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Three-view cotton flower counting through multi-object tracking and RGB-D imagery 通过多目标跟踪和 RGB-D 图像进行三视角棉花花朵计数
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-18 DOI: 10.1016/j.biosystemseng.2024.08.010

Monitoring the number of cotton flowers can provide important information for breeders to assess the flowering time and the productivity of genotypes because flowering marks the transition from vegetative growth to reproductive growth and impacts the final yield. Traditional manual counting methods are time-consuming and impractical for large-scale fields. To count cotton flowers efficiently and accurately, a multi-view multi-object tracking approach was proposed by using both RGB and depth images collected by three RGB-D cameras fixed on a ground robotic platform. The tracking-by-detection algorithm was employed to track flowers from three views simultaneously and remove duplicated counting from single views. Specifically, an object detection model (YOLOv8) was trained to detect flowers in RGB images and a deep learning-based optical flow model Recurrent All-pairs Field Transforms (RAFT) was used to estimate motion between two adjacent frames. The intersection over union and distance costs were employed to associate flowers in the tracking algorithm. Additionally, tracked flowers were segmented in RGB images and the depth of each flower was obtained from the corresponding depth image. Those flowers tracked with known depth from two side views were then projected onto the middle image coordinate using camera calibration parameters. Finally, a constrained hierarchy clustering algorithm clustered all flowers in the middle image coordinate to remove duplicated counting from three views. The results showed that the mean average precision of trained YOLOv8x was 96.4%. The counting results of the developed method were highly correlated with those counted manually with a coefficient of determination of 0.92. Besides, the mean absolute percentage error of all 25 testing videos was 6.22%. The predicted cumulative flower number of Pima cotton flowers is higher than that of Acala Maxxa, which is consistent with what breeders have observed. Furthermore, the developed method can also obtain the flower number distributions of different genotypes without laborious manual counting in the field. Overall, the three-view approach provides an efficient and effective approach to count cotton flowers from multiple views. By collecting the video data continuously, this method is beneficial for breeders to dissect genetic mechanisms of flowering time with unprecedented spatial and temporal resolution, also providing a means to discern genetic differences in fecundity, the number of flowers that result in harvestable bolls. The code and datasets used in this paper can be accessed on GitHub: https://github.com/UGA-BSAIL/Multi-view_flower_counting.

监测棉花开花数量可为育种者评估开花时间和基因型的生产力提供重要信息,因为开花标志着棉花从无性生长向生殖生长的过渡,并影响最终产量。传统的人工数花方法既费时又不适合大面积种植。为了高效准确地计数棉花花朵,我们提出了一种多视角多目标跟踪方法,利用固定在地面机器人平台上的三台 RGB-D 摄像机收集的 RGB 和深度图像。采用逐个检测跟踪算法同时跟踪三个视角的花朵,并去除单个视角的重复计数。具体来说,训练了一个对象检测模型(YOLOv8)来检测 RGB 图像中的花朵,并使用基于深度学习的光流模型循环全对场变换(RAFT)来估计相邻两帧之间的运动。在跟踪算法中,采用了交集大于联合和距离成本来关联花朵。此外,在 RGB 图像中对跟踪到的花朵进行分割,并从相应的深度图像中获得每朵花的深度。然后,利用相机校准参数,将从两个侧视图追踪到的已知深度的花朵投影到中间图像坐标上。最后,使用约束层次聚类算法对中间图像坐标上的所有花朵进行聚类,以去除三个视图中的重复计数。结果表明,经过训练的 YOLOv8x 的平均精度为 96.4%。所开发方法的计数结果与人工计数结果高度相关,决定系数为 0.92。此外,所有 25 个测试视频的平均绝对误差为 6.22%。皮马棉花的预测累积花数高于 Acala Maxxa,这与育种人员的观察结果一致。此外,所开发的方法还能获得不同基因型的花数分布,而无需在田间进行费力的人工计数。总之,三视角方法提供了一种从多个视角对棉花花朵进行计数的高效方法。通过连续收集视频数据,该方法有利于育种人员以前所未有的空间和时间分辨率剖析开花时间的遗传机制,同时还提供了一种方法来鉴别受精率(即可采收棉铃的花朵数量)的遗传差异。本文使用的代码和数据集可在 GitHub 上访问:https://github.com/UGA-BSAIL/Multi-view_flower_counting。
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引用次数: 0
Attention-driven next-best-view planning for efficient reconstruction of plants and targeted plant parts 注意力驱动下一最佳视角规划,高效重建植物和目标植物部位
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-17 DOI: 10.1016/j.biosystemseng.2024.08.002

