A Study of 3D CAD Model and Feature Analysis for Casting Object (original) (raw)

3D Cad Models And Its Feature Similarity

2009

Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Pose Estimation using 1D Fourier Transform and Euclidean Distance Matching of CAD Model and Inspected Model Part

IOP Conference Series: Materials Science and Engineering, 2016

This paper present pose estimation relation of CAD model object and Projection Real Object (PRI). Image sequence of PRI and CAD model rotate on z axis at 10 degree interval in simulation and real scene used in this experiment. All this image is go through preprocessing stage to rescale object size and image size and transform all the image into silhouette. Correlation of CAD and PRI image is going through in this stage. Magnitude spectrum shows a reliable value in range 0.99 to 1.00 and Phase spectrum correlation shows a fluctuate graph in range 0.56-0.97. Euclidean distance correlation graph for CAD and PRI shows 2 zone of similar value due to almost symmetrical object shape. Processing stage of retrieval inspected PRI image in CAD database was carried out using range phase spectrum and maximum magnitude spectrum value within tolerance. Additional processing stage of retrieval inspected PRI image using Euclidean distance within tolerance also carried out. Euclidean matching shows a reliable result compared to range phase spectrum and maximum magnitude spectrum value by sacrificing more than 5 times processing time.

Surface defect identification and measurement for metal castings by vision system

Manufacturing Letters, 2018

An inspection system based on vision technology was developed to identify defects on the surface of a metal part produced by a casting process. In the proposed methodology, binary images of the bright and dark regions of the surface are first obtained. Connected components of these images are processed to find the shadows originated from defects. The algorithm to process the binary images was implemented on a Jetson TK1 board, and programmed in CUDA. The setup performs the computation in 900 ms for images of 5 megapixels, and the connected components algorithm is three times faster compared to commercial software running on a CPU. The parameters to find the shadows are independent of the field of view and resolution, i.e., the quantities that relate the two binary images can be expressed in pixels.

Automatic Inspection of Aeronautical Mechanical Assemblies by Matching the 3D CAD Model and Real 2D Images

Journal of Imaging

In the aviation industry, automated inspection is essential for ensuring quality of production. It allows acceleration of procedures for quality control of parts or mechanical assemblies. As a result, the demand of intelligent visual inspection systems aimed at ensuring high quality in production lines is increasing. In this work, we address a very common problem in quality control. The problem is verification of presence of the correct part and verification of its position. We address the problem in two parts: first, automatic selection of informative viewpoints before the inspection process is started (offline preparation of the inspection) and, second, automatic treatment of the acquired images from said viewpoints by matching them with information in 3D CAD models is launched. We apply this inspection system for detecting defects on aeronautical mechanical assemblies with the aim of checking whether all the subparts are present and correctly mounted. The system can be used durin...

Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process

Advances in Materials Science and Engineering, 2017

Advanced vision solutions enable manufacturers in the technology sector to reconcile both competitive and regulatory concerns and address the need for immaculate fault detection and quality assurance. The modern manufacturing has completely shifted from the manual inspections to the machine assisted vision inspection methodology. Furthermore, the research outcomes in industrial automation have revolutionized the whole product development strategy. The purpose of this research paper is to introduce a new scheme of automation in the sand casting process by means of machine vision based technology for mold positioning. Automation has been achieved by developing a novel system in which casting molds of different sizes, having different pouring cup location and radius, position themselves in front of the induction furnace such that the center of pouring cup comes directly beneath the pouring point of furnace. The coordinates of the center of pouring cup are found by using computer vision...

Feature Descriptors Applied to Slag Characterization on Casting Process

Regular Issue, 2020

Vision systems are increasingly entering the field of metallurgy, carrying out operations where a human operator is not possible due to the process conditions. The purpose of these systems is the monitoring and control of the process to improve the quality and manufacturing of the products. Nevertheless, the amount of slag, the presence of gases and high temperatures are the main problems that make this task difficult. In this proposal the characterization of the slag is treated, through the analysis of the light changes with the functions of Fourier and Gabor, which allow to identify or locate the location of the slag in the material, so that, in future works the slag It can be segmented, measured or used to detect the level of the metal in the refractory. In addition, results obtained when evaluating sensitivity and precision curves are presented, with which the information recovered by the algorithms is evaluated.

