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Review of marine environment monitoring methods based on GNSS technology
QI Suiping, XU Xiaofei, LI Yunzhou, WANG Juncheng, DU Jun
Shandong Science    2024, 37 (2): 1-11.   DOI: 10.3976/j.issn.1002-4026.20240023
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Real-time, accurate and reliable monitoring of marine environmental information plays a crucial role in marine disaster warning and prediction, disaster prevention and reduction, marine resource development, and ensuring marine safety. In recent years, with the continuous development and upgrading of global navigation satellite systems (GNSS), the detection of atmospheric and marine environmental information based on GNSS navigation signals has become a new method and a hot research topic in the marine environmental monitoring technology. This method has been widely applied to domains such as marine meteorological monitoring and numerical forecasting. This article systematically reviews the current research status of the GNSS technology in marine environmental monitoring, including effective wave height, wind speed, rainfall intensity, water vapor and tide level monitoring. Furthermore, this paper systematically summarizes new technologies and methods and looks forward to provide reference for the future research in related fields.

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Survey of underwater biological object detection methods based on deep learning
YU Yu, GUO Baoqi, CHU Shibo, LI Heng, YANG Pengru
Shandong Science    2023, 36 (6): 1-7.   DOI: 10.3976/j.issn.1002-4026.2023.06.001
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Underwater biological object detection is crucial for aquaculture, endangered species protection,and ecological environment monitoring. This study comprehensively analyzes the applications of various deep learning methods in underwater biological object detection. The commonly used underwater biological object detection datasets are introduced. The state-of-the-art underwater biological object detection methods are classified, analyzed, and summarized by two stages and one stage. The actual applications of various detection methods are thoroughly described, and the advantages and disadvantages of their optimization strategies are analyzed and summarized. Future works in the field of underwater biological object detection based on deep learning are presented. This study provides a reference basis for researchers in the field of underwater biological object detection.

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Streamline optimization analysis of side-scan sonar on small autonomous underwater vehicle
LIU Jin, TAN Hua, SU Liang, QIU Guoji, LIU Rui, LUO Chongxin, WANG Yu, LIU Hao
Shandong Science    2023, 36 (6): 8-14.   DOI: 10.3976/j.issn.1002-4026.2023.06.002
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Water dynamics analysis was conducted on a compact and portable autonomous underwater vehicle(AUV) with side-scan sonar and amodified AUV with streamlined side-scan sonar. The analysis focused on examining the drag forces experienced by both AUVs at different speeds. The results demonstrated that the streamlined side-scan sonar effectively reduced pressure and viscous drag forces, resulting in an overall drag reduction of 15.4% at a normal speed of 3 knots, with a 9% reduction in viscous drag and an 18% reduction in pressure drag.At a high speed of 6 knots, the overall drag was reduced by 10.1%, with a 4.2% reduction in viscous drag and a 12% reduction in pressure drag. These findings demonstrate that optimizing the streamlined design of the AUV with side-scan sonar can effectively enhance the dynamic performance of the AUV, reduce its drag force, and improve its efficiency and performance.

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Wave sensor fault diagnosis method based on t-SNE reduction and KNN algorithm
TAI Peng, SONG Miaomiao, WANG Bo, CHEN Shizhe, FU Xiao, HU Wei, GAO Saiyu, CHENG Kaiyu, ZHENG Shanshan, JIAO Zixuan, WANG Longfei
Shandong Science    2023, 36 (4): 1-9.   DOI: 10.3976/j.issn.1002-4026.2023.04.001
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This study proposes an efficient wave sensor fault diagnosis method based on wavelet packet decomposition, dimension reduction, and k-nearest neighbor algorithm(KNN) classification network to address the difficulty of wave sensor fault diagnosis, unidentifiable fault types, and time-consuming diagnosis. First, the standard deviation of the original signal is normalized. The normalized data is then subjected to a three-layer wavelet packet decomposition. The extracted feature vectors represent normalized data from the eight bands on layer 3. The second step involves using the t-distributed stochastic neighbor embedding (t-SNE) algorithm to reduce the dimension of the feature data. Finally, the dimension-reduced feature data is input into the KNN classification network for fault classification and detection. Experimental results show that the proposed method can improve the accuracy and diagnosis speed of the wave sensor fault diagnosis, with a diagnosis accuracy of up to 93.55% for normal and six faulty conditions.

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Balance stance analysis of a single-point-mooring submerged buoy system for performing electromagnetic measurements
WANG Xin, WU Pingwei, HUANG Wei, DAI Jinhui
Shandong Science    2023, 36 (1): 1-9.   DOI: 10.3976/j.issn.1002-4026.2023.01.001
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Based on the actual marine hydrological data obtained from apredetermined sea area, a submerged buoy system is established herein for performing electromagnetic measurements using the lumped mass method. Further, the balance stance of the submerged buoy system and the tension distribution of the cable are simulated and analyzed. The results show that the design of the system has maintained a good linear correlation between the measurement nodes; the linear correlation coefficient is maintained above 0.995.The counterweight buffer cable can achieve good antiwave buffer effect. The analysis of field trial data at the sea shows that the submerged buoy system with a static buoyancy of 600 N, a buffer cable length of 150 m, and a counterweight of 40 m and 1 N/m can form a U shaped buffer belt with a buffer depth of 21 m when the surface current velocity is 0.5 m/s, which is consistent with the results of simulation analysis.

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Design and development of seabed cold spring gas leakage simulation observation system
LI Chenhao, HUA Zhili, HE Rui, LIAN Junshuai, HAO Zongrui
Shandong Science    2023, 36 (1): 10-17.   DOI: 10.3976/j.issn.1002-4026.2023.01.002
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As the acoustic detection of seabed cold springs requires accurate information of bubble characteristics, this paper develops a simulated observation system for the gas leakage of seabed cold springs with high control accuracy and full functions based on the bubble distribution characteristics of real seabed cold springs.The gas flow is precisely controlled viathe fuzzy PID control algorithm. Compared with the conventional control method, the flow error rate can be reduced by up to 1.5% and the cold spring bubbles in the real environment can be simulated accurately and controllably. The dual cameras are driven viaan Ethernet synchronous trigger, and thesynchronized shooting reduces the shooting synchronization error range by 1.1 ms.The system accurately realizes the orthogonal synchronous observation of the bubble shape in the initial overflow stage and provides data support for the detection of seabed cold springs.

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Experimental study on performance of breakwater integrated with oscillating water column wave-energy converter
JI Junna
Shandong Science    2023, 36 (1): 18-22.   DOI: 10.3976/j.issn.1002-4026.2023.01.003
Abstract192)   HTML8)    PDF(pc) (2087KB)(232)       Save

To investigate the operating performance of breakwater integrated with an oscillating water column wave-energy converter, a model experimental study was performed in the wave flume. An air turbine and an electric generator were used for converting pneumatic power to electricity. Performances of the device under different incident wave conditions were examined. The results show that the wave period has a considerable effect on the performance of breakwater integrated with an oscillating water column and the device shows better performance under long wave period conditions. The device represents low energy conversion efficiency when the incident wave height is small.

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