Robots in tomato greenhouses need to perceive the plant and plant parts accurately to automate monitoring, harvesting, and de-leafing tasks. Existing perception systems struggle with the high levels of occlusion in plants and often result in poor perception accuracy. One reason for this is because they use fixed cameras or predefined camera movements. Next-best-view (NBV) planning presents an alternate approach, in which the camera viewpoints are reasoned and strategically planned such that the perception accuracy is improved. However, existing NBV-planning algorithms are agnostic to the task-at-hand and give equal importance to all the plant parts. This strategy is inefficient for greenhouse tasks that require targeted perception of specific plant parts, such as the perception of leaf nodes for de-leafing. To improve targeted perception in complex greenhouse environments, NBV planning algorithms need an attention mechanism to focus on the task-relevant plant parts. In this paper, the role of attention in improving targeted perception using an attention-driven NBV planning strategy was investigated. Through simulation experiments using plants with high levels of occlusion and structural complexity, it was shown that focusing attention on task-relevant plant parts can significantly improve the speed and accuracy of 3D reconstruction. Further, with real-world experiments, it was shown that these benefits extend to complex greenhouse conditions with natural variation and occlusion, natural illumination, sensor noise, and uncertainty in camera poses. The results clearly indicate that using attention-driven NBV planning in greenhouses can significantly improve the efficiency of perception and enhance the performance of robotic systems in greenhouse crop production.

番茄温室中的机器人需要准确感知植物和植物的各个部分,以便自动完成监控、收获和去叶任务。现有的感知系统难以应对植物的高遮挡度,往往导致感知精度低下。其中一个原因是这些系统使用固定的摄像头或预定义的摄像头移动。下一个最佳视角(NBV)规划提出了另一种方法,即对摄像机视点进行推理和战略规划,从而提高感知精度。然而,现有的 NBV 规划算法与手头的任务无关,对所有植物部分都同等重视。对于需要有针对性地感知特定植物部位的温室任务(如感知叶片节点以进行摘叶)来说,这种策略效率低下。为了提高复杂温室环境中的定向感知能力,NBV 规划算法需要一种注意力机制来关注与任务相关的植物部分。本文利用注意力驱动的 NBV 规划策略,研究了注意力在改善目标感知中的作用。通过使用具有高度遮挡和结构复杂性的植物进行模拟实验,结果表明,将注意力集中在与任务相关的植物部分可以显著提高三维重建的速度和准确性。此外,真实世界的实验还表明,这些优势可以扩展到具有自然变化和遮挡、自然光照、传感器噪声以及相机姿势不确定性的复杂温室条件。研究结果清楚地表明,在温室中使用注意力驱动的 NBV 规划可以显著提高感知效率,增强机器人系统在温室作物生产中的性能。
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引用次数: 0
Numerical and experimental study on the performance of a stabilising turbine inside a seed distribution device 关于种子分配装置内稳定涡轮性能的数值和实验研究
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-15 DOI: 10.1016/j.biosystemseng.2024.08.009

A design was proposed for a seed turbine installed within the distribution device to reduce the influence of surface slope variations on the uniformity of seeding mass at each row. Through a comparative analysis based on the computational fluid dynamics (CFD) 6 degrees of freedom (DOF) dynamic mesh model simulation and the bench test, the influence of five different stabilising turbines on airflow distribution performance was investigated. The type Ⅰ stabilising turbine, characterised by acute inlet and outlet angles, exhibited a smaller vortex region at the blade inlet and improved the conveying and mixing performance of the seed. A CFD 6DOF simulation experiment was conducted to investigate the influence of the type I stabilising turbine on the airflow field distribution. As the number of blades increased from 4 to 10, the stability and uniformity of the conveying airflow distribution were enhanced at the turbine outlet. Simulations using a comprehensive performance test platform of the planter evaluated the influence of stabilising turbines with different numbers of blades on uniformity during field operations at varying surface slopes. When the angles of the front-rear and lateral one-way oscillation combination, and the front-rear and lateral reciprocating oscillation combination varied within the range of −5°–5°, the stabilising turbine with 8 blades exhibited the smallest uniformity coefficient of variation of the seeding mass at each row. The values ranged from 4.1 % to 5.8 % for rapeseeds and from 3.8 % to 5.0 % for wheat seeds.

