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首页> 外文会议>Waste management 2004 symposium (WM'04): waste management, energy security and a clean environment >REMOTE SITE MONITORING FOR LONG TERM STEWARDSHIP:AN APPLICATION OF MACHINE VISION AT THE DOE MIAMISBURG CLOSURE PROJECT,MOUND SITE,OHIO
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REMOTE SITE MONITORING FOR LONG TERM STEWARDSHIP:AN APPLICATION OF MACHINE VISION AT THE DOE MIAMISBURG CLOSURE PROJECT,MOUND SITE,OHIO

机译：长期监理的远程站点监视：机器视觉在美国俄亥俄州DOE MIAMISBURG关闭项目中的应用

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MSE Technology Applications,Inc.(MSE)is demonstrating machine vision technology for automated remote site monitoring at the U.S.Department of Energy(DOE)Miamisburg Closure Project(MCP) Mound Site in Miamisburg,Ohio.The machine vision system will monitor soil intrusion and or disturbances,erosion,and subsidence.Additionally,the machine vision system will monitor part of a remediation activity.The demonstration has two parts:design and installation of the hardware,and development and optimization of the machine vision algorithms. rnThe machine vision hardware installed at Mound includes three digital cameras;a secure wireless data transfer network;and a computer for image processing,storage,and retrieval.Power for the machine vision system comes from both 120-volt ac electrical power and a 12-volt dc solar panel and battery system. rnThe machine vision image-processing algorithm subtracts one image from another image to identify regions where change has occurred.The image-processing algorithm can provide the image coordinates where the change occurred and magnitude of the area on the image that has changed.If the identified change meets some pre-defined criteria,the algorithm can initiate a response(i.e.,automated email, phone call,etc.). rnMSE has identified several issues associated with automated monitoring of remote areas using machine vision.These are based on the preliminary demonstration results,which show a significant amount of change occurring across the sites.The majority of the changes observed occur because of irrelevant factors or noise.Irrelevant noise in the images may include insects on camera lenses;variable lighting, due to clouds and or changing positions of the sun;and variable weather,such as snow,rain,and wind. To address these issues,MSE is exploring techniques such as averaging images over a time window and normalizing the light intensity of images.We expect these additional processing steps to improve the detection of relevant change(s)and reduce the number of false alarms generated by the machine vision system.
机译：MSE Technology Applications，Inc。（MSE）正在美国俄亥俄州能源部（Miamisburg Closure Project）（MCP）土墩工地的美国能源部（DOE）演示用于自动远程站点监控的机器视觉技术。该机器视觉系统将监视土壤入侵和此外，机器视觉系统还将监视部分修复活动。该演示包括两个部分：硬件的设计和安装以及机器视觉算法的开发和优化。 rn土墩安装的机器视觉硬件包括三个数码相机；一个安全的无线数据传输网络；以及用于图像处理，存储和检索的计算机。机器视觉系统的电源来自120伏交流电源和一个12伏交流电源。伏特直流太阳能电池板和电池系统。 rn机器视觉图像处理算法从另一幅图像中减去一张图像以识别发生变化的区域。该图像处理算法可以提供发生变化的图像坐标和已改变图像区域的大小。更改符合一些预定义的标准，该算法可以启动响应（即，自动电子邮件，电话等）。 rnMSE已经发现了一些与使用机器视觉自动监视偏远地区有关的问题，这些问题基于初步的演示结果，这些结果表明整个站点发生了很大的变化。观察到的大多数变化是由于无关的因素或噪音引起的图像中的有害噪声可能包括照相机镜头上的昆虫；由于云层和/或太阳位置的变化而导致的光照可变；以及天气变化，例如雪，雨和风。为了解决这些问题，MSE正在探索一些技术，例如在时间窗口内对图像进行平均并对图像的光强度进行归一化。我们期望这些额外的处理步骤能够改善对相关变化的检测并减少由错误产生的错误警报的数量。机器视觉系统。

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