基于机器视觉的非接触式土石方运输车辆智能计量方法

Machine Vision Based Non-contact Statistic Method for Truck Earthmoving Quantity

水利工程中土石方运输计量管理是顺利开展工程建设的重要保障。当前人工台账和停车称重计量方法,存在成本高、效率低、应用受限、人工错漏等问题,对此,基于机器视觉技术,提出了一种非接触式土石方车辆运输智能计量方法,可通过工程现场视频监控智能判别运输车辆的土石方装载状态,并配合车辆信息快速感知技术及计量管理数据库实现智能计量。该方法不影响运输效率、无需人工参与、利用工程监控系统,较现有方法在运行费、效率上具有优势。案例应用表明,深度学习后的机器视觉模型识别卡车装载状态速度快、准确率高,能够实现非接触土石方车辆运输智能计量。

Hydraulic engineering generally has large earthmoving demand,and dump-trucks are the main delivery machinery.Statistics of truck earthmoving quantity is important for project management.Manual ledger or weighbridge are currently the main approaches for truck earthmoving quantity statistics,which have shortcomings of human error,high cost,low efficiency and limited application.This paper proposes a machine vision based non-contact method for intelligent truck earthmoving quantity statistics.The method can recognize the loading conditions of empty/full for earthmoving trucks through site surveillance video images,and obtain the truck information with rapid sensing technology and database to achieve intelligent statistics.The method does not interfere earthmoving activities,is labor-free,and utilizes the field surveillance system,thus it possesses advantages to current methods in cost and efficiency.Case study shows that the proposed method can achieve non-contact intelligent truck earthmoving quantity statistics on field,and its deep-learned machine vision model has fast speed and good accuracy in recognizing empty/full loaded trucks.