为减少表面坡度变化对每行播种质量均匀性的影响,提出了在分配装置内安装种子涡轮的设计方案。通过基于计算流体动力学(CFD)6 自由度(DOF)动态网格模型模拟和台架试验的对比分析,研究了五种不同稳定涡轮对气流分布性能的影响。第Ⅰ型稳定涡轮的特点是进气和出气角度锐利,在叶片入口处表现出较小的涡流区域,改善了种子的输送和混合性能。为研究 I 型稳定涡轮对气流场分布的影响,进行了 CFD 6DOF 模拟实验。随着叶片数量从 4 个增加到 10 个,涡轮出口处输送气流分布的稳定性和均匀性得到了提高。利用播种机的综合性能测试平台进行模拟,评估了不同叶片数量的稳定涡轮在不同地表坡度下进行田间作业时对均匀性的影响。当前后和横向单向摆动组合以及前后和横向往复摆动组合的角度在 -5°-5° 范围内变化时,8 片叶片的稳定涡轮在每行播种质量的均匀性变化系数最小。油菜籽的均匀度变化系数在 4.1 % 到 5.8 % 之间,小麦种子的均匀度变化系数在 3.8 % 到 5.0 % 之间。
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引用次数: 0
CFD design and testing of an air flow distribution device for microwave infrared hot-air rolling-bed dryer 微波红外热风滚床干燥机气流分配装置的 CFD 设计与测试
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-14 DOI: 10.1016/j.biosystemseng.2024.08.005

In this study, a new microwave infrared hot air rolling bed dryer (MIHRBD) was developed and computational fluid dynamics (CFD) techniques were introduced into the design process of the integrated drying system. The structure of the air distribution device was optimised to improve the airflow uniformity over the curved surface of the rolling bed in the microwave-hot air drying combined equipment. The research findings reveal that, across eleven models, the outlet airflow velocity stabilises once the number of mesh elements reaches 5 million, achieving significant computational accuracy at that point. Optimizing components like the uniform air distribution pipe, turbulence plates, and wind deflectors significantly enhanced airflow distribution uniformity by 52.1%. The best airflow and temperature distribution uniformity on the rolling bed surface was achieved when the inlet airflow velocity ranged from 1 to 3 m s−1, with minimum Vd, Uv and temperature non-uniformity coefficients of 0.007 m s−1, 7.2% and 0.2%, respectively. Validation tests on the MIHRBD pilot equipment showed that after optimizing the uniform air distribution device, the minimum temperature difference on the pleurotus eryngii surface was 3.1 °C. This confirmed the feasibility of the computational fluid dynamics method. Introducing hot air significantly enhanced pleurotus eryngii's drying uniformity, with the Page model effectively predicting the MIHRBD drying process. This study provides technical support for future developments in this field of equipment manufacturing and drying process analysis.

本研究开发了一种新型微波红外热风滚动床干燥器(MIHRBD),并在集成干燥系统的设计过程中引入了计算流体动力学(CFD)技术。对空气分配装置的结构进行了优化,以改善微波-热风干燥组合设备中滚动床弯曲表面上的气流均匀性。研究结果表明,在 11 个模型中,一旦网格元素数量达到 500 万,出口气流速度就会趋于稳定,从而达到显著的计算精度。对均匀空气分布管道、湍流板和导风板等组件进行优化后,气流分布均匀性显著提高了 52.1%。当入口气流速度在 1 至 3 m s-1 之间时,滚动床表面的气流和温度分布均匀性最佳,最小 Vd、Uv 和温度不均匀系数分别为 0.007 m s-1、7.2% 和 0.2%。在 MIHRBD 试验设备上进行的验证测试表明,在优化均匀配风装置后,红褶菌表面的最小温差为 3.1 °C。这证实了计算流体动力学方法的可行性。热空气的引入大大提高了红曲的干燥均匀性,佩奇模型有效地预测了 MIHRBD 干燥过程。这项研究为设备制造和干燥过程分析领域的未来发展提供了技术支持。
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引用次数: 0
Development of a microwave sensor for the non-invasive detection of plant responses to water stress: A practical application on maize (Zea mays L.) 开发用于非侵入式检测植物对水分胁迫反应的微波传感器:在玉米上的实际应用
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-13 DOI: 10.1016/j.biosystemseng.2024.08.007

