Pub Date : 2023-01-01DOI: 10.25165/j.ijabe.20231602.5931
A. Numsong, J. Posom, S. Chuan-udom
: This research proposes an artificial neural network (ANN)-based repair and maintenance (R&M) cost estimation model for agricultural machinery. The proposed ANN model can achieve high estimation accuracy with small data requirement. In the study, the proposed ANN model is implemented to estimate the R&M costs using a sample of locally-made rice combine harvesters. The model inputs are geographical regions, harvest area, and curve fitting coefficients related to historical cost data; and the ANN output is the estimated R&M cost. Multilayer feed-forward is adopted as the processing algorithm and Levenberg-Marquardt backpropagation learning as the training algorithm. The R&M costs are estimated using the ANN-based model, and results are compared with those of conventional mathematical estimation model. The results reveal that the percentage error between the conventional and ANN-based estimation models is below 1%, indicating the proposed ANN model’s high predictive accuracy. The proposed ANN-based model is useful for setting the service rates of agricultural machinery, given the significance of R&M cost in profitability. The novelty of this research lies in the use of curve-fitting coefficients in the ANN-based estimation model to improve estimation accuracy. Besides, the proposed ANN model could be further developed into web-based applications using a programming language to enable ease of use and greater user accessibility. Moreover, with minor modifications, the ANN estimation model is also applicable to other geographical areas and tractors or combine harvesters of different countries of origin.
{"title":"Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters","authors":"A. Numsong, J. Posom, S. Chuan-udom","doi":"10.25165/j.ijabe.20231602.5931","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.5931","url":null,"abstract":": This research proposes an artificial neural network (ANN)-based repair and maintenance (R&M) cost estimation model for agricultural machinery. The proposed ANN model can achieve high estimation accuracy with small data requirement. In the study, the proposed ANN model is implemented to estimate the R&M costs using a sample of locally-made rice combine harvesters. The model inputs are geographical regions, harvest area, and curve fitting coefficients related to historical cost data; and the ANN output is the estimated R&M cost. Multilayer feed-forward is adopted as the processing algorithm and Levenberg-Marquardt backpropagation learning as the training algorithm. The R&M costs are estimated using the ANN-based model, and results are compared with those of conventional mathematical estimation model. The results reveal that the percentage error between the conventional and ANN-based estimation models is below 1%, indicating the proposed ANN model’s high predictive accuracy. The proposed ANN-based model is useful for setting the service rates of agricultural machinery, given the significance of R&M cost in profitability. The novelty of this research lies in the use of curve-fitting coefficients in the ANN-based estimation model to improve estimation accuracy. Besides, the proposed ANN model could be further developed into web-based applications using a programming language to enable ease of use and greater user accessibility. Moreover, with minor modifications, the ANN estimation model is also applicable to other geographical areas and tractors or combine harvesters of different countries of origin.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"51 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86339653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: In order to further reduce the damage rate in threshing seed corn, a seed corn threshing testbed with variable diameter and spacing that can realize dynamic adjustment of parameters, such as feed quantity, rotating speed of the threshing device, threshing spacing of the threshing units, was designed in this research. The software of finite element analysis ANSYS Workbench was applied to do modal analysis on the threshing axis designed for variable diameter and spacing of seed corn. The first 8 orders of natural frequencies were distributed in 201.12-1640.20 Hz, with corresponding vibration amplitude in 5.86-27.04 mm, showing reasonable structural design of the threshing axis, which could realize effective seed corn threshing and conveying. Discrete element method was applied to do simulation analysis on the seed corn threshing and conveying process with variable diameter and spacing. Under the condition of different feed quantity, different rotating speed of the thresher, the moving speed of corn clusters and contact force among clusters were measured through simulation, and the working characteristics of the threshing testbed for low-damage and dynamic threshing and conveying of seed corn with variable diameter and spacing were revealed. Working performance test results of the testbed of seed corn with variable diameter and spacing showed that, when the rotating speed of the threshing axis was 190-290 r/min, feed quantity was 1.80-3.80 kg/s, the damage rate of seed corn was 0.32%-0.63%, threshing rate was 99.20%-99.82%, and content impurity rate was 4.23%-5.86%, the mass of threshed corn grains first increased and then decreased along the axial direction. The test verification process was in line with the simulation results; thus, the test results could satisfy the requirements in design and actual operation.
