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Line optimization of multi-beam sonar sounding technology in ocean surveying and mapping 海洋测绘中多波束声纳探测技术的线路优化
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2813/1/012004
Mengjia Li, Zien Zhou, Shaowei Lyu, Mengxuan Liang, Zixuan Gao and Chengming Xia
In this paper, the problem of line optimization existing in the practical application of multi-beam sonar-sounding technology is studied. Firstly, by analyzing the working principle of multi-beam sonar, the multi-beam coverage width model and the overlap rate model between adjacent strips are established considering the slope of seabed terrain. Then, a more general parameterized multi-beam coverage width formula with an adjustable azimuth angle of the line is derived under three-dimensional space coordinates. Then, the minimum total line length is defined as the objective function, and the constraint conditions of overlap rate and complete coverage are added to establish the mathematical model of line planning. Then, an iterative algorithm is designed to quickly determine the line spacing, and an improved particle swarm optimization algorithm, including a trigonometric function change learning factor, is used to search for the optimal line layout. Finally, the simulation results show that the optimized scheme can reduce the total line length by 2% compared with the unoptimized line layout, which verifies the effectiveness of the established model and algorithm. This study provides a theoretical basis for navigation planning and shipboard system optimization of multi-beam sonar survey. Subsequent work taking into account the influence of complex sea conditions, efforts were made to expand the model’s applicability.
本文研究了多波束声纳探测技术在实际应用中存在的线路优化问题。首先,通过分析多波束声纳的工作原理,建立了考虑海底地形坡度的多波束覆盖宽度模型和相邻条带间的重叠率模型。然后,在三维空间坐标下,推导出了一个更通用的参数化多波束覆盖宽度公式,该公式具有可调的测线方位角。然后,将最小线路总长定义为目标函数,并加入重叠率和完全覆盖的约束条件,建立了线路规划的数学模型。然后,设计了一种迭代算法来快速确定线路间距,并使用改进的粒子群优化算法(包括三角函数变化学习因子)来搜索最优线路布局。最后,仿真结果表明,与未优化的线路布局相比,优化方案可将线路总长度减少 2%,这验证了所建立的模型和算法的有效性。这项研究为多波束声纳测量的导航规划和船载系统优化提供了理论依据。后续工作考虑到复杂海况的影响,努力扩大模型的适用范围。
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引用次数: 0
Black-box modeling of PMSG-based wind energy conversion systems based on neural ODEs 基于神经 ODE 的 PMSG 风能转换系统黑箱建模
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2814/1/012005
Zhanhua Huang, Ran Hu, Nan Ma, Bing Li, Chen Chen, Qiangqiang Guo, Wuping Cheng and Chunpeng Pan
Integrating renewable energy sources like wind power into the power grid enhances the dynamic interactions among renewable energy-producing equipment, leading to new technological issues for the power grid. Modeling and simulation are essential to ensure the stability of the emerging power grid, but they require precise dynamic component modeling, which is often unavailable due to technical confidentiality and other factors. Conventional hardware-in-the-loop (HIL) simulation can accurately simulate the dynamics of a single renewable energy device, but not the complex dynamics of multiple devices. This research introduces a method that combines classical mechanism modeling and differential neural network modeling to create accurate wind turbine models utilizing equipment measurement data or HIL simulation data. A realistic wind turbine electromagnetic transient simulation model of a specific type is developed and validated by connecting it to the IEEE-39 node system, confirming the model’s accuracy.