In this study, a novel microwave sensing system, consisting of a microstrip self-resonant spiral coil inductively coupled to an external concentric planar probe loop, is presented and applied to the non-destructive detection of morpho-physiological plant responses to water stress. The optimised set-up of the proposed sensor ensures a highly sensitive spiral coil, which is a fundamental requirement to derive accurate information on plants' behavioural alterations related to water stress conditions. The proposed microwave sensor was tested it on two potted maize cultivars (Zea mays L.), namely “Cinquantino Bianchi” (CB) and “Scagliolo Frassine” (SF). For each cultivar, half of the samples were maintained at 100% (T100) field capacity while the other half was at 25% (T25) from 46 to 74 Days After Sowing (DAS). The frequency (fr) shift and the amplitude peaks variation of the real component of the external planar probe input impedance (ℜ(Zinput)) were obtained daily by positioning the sensor on the stem. These measured data were related to morpho-physiological parameters destructively acquired at four different growth stages. The resulting linear correlation between the stem's freshwater content (FWCstem) with both fr (r > −0.64) and the amplitude peaks (ℜ (Zinput)) (r > -0.70) provided evidence of the sensor's ability to identify stem dielectric properties' variations between the two water treatments. Concurrently, the sensor response demonstrated the capability to identify changes in the morphology and histology of the stem. Based on preliminary findings, the proposed sensor shows potential for employment in the real-time monitoring of plant water status, contributing to more economically and environmentally sustainable crop management practices. While the current correlations between plant water content and sensor measurements require further refinement to meet the rigorous industrial standards, nevertheless a large-scale adoption can be envisioned by leveraging IoT methodologies.

本研究介绍了一种新型微波传感系统,该系统由一个微带自谐振螺旋线圈与外部同心平面探头环路电感耦合组成,可用于非破坏性检测植物对水分胁迫的形态生理反应。拟议传感器的优化设置确保了螺旋线圈的高灵敏度,而这正是获得与水胁迫条件相关的植物行为变化的准确信息的基本要求。在两个盆栽玉米品种(Zea mays L.)(即 "Cinquantino Bianchi"(CB)和 "Scagliolo Frassine"(SF))上测试了拟议的微波传感器。从播种后 46 天到 74 天(DAS),每个栽培品种的一半样品保持 100%(T100)的田间能力,另一半样品保持 25%(T25)的田间能力。通过将传感器定位在茎上,每天都能获得外部平面探头输入阻抗实分量的频率(fr)偏移和振幅峰值变化(ℜ(Zinput))。这些测量数据与在四个不同生长阶段破坏性获取的形态生理参数相关。结果表明,茎干淡水含量(FWCstem)与fr(r >-0.64)和振幅峰值(ℜ (Zinput))(r >-0.70)之间的线性相关,证明传感器有能力识别两种水处理之间茎干介电性质的变化。同时,传感器的响应也证明了其识别茎干形态和组织变化的能力。根据初步研究结果,该传感器有望用于植物水分状况的实时监测,从而促进经济和环境可持续的作物管理实践。虽然目前植物含水量与传感器测量值之间的相关性还需要进一步完善,以符合严格的工业标准,但利用物联网方法,可以实现大规模应用。
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引用次数: 0
Numerical simulation and optimisation of the inlet structure of dentiform emitters in drip-irrigation systems 滴灌系统中齿形喷头入口结构的数值模拟与优化
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-12 DOI: 10.1016/j.biosystemseng.2024.08.004

