기존 측정점 재사용을 위한 유사도 기반의 CAIP 시스템 개발
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 양정삼 | - |
dc.contributor.author | 전혜성 | - |
dc.date.accessioned | 2018-11-08T08:16:28Z | - |
dc.date.available | 2018-11-08T08:16:28Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.other | 21627 | - |
dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/12153 | - |
dc.description | 학위논문(석사)--아주대학교 일반대학원 :산업공학과,2016. 2 | - |
dc.description.tableofcontents | Chapter 1. Introduction 1 Chapter 2. Related Works 4 2.1 Comparison with similar models 4 2.2 Computer Aided Inspection Planning(CAIP) 8 Chapter 3. Similarity analysis for model 11 3.1 Overview 11 3.2 Creating feature vectors 14 3.3 How to compare similarity between feature vectors 19 Chapter 4. Creating measurement path 22 4.1 Reusing measurement points of similar models 22 4.2 Creating measurement path 25 Chapter 5. System implementation and experiment 29 5.1 System implementation 29 5.2 Experiment 32 Chapter 6. Conclusion 36 Bibliography 38 국문요약 40 | - |
dc.language.iso | eng | - |
dc.publisher | The Graduate School, Ajou University | - |
dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
dc.title | 기존 측정점 재사용을 위한 유사도 기반의 CAIP 시스템 개발 | - |
dc.title.alternative | Development of Similarity Based CAIP System to Reuse Measuring Points | - |
dc.type | Thesis | - |
dc.contributor.affiliation | 아주대학교 일반대학원 | - |
dc.contributor.department | 일반대학원 산업공학과 | - |
dc.date.awarded | 2016. 2 | - |
dc.description.degree | Master | - |
dc.identifier.localId | 739495 | - |
dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000021627 | - |
dc.subject.keyword | Similarity comparison | - |
dc.subject.keyword | OMM(On-Machine Measurement) | - |
dc.subject.keyword | Inspection feature | - |
dc.subject.keyword | Measuring point | - |
dc.subject.keyword | Collision detectSimilarity comparison | - |
dc.subject.keyword | Collision detect | - |
dc.description.alternativeAbstract | On-Machine Measurement (OMM), which measures workpieces where machining is progressing or finished in CNC machining center, has its own strength that is capable of measuring workpieces directly in work space without moving them. However, planning of measurement to determine measurement sequence and elements for each shape of complicated objects has its limitation requiring time-consuming tasks to generate measurement points mostly relying on skills of workers on site. This paper will suggest how to apply an existing and highly similar model’s measurement paths to a new model by analyzing similarity between existing 3D shapes whose measurement path are built and new models. For the purposes of similarity analysis, this paper extracted feature vectors from 3D shapes models which are able to express characteristics of shape models and then applied this feature vectors to histogram of probability distribution based on algorithm of similarity analysis. In addition, this paper developed CAIP system by correcting unapplied measurement points, which are generated by minute difference between two models when their similar measurement points are applied to a new model and then generate final measurement paths. | - |
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