将风能等可再生能源整合到电网中会增强可再生能源生产设备之间的动态互动,从而为电网带来新的技术问题。建模和仿真对于确保新兴电网的稳定性至关重要,但它们需要精确的动态组件建模,而由于技术保密性和其他因素,通常无法实现这种建模。传统的硬件在环(HIL)仿真可以精确模拟单个可再生能源设备的动态,但无法模拟多个设备的复杂动态。本研究介绍了一种结合经典机构建模和微分神经网络建模的方法,利用设备测量数据或 HIL 仿真数据创建精确的风力涡轮机模型。通过将特定类型的风力涡轮机电磁瞬态仿真模型连接到 IEEE-39 节点系统,开发并验证了该模型的准确性。
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引用次数: 0
A real-time estimation method of carbon emission for cement corporations based on load identification 基于负荷识别的水泥企业碳排放实时估算方法
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2814/1/012008
Juntao Pan, Zhou Yang, Xingqiu Wei and Zhenglei Zhou
Accurate carbon emission estimation is the basis for assessing the carbon emissions of various regions and industries and formulating reasonable and feasible emission reduction programs. This paper presents a generalized real-time corporate carbon footprint measurement method. The total carbon emissions are categorized into direct emissions and indirect emissions. For the former, a load identification method based on CNN-BLSTM is proposed to monitor the state of the devices, and the carbon emissions are directly calculated in combination with the carbon emission intensity of the devices; for the latter, accurate estimation of carbon emissions is achieved through the application of marginal carbon emission factor. By utilizing this analytical model, the estimated carbon emissions are more accurate than those of other methods, which can better grasp the carbon emissions of enterprises and promote energy saving and emission reduction.
准确的碳排放估算是评估各地区、各行业碳排放量,制定合理可行的减排方案的基础。本文提出了一种通用的企业碳足迹实时测量方法。碳排放总量分为直接排放和间接排放。对于前者,提出了一种基于 CNN-BLSTM 的负载识别方法来监测设备状态,并结合设备的碳排放强度直接计算碳排放量;对于后者,则通过应用边际碳排放因子来实现碳排放量的精确估算。利用该分析模型,估算出的碳排放量比其他方法更加准确,可以更好地掌握企业的碳排放量,促进节能减排。
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引用次数: 0
Photovoltaic MPPT based on improved Cuckoo algorithm 基于改进型 Cuckoo 算法的光伏 MPPT
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2814/1/012001
Xiaodong Liu and Hairong Zou
Photovoltaic power generation is susceptible to external factors such as light, resulting in a reduction in the actual efficiency of photovoltaic power generation. However, the traditional maximum power point tracking technology has the characteristics of slow convergence speed and poor accuracy. In order to improve the above problems, a new photovoltaic maximum power control algorithm with an improved cuckoo algorithm is proposed. By adjusting the iterative step size in the cuckoo algorithm and changing the probability of finding the bird nest, the iterative convergence speed is accelerated, and the global optimization ability is increased. Finally, the algorithm is applied to the maximum power tracking, and the simulation model is built on the Matlab/Simulink platform. After comparing the standard Cuckoo algorithm with the improved Cuckoo algorithm under static and dynamic conditions, the simulation results show that the improved Cuckoo algorithm has more advantages in maximum power tracking speed and accuracy.
光伏发电容易受到光照等外部因素的影响,导致光伏发电的实际效率降低。然而,传统的最大功率点跟踪技术具有收敛速度慢、精度差等特点。为了改善上述问题,本文提出了一种采用改进型杜鹃算法的新型光伏最大功率控制算法。通过调整布谷鸟算法的迭代步长和改变寻找鸟巢的概率,加快了迭代收敛速度,提高了全局优化能力。最后,将该算法应用于最大功率跟踪,并在 Matlab/Simulink 平台上建立了仿真模型。在静态和动态条件下比较了标准布谷鸟算法和改进布谷鸟算法后,仿真结果表明改进布谷鸟算法在最大功率跟踪速度和精度方面更具优势。
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引用次数: 0
Thermal management of a battery pack using fin-embedded phase change material 利用鳍片嵌入式相变材料对电池组进行热管理
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2805/1/012005
S Acharya and C Anand
The present study focuses on the numerical investigation of heat transfer from a battery cell surrounded by phase change material (PCM) with longitudinal fins embedded in it. Three-dimensional transient heat conduction equation is solved numerically in the battery domain, whereas the solidification-melting model adopting Enthalpy-Porosity approach is solved in PCM to obtain liquid fraction and temperature distribution. PCM with 16 fins was found to be quite effective in reducing the battery surface temperature compared to 12, 8, and 4 fins. However, the effectiveness of 16 fins is observed up to 1500 sec till the PCM completely melts into liquid. A maximum reduction of 25 K has been achieved at 1500 sec by adding 16 fins to PCM. Beyond 1500 sec, the temperature rises sharply, exceeding all other cases at 2200 sec. Fins play an essential role in augmenting heat transfer, which benefits in achieving the phase change process in less time to restrict the temperature rise; however, at the same time, when the phase change process completes, fins become detrimental to the system since the temperature of the battery starts rising sharply.