Emitter clogging adversely affects the performance of drip-irrigation systems. Many studies overlook the primary reason for emitter clogging by substances that precipitate within the emitter inlet. This study used computational fluid dynamics (CFD) to analyse the process of sedimentation in the inlet of emitters. Subsequently, the inlet structure was optimised based on the simulation results, production demand, and produced dripline. Anti-clogging physical tests were conducted in the laboratory and verified. Simulation results revealed that compared to the maximum discharge at the inlet of the domestic (CM) and Netafim (NF) emitters, that of the optimised (OS) emitter was increased by 60.0% and 13.2%, respectively; the maximum turbulent kinetic energy was increased by 88.9% and 13.3%, respectively; and the escape rate of solid particles in the dripline was increased by 3.2 and 5.9%, respectively. The results of an eighth-stage laboratory experiment with particle size ranges from 0.045 to 0.25 mm showed that the solid concentration was 1400 mg l−1 for the CM-type emitter and 200 mg l−1 for the OS-type emitter. However, the relative discharge of the OS-type emitter increased by 17.5%. At the end of the anti-clogging test, the relative discharge of the OS-type emitter was 0.12% more than that of the NF-type emitter. The water flowing through the OS-type emitter had a lower sediment content and higher relative discharge than of both comparison emitters. Therefore, optimising the emitter inlet can be an effective physical method for reducing the entry of solid particles into the emitter channel, which can greatly promote the sustainable development of drip irrigation.

发射器堵塞会对滴灌系统的性能产生不利影响。许多研究忽略了发射器入口沉淀物质造成发射器堵塞的主要原因。本研究利用计算流体动力学(CFD)分析了发射器入口的沉淀过程。随后,根据模拟结果、生产需求和生产滴管对入口结构进行了优化。在实验室进行了防堵塞物理测试并进行了验证。模拟结果表明,与家用(CM)和 Netafim(NF)排放器入口的最大排放量相比,优化(OS)排放器入口的最大排放量分别增加了 60.0% 和 13.2%;最大湍流动能分别增加了 88.9% 和 13.3%;固体颗粒在滴管中的逃逸率分别增加了 3.2% 和 5.9%。粒径范围为 0.045 至 0.25 毫米的第八级实验室实验结果表明,CM 型排放器的固体浓度为 1400 毫克/升,OS 型排放器的固体浓度为 200 毫克/升。然而,OS 型辐射器的相对排放量增加了 17.5%。防堵试验结束时,OS 型辐射器的相对排放量比 NF 型辐射器多 0.12%。流经 OS 型排放器的水的沉淀物含量和相对排放量均低于两种对比排放器。因此,优化辐射器入口是减少固体颗粒进入辐射器通道的有效物理方法,可极大地促进滴灌的可持续发展。
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引用次数: 0
A novel variable discharge emitter for irrigation and salt-leaching 用于灌溉和盐沥的新型可变排放喷射器
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-10 DOI: 10.1016/j.biosystemseng.2024.08.006

Enhancing the utilisation rate and productivity of saline-alkali land is critical in ensuring sufficient cultivated land resources and food security. Although drip irrigation technology maintains the crop yield in saline-alkali land, the irrigation water amount must be higher than the crop demand. To address this, the present study develops a novel variable discharge emitter (VDE), which consists of an upper cover, a bottom cover, and a diaphragm with a linear incision. The experimental results showed that the VDE achieved two rated discharge levels of 4.1 L h−1 and 9.7 L h−1 when the working water pressure was at 0.10 MPa and 0.16 MPa and when the length of the incision, the thickness of the diaphragm, and the hardness of diaphragm inside the VDE were 3.5 mm, 1.5 mm, and 55.0 HA, respectively. It suggests that VDE has two rated discharges for irrigation and salt-leaching based on two working water pressure ranges.

