نشریه علوم و مهندسی سطح

نشریه علوم و مهندسی سطح

مروری بر انفورماتیک تریبولوژی و دستاوردهای حاصله از به‌کارگیری یادگیری ماشین در پژوهش‌های تریبولوژی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 گروه مهندسی مواد، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان، ایران
2 دانشگاه بوعلی سینا همدان
3 وان کیو بیت، ونکوور، کانادا
چکیده
داده‌های متنوع و مختلفی مربوط به خواص و ویژگی‌های تریبولوژیکی وجود دارند که در قالب‌های متنوعی از جمله مقالات علمی، اسناد فنی و پایگاه‌های داده پراکنده هستند. این داده‌ها می‌توانند برای حل مسائل پیچیده مرتبط با تریبولوژی، مانند بررسی رابطه بین ساختار و خواص مواد در سطوح تحت اصطکاک و سایش مورد استفاده قرار گیرند. انفورماتیک تریبولوژی با ترکیب تریبولوژی و انفورماتیک به چگونگی به‌کارگیری دانش و ابزارهای تحلیل این داده‌های مختلف به‌منظور استفاده از آنها در بررسی مسایل تریبولوژی می‌پردازد. یادگیری ماشین که یکی از زیرمجموعه‌های هوش مصنوعی است، ابزارهای توانمندی در تحلیل داده‌های پیچیده و کشف روابط چند بعدی بین‌ داده‌ها داشته و می‌تواند درک بهتری از ویژگی‌ها و فرآیندهای تریبولوژیکی ارائه دهد. در این مقاله پس از تشریح مفهوم انفورماتیک تریبولوژی، الگوریتم‌های اصلی یادگیری ماشین که توسط پژوهشگران در مطالعه‌های مختلف به‌منظور تحلیل داده‌های تریبولوژیکی استفاده شده است، به طور خلاصه مرور شده‌اند. در ادامه، پژوهش‌هایی که تا کنون در زمینه انفورماتیک تریبولوژی انجام شده‌اند، بررسی شده است. در این پژوهش‌ها از ابزارهای یادگیری ماشین جهت ارتباط‌دهی بین عواملی مانند ترکیب شیمیایی ماده، فرایند ساخت یا خواص مکانیکی با خواص تریبولوژیک به‌ویژه نرخ سایش و ضریب اصطکاک استفاده شده است. نتایج گزارش‌شده در این مطالعات، قابلیت یادگیری ماشین در پیش‌‌بینی خواص تریبولوژیک با دقت‌هایی تا حدود 90 درصد را نشان می‌دهد. چنین دقت‌هایی می‌تواند کارگشا بودن یادگیری ماشین در توسعه دانش تریبولوژی و حل برخی مسایل پیچیده در این زمینه را نشان دهد.
کلیدواژه‌ها

موضوعات


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