本研究的重点是对被相变材料(PCM)包围并嵌入纵向鳍片的电池单元的传热进行数值研究。在电池域中对三维瞬态热传导方程进行了数值求解,而在 PCM 中则采用焓-孔方法对凝固-熔化模型进行了求解,以获得液体分数和温度分布。与 12 片、8 片和 4 片鳍片相比,16 片鳍片的 PCM 在降低电池表面温度方面相当有效。不过,16 片鳍片的效果只能持续到 1500 秒,直到 PCM 完全融化成液体。在 PCM 中添加 16 片鳍片后,1500 秒时的最大降温幅度为 25 K。超过 1500 秒后,温度急剧上升,在 2200 秒时超过了所有其他情况。翅片在增强热传导方面起着至关重要的作用,有利于在更短的时间内完成相变过程,从而限制温度的上升;但与此同时,当相变过程完成时,翅片会对系统产生不利影响,因为电池的温度会开始急剧上升。
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引用次数: 0
Robot material processing and hardware-in-the-loop-based real-time simulations 机器人材料处理和基于硬件在环的实时模拟
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2805/1/012002
Osama A Q Ziada, Yanxi Zhang, Hatem Algabroun, Olufunminiyi Abiri, Olayinka Olaogun, Gurtej Singh, Ali Hajian Foroushany and Jetro Kenneth Pocorni
This paper presents a cyber-physical production system that consists of a simulation, an industrial robot cell, and sensors. The industrial robot hardware, used for welding and additive manufacturing applications, is connected or “in-the-loop” with a real-time target machine on which simulations are running. These simulations are updated in real-time by the data provided by process sensors. Particular focus is given to wire-arc additive manufacturing (WAAM). Still, the cyber-physical system allows use in other robot-based material processes, such as sheet forming, (dis)assembly and material handling applications. It is also argued that the proposed cyber-physical system can be used so that it competes against the concept of using machine learning to optimize manufacturing processes. The proposed cyber-physical system enables the transition from traditional robot automation to autonomous robot systems.
本文介绍了一个由模拟、工业机器人单元和传感器组成的网络物理生产系统。工业机器人硬件用于焊接和增材制造应用,与正在运行模拟的实时目标机器相连或 "在环 "内。这些模拟根据过程传感器提供的数据进行实时更新。该系统尤其侧重于线弧增材制造(WAAM)。不过,该网络物理系统还可用于其他基于机器人的材料工艺,如板材成型、(拆卸)装配和材料处理应用。还有人认为,建议的网络物理系统可以与使用机器学习优化制造流程的概念相抗衡。拟议的网络物理系统可实现从传统机器人自动化向自主机器人系统的过渡。
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引用次数: 0
Analytical Study of Barrier-free Door Closer Guide Rail System based on Slider-Crank Mechanism 基于滑块-曲柄机构的无障碍闭门器导轨系统分析研究
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2805/1/012004
Man-Yee Leong and Alfred C.H. Tan
One of the most important elements of barrier-free design is the door entrance system, particularly door closers. Door closers ensure that doors are easy to operate and do not pose any physical barriers to users. However, existing electro-mechanical door closers are relatively heavy, costly and have reliability issues in cases of power outages. Purely mechanical door closers, such as cam action with guide rail and rack-and-pinion with scissors arm, offer a more affordable option due to simpler design and fewer components used. Static forces and torque with geometrical constraints of the door closer guide rail system are considered in deriving the mathematical expressions of a door closer guide rail system using similar approaches as slider-crank mechanism. The formulation considers the effects of pinion torque of a door closer, installation inputs as design parameters, door angle and efficiency. The mathematical model and experimental results show close agreement. The contribution of this paper is that it demonstrates the underlying physics of the door closer guide rail system, thereby aiding in understanding the door behaviour. Additionally, the model can predict the behaviour of the system under different operating conditions, which can be useful for design and optimization purposes. More importantly, this model can be utilised to identify the most effective strategies in reducing opening forces on doors thereby providing design insights to barrier-free application in the future.
