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پیشبینی نیروهای وارد بر شاخه و مصرف سوخت تراکتور تحت شرایط کاری متفاوت حین عملیات زیرشکنی با استفاده از سیستم استنتاج عصبی فازی (ANFIS) | ||
| تحقیقات سامانه‌ها و مکانیزاسیون کشاورزی | ||
| مقاله 5، دوره 21، شماره 74، شهریور 1399، صفحه 47-66 اصل مقاله (1.54 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/erams.2018.122163.1262 | ||
| نویسندگان | ||
| محمد عسکری* 1؛ یوسف عباسپور گیلانده2 | ||
| 1پسادکترای مکانیک ماشین های کشاورزی، گروه مهندسی بیوسیستم، دانشکده کشاورزی و منابع طبیعی، ، دانشگاه محقق اردبیلی، اردبیل، ایران | ||
| 2استاد گروه مهندسی بیوسیستم، دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران | ||
| چکیده | ||
| در این تحقیق، از سیستم استنتاج عصبی فازی (ANFIS) به منظور پیشبینی نیروهای وارد بر شاخه و مصرف سوخت تراکتور تحت شرایط کاری متفاوت حین عملیات زیرشکنی استفاده شد. نیروهای مقاوم افقی و عمودی وارد بر شاخههای زیرشکن و مصرف سوخت تراکتور تحت تأثیر متغیرهای مستقل شامل نوع شاخه (زیرشکن و پاراپلو)، عمق (30، 40 و50 سانتیمتر) و سرعت پیشروی (1/8، 2/3، 2/9 و 3/5 کیلومتر بر ساعت) اندازه گیری شدند. از داده های مزرعه ای برای ایجاد مدل های رگرسیونی و انفیس به منظور پیش بینی پارامترهای تحت بررسی استفاده و نتایج دو سری مدل با یکدیگر مقایسه شد. نتایج بررسی های مزرعه ای نشان داد که همۀ متغیرهای مستقل اثر معنی داری بر پارامترهای تحت بررسی دارند. افزایش عمق خاکورزی و سرعت پیشروی به افزایش نیروهای مقاوم افقی و عمودی وارده و مصرف سوخت تراکتور انجامید. به علاوه، پاراپلو از نظر انرژی موردنیاز نسبت به زیرشکن، مقرون به صرفه تر بود. نتایج بخش انفیس نشان داد که در مورد نیروهای افقی، عمودی و مصرف سوخت، به ترتیب، توابع عضویت Gaussmf، Trimf و dsigmf با میانگین مربعات خطای 0/0156، 0/0231 و 0/0212 و ضریب همبستگی 0/999، 0/989 و 0/991، بهترین مدل ها برای پیش بینی هستند. مدل های انفیس نسبت به مدل های رگرسیونی دقت بالاتری دارند و با استفاده از سطوح شکل های خروجی در انفیس می توان خروجی مدل را برای یک ورودی خاص محاسبه کرد. | ||
| کلیدواژه‌ها | ||
| انفیس؛ زیرشکن؛ مصرف انرژی؛ مقاومت کششی | ||
| عنوان مقاله [English] | ||
| Predicting the Imposed Forces on the Tines and Tractor Fuel Consumption during Subsoiling Operation Using Adaptive Neuro-Fuzzy Inference System (ANFIS) | ||
| نویسندگان [English] | ||
| Mohammad Askari1؛ Yousef Abbaspour-Gilandeh2 | ||
| 1Post Doc of mechanics of agricultural machinery, Biosytem Engineering Department. Faculty of agriculture and natural resources, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| 2Professor, Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili. Ardabil, Iran | ||
| چکیده [English] | ||
| In this research, the adaptive neuro-fuzzy inference system was used for predicting the imposed forces on the tines and tractor fuel consumption during subsoiling operation. The draft and vertical forces imposed on subsoiling tines and tractor fuel consumption were measured under the effect of tine type (subsoiler and paraplow), tillage depth (30, 40 and 50 cm) and forward speed (1.8, 2.3, 2.9 and 3.5 km/h). The field data were used to create the regression and ANFIS models for predicting the studied parameters; the results obtained from applying two models were compared with each other. The field results showed that all independent variables were effective on the studied parameters. Increase in forward speed and tillage depth resulted increase in draft force, vertical forces, and also fuel consumption. Moreover, from the point of consumption of fuel, the paraplow tine was more profitable than subsoiler tine. The results of ANFIS part showed that draft force, vertical force, and fuel consumption, the membership functions of Gaussmf, Trimf and dsigmf, with the mean square error of 0.0156, 0.0231 and 0.0212 also correlation coefficient of 0.999, 0.989 and 0.991, respectively, were the best models for prediction. ANFIS models were found more accurate than regression models, and it could be possible to calculate the model outlet for a special inlet using ANFIS outlet surfaces. | ||
| کلیدواژه‌ها [English] | ||
| ANFIS, Draft force, Energy consumption, Subsoiler | ||
| مراجع | ||
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