{"title":"Analysis and performance test on dynamic seed corn threshing and conveying process with variable diameter and spacing","authors":"Fei Dai, Yuanxiang Liu, Ruijie Shi, Yiming Zhao, Shanglong Xin, Qiufeng Fu, Wuyun Zhao","doi":"10.25165/j.ijabe.20231602.7741","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7741","url":null,"abstract":": In order to further reduce the damage rate in threshing seed corn, a seed corn threshing testbed with variable diameter and spacing that can realize dynamic adjustment of parameters, such as feed quantity, rotating speed of the threshing device, threshing spacing of the threshing units, was designed in this research. The software of finite element analysis ANSYS Workbench was applied to do modal analysis on the threshing axis designed for variable diameter and spacing of seed corn. The first 8 orders of natural frequencies were distributed in 201.12-1640.20 Hz, with corresponding vibration amplitude in 5.86-27.04 mm, showing reasonable structural design of the threshing axis, which could realize effective seed corn threshing and conveying. Discrete element method was applied to do simulation analysis on the seed corn threshing and conveying process with variable diameter and spacing. Under the condition of different feed quantity, different rotating speed of the thresher, the moving speed of corn clusters and contact force among clusters were measured through simulation, and the working characteristics of the threshing testbed for low-damage and dynamic threshing and conveying of seed corn with variable diameter and spacing were revealed. Working performance test results of the testbed of seed corn with variable diameter and spacing showed that, when the rotating speed of the threshing axis was 190-290 r/min, feed quantity was 1.80-3.80 kg/s, the damage rate of seed corn was 0.32%-0.63%, threshing rate was 99.20%-99.82%, and content impurity rate was 4.23%-5.86%, the mass of threshed corn grains first increased and then decreased along the axial direction. The test verification process was in line with the simulation results; thus, the test results could satisfy the requirements in design and actual operation.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"33 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88279331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.25165/j.ijabe.20231602.7216
S. Fu, Jin-Quan Lu, I. Walder, Daishe Wu
: The leaching of heavy metals from tailings deposit due to the oxidation of sulphidic tailings and formation of acidic leachate is considered a high risk to the surrounding environment. Temperature plays an important role in the leaching of heavy metals from tailings in changing acid-based environment, especially in the Arctic area. To investigate how the temperature variation affected metal release from tailings in the Arctic area, a series of column leaching experiments was conducted under four temperature situations (5°C, 10°C, 14°C and 18°C). Physicochemical properties, Fe, Zn, Ni and Mn concentrations of leachates at each cycle were measured, and multivariate statistical analysis was applied to research the effect of temperature on heavy metals leaching from tailings in the Arctic area. The results showed that higher temperatures encouraged tailings to oxidation and sulfuration of and promoted heavy metal release from the tailings through precipitation and erosion. Ni, Zn and Mn have similar releasing resources from tailings and positive correlation in the leaching activity. Rising temperature accelerated Fe leaching; Fe leaching promoted leaching of the other metals, especially of Mn. Appropriately increase temperature will accelerate oxidization and sulfidization of the tailings, promote acid generation and increase TDS and, finally, promote the release of heavy metals. Climate change, with rising temperatures increasing the risk of heavy metals leaching from the tailings, should be given greater attention. Keeping tailings away from the appropriate temperature and in a higher alkalinity is a good method to control the leaching of heavy metals from tailings.
{"title":"Effect of temperature on the leaching of heavy metals from nickel mine tailings in the arctic area, Norway","authors":"S. Fu, Jin-Quan Lu, I. Walder, Daishe Wu","doi":"10.25165/j.ijabe.20231602.7216","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231602.7216","url":null,"abstract":": The leaching of heavy metals from tailings deposit due to the oxidation of sulphidic tailings and formation of acidic leachate is considered a high risk to the surrounding environment. Temperature plays an important role in the leaching of heavy metals from tailings in changing acid-based environment, especially in the Arctic area. To investigate how the temperature variation affected metal release from tailings in the Arctic area, a series of column leaching experiments was conducted under four temperature situations (5°C, 10°C, 14°C and 18°C). Physicochemical properties, Fe, Zn, Ni and Mn concentrations of leachates at each cycle were measured, and multivariate statistical analysis was applied to research the effect of temperature on heavy metals leaching from tailings in the Arctic area. The results showed that higher temperatures encouraged tailings to oxidation and sulfuration of and promoted heavy metal release from the tailings through precipitation and erosion. Ni, Zn and Mn have similar releasing resources from tailings and positive correlation in the leaching activity. Rising temperature accelerated Fe leaching; Fe leaching promoted leaching of the other metals, especially of Mn. Appropriately increase temperature will accelerate oxidization and sulfidization of the tailings, promote acid generation and increase TDS and, finally, promote the release of heavy metals. Climate change, with rising temperatures increasing the risk of heavy metals leaching from the tailings, should be given greater attention. Keeping tailings away from the appropriate temperature and in a higher alkalinity is a good method to control the leaching of heavy metals from tailings.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81630699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experiment and parameter optimization of an automatic row following system for the traction beet combine harvester","authors":"Shenying Wang, Xuemei Gao, Zhao You, Baoliang Peng, Huichang Wu, Zhichao Hu, Yongwei Wang","doi":"10.25165/j.ijabe.20231601.7245","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.7245","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"20 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75601288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.25165/j.ijabe.20231601.7810
Yan Li, G. Che, Lin Wan, Qilin Zhang, Tianqi Qu, F. Zhao
{"title":"Characteristics and mathematical models of the thin-layer drying of paddy rice with low-pressure superheated steam","authors":"Yan Li, G. Che, Lin Wan, Qilin Zhang, Tianqi Qu, F. Zhao","doi":"10.25165/j.ijabe.20231601.7810","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.7810","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"59 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84603902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.25165/j.ijabe.20231601.7574
Haoyu Yang, J. Wu, Chenyao Guo, Hang Li, Zhe Wu
{"title":"Effects of geotextile envelope and perforations on the performance of corrugated drain pipes","authors":"Haoyu Yang, J. Wu, Chenyao Guo, Hang Li, Zhe Wu","doi":"10.25165/j.ijabe.20231601.7574","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.7574","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"28 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85249241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.25165/j.ijabe.20231601.7309
Luyu Ding, L. E, Yang Lyu, Chunxia Yao, Qifeng Li, Shiwei Huang, Weihong Ma, Ligen Yu, Ronghua Gao
{"title":"Estimating the air exchange rates in naturally ventilated cattle houses using Bayesian-optimized GBDT","authors":"Luyu Ding, L. E, Yang Lyu, Chunxia Yao, Qifeng Li, Shiwei Huang, Weihong Ma, Ligen Yu, Ronghua Gao","doi":"10.25165/j.ijabe.20231601.7309","DOIUrl":"https://doi.org/10.25165/j.ijabe.20231601.7309","url":null,"abstract":"","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":"11 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87227606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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