Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Reverse engineering


Computer Reverse Engineering for Reproducing Spur Gears using Digital Image Processing (DIP) Technique

Mohanad Qusay Abbood

Engineering and Technology Journal, 2016, Volume 34, Issue 5, Pages 973-982

Reverse Engineering (RE) is a technique that uses different approaches to obtain characteristic data of a physical object for which no drawings, documentations or computer models are available. This paper presents an experimental approach of reverse engineering for reconstructing the spur gears. 3D CAD model is made using digital image processing (DIP). Gears have been scanned using a single digital camera. The digitized data of spur gears was collected and processed using MATLAB package with Digital image processing (DIP) technique. It is worth mentioning that the accuracy of the modeling process of given piece depends on the number of points that are captured on the work piece surface. This proposed method is the best tool used in reverse engineering because it is faster and more accurate than the method used the coordinate measurement machines (CMMs). To confirm the effectiveness of the proposed method a comparison is madeusing image processing between the first data of spur gears and the data from the manufactured gears. The obtained results indicated that the proposed digital image processing system is an accurate and reliable reverse engineering for reproducing Spur gears using inexpensive equipment.

A New Method For Three Dimensional Cubic Bezier Surface Reconstruction Based On Matching The Surface Framework

Wissam K. Hamdan

Engineering and Technology Journal, 2010, Volume 28, Issue 8, Pages 1654-1671

Numerous efforts have been directed to convert the physical model ( in-hand
model) to a computer model. This work is dedicated for the cubic Bezier surface
reconstruction based on finding the positions of the sixteen control points that form the
surface of the product. The idea is based on inverse progressive search (IPS) method
rather than the approximate surface fitting method already used in previous researches.
The presented method is based on three successive steps:(a) converting the continuous
coordinate measuring machine (CMM) data to discrete data,(b) estimating the
positions of the 12 boundary control points and (c) estimating the positions of the 4
intermediate control points to generate the intended surface. To show the feasibility of
the suggested method two experimental examples are conducted. The results show the
validity and effectiveness of the method from the accuracy and computation time point
of view.