Analyses of Trawling Track and Fishing Activity Based on the Data of Vessel Monitoring System(VMS): A Case Study of the Single Otter Trawl Vessels in the Zhoushan Fishing Ground

The original purpose of Vessel Monitoring System(VMS) is for enforcement and control of vessel sailing. With the application of VMS in fishing vessels, more and more population dynamic studies have used VMS data to improve the accuracy of fisheries stock assessment. In this paper, we simulated the trawl trajectory under different time intervals using the cubic Hermite spline(c Hs) interpolation method based on the VMS data of 8 single otter trawl vessels(totally 36000 data items) fishing in Zhoushan fishing ground from September 2012 to December 2012, and selected the appropriate time interval. We then determined vessels' activities(fishing or non-fishing) by comparing VMS speed data with the corresponding speeds from logbooks. The results showed that the error of simulated trajectory greatly increased with the increase of time intervals of VMS data when they were longer than 30 minutes. Comparing the speeds from VMS with those from the corresponding logbooks, we found that the vessels' speeds were between 2.5 kn and 5.0 kn in fishing. The c Hs interpolation method is a new choice for improving the accuracy of estimation of sailing trajectory, and the VMS can be used to determine the vessels' activities with the analysis of their trajectories and speeds. Therefore, when the fishery information is limited, VMS can be one of the important data sources for fisheries stock assessment, and more attention should be paid to its construction and application to fisheries stock assessment and management.

FVID: Fishing Vessel Type Identification Based on VMS Trajectories

Vessel Monitoring System(VMS) provides a new opportunity for quantified fishing research. Many approaches have been proposed to recognize fishing activities with VMS trajectories based on the types of fishing vessels. However, one research problem is still calling for solutions, how to identify the fishing vessel type based on only VMS trajectories. This problem is important because it requires the fishing vessel type as a preliminary to recognize fishing activities from VMS trajectories. This paper proposes fishing vessel type identification scheme(FVID) based only on VMS trajectories. FVID exploits feature engineering and machine learning schemes of XGBoost as its two key blocks and classifies fishing vessels into nine types. The dataset contains all the fishing vessel trajectories in the East China Sea in March 2017, including 10031 pre-registered fishing vessels and 1350 unregistered vessels of unknown types. In order to verify type identification accuracy, we first conduct a 4-fold cross-validation on the trajectories of registered fishing vessels. The classification accuracy is 95.42%. We then apply FVID to the unregistered fishing vessels to identify their types. After classifying the unregistered fishing vessel types, their fishing activities are further recognized based upon their types. At last, we calculate and compare the fishing density distribution in the East China Sea before and after applying the unregistered fishing vessels, confirming the importance of type identification of unregistered fishing vessels.

Elimination of the impact of vessels on ocean wave height inversion with X-band wave monitoring radar

Directional wave spectra and integrated wave parameters can be derived from X-band radar sea surface images.A vessel on the sea surface has a significant influence on wave parameter inversions that can be seen as intensive backscatter speckles in X-band wave monitoring radar sea surface images.A novel algorithm to eliminate the interference of vessels in ocean wave height inversions from X-band wave monitoring radar is proposed.This algorithm is based on the characteristics of the interference.The principal components(PCs) of a sea surface image sequence are extracted using empirical orthogonal function(EOF)analysis.The standard deviation of the PCs is then used to identify vessel interference within the image sequence.To mitigate the interference,a suppression method based on a frequency domain geometric model is applied.The algorithm framework has been applied to OSMAR-X,a wave monitoring system developed by Wuhan University,based on nautical X-band radar.Several sea surface images captured on vessels by OSMAR-X are processed using the method proposed in this paper.Inversion schemes are validated by comparisons with data from in situ wave buoys.The root-mean-square error between the significant wave heights(SWH) retrieved from original interference radar images and those measured by the buoy is reduced by 0.25 m.The determinations of surface gravity wave parameters,in particular SWH,confirm the applicability of the proposed method.

