Biosystems Engineering最新文献_第7页

A method for optimising the parameters of connecting parts of a corn no-till planter 一种优化玉米免耕播种机连接部件参数的方法

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-24 DOI: 10.1016/j.biosystemseng.2024.07.006

引用次数: 0

Soft-sensor based on sliding modes for industrial raceway photobioreactors 基于滑动模式的工业滚道光生物反应器软传感器

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-23 DOI: 10.1016/j.biosystemseng.2024.07.015

{"title":"Soft-sensor based on sliding modes for industrial raceway photobioreactors","authors":"","doi":"10.1016/j.biosystemseng.2024.07.015","DOIUrl":"10.1016/j.biosystemseng.2024.07.015","url":null,"abstract":"<div><p>Microalgae reactors provide an efficient and clean alternative for the production of biofuels, nutritional and cosmetic bioproducts, wastewater treatment, and mitigation of industrial gases to reduce greenhouse gas emissions. The main control objective in these systems is productivity optimisation. For this reason, real-time monitoring of key biological performance indicators affecting microalgae production such as microalgae growth rate, biomass concentration, dissolved oxygen, pH level or total inorganic carbon is crucial. However, there are no sufficiently robust solutions on the market to estimate or measure all of these variables, especially for open reactors on an industrial scale. This paper presents a new online state estimator, based on a robust sliding mode observer combined with a nonlinear dynamic model endowed with a minimum number of states to capture dynamics of key biological performance indicators. This soft-sensor has been verified with a realistic reactor model that has been experimentally tested. Simulations showed promising results in terms of accuracy (with mean values of the state estimation errors in the order of 10<sup>−4</sup> <em>g m</em><sup>−3</sup> for the biomass concentration, 10<sup>−5</sup> to 10<sup>−13</sup> <em>mol m</em><sup>−3</sup> for the other states and deviations in the order of 10<sup>−4</sup> <em>g m</em><sup>−3</sup> for the biomass concentration, 10<sup>−5</sup> to 10<sup>−10</sup> <em>mol m</em><sup>−3</sup> for the other states) and robustness with respect to signal noise, state deviations, initial errors and parametric uncertainty.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Updating apple Vis-NIR spectral ripeness classification model based on deep learning and multi-seasonal database 基于深度学习和多季节数据库更新苹果可见光-近红外光谱成熟度分类模型

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-19 DOI: 10.1016/j.biosystemseng.2024.07.010

{"title":"Updating apple Vis-NIR spectral ripeness classification model based on deep learning and multi-seasonal database","authors":"","doi":"10.1016/j.biosystemseng.2024.07.010","DOIUrl":"10.1016/j.biosystemseng.2024.07.010","url":null,"abstract":"<div><p>Judicious assessment of ripeness is crucial for ensuring the quality and commercial value of apples. However, when it comes to detecting apples spectrally under different seasonal variations, there are limitations in the application of calibration models that are built for a single season. Therefore, it is necessary to implement model updating. In this study, a large dataset was acquired of apple visible and near-infrared spectra spanning four seasons and assessed the ripeness of the samples based on computer vision tools. After completing a series of data processing and parameter optimisation, a one-dimensional convolution neural network was built on the initial seasonal dataset. Subsequently, model transfer between seasons was completed using deep transfer learning. Further, multi-seasonal model updating of apple ripeness classification models was achieved in two scenarios with and without historical data. The results indicated that by retraining the network’s convolution layer, the classification accuracies for the three new seasons improved by 4%, 18%, and 15% respectively, while remaining stable for the original season. Combining 5%–20% new season samples with cumulative historical data, the model’s classification performance improves by up to 54% and 55% on the two new seasons. This study contributes to the updating of the multi-seasonal spectral database model for fruit quality control.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141728654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameter calibration of the angle of repose of particle materials based on convolutional neural network 基于卷积神经网络的颗粒材料静止角参数校准

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-18 DOI: 10.1016/j.biosystemseng.2024.07.011

