شناسایی هندسه آسیب در قطعات با کمک تصویربرداری و فتوگرامتری با استفاده از روش‌های هوشمند

نوع مقاله : مقاله پژوهشی

نویسندگان

مجتمع مواد و فناوری‌های ساخت، دانشگاه صنعتی مالک اشتر، تهران، ایران

چکیده

مشخص شدن هندسه و حجم دقیق آسیب در قطعات تحت بازسازی و تعمیر با فرایند رسوب نشانی مستقیم لیزری نقش مهمی در بهبود کیفیت تعمیر قطعه با این روش دارد. در این مقاله یک روش شناسایی آسیب قطعات با استفاده از روش‌ها و ابزارهای هوشمند ارائه شده است. در این روش ابتدا با استفاده از فتوگرامتری و سپس با خوشه‌بندی، محدوده‌ی آسیب روی ابر نقاط قطعه‌ی آسیب‌دیده تعیین می‌شود. مقدار حجم آسیب با انطباق یک صفحه بر روی مرز آسیب با سطح که حجم بین سطح داخلی آسیب و صفحه منطبق بر آن را محصور می‌کند محاسبه شده است. خوشه‌بندی ابر نقاط با روش کا میانگین انجام شده و انطباق صفحه و ابر نقاط با استفاده از ویژگی‌های تصویر بخش‌بندی شده‌ی قطعه، شامل مرکز آسیب و خط لبه‌ی بالایی مدل انجام شد. بخش‌بندی تصویر با روش ماسک ار سی ان ان و جداسازی هر نوع اشیاء انجام شده است. پس از طی مراحل فوق، مسیر ابزار رسوب نشانی در حجم حاصل‌شده ایجاد و به مکانیسم شبیه‌سازی‌شده برای بازوی ربات به‌منظور حرکت سامانه رسوب نشانی لیزری داده‌ شده است. از این روش برای آسیب‌های کوچک به‌خصوص در مواردی که از قطعه، نمونه‌ی سالمی وجود ندارد می‌توان استفاده نمود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Geometrical Identification of Defect in Parts Using Imaging and Photogrammetry Using Intelligent Methods

نویسندگان [English]

  • Mohammad Esfandyari
  • Ahmad Reza Khoogar
  • Reza Shoja Razavy
  • Masoud Barekat
Faculty of Material and Manufacturing Technologies, Malek Ashtar University of Technology
چکیده [English]

This paper presents a damage identification method for components using intelligent techniques and tools. In this method, the damaged area on the point cloud of the affected component is first determined using photogrammetry, followed by clustering. The damage volume is calculated by fitting a plane to the damage boundary, enclosing the volume between the internal damaged surface and the fitted plane. The point cloud clustering is performed using the K-means method, while plane fitting and point cloud alignment are achieved using features from the segmented image of the component, including the damage center and the upper edge line of the model. Image segmentation is carried out using Mask R-CNN to isolate different objects. After completing the above steps, the toolpath for deposition is generated within the resulting volume and fed into a simulated robotic arm mechanism to guide the laser deposition system. This method is particularly useful for small-scale damage, especially in cases where an undamaged reference sample of the component is unavailable.

کلیدواژه‌ها [English]

  • Laser Direct Deposition
  • Identifying the Geometry of Damaged Parts
  • 4dDOF Robot
  • Geometry of Damages
  • Photogrammetry
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