Typical Refractory Wear Phenomena in Copper Vessels and Novel Monitoring Technologies

Copper smelting furnaces are typically lined with magnesia-chromite refractories,which are exposed to multiple and complex stresses.The selection of the processing route,furnace type,and slag system is dictated by the specific ore type available;which will determine the individual refractory wear.This paper evaluates the common refractory wear mechanisms as observed in the copper Peirce-Smith converter and in the copper anode furnace.The chemical factors include corrosion caused by fayalite type slag and sulphur supply,as well as by Cu-oxide attack.Changes in the temperature during the furnace operation(thermal shock)create stresses in the brick lining which can only be absorbed to a limited extent.Mechanical factors include erosion,caused primarily by the movement of the metal bath,slag and charging material,as well as stresses in the brickwork due to punching.Finally,improper lining procedures can also affect the service life.All these wear parameters lead to severe degeneration of the brick microstructure and a decreased lining life,and in the worst case overheated furnace structures and possibly dangerous hot spots or even breakouts.Therefore,a detailed investigation and understanding of the wear mechanisms through“post-mortem studies”together with thermochemical calculations by FactSageTM software is an important prerequisite for the refractory producer.Based on these research results,combined with specific process knowledge,appropriate brick lining solutions for copper processing furnaces can be recommended.In addition to the described efforts to investigate refractory wear and optimise lining qualities,it is also essential to monitor the process and the effect on the refractories to further improve both safety and process.For this purpose,technologies using sensors and novel digital solutions can be applied.

渔船监控系统(VMS)设计

通过对渔船监控系统(VMS)的功能分析,给出了渔船监控系统的总体思路与设计方案。从船载终端、岸上监控中心、船岸通讯三个方面对VMS的软硬件开发做出了说明。选用高性价比的ARM控制器作为船载终端的主控制器,采用Inmarsat-C卫星系统,近海与内河采用公众无线通讯作为补充,能够达到监控要求,降低了通讯成本,有利于渔船监控系统的推广与应用。

Identification of navigation characteristics of single otter trawl vessel using four machine learning models

Fishing logbook records the fishing behaviors and other information of fishing vessels.However,the accuracy of the recorded information is often difficult to guarantee due to the misreport and concealment.The fishing vessel monitoring system(VMS)can monitor and record the navigation information of fishing vessels in real time,and it may be used to improve the accuracy of identifying the state of fishing vessels.If the VMS data and fishing logbook are combined to establish their relationships,then the navigation characteristics and fishing behavior of fishing vessels can be more accurately identified.Therefore,first,a method for determining the state of VMS data points using fishing log data was proposed.Secondly,the relationship between VMS data and the different states of fishing vessels was further explored.Thirdly,the state of the fishing vessel was predicted using VMS data by building machine learning models.The speed,heading,longitude,latitude,and time as features from the VMS data were extracted by matching the VMS and logbook data of three single otter trawl vessels from September 2012 to January 2013,and four machine learning models were established,i.e.,Random Forest(RF),Adaptive Boosting(AdaBoost),K-Nearest Neighbor(KNN),and Gradient Boosting Decision Tree(GBDT)to predict the behavior of fishing vessels.The prediction performances of the models were evaluated by using normalized confusion matrix and receiver operator characteristic curve.Results show that the importance rankings of spatial(longitude and latitude)and time features were higher than those of speed and heading.The prediction performances of the RF and AdaBoost models were higher than those of the KNN and GBDT models.RF model showed the highest prediction performance for fishing state.Meanwhile,AdaBoost model exhibited the highest prediction performance for non-fishing state.This study offered a technical basis for judging the navigation characteristics of fishing vessels,which improved the algorithm for judging the behavior of fishing vessels based on VMS data,enhanced the prediction accuracy,and upgraded the fishery management being more scientific and efficient.

VMS和ESD系统在自升式钻井平台上的设计和应用

船舶监控系统(VMS)和应急切断(ESD)是海上作业平台的神经中枢系统,用于监控全船设备的运行情况。一方面连续监测全船设备正常运行情况,另一方面监测到任何设备发生故障,及时进行全船报警,通过对故障点运算结果做出相应的切断处理,确保把故障范围降到最小,因而确保生产、人员和设施的安全。只有VMS和ESD正常工作才能为海上作业顺利完成保驾护航。

基于3D Slicer的多模态影像融合技术及神经电生理监测在面肌痉挛微血管减压术中的应用

目的探讨基于3D Slicer的多模态影像融合技术及神经电生理监测在面肌痉挛微血管减压术中的应用价值。方法采用回顾性分析法,选取41例行血管减压术的面肌痉挛患者为研究对象。术前通过3D Slicer软件对责任血管进行多模态影像融合分析,确定手术方案,术中进行神经电生理监测以判断减压。观察手术效果并追踪术后复发情况。结果术前建模图像发现40例存在微血管压迫,1例未见微血管压迫。未见微血管压迫的1例经术中证实为岩静脉压迫,1例小脑前下动脉经术中证实为小脑上动脉,其余责任血管判定均与术中所见一致。术前建模图像的责任血管判定正确39例,正确率为95%。41例患者经手术治疗后症状均完全缓解,完全缓解率为100%。术后住院期间1例发生面瘫,1例发生听力下降,经对症处理后很快缓解,术后随访3~36个月无复发。结论在面肌痉挛微血管减压术中联合应用多模态影像融合技术可直观了解责任血管及周围重要结构解剖情况,配合神经电生理监测可避免术中减压过度或不充分的情况,两项技术的联合应用可有效提高手术疗效。