{"title":"Parameter calibration of the angle of repose of particle materials based on convolutional neural network","authors":"","doi":"10.1016/j.biosystemseng.2024.07.011","DOIUrl":"10.1016/j.biosystemseng.2024.07.011","url":null,"abstract":"<div><p>Accurate determination of microscopic parameters is crucial for employing the discrete element method in addressing practical engineering challenges. The angle of repose calibration method for bulk materials is employed but frequently relies on subjective human measurements, potentially resulting in errors. This paper introduces a parameter calibration method that utilises a convolutional neural network to enhance standardisation, universality, and accuracy in predicting particle material behaviour. Firstly, the angle of repose simulations are conducted to establish training and test datasets. Next, sensitivity analysis is performed to determine the evaluation index. Subsequently, the performance differences in prediction accuracy among various input data types and network models, including one-dimensional convolutional, two-dimensional convolutional, and fully connected networks were compared. Finally, the influence of particle size and material type on the trained network model was investigated. The experimental results demonstrate that convolutional neural networks outperform traditional parameter calibration methods, in terms of feature extraction capabilities. According to the evaluation indicators in this paper, the conventional method achieves the highest prediction accuracy of 63.33%, whereas the deep learning method achieves a prediction accuracy of 86.67%. Additionally, the accuracy of one-dimensional convolutional network predictions is relatively high when compared to two-dimensional convolutional and fully connected networks. Furthermore, contour feature data exhibits superiority over slope data. Specifically, when the network input data consists of contour data, the prediction accuracy is further enhanced by 6.67% due to its inclusion of more effective features. This study provides new insights into the angle of repose parameter calibration.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141728653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental verification and simulation analysis of a multi-sphere modelling approach for wheat seed particles based on the discrete element method 基于离散元素法的小麦种子颗粒多球建模方法的实验验证和模拟分析

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-17 DOI: 10.1016/j.biosystemseng.2024.07.009

{"title":"Experimental verification and simulation analysis of a multi-sphere modelling approach for wheat seed particles based on the discrete element method","authors":"","doi":"10.1016/j.biosystemseng.2024.07.009","DOIUrl":"10.1016/j.biosystemseng.2024.07.009","url":null,"abstract":"<div><p>A comprehensive modelling methodology is proposed to describe wheat seeds using the discrete element method. By analysing the geometrical characteristics of wheat seeds, the multi-sphere approach is employed to establish 7-, 11-, 15-, 19-, and 23-sphere models based on ellipsoids. The physical and mechanical characteristics of wheat grain are measured and calibrated. Then, the proposed model is verified with several assessment criteria by contrasting the results of the experiment and simulation, including the wheat seed volume fraction, static angle of repose, hopper discharge, rotating drum and “self-flow screening”. By balancing the accuracy of the multi-sphere model and computational efficiency, the 7-sphere or 11-sphere model is found to be the optimal model for determining the static stacking behaviour and hopper discharge of wheat seeds. For the rotating drum and the “self-flow screening”, there is a considerable discrepancy between the simulation and experimental findings due to the surface roughness of the 7- and 11-sphere models. However, 15-, 19-, and 23-sphere models show a high accuracy, which can be applied for drying seeds of the rotating drum and accurately reproducing the sieve permeability of the “self-flow screening” experiment. In summary, the proposed multi-sphere method can be extended to related industry fields by demonstrating satisfactory accuracy in several validation tests.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141638458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental study on the sugarcane stubble base-cutting mechanism 甘蔗茬基切机理试验研究

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-17 DOI: 10.1016/j.biosystemseng.2024.07.005

