基于人为因素的船舶领域模型与通过能力研究

发布时间：2018-08-31 09:44

【摘要】：随着航运经济的发展,大量的船舶频繁活跃于港口、航道及其附近水域,使水域通航密度大为增加,从而导致船舶交通量不断增多,航道船舶交通日趋繁忙。因此,对航道的通过能力要求也日益提高。在保障航运安全的前提下,进一步挖掘航道的通过能力,将是亟待解决的难题。在影响航道通过能力的诸多因素中,船舶领域是一个非常重要的影响因素。但是,目前对船舶领域的研究主要限于船速、船长、会遇情况等容易获得的信息,对于船舶操纵性能以及人为因素等不确定因素极少考虑。本文主要基于人为因素的动态四元船舶领域模型和航道通过能力展开研究。首先,本文提出了一种基于快速准确在线自组织模糊神经网络(FAOS-PFNN)识别的船舶领域模型辨识方法,该方法能够有效建立参考输入变量与船舶领域的形状和大小等输出变量之间的非线性关系。通过FAOS-PFNN方法,采用三个分离的模糊神经网络实现了船舶领域模型的多输入输出系统的模型辨识。此外,本文结合船舶运动理论,在现有四元船舶领域模型的基础上,充分考虑了不同船舶的动态操纵性能和船舶驾驶员人为因素对船舶领域的影响,从而提出基于人为因素的动态四元船舶领域模型。该模型有效融合了船舶子系统和人因子系统,充分考虑了船舶操纵性能及船舶驾驶员的业务技能水平、生理状态、心理状态和航行环境的影响等人为因素,实现了船舶领域建模的动态智能化。同时,本文将该基于人为因素的动态四元船舶领域模型分别应用于Mariner、Esso Osaka Tanker和Container三种经典船舶类型,仿真结果验证了该船舶领域模型的合理性和有效性。其次,针对航道通过能力评估问题,本文利用所提出的动态四元船舶领域模型充分考虑了船舶性能和人为因素的影响,同时将模糊理论用于调查问卷的数据处理,以获得人因参数,从而提出了考虑人为因素的航道通过能力计算方法,利用该方法可有效挖掘通过能力,提高航运能力。最后,本文将基于人为因素的动态四元船舶领域模型及通过能力计算方法应用于尹公洲航段的内河航道及老铁山水道复杂航段的通过能力研究。实际计算了航道的通过能力,实验结果表明,利用该方法得出的通过能力较传统基于Fujii椭圆船舶领域方法有较大提升,并通过对老铁山水道的通过能力计算,给出未来5年到10年的老铁山航段的拓宽规划建议,为相关部门通航评估、水上交通规划与管理提供借鉴与参考。
[Abstract]:With the development of shipping economy, a large number of ships are frequently active in ports, waterways and their adjacent waters, which greatly increase the navigable density of the waters, resulting in the increase of ship traffic volume, and the traffic of waterway ships become more and more busy. Therefore, the passage of the channel capacity requirements are also increasing. On the premise of ensuring shipping safety, it will be an urgent problem to further excavate the passage capacity of waterway. The ship field is a very important factor in influencing the passage capacity of waterway. However, the current research in the field of ship is mainly limited to the ship speed, captain, situation and other readily available information, as well as the ship maneuvering performance and human factors and other uncertain factors are rarely considered. This paper is mainly based on the dynamic quaternion ship domain model and waterway transit capacity based on human factors. Firstly, a ship domain model identification method based on fast and accurate online self-organizing fuzzy neural network (FAOS-PFNN) is proposed. This method can effectively establish the nonlinear relationship between the reference input variables and the output variables such as the shape and size of the ship domain. By using the FAOS-PFNN method, three separate fuzzy neural networks are used to realize the model identification of multi-input and output systems in ship domain model. In addition, combined with ship motion theory, based on the existing quaternion ship field model, the dynamic maneuverability of different ships and the influence of human factors of ship pilots on the ship field are fully considered in this paper. A dynamic quaternion ship domain model based on human factors is proposed. The model effectively integrates ship subsystem and human factor system, and fully considers the factors such as ship maneuvering performance and the influence of ship driver's professional skill level, physiological state, psychological state and navigation environment, etc. The dynamic intelligence of ship modeling is realized. At the same time, the dynamic quaternion ship domain model based on human factors is applied to the three classical ship types, Mariner,Esso Osaka Tanker and Container, respectively. The simulation results show that the ship domain model is reasonable and effective. Secondly, aiming at the problem of evaluation of waterway passing capacity, the dynamic quaternion ship domain model is used to fully consider the influence of ship performance and human factors, and the fuzzy theory is applied to the data processing of the questionnaire at the same time. In order to obtain the parameters of human factors, a method for calculating the passage capacity of waterway considering human factors is put forward, which can effectively excavate the passing capacity and improve the shipping capacity. Finally, the dynamic quaternion ship domain model based on human factors and the calculation method of passing capacity are applied to the study of the passage capacity of the inland waterway and the complex section of Laotieshan waterway in Yin Gongzhou section. The actual passage capacity of the channel is calculated. The experimental results show that the passage capacity obtained by this method is much higher than that obtained by the traditional elliptical ship method based on Fujii, and the passing capacity of Laotieshan waterway is calculated. The suggestions of widening the section of Laotie Mountain in the next 5 to 10 years are given, which can be used for reference and reference for the evaluation of navigation and the planning and management of waterborne traffic in the relevant departments.
【学位授予单位】：大连海事大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：U697

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