基于北斗VMS数据和DBSCAN算法的夏季海州湾中国毛虾资源分布

2020年我国伏季休渔期间中国毛虾限额捕捞试点在黄海海州湾实施,2021年该限额捕捞项目继续实施,在此背景下探究夏季海州湾中国毛虾资源分布对其限额捕捞精细化管理至关重要。首先基于2021年海州湾中国毛虾限额捕捞期间北斗渔船监控系统(Vessel monitoring system,VMS)数据提取得到各毛虾张网渔船所有捕捞网位点及其捕捞努力量,然后运用具有噪声的密度聚类(Density-based spatial clustering of application with noise,DBSCAN)算法进一步识别含有捕捞产量的网位点,从而探究夏季海州湾中国毛虾资源分布格局。结果显示,含有产量的网位点识别率为97.18%,表明DBSCAN算法能精准识别含有产量的捕捞网位点。含有产量的网位点共有898个,空间上呈聚集性分布。依据捕捞努力量情况探究得到中国毛虾资源主要分布在120°00′E~120°15′E,34°43′N~34°48′N和119°47′E~119°53′E,34°36′N~34°43′N。本研究思路可作为其他渔业捕捞活动中运用VMS数据提取含产量捕捞网位点的科学参考。

内河船舶尾气监测的多无人机路径规划研究

由于高、低硫油价格的较大差距,低硫油高昂的使用成本使得内河船舶高硫燃油使用的违规率依然较高,给有关部门的监管与防治工作带来了不小的挑战。为降低内河船舶活动产生的大气污染物排放对航道沿线地区的空气质量的影响,如何通过非接触式取样检测船舶燃油质量成为重要问题。针对内河船舶尾气排放监测的多无人机协同路径规划问题,构建了多无人机巡检路径规划模型,并提出基于K-means++和混合模拟退火遗传算法构成的两阶段算法进行求解。结果表明,该两阶段算法能够在不同条件下合理均衡地分配巡检任务,为内河船舶尾气排放监测的无人机巡检系统的建立提供理论支撑。

路网级桥梁集群监测系统建设关键技术及实践

桥梁健康监测是防范结构运行风险、提升养护管理和应急处置水平的重要举措之一,国家和行业政策对于桥梁结构健康监测系统建设提出了明确的要求。以广东交通集团路网节点桥梁集群监测系统为例,介绍了路网级桥梁监测系统的技术路线、总体架构、关键技术和建设实践,可为地市级、路网级桥梁健康监测系统的构建提供参考。

基于声发射技术的密封压力容器泄漏检测模型研究

密封压力容器在化工、能源、石油等行业中广泛应用,承担着重要的工业生产任务。然而,由于工作环境恶劣和容器本身老化、损伤等情况,容器泄漏已成为严重的安全隐患。开发了一种基于声发射技术的密封压力容器泄漏检测模型,通过设计声发射传感器和采用特征提取方法所构建的泄漏检测模型表现出较高的准确性和可行性,对无泄漏孔径识别的正确率高达99%。

120000 kN抬浮力打捞船电气系统设计

为增强船舶的可操作性和安全性,对某120000 kN抬浮力打捞船的电气系统进行介绍,并结合打捞船的工作特点,对该船的工作模式和电气系统的主要功能进行说明。研究成果可为打捞船电气系统设计提供一定参考。

基于物联网的无人水面艇航行状态监测系统设计

针对无人水面艇(Unmanned Surface Vessel,USV)航行状态监测及试航性能评估试验中的参数获取问题,设计一套USV航行状态监测系统。以物联网(Internet of Things,IoT)3层架构为基础,设计小尺寸、低功耗的监测方案。以多源传感器和STM32微控制器作为感知层,以远距离无线电(Long Range Radio,LoRa)网关及LoRa终端作为数据远程传输途径,以传输控制协议(TCP)作为数据远程传输协议,以云平台作为系统应用层,实现数据采集、传输和应用功能。基于监测系统要求,在应用层设置阈值实现航行状态预警功能。对系统功能及性能进行测试,结果表明,系统横、纵摇精度为±0.02°RMS,风速为(0.2±0.03)m/s,风向为±2.5°,所有监测参数技术指标均符合要求,且丢包率在通信距离小于1.4 km时为1.5%,较传统方法降低约22%。该系统可为进一步完善USV航行状态监测提供技术支持。