{"title":"Experimental study on the sugarcane stubble base-cutting mechanism","authors":"","doi":"10.1016/j.biosystemseng.2024.07.005","DOIUrl":"10.1016/j.biosystemseng.2024.07.005","url":null,"abstract":"<div><p>Base-cutting is essential in sugarcane harvesting, and violent collisions between the base-cutter and stalk can cause stubble damage. Therefore, it is necessary to study the base-cutting mechanism to reduce stubble damage. Based on the mechanical analysis method, this study analysed the base-cutting process of sugarcane vascular bundles and stems from fibber and macro perspectives, respectively. In addition, the base-cutting process was simulated based on Discrete Element Method, and field experiments were conducted to validate the analysis results. The tensile length function <em>L (z)</em> of the vascular bundle was derived from a fibber perspective. A mechanical model of the cutting force on the entire stem was obtained from a macro perspective. From the equations, it can be found that the kinematic parameters of the base-cutter have a significant influence on the cutting force. The simulation test revealed that the cutting force increased sharply when the blade was cut into stems, and the maximum cutting force reached 146.9N. Field tests were conducted to explore the relationship between these factors and the stubble damage rate. To decrease the damage rate to a smaller level, the single-factor test results showed that the forward speed of harvester, rotational speed of disc, and cutting depth should be controlled in the range of 0.8–1.4 m s<sup>−1</sup>, 600–1000 r·min<sup>−1</sup>, and 60–120 mm, respectively. The response surface test showed that the order of the effect of each factor on stubble damage was forward speed > rotational speed > cutting depth. The lowest stubble damage rate was 6.20% when the forward speed, rotational speed of disc, and cutting depth were 1.4 m s<sup>−1</sup>, 800 r·min<sup>−1</sup>, and 79.07 mm, respectively. After experimental field verification, the damage rate met the harvesting standard.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141638457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of perforation placement on the hydrodynamics of a culture tank onboard a self-exchange aquaculture vessel 穿孔位置对自交换式水产养殖船上养殖水槽流体力学的影响

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-16 DOI: 10.1016/j.biosystemseng.2024.07.004

{"title":"Influence of perforation placement on the hydrodynamics of a culture tank onboard a self-exchange aquaculture vessel","authors":"","doi":"10.1016/j.biosystemseng.2024.07.004","DOIUrl":"10.1016/j.biosystemseng.2024.07.004","url":null,"abstract":"<div><p>A self-exchange aquaculture vessel stands as an environmentally sustainable solution for fish farming, capitalising on seawater utilization and minimising the risk of fish escapes through the implementation of perforated culture tanks. This research aims to lay the groundwork for the conceptual design, modelling, and simulation analysis of such vessels, focusing on how near-bottom perforation placement affects flow field characteristics within the culture tank. This paper presents a computational study using Computational Fluid Dynamics (CFD) to analyse self-exchange aquaculture vessels under both head and beam current conditions. The solution of conservation equations governing tank hydrodynamics is achieved using an implicit unsteady second-order Eulerian (finite volume) technique on optimised trimmed meshes. Experimental and predicted values for the vessel model's total resistance were evaluated using uncertainty analysis, validating the numerical model. It was found that proper positioning of perforations near the bottom significantly enhances the synergistic effect of fluid within the culture tank and the mixing characteristics of the flow field. To enhance water circulation, it is recommended to install two or more rows of perforations on the sides of self-exchange aquaculture vessels. The coordination between perforation placement and vessel structure should be considered to determine the optimal layout. By offering valuable insights into the effects of perforation placement, this study contributes to the development of more efficient and environmentally friendly aquaculture practices.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141630675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterisation of discharge and flow rate predictions for asymmetric wedge-shaped hoppers 非对称楔形料斗的出料特性和流速预测

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-16 DOI: 10.1016/j.biosystemseng.2024.07.007

{"title":"Characterisation of discharge and flow rate predictions for asymmetric wedge-shaped hoppers","authors":"","doi":"10.1016/j.biosystemseng.2024.07.007","DOIUrl":"10.1016/j.biosystemseng.2024.07.007","url":null,"abstract":"<div><p>It is important to understand the flow behaviour inside wedge-shaped hoppers and accurately predict the discharge rate for the processing and handling of granular materials, regardless of whether the wedge hopper is symmetric or asymmetric. In this paper, the discrete element method (DEM) was used to reveal the flow behaviour of pellet feed in an asymmetric wedge-shaped hopper from the discharge rate, flow pattern, velocity distribution, normal contact force between particles and free-fall arch. The results showed that, with the hopper angle decreasing, the area of the active region of the particles increased, the stagnation zone decreased, and the free-fall arch became unstable. When the unilateral hopper angle was less than 45°, the discharge rate of the wedge-shaped hopper increased, and the average discharge rate reached the maximum value of 1.070 kg s<sup>−</sup><sup>1</sup> when the left and right hopper angles were equal to 15°. In addition, using the discharging mass proportion coefficient to represent the size of the region in which the unilateral hopper angle affected the flow of particles in the hopper, the hopper angle term in the Brown and Sellers model was corrected. The predictive errors of the corrected discharge rate model were less than 7.6% and 3.3% in the simulated and actual discharging tests respectively, which was better than that of the Brown and Sellers model. The results of the study could provide a theoretical basis for the intelligent upgrading of feed accurate handling equipment, and provide a reference basis for the design of asymmetric wedge-shaped hopper.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141630674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and experiment of an intelligent testing bench for air-suction seed metering devices for small vegetable seeds 小型蔬菜种子气吸式种子计量装置智能测试台的设计与实验