无障碍设计最重要的元素之一是门禁系统,尤其是闭门器。闭门器可确保门易于操作,不会对用户造成任何物理障碍。然而,现有的电动机械闭门器相对较重、成本较高,而且在停电时存在可靠性问题。纯机械式闭门器,如带导轨的凸轮式闭门器和带剪刀臂的齿轮齿条式闭门器,由于设计简单、使用的部件较少,因此是一种更经济实惠的选择。在推导闭门器导轨系统的数学表达式时,考虑了闭门器导轨系统的静态力和扭矩以及几何约束,采用的方法与滑块曲柄机构类似。该公式考虑了闭门器小齿轮扭矩、作为设计参数的安装输入、门角度和效率的影响。数学模型和实验结果表明两者非常接近。本文的贡献在于展示了闭门器导轨系统的基本物理原理,从而有助于理解门的行为。此外,该模型还能预测系统在不同运行条件下的行为,有助于设计和优化。更重要的是,该模型可用于确定减少门开启力的最有效策略,从而为未来的无障碍应用提供设计见解。
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引用次数: 0
Adaptive spatial attention dual-branch fishing boat detection network 自适应空间注意力双分支渔船探测网络
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2813/1/012001
Jiaxuan Yang and Xiang Liu
Aiming at the harbor environment, the target detection accuracy of fishing vessels is low, and it is prone to the problems of fishing vessel misdetection and omission detection. In this paper, we propose a fishing vessel target detection algorithm called ASDNet based on YOLOX. Firstly, an Adaptive Spatial Attention Module (ASAM) was designed and used to improve the detection of fishing vessel targets; secondly, a two-branch backbone network was designed for multidimensional fishing vessel feature extraction. Meanwhile, a bilateral enhanced fusion strategy (BFFS) is designed to fuse the branch features to improve the characterization ability of the network; finally, the loss function is improved by introducing the Focal-CIOU loss bounding box loss function to reduce the effects of the detection position deviation of the fishing vessel target and the overlap of the vessel hull to improve the detection performance. The above methods are validated using the homemade fishing vessel dataset, and the results show that the precision rate (P) and recall rate (R) are greatly improved. The average precision rate (mAP@50-95) value reaches 80.25%, which is 2.39% higher than that of the 77.86% of the YOLOX. It significantly improves the precision of the detection, meets the requirements of the performance of the target detection of the fishing vessel, and has certain practical significance in engineering.
针对港口环境,渔船目标检测精度较低,容易出现渔船误检和漏检问题。本文提出了一种基于 YOLOX 的渔船目标检测算法 ASDNet。首先,设计了自适应空间注意力模块(ASAM),用于提高渔船目标的检测能力;其次,设计了双分支骨干网络,用于多维渔船特征提取。同时,设计了双边增强融合策略(BFFS)对分支特征进行融合,以提高网络的表征能力;最后,通过引入 Focal-CIOU 损失边界框损失函数对损失函数进行改进,以降低渔船目标检测位置偏差和船体重叠的影响,从而提高检测性能。利用自制渔船数据集对上述方法进行了验证,结果表明精确率(P)和召回率(R)都有很大提高。平均精确率(mAP@50-95)值达到 80.25%,比 YOLOX 的 77.86%高出 2.39%。大大提高了检测精度,满足了渔船目标检测的性能要求,具有一定的工程实用意义。
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引用次数: 0
Design of diesel engine vibration signal acquisition system based on Zynq 基于 Zynq 的柴油机振动信号采集系统设计
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2813/1/012002
Huishuai Wang, Haibo Gao and Wen Zuo
The vibration signal of a diesel engine contains a large amount of fault information, and an accurate collection of vibration signals will provide reliable data support for diesel engine condition monitoring. This paper designs a diesel engine vibration signal acquisition system based on the powerful Zynq chip. IEPE piezoelectric acceleration sensors are selected to collect diesel engine vibration signals, and a signal conditioning circuit is designed to filter out interference during signal transmission using the characteristics of differential signals and to adjust the voltage amplitude of the signal to ensure compliance with the input voltage level requirements of the AD conversion module. Considering the excellent performance of the AD7771, it is selected as the AD conversion chip, and the peripheral circuit design is completed. With the help of Vivado software, the software and hardware design based on the Zynq chip is completed, controlling the AD7771 to sample 8 channels of vibration signals. Finally, a signal conditioning circuit simulation model is established in Multisim 14.1 software to verify its good performance, and upper computer software is developed to monitor the fault information of the diesel engine.