提高盐碱地的利用率和生产力对于确保充足的耕地资源和粮食安全至关重要。虽然滴灌技术能保持盐碱地的作物产量,但灌溉水量必须高于作物需求。为此,本研究开发了一种新型可变排量喷头(VDE),它由上盖、下盖和带有线性切口的隔膜组成。实验结果表明,当工作水压为 0.10 兆帕和 0.16 兆帕,VDE 内部的切口长度、隔膜厚度和隔膜硬度分别为 3.5 毫米、1.5 毫米和 55.0 HA 时,VDE 达到了 4.1 升/小时和 9.7 升/小时的两个额定排放水平。这表明,根据两种工作水压范围,VDE 有两种额定排水量,可用于灌溉和浸盐。
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引用次数: 0
Livestock feeding behaviour: A review on automated systems for ruminant monitoring 牲畜采食行为:反刍动物自动监测系统综述
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-09 DOI: 10.1016/j.biosystemseng.2024.08.003

Livestock feeding behaviour is an influential research area in animal husbandry and agriculture. In recent years, there has been a growing interest in automated systems for monitoring the behaviour of ruminants. Current automated monitoring systems mainly use motion, acoustic, pressure and image sensors to collect and analyse patterns related to ingestive behaviour, foraging activities and daily intake. The performance evaluation of existing methods is a complex task and direct comparisons between studies is difficult. Several factors prevent a direct comparison, starting from the diversity of data and performance metrics used in the experiments. This review on the analysis of the feeding behaviour of ruminants emphasise the relationship between sensing methodologies, signal processing, and computational intelligence methods. It assesses the main sensing methodologies and the main techniques to analyse the signals associated with feeding behaviour, evaluating their use in different settings and situations. It also highlights the potential of the valuable information provided by automated monitoring systems to expand knowledge in the field, positively impacting production systems and research. The paper closes by discussing future engineering challenges and opportunities in livestock feeding behaviour monitoring.

牲畜采食行为是畜牧业和农业中一个有影响力的研究领域。近年来,人们对反刍动物行为自动监测系统的兴趣与日俱增。目前的自动监测系统主要使用运动、声学、压力和图像传感器来收集和分析与摄食行为、觅食活动和每日摄入量有关的模式。对现有方法进行性能评估是一项复杂的任务,很难对不同研究进行直接比较。从实验中使用的数据和性能指标的多样性开始,有几个因素阻碍了直接比较。这篇反刍动物采食行为分析综述强调了传感方法、信号处理和计算智能方法之间的关系。它评估了与采食行为相关的主要传感方法和主要信号分析技术,评价了它们在不同环境和情况下的应用。论文还强调了自动监测系统提供的宝贵信息在拓展该领域知识、对生产系统和研究产生积极影响方面的潜力。论文最后讨论了牲畜采食行为监测领域未来的工程挑战和机遇。
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引用次数: 0
Harnessing multimodal data fusion to advance accurate identification of fish feeding intensity 利用多模态数据融合推进鱼类摄食强度的精确识别
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-08-06 DOI: 10.1016/j.biosystemseng.2024.08.001

Accurately identifying the fish feeding intensity plays a vital role in aquaculture. While traditional methods are limited by single modality (e.g., water quality, vision, audio), they often lack comprehensive representation, leading to low identification accuracy. In contrast, the multimodal fusion methods leverage the fusion of features from different modalities to obtain richer target features, thereby significantly enhancing the performance of fish feeding intensity assessment (FFIA). In this work a multimodal dataset called MRS-FFIA was introduced. The MRS-FFIA dataset consists of 7611 labelled audio, video and acoustic dataset, and divided the dataset into four different feeding intensity (strong, medium, weak, and none). To address the limitations of single modality methods, a Multimodal Fusion of Fish Feeding Intensity fusion (MFFFI) model was proposed. The MFFFI model is first extracting deep features from three modal data audio (Mel), video (RGB), Acoustic (SI). Then, image stitching techniques are employed to fuse these extracted features. Finally, the fused features are passed through a classifier to obtain the results. The test results show that the accuracy of the fused multimodal information is 99.26%, which improves the accuracy by 12.80%, 13.77%, and 2.86%, respectively, compared to the best results for single-modality (audio, video and acoustic dataset). This result demonstrates that the method proposed in this paper is better at classifying the feeding intensity of fish and can achieve higher accuracy. In addition, compared with the mainstream single-modality approach, the model improves 1.5%–10.8% in accuracy, and the lightweight effect is more obvious. Based on the multimodal fusion method, the feeding decision can be optimised effectively, which provides technical support for the development of intelligent feeding systems.