A A R C H I V E S The use of optical scanning for analysis of casting shape

In the paper the use of optical scanning for inspection of casting shape and its accuracy was described. Optical system applied to digitization of objects determines all dimensions and shape of inspected object. This technology is used in quality control and reverse engineering. System is based on triangulation: sensor head performs projection of different patterns of fringes onto measured object and scanner tracks their distribution with two cameras. Basing on optical transform equations, a processing unit automatically and with remarkable accuracy calculates 3D coordinates for every pixel of camera. Depending on camera resolution the result of such a scan is a cloud of points with up to 5 million points for every image. In the paper examples of applications for castings with different designation was presented.

Improving Productivity and Quality in Manufacturing by Applying Computer Vision Systems (Image Processing Technique

Automated inspection systems is the target for all automated organizations. The objective zero defect considers as a challenge for many industries since there are many factors effect on production line. Increase scrape items effect on productivity and environment; rework produced items as bottle neck for production lines and decrease products rates. The objectives for the research project focused on four main concerning, Evaluate automated inspection and control system in manufactures. Redesign online inspection system for some industrial case studies for the purpose of enhancing Quality control, tracking quality control in manufacturing systems and embedded improving computer vision systems in the production lines levels, and reduce defect items by correct parameters during the production lines. Research project focused on some case studies like (plastic, hot stamping, assembly, and textile) industries in Malaysia and Iraq. Computer vision systems was the common methods since it considers as non-destruction testing system. One of the machine vision systems techniques is image processing technique. Image processing algorithm implement by using MATLAB and Simulink. The developed points in this research focused on interpret defects and signal feedback for correcting deviations in the setting parameter for the fabrication machines. This system will help manufacturers to understand faults for their products online during fabrication route. Three main functions were using feature matching, color recognition and orientation and recognize the object functions. The results for this system showed that the ability for the system to know the weak points in the produced items and the production systems and accurate them with keeping on the stability for the automated system. Growth in information technology and cameras will improve system capabilities in different fields and adaptable for heavy environments.

A Comparative Study on Extraction and Recognition Method of CAD Data from CAD Drawings

2009 International …, 2009

In recent years, various researchers have put in great effort to produce an efficient method of drawing extraction. This paper will focus on CAD data extraction from CAD drawing and study the method that has been proposed by previous researchers. CAD data extraction became a popular research since the early 80's. Nowadays, most applications in engineering field are already computerized. This includes the CAD application system, the systems used by engineers to design their products. As the use of computerized application became important tool in engineering field, the production field is also affected. This raises the issue of integrating CAD with manufacture systems. For that reason, most researchers try to create a system that can extract meaningful information from the CAD drawing and create a connection between CAD and manufacture system. For example in manufacturing field, manufacture system is a machine system where it is also known as CAM systems. However, there is no direct connection from CAD system to CAM system. Therefore, many approaches have been proposed by the previous researchers to solve the issues. Focus on this paper is to study the approaches and make comparison among it. Finding from this paper is suitable approach can be used for next stage in this research.

A new methodology for extracting manufacturing features from CAD system

Computers & Industrial Engineering, 2006

In recent years, various researchers have come up with different ways and means to integrate CAD and CAM. Automatic feature recognition from CAD solid systems highly impacts the level of integration. CAD files contain detailed geometric information of a part, which are not suitable for using in the downstream applications such as process planning. Different CAD or geometric modeling packages store the information related to the design in their own databases. Structures of these databases are different from each other. As a result no common or standard structure has been developed so far, that can be used by all CAD packages. For that reason this paper proposes an intelligent feature recognition methodology (IFRM) to develop a feature recognition system which has the ability to communicate with various CAD/ CAM systems. The proposed methodology is developed for 3D prismatic parts that are created by using solid modeling package by using CSG technique as a drawing tool. The system takes a neutral file in Initial Graphics Exchange Specification (IGES) format as input and translates the information in the file to manufacturing information. The boundary (B-rep) geometrical information of the part design is then analyzed by a feature recognition program that is created specifically to extract the features from the geometrical information based on a geometric reasoning approach by using object oriented design software which is included in C++ language. A feature recognition algorithm is used to recognize different features of the part such as step, holes, etc. Finally, a sample application description for a workpiece is presented for demonstration purposes.