风力助航船的风速监测技术

风力助航船作为一种新型船舶种类,可以利用海上丰富的风能资源补充自身动力系统,提高能源利用率。本文的研究重点是风力助航船的风速、风向监测技术,作为风力助航船的关键信号输入,风速和风向信息是船舶进行船帆控制的关键,因此提高海上风速、风向的监测水平十分重要。本文介绍风力助航船的风速监测原理,搭建风力助航船的风速监测平台,对平台原理和工作流程做了详细阐述。

脑氧饱和度监测目标导向治疗在急性缺血性脑卒中机械取栓术后管理中的效果

目的观察急性缺血性脑卒中机械取栓术后管理中应用脑氧饱和度监测目标导向治疗的临床效果。方法选取2020年4月—2022年10月新疆医科大学第一附属医院昌吉分院神经医学科收治的急性缺血性脑卒中机械取栓术患者60例,根据随机对照法分为两组,各30例,对照组进行常规神经重症监护治疗,包括降血压治疗、抗凝治疗,基础疾病积极治疗等,研究组在对照组的基础上予以局部脑氧饱和度(rScO2)目标导向治疗,分析两组取栓术前、取栓术后24 h、1个月、3个月、1年的脑氧监测数值、mRS评分、NIHSS评分,及病死率、脑血管再闭塞、脑出血转化发生率。结果两组取栓术后24 h、1个月、3个月、1年后的rScO2值均高于治疗前,且研究组高于对照组,而mRS评分、NIHSS评分均低于治疗前,且研究组低于对照组,差异有统计学意义(P<0.05)。研究组的病死率、脑血管再闭塞、脑出血转化总发生率20.0%低于对照组的46.7%,差异有统计学意义(χ^(2)=4.80,P<0.05)。结论急性缺血性脑卒中机械取栓术后管理中应用脑氧饱和度监测目标导向治疗,可明显改善脑神经功能缺损状态,降低病死率及并发症发生率。

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.

基于物联网的压力容器腐蚀监测研究的现状和展望

本文介绍了红外成像的技术应用于在线监测领域的技术背景以及其自身在监测方面的优点,针对重大危险压力容器的在线监测手段的研究现状进行总结分析,并提出了基于物联网和红外成像技术的在线监测系统的技术难点和主要解决问题,对红外成像技术以及监测领域的应用前景和发展方向提出了一些看法。

生产监测船数量的优化——通过不同地区各物种产量计算

对不同作业类型的监测船进行分层抽样调查,可以在兼顾监测信息精度的前提下减少大量成本。以带鱼等9种经济物种的单船全年产量及总产量作为渔业生产监测目标,并以相对估计误差(REE)作为评价指标,分析并优化渔业生产监测船数量对渔业生产监测目标估计的影响。将浙江省舟山市等4个重要渔业地市作为个体,通过计算机软件在每个个体内进行基于作业方式的分层抽样。研究表明:(1)各地区中各物种的单船产量及总产量的REE均值均随着监测船数量的增加而下降,当监测船数量增加至一定数量后下降的幅度减缓。(2)在监测船优化过程中出现目标物种产量及总产量的REE均值下降幅度较大现象。通过分析各目标物种的产量与总产量的REE均值与监测船数量的关系,将浙江省4个地区监测船数由240优化至145,此时监测船数减少了39.58%,且各目标物种的总产量REE均值上升均不超过10%。不同作业方式对REE值的影响不同,可以增加影响较大的作业方式渔船数保证监测数据准确,减少影响较小的作业方式渔船数降低监测成本。本研究的优化过程可重复性强,对改进海洋捕捞生产统计方法具有重要意义。

大型半潜船波浪弯矩间接监测方法研究

为准确得到大型半潜船波浪弯矩监测结果,本文阐述了船体波浪弯矩间接监测传统方法,并基于某大型半潜船的全船有限元仿真验证该方法的精度。在船体波浪弯矩间接监测传统方法的基础上,提出一种稳定且精度较高的船体波浪弯矩间接监测的改进方法,利用C-最优设计法和D-最优设计法优化长基线应变仪的安装位置,并通过全船有限元仿真构建改进方法的数学模型。对国内某大型半潜船进行实船监测和全船有限元仿真,验证了改进方法的精度,并将改进方法的计算结果与装载计算机的计算结果进行对比以进一步验证改进方法的适用性。