题名

營建生產作業行為自動辨識系統

并列篇名

MOTION-SENSING IDENTIFICATION SYSTEM FOR CONSTRUCTION OPERATION

DOI

10.6652/JoCICHE.202003_32(1).0007

作者

楊廷曄(Ting-Yeh Yang);薛憲徽(Sian-Jhen Syue);曾仁杰(Ren-Jye Dzeng)

关键词

營建自動化 ; 作業行為辨識 ; 深度攝影 ; 體感姿態感測 ; construction automation ; work posture analysis ; depth camera ; motion sensing

期刊名称

中國土木水利工程學刊

卷期/出版年月

32卷1期(2020 / 03 / 01)

页次

75 - 90

内容语文

繁體中文

中文摘要

生產效率評估有助於營造廠商評估勞力成本以及規劃作業工期,現行有現場工作抽樣、DEA資料包絡分析等方法可使用,然而這些方法皆屬事後分析(非直接即時量測生產過程),亦需仰賴人為判斷,以及有限可供人工處理之採樣頻率。本研究以深度攝影技術補捉工人之骨骼節點,並建立演算法及系統,根據工人姿態辨識其是否有在生產。當生產作業(如模板)己知時,並可進一步自動辨識其子項作業類別(如模板組立、釘模板)。研究並針對常見施工作業,包含鋼筋綁紮、模板組立、搬運作業、讀圖溝通、砌磚作業、磁磚鋪貼六項生產作業,評估系統之辨識準確率。結果顯示,在已知受測者之作業類別(如已知進行模板組立中)時,在已知狀態下,系統針對上述各作業之生產行為之辨識準確率依序為92.23%、80.19%、90.82%、90.65%、62.24%和94.40%。

英文摘要

Productivity assessment helps contractors estimate labor cost and activity duration. Some methods such as work sampling or Data Envelope Analysis can be used to assess productivity. However, they are post-analyzed based on recorded video of construction activities instead of real-time assessment. Their base upon human judgment also limits the feasible sampling rate of the video. This research uses depth cameras to capture joints of human skeleton and builds a system to automatically determine whether a subject's posture is a productive or nonproductive in a real time fashion. When the target activity (e.g., formwork) is known, the system may further categorize the subject's posture into the associated sub-activities (e.g., formwork assembly, formwork nailing). Experiments, which targeted on common construction activities including rebar assembly, formwork assembly, moving materials, reading blueprints, laying bricks, and tiling, were conducted to evaluate the identification accuracy. The results show that accuracies are 92.23%, 80.19%, 90.82%, 90.65%, 62.24%, and 94.40%, respectively.

主题分类 工程學 > 土木與建築工程
工程學 > 水利工程
工程學 > 市政與環境工程
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被引用次数
  1. 薛憲徽,劉家喻,曾仁杰(2021)。利用穿載式傳感訊號辨識營建施工人員作業行為之機器學習模型。中國土木水利工程學刊,33(8),629-639。