Abstract

AbstractIn view of the wide distribution and large number of unattended stations in the gas field, the problems of large workload, low work efficiency and high driving safety troubles the inspection personals when they inspect the unattended stations by driving a car every day. Under this background, a intelligent inspection system which uses the technology of “video tour + image recognition” is researched and applied in gas field. Based on the neural network algorithm, A set of image recognition algorithm which is suitable for on-site production monitoring meters is formed, and high-definition industrial video is used to inspect and identify on-site parameters automatically. Combined with these tow technologies, the intelligent inspection system is researched successfully, which can replace workers for executing inspection tasks, finding abnormal parameters and generating inspection reports The application results show that the recognition accuracy of intelligent inspection system is more than 95%, the inspection workload of staff can be reduced by 85%, and the inspection efficiency can be increased by 80%. At the same time, the intelligent inspection system effectively reduces the staff's stay time in high-risk areas and releases the internal human resources, which provides a reliable and effective technical means for the safety control of unattended stations.KeywordsIntelligent inspectionNeural networkImage recognitionUnattended station

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