柴油发动机的振动信号包含大量故障信息,准确采集振动信号将为柴油发动机状态监测提供可靠的数据支持。本文基于功能强大的 Zynq 芯片设计了一种柴油发动机振动信号采集系统。选用 IEPE 压电加速度传感器采集柴油机振动信号,并设计了信号调理电路,利用差分信号的特性滤除信号传输过程中的干扰,并调整信号的电压幅度,确保符合 AD 转换模块的输入电压电平要求。考虑到 AD7771 的优异性能,选择其作为 AD 转换芯片,并完成外围电路设计。在 Vivado 软件的帮助下,完成了基于 Zynq 芯片的软硬件设计,控制 AD7771 对 8 个通道的振动信号进行采样。最后,在 Multisim 14.1 软件中建立了信号调理电路仿真模型,验证了其良好的性能,并开发了上位机软件,用于监测柴油机的故障信息。
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引用次数: 0
Logical Mapping-based hierarchical safe reinforcement learning for autonomous driving 基于逻辑映射的自动驾驶分层安全强化学习
Pub Date : 2024-07-31 DOI: 10.1088/1742-6596/2813/1/012005
Jihui Nie and Yingda Li
Making decisions in complex and multiple scenarios presents great challenges for autonomous driving systems (ADS). In recent years, deep reinforcement learning algorithms (DRL) have made remarkable breakthroughs in decision-making. However, there remain many problems, such as sparse reward and slow convergence in traditional DRL when facing multiple sub-goals. In this paper, we propose a hierarchical deep deterministic policy gradient (DDPG) based on the BDIK model for autonomous driving, which enables ADS to have the ability to make decisions in human-like deliberation ways as well as deal with uncertainties in the environment. First, we propose the BDIK model based on the Beliefs-Desires-Intentions (BDI) model so that the agents are guided by domain knowledge when generating their sub-goals. Furthermore, in contrast to traditional BDI systems making plans by hand, a BDIK hierarchical DDPG (BDIK HDDPG) algorithm is employed to deduce the optimal actions automatically in an uncertain environment. The results show that our method outperforms the standard DDPG for both processing speed and effectiveness in multiple and complex scenarios.
在复杂多变的场景中做出决策是自动驾驶系统(ADS)面临的巨大挑战。近年来,深度强化学习算法(DRL)在决策方面取得了显著突破。然而,传统的 DRL 仍然存在很多问题,比如面对多个子目标时,奖励稀疏、收敛缓慢等。本文提出了一种基于 BDIK 模型的分层深度确定性策略梯度(DDPG),用于自动驾驶,使 ADS 能够以类似人类的深思熟虑方式做出决策,并应对环境中的不确定性。首先,我们提出了基于 "信念-愿望-意图"(BDI)模型的 BDIK 模型,从而使代理在生成子目标时受到领域知识的指导。此外,与传统的 BDI 系统手工制定计划不同,我们采用了 BDIK 分层 DDPG(BDIK HDDPG)算法,在不确定的环境中自动推导出最优行动。结果表明,我们的方法在多种复杂场景下的处理速度和效果都优于标准 DDPG。
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引用次数: 0
期刊
Journal of Physics: Conference Series
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