准确识别鱼类的摄食强度在水产养殖中起着至关重要的作用。传统方法受限于单一模式(如水质、视觉、音频),往往缺乏全面的表征,导致识别准确率较低。相比之下,多模态融合方法利用不同模态的特征进行融合,以获得更丰富的目标特征,从而显著提高鱼类摄食强度评估(FFIA)的性能。本研究引入了一个名为 MRS-FFIA 的多模态数据集。MRS-FFIA 数据集由 7611 个带标签的音频、视频和声学数据集组成,并将数据集分为四种不同的摄食强度(强、中、弱和无)。针对单一模态方法的局限性,提出了鱼类摄食强度多模态融合模型(MFFFI)。MFFFI 模型首先从音频(Mel)、视频(RGB)和声学(SI)三种模态数据中提取深度特征。然后,采用图像拼接技术来融合这些提取的特征。最后,将融合后的特征通过分类器得出结果。测试结果表明,融合后的多模态信息准确率为 99.26%,与单模态(音频、视频和声学数据集)的最佳结果相比,准确率分别提高了 12.80%、13.77% 和 2.86%。这一结果表明,本文提出的方法能更好地对鱼类的摄食强度进行分类,并能达到更高的准确度。此外,与主流的单模态方法相比,该模型的准确率提高了 1.5%-10.8%,轻量化效果更加明显。基于多模态融合方法,可以有效优化投喂决策,为智能投喂系统的开发提供技术支持。
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引用次数: 0
Modelling the interaction of soil with a passively-vibrating sweep using the discrete element method 利用离散元素法模拟土壤与被动振动扫地机的相互作用
IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Pub Date : 2024-07-31 DOI: 10.1016/j.biosystemseng.2024.06.006

This study investigates the passive vibration dynamics of a sweep tool in a laboratory soil bin test, employing various spring configurations. A discrete element method (DEM) model of simulating the passively vibrating sweep tool was developed based on the laboratory soil bin tests. Ensuring precision in the DEM model parameters was achieved by applying a genetic algorithm tailored for this purpose. The genetic algorithm revealed that within the particle assemblies of the three geometries used in the DEM, several parameter sets were suitable for accurately describing the modelled soil. The final parameter set was chosen by integrating the DEM model with results from the laboratory direct shear box test. Employing Fast Fourier Transformation, both the laboratory soil bin test and the calibrated DEM model of the soil and the vibrating sweep tool facilitated an examination of frequencies and amplitudes during force and displacement measurements. The results indicated that, compared to a rigid tool, the draught force required by the 16 spring sweep tool was reduced by 6–9%. The absence of DEM would have limited the investigation of kinetic energy in the sweep tool and the dynamics of energy dissipation in the soil, if measurement equipment alone was used. This research successfully demonstrated that the reduced draught force with the 16 spring passively vibrating sweep tool, operating near the system's eigenfrequency, resulted from its ability to generate higher kinetic energy in the sweep tool while minimising energy dissipation in the soil.

本研究采用不同的弹簧配置,对实验室土壤仓试验中的扫地工具的被动振动动力学进行了研究。在实验室土壤仓试验的基础上,开发了离散元法(DEM)模型,用于模拟被动振动的扫地工具。通过应用专门定制的遗传算法,确保了 DEM 模型参数的精确性。遗传算法显示,在 DEM 中使用的三种几何形状的颗粒组合中,有几组参数适合精确描述模型土壤。通过将 DEM 模型与实验室直接剪切箱试验结果进行整合,选择了最终的参数集。通过快速傅里叶变换,实验室土壤箱试验和校准后的土壤 DEM 模型以及振动扫描工具都有助于检查力和位移测量过程中的频率和振幅。结果表明,与刚性工具相比,16 个弹簧扫地工具所需的牵引力降低了 6-9%。如果仅使用测量设备,没有 DEM 会限制对清扫工具动能和土壤中能量消耗动态的研究。这项研究成功证明,在系统特征频率附近工作的 16 个弹簧被动振动扫地工具,由于能够在扫地工具中产生更高的动能,同时最大限度地减少土壤中的能量耗散,从而降低了吃水力。
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