Study Correlation Wear Rate Measurement Technique of Flared Chisel Bucket Teeth Using 3D Scan Imaging and ASTM G105

The aim of this study is searching a new method to provide wear rate measurement which simple and have better accuracy that occur in worn mining component surface addressed like flare chisel bucket teeth. Having correlation between Wet Sand Abrasion Test ASTM G105 and 3D scan modeling of worn surface, the validation of a new method to provide wear rate measurement using 3D scan technology would be elaborated. The preliminary study to provide wear rate measurement using 3D scan imaging have been established. The study related volume comparison by which 3d scan imaging process generated and buoyancy. Specimens were abraded using Wet Sand Abrasion Test ASTM G105 to provide specimen in certain percentage of volume loss. Several specimens consist of different percentage of volume loss were prepared. Specimens measured its volume over buoyancy and 3D scan imaging in two grade of meshing which are normal and smooth. Both of volume generated from 3D scan imaging compared to buoyancy volume measurement.  Study focused on dissimilarity among volume data generated. Analysis are carried out through the center and variability both 3D scan volume compared to buoyancy volume. The study shows that normal meshing has less dissimilarity level compare to smooth meshing. Both dissimilarity level span at -0.01% and -0.027% respectively. Higher mesh level tends to inaccurate volume measurement. Further study to determine suitable mesh level should be conduct in near future

Intelligent systems for volumetric feature recognition from CAD mesh models

This paper presents an intelligent technique to recognise the volumetric features from CAD mesh models based on hybrid mesh segmentation. The hybrid approach is an intelligent blending of facet-based, vertex based, rule-based, and artificial neural network (ANN)-based techniques. Comparing with existing state-of-the-art approaches, the proposed approach does not depend on attributes like curvature, minimum feature dimension, number of clusters, number of cutting planes, the orientation of model and thickness of the slice to extract volumetric features. ANN-based intelligent threshold prediction makes hybrid mesh segmentation automatic. The proposed technique automatically extracts volumetric features like blends and intersecting holes along with their geometric parameters. The proposed approach has been extensively tested on various benchmark test cases. The proposed approach outperforms the existing techniques favourably and found to be robust and consistent with coverage of more than 95% in addressing volumetric features

A Divide-and-Conquer Algorithm for Machining Feature Recognition over Network

In this paper, a divide-and-conquer algorithm for machining feature recognition over network is presented. The algorithm consists of three steps. First, decompose the part and its stock into a number of sub-objects in the client and transfer the sub-objects to the server one by one. Meanwhile, perform machining feature recognition on each sub-object using the MCSG based approach in the server in parallel. Finally, generate the machining feature model of the part by synthesizing all the machining features including decomposed features recognized from all the sub-objects and send it back to the client. With divide-and-conquer and parallel computing, the algorithm is able to decrease the delay of transferring a complex CAD model over network and improve the capability of handling complex parts. Implementation details are included and some test results are given

DETC2003/CIE-48228 THE DESIGN EXEMPLAR: THE FOUNDATION FOR A CAD QUERY LANGUAGE

ABSTRACT This paper seeks to identify the needs of a CAD-specific query language based upon an analysis of the essential characteristics and the tasks performed by traditional query languages. Query languages are non-procedural, high-level computer languages that are primarily focused towards retrieving data held in files and databases. They could also be used for updates, deletions, and additions Design engineers create models of design artifacts with commercial Computer Aided Design (CAD) solid modeling systems and manage the data files through Product Data Management (PDM) systems. These systems stop short of providing support for querying and retrieving data from "within" the CAD data files. A true CAD query language that allows designers the flexibility to describe queries against single and multiple CAD files would be of great benefit for design engineers. This query language ought to be both datacentric and user-centric in nature. The design exemplar, a datastructure that provides a standard representation of design knowledge based upon a general constraint validation and satisfaction algorithm, is shown here to be a concept upon which a CAD query language may be developed. The first required extension of the design exemplar is the inclusion of logical connectives. Some insights into the different levels at which the extensions may be implemented are discussed. Also, some applications retrieving geometric data using this query language are demonstrated. The query language, as it evolves, is expected to support geometric retrieval across domains and offer an all-purpose approach to geometric retrieval. The relational, or hierarchical, data model found in many legacy applications, and the query languages supporting this model, have solved problems facing most dat

Development of Feature Recognition Algorithm for Automated Identification of Duplicate Geometries in CAD Models

This research presents a feature recognition algorithm for the automated identification of duplicate geometries in the CAD assembly. The duplicate geometry is one of the seven indicators of the lazy parts mass reduction method. The lazy parts method is a light weight engineering method that is used for analyzing parts with the mass reduction potential. The duplicate geometry is defined as any geometries lying equal to or within the threshold distance with the user-defined orientation between them and have the percentage similarity that is equal to or greater than the threshold value. The feature recognition system developed in this research for the identification of duplicate geometries is also extended to retrieve the weighted bipartite graph of part connections for the assembly time estimation. The weighted bipartite graph is used as input for the part connectivity based assembly time estimation method. The SolidWorks API software development kit is used in this research to develop a feature recognition system in SolidWorks CAD software package using C++ programming language. The feature recognition system built in the SolidWorks CAD software uses a combination of topology and geometric data for the evaluation of duplicate geometry. The measurement of distances between the sampling points strategy is used for the duplicate geometry feature recognition. The feature recognition algorithm has three phases of evaluation: first, is the evaluation for threshold distance condition of parts in the CAD assembly. Second, the part pairs that have satisfied the threshold distance condition are evaluated for the orientation condition. The threshold distance and orientation are the necessary but not the sufficient conditions for duplicate geometries. In the third phase, the geometries that have satisfied orientation condition are evaluated for the percentage similarity condition. The geometries that satisfy the percentage similarity condition are highlighted in order to help designers review the results of the duplicate geometry analysis. The test cases are used to validate the algorithm against the requirements list. The test cases are designed to check the performance of the algorithm for the evaluation of the threshold distance, orientation, and percentage similarity condition. The results indicate that the duplicate geometry algorithm is able to successfully conduct all the three phases of evaluation. The algorithm is independent of the geometric type and is able to analyze planar, cylindrical, conical, spherical, freeform, and toroidal shapes. The number of sampling points generated on the faces of parts for the orientation and percentage similarity evaluation has the significant effect on the analysis time. The worst case complexity of the algorithm is the big O (nC2x m12 x m22x p4), where n = the number of parts in the assembly m1 = the number of faces in the parts that meet the threshold distance condition m2 = the number of faces that meet the orientation condition p = the number of sampling points on the face The duplicate geometry feature recognition approach is used to demonstrate the applicability in the extraction of assembly relations for the part connectivity based assembly time estimation method. The algorithm is also able to extract part connectivity information for the patterns. Further research is required to automate the identification of other laziness indicators in order to make the lazy parts method a completely automated tool. With regards to the complete automation of part connectivity based assembly time estimation method, the duplicate geometry feature recognition system needs integration with the algorithm for the computation of bipartite graph of part connections for the prediction of assembly time

Automated Volumetric Feature Extraction from the Machining Perspective

Master'sMASTER OF ENGINEERIN