Bing Jia Science and Technology on Underwater Test and Control Laboratory Dalian Scientific Test and Control Technology Institute Dalian China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

To study the vertical distribution characteristics of object echo in water, a simulation method based on a large-aperture virtual extended array is proposed. The proposed method adopts the near-field plate element method to predict the object echo waveform at the array end and takes advantage of the high resolution of the large aperture virtual extended array beam. Two-dimensional acoustic images of the object, such as the horizontal-vertical direction, horizontal distance, and range vertical, are obtained. The results show that the object echo highlights of the single-layer shell are obtained three parts of the boat: the hull, shell, and stern, and the vertical distribution characteristics reflect the vertical position relationship of the three parts. The formation mechanism of the echo highlights includes the smooth surface echo of a large area in the hull, hull, and other parts, and the angular wave at the joint of the hull and hull and the hull and stern.

关键词： Water Sea surface Image resolution Surface acoustic waves Boats Apertures Acoustic arrays Acoustics Acoustic beams

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Short‐term and long‐term memory self‐attention network for segmentation of tumours in 3D medical images

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1524-1537页

作者： Mingwei Wen Quan Zhou Bo Tao Pavel Shcherbakov Yang Xu Xuming Zhang Department of Biomedical Engineering College of Life Science and TechnologyHuazhong University of Science and TechnologyWuhanChina State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Institute for Control Science Russian Academy of SciencesMoscowRussia Hubei Medical Devices Quality Supervision and Test Institute WuhanChina

Tumour segmentation in medical images(especially 3D tumour segmentation)is highly challenging due to the possible similarity between tumours and adjacent tissues,occurrence of multiple tumours and variable tumour shapes and *** popular deep learning‐based segmentation algorithms generally rely on the convolutional neural network(CNN)and *** former cannot extract the global image features effectively while the latter lacks the inductive bias and involves the complicated computation for 3D volume *** existing hybrid CNN‐Transformer network can only provide the limited performance improvement or even poorer segmentation performance than the pure *** address these issues,a short‐term and long‐term memory self‐attention network is ***,a distinctive self‐attention block uses the Transformer to explore the correlation among the region features at different levels extracted by the ***,the memory structure filters and combines the above information to exclude the similar regions and detect the multiple ***,the multi‐layer reconstruction blocks will predict the tumour *** results demonstrate that our method outperforms other methods in terms of subjective visual and quantitative *** with the most competitive method,the proposed method provides Dice(82.4%vs.76.6%)and Hausdorff distance 95%(HD95)(10.66 vs.11.54 mm)on the KiTS19 as well as Dice(80.2%vs.78.4%)and HD95(9.632 vs.12.17 mm)on the LiTS.

关键词： 3D medical images convolutional neural network self‐attention network transformer tumor segmentation

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Modeling of Ship Target Radiated Noise Spectrum Characteristics

Modeling of Ship Target Radiated Noise Spectrum Characterist...

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Computer technology and Information science (ISCTIS), International Symposium on

作者： Xuemeng Yang Science and Technology on Underwater Test and Control Laboratory Dalian China

This paper presents a comprehensive methodology for modeling ship target radiated noise spectrum characteristics, addressing the challenges of limited data availability. The proposed methodology includes data collection, preprocessing, feature extraction, and selection, along with the development of a noise spectrum model using advanced statistical techniques. Experimental evaluations using real-world ship noise data confirm the effectiveness of the proposed methodology in accurately capturing ship target radiated noise spectra. The findings have implications for underwater acoustic analysis and naval applications.

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Multivariate Multiscale Sample Entropy for Multi-Channel underwater Acoustic Signal Analysis 7

Multivariate Multiscale Sample Entropy for Multi-Channel Und...

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7th IEEE Information technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Zhou, Jing Li, Yaan Wang, Mingzhou Shi, Lei School of Marine Science and Technology Northwestern Polytechnical University Xi'an China Xi'an Precision Machinery Research Institute National Key Laboratory of Underwater Information and Control Xi'an China

ISBN: (纸本)9798350370782

Multi-channel time series collected by arrays are prevalent in underwater acoustic signal processing and are crucial for uncovering the intrinsic characteristics of the observed system. This paper introduces the multivariate multiscale sample entropy (MMSE) to assess the complexity information in multi-channel underwater acoustic signals. Simulation analysis is employed to validate the effectiveness of the MMSE algorithm in extracting both within-channel and cross-channel information from multi-channel signals. Various types of simulated ship-radiated noise are generated to illustrate the MMSE algorithm's capability to differentiate between signals. Additionally, we employ MMSE to analyze various real-world signals, including ship-radiated noise, ambient noise, and interface reverberation. The MMSE results demonstrate its proficiency in differentiating various underwater acoustic signals compared to traditional frequency domain methods. © 2024 IEEE.

关键词： Frequency domain analysis

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Overview of underwater target feature extraction methods 6

Overview of underwater target feature extraction methods

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6th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2022

作者： Li, Xiaoyuan Hou, Hongying Wang, Kewen Meng, Chunxia Dalian Scientific Test and Control Technology Institute Binhai street 16 DaLian116013 China Science and Technology on Underwater Test and Control Laboratory Binhai street 16 DaLian116013 China

ISBN: (纸本)9781510656635

Target of underwater environments classification and distinguish using active sonar is very complex signal processing work, therefore, many research institutions in the world study the classification and recognition methods of underwater small targets using active *** recognition methods of static underwater small targets can be roughly divided into imaging method and echo method. The imaging method is based on high-frequency narrow beam to obtain the acoustic image of the target and its shadow while suppressing the reverberation interference, so as to realize the classification and recognition of the target. Imaging sonar has high working frequency, limited sonar range, and can not effectively identify false targets with similar geometry. Bright spot model and resonance scattering theory are important theoretical basis of target echo method. The two theories agree that the echo is the result of the interaction between the incident signal and the underwater target, which must contain the characteristics of the target, so it is feasible to detect the target by analyzing the characteristics of the echo signal. However, in the actual underwater target detection process, due to the weak target echo signal, complex seabed environment and target geometry, uncertain sound propagation conditions and so on, the target recognition based on echo method still has great challenges1,11,13-40 © 2022 SPIE.

关键词： Feature extraction

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