Journals / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi / 2019 / Cilt: 21 - Sayı: 63

Developing a Cross-Section Model by K-Means Clustering Algorithm for Determining the Underground Deformations

Yeraltı Deformasyonlarının Belirlenmesi Amacıyla KOrtalamalar Kümeleme Algoritması Kullanılarak Kesit Model Geliştirilmesi

Pages
707–717
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The deformation results of k-means algorithm and mesh models have been compared and advantage of k-means algortihm has been revealed.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The scientific studies on determination of deformations for underground structures by terrestrial laser scanner have been developing with the increasing of the usage of terrestrail laser scanners in underground structures.
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Key Findings & Data:One of the most known research subject is the determination of deformation from the cross-sections which derived from point clouds acquired by terrestrail laser scanners.
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Conclusion & Impact:The deformation results of k-means algorithm and mesh models have been compared and advantage of k-means algortihm has been revealed.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The scientific studies on determination of deformations for underground structures by terrestrial laser scanner have been developing with the increasing of the usage of terrestrail laser scanners in underground structures. One of the most known research subject is the determination of deformation from the cross-sections which derived from point clouds acquired by terrestrail laser scanners. Because of the difficulty of proccessing the thousand of points on cross sections developing a best-fit cross-section model from raw data has been studied by many researchers in recent years. In this study first a new cross-section model has been developed by using k-means clustering machine learning algorithm from a raw point cloud data then deformation analyses have been carrried out on these models. Also mesh models have been created from point cloud data and a standard deformation study have been performed on mesh models. The deformation results of k-means algorithm and mesh models have been compared and advantage of k-means algortihm has been revealed.

Özet

Yersel lazer tarayıcıların yeraltı yapılarındaki deformasyonların belirlenmesi amacıyla kullanımının son yıllarda hızla artmasıyla bu alandaki bilimsel çalışmalarda buna paralel olarak artmaktadır. Bu çalışmalardan biri de lazer tarayıcı ile elde edilen nokta bulutu verileri üzerinden alınan kesitlerden üzerinden yapılan deformasyon çalışmalarıdır. Nokta bulutu üzerinden alınan kesitler üzerindeki binlerce veriden analiz yapmanın zorluğundan dolayı kesiti en iyi temsil eden kesit model oluşturma yöntemi son yıllarda bir çok araştırmanın konusu olmaktadır. Bu çalışmada da yersel lazer tarayıcı ile taranmış olan bir yeraltı galerisinde nokta bulutu verileri üzerinden alınan kesitler üzerinden kortalamalar makina öğrenme algoritması yeni bir kesit modeli oluşturulmuş ve bu kesit model üzerinden deformasyon analizleri yapılmıştır. Yapılan analizler mevcut yöntemlerden olan meshlenmiş yüzeyler üzerinden yapılan analizlerle karşılaştırılmış ve geliştirilen yöntemin üstünlükleri ortaya konmuştur.

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Cite This Article

ÖZDOĞAN, M. V. (2019). Developing a Cross-Section Model by K-Means Clustering Algorithm for Determining the Underground Deformations. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi, Cilt: 21 - Sayı: 63, 707–717. https://ajindex.com/articles/222225

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References (2)

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