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مدلسازی رفتار نیرو در فرآیند فرزکاری اتوماتیک استخوان کورتیکال گاو با استفاده از سیستم عصبی- فازی تطبیقی | ||
| نشریه مهندسی مکانیک امیرکبیر | ||
| مقاله 16، دوره 53، شماره 2 (Special Issue)، اردیبهشت 1400، صفحه 1287-1306 اصل مقاله (1.03 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/mej.2020.16766.6436 | ||
| نویسندگان | ||
| وحید طهماسبی* 1؛ امیرحسین ربیعی2؛ مهدی صفری3 | ||
| 1صنعتی اراک-مهندسی مکانیک | ||
| 2مهندسی مکانیک، دانشگاه صنعتی اراک | ||
| 3دانشگاه صنعتی اراک*مکانیک | ||
| چکیده | ||
| در این مقاله، یک سیستم استنتاج عصبی- فازی تطبیقی برای مدلسازی اثر پارامترهای مهم در فرزکاری استخوان کورتیکال شامل سرعت دورانی ابزار، نرخ پیشروی، عمق برش و قطر ابزار برای پیش‌بینی نیروهای برش مورد استفاده قرار گرفته است. به منظور مدلسازی رفتار نیروی فرآیند، آزمایش‌های تجربی بر روی استخوان تازه ران گاو صورت پذیرفته است. سپس از نتایج آزمایش‌های انجام‌شده برای آموزش و تست سیستم استنتاج، بهره گرفته شده است. در این مدل مهمترین پارامترهای فرزکاری اتوماتیک استخوان کورتیکال شامل سرعت دورانی ابزار، نرخ پیشروی، قطر ابزار و عمق برش به عنوان پارامترهای ورودی و نیروهای برش در سه جهت پیشروی، عمود بر پیشروی و عمود بر سطح استخوان و همچنین نیروی برآیند به عنوان خروجی در نظر گرفته شده‌اند. در این راستا، سیستم استنتاج عصبی- فازی تطبیقی بر مبنای 75 درصد از داده‌‌های آزمایشگاهی آموزش داده شده و از 25 درصد داده‌‌های باقیمانده به منظور تست درستی مدل بدست‌آمده استفاده شده است. دقت مدل بدست‌آورده‌شده با استفاده از نمودارهای مختلف و همچنین معیارهای آماری متعددی بررسی شده است. از نتایج بدست‌آمده مشخص می‌شود که شبکه عصبی-فازی تطبیقی در پیش‌بینی نیروهای برش در فرآیند سوراخکاری استخوان کورتیکال بسیار موفق عمل کرده‌است. | ||
| کلیدواژه‌ها | ||
| فرزکاری استخوان؛ استخوان کورتیکال؛ ماشینکاری؛ شبکه فازی- عصبی؛ نیروهای برش استخوان | ||
| عنوان مقاله [English] | ||
| Process modeling of force behavior in the automatic bovine cortical bone milling process using adaptive neuro-fuzzy inference system | ||
| نویسندگان [English] | ||
| Vahid Tahmasbi1؛ Amir Hossein Rabiee2؛ Mahdi Safari3 | ||
| 1صنعتی اراک-مهندسی مکانیک | ||
| 2mechanical engineering, arak university of technology | ||
| 3Department of Mechanical Engineering/Arak University of Technology | ||
| چکیده [English] | ||
| In this article, an adaptive neuro-fuzzy inference system is utilized to model the effect of important parameters in the cortical bone milling process including the rotational speed, feed rate, depth of cut and tool diameter to predict the cutting forces. To model the process force behavior, experimental tests are conducted on the fresh cow femur. Next, the results of performed experiments are used to train and test the inference system. In this model, the most influential parameters of automatic cortical bone milling process including the rotational speed, feed rate, tool diameter and depth of cut are taken as the input parameters, while the cutting forces in the feed direction, normal to the feed direction and normal to the bone surface as well as the resultant force are considered as the output. To this aim, the adaptive neuro-fuzzy inference system relies on 75% of the trained laboratory data and the remaining 25% to test the model validation. The accuracy of the obtained model is investigated using different diagrams and numerous statistical criteria. The results indicate that the adaptive neuro-fuzzy network has shown a successful performance in predicting the cutting forces of cortical bone milling process. | ||
| کلیدواژه‌ها [English] | ||
| Bone milling, Cortical bone, Machining, Neuro-fuzzy Network, Bone cutting forces | ||
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| مراجع | ||
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