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-13 DOI: 10.1016/j.biosystemseng.2024.07.003

Zhang Weipeng , Zhao Bo , Gao Shengbo , Zhu Yue , Zhou Liming , Niu Kang , Qiu Zhaomei , Jin Xin

{"title":"Design and experiment of an intelligent testing bench for air-suction seed metering devices for small vegetable seeds","authors":"Zhang Weipeng , Zhao Bo , Gao Shengbo , Zhu Yue , Zhou Liming , Niu Kang , Qiu Zhaomei , Jin Xin","doi":"10.1016/j.biosystemseng.2024.07.003","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.07.003","url":null,"abstract":"<div><p>In order to realise the real-time monitoring of seeding quality of small vegetable seeds, and solve the problem of inconvenience caused by the small particle sizes of vegetable seeds, an intelligent testing bench for air-suction seed metering device for small vegetable seeds with a particle diameter of 0.5–3 mm was designed, and a complementary quality monitoring and controlling system was developed. The photoelectric sensing technology and image recognition technology were used together in the system. Photoelectric sensing technology was used for real-time monitoring of seed counting, while the image recognition technology can dynamically monitor the missed seeding, repeated seeding and the falling trajectory of seed deposition in real time. The system was installed on the air-suction intelligent testing bench to test the monitoring accuracy of the monitoring system. The experimental results demonstrated that the monitoring accuracy of drilling quality monitoring system was over 97%, the monitoring accuracy of miss seeding was over 95%, and the monitoring accuracy of repeated seeding was over 93%. Furthermore, the monitoring system was less affected by the seed particle size, shape, and plant spacing, etc., and the system was stable, which effectively realised the real-time monitoring of the operation of air-suction metering device.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of deep learning-based methods for non-destructive evaluation of agricultural products 基于深度学习的农产品无损评估方法综述

IF 4.4 1区农林科学

Biosystems Engineering Pub Date : 2024-07-13 DOI: 10.1016/j.biosystemseng.2024.07.002

Zhenye Li , Dongyi Wang , Tingting Zhu , Yang Tao , Chao Ni

{"title":"Review of deep learning-based methods for non-destructive evaluation of agricultural products","authors":"Zhenye Li , Dongyi Wang , Tingting Zhu , Yang Tao , Chao Ni","doi":"10.1016/j.biosystemseng.2024.07.002","DOIUrl":"https://doi.org/10.1016/j.biosystemseng.2024.07.002","url":null,"abstract":"<div><p>Deep Learning (DL) has emerged as a pivotal modelling tool in various domains because of its proficiency in learning distributed representations. Numerous DL algorithms have recently been proposed and applied to non-destructive testing (NDT) methods in agriculture. This study aimed to review the state-of-the-art applications of DL algorithms in NDT by analysing the application of DL to specific NDT applications and highlighting their contributions and challenges. It first presents a comprehensive overview of various NDT techniques that have been combined with DL in agricultural product evaluation, and then briefly describes their applications in diverse NDT tasks, such as image classification, object detection, image retrieval, and semantic segmentation. Second, this study addresses the ongoing challenges associated with data collection and fusion, model complexity, computational requirements, and robustness. Finally, future research directions are examined, underscoring the potential of novel neural network architectures and cross-disciplinary collaborations. This review aims to provide a clear understanding of the current state of DL-based NDT in agricultural product examinations and its prospects for the future.</p><p>© 2017 Elsevier Inc. All rights reserved.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0