Automatic monitoring and early warning method for power grid infrastructure investment progress using building information model and blockchain

IET Blockchain Pub Date : 2024-01-17 DOI:10.1049/blc2.12061
Jing Lu, Weidong Yu, Shihong Wu
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Abstract

In order to improve the precise control level of power grid infrastructure investment, this paper proposes a monitoring and early warning method of power grid infrastructure investment progress based on building information model and blockchain. By capturing the project construction progress images, the features of the power grid infrastructure are extracted automatically. Combined with the technical characteristics of distributed, tamper‐proof, and traceable blockchain, statistical indicators are generated automatically, monitoring and early warning of the investment progress execution deviation are triggered by the rules running on the smart contracts. The case study results show that the mean absolute error of the target image recognition method based on the image features is 4.32%, and the prediction accuracy of the incoming line is better than that of the engineering civil and substation. The early warning model of investment statistics based on smart contracts can automatically monitor the investment progress and generate early warnings, which provides a basis for the dynamic adjustment of the investment plan, and effectively improves the refined management level of power grid infrastructure investment projects.
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利用建筑信息模型和区块链的电网基础设施投资进度自动监测和预警方法
为了提高电网基建投资的精准管控水平,本文提出了一种基于建筑信息模型和区块链的电网基建投资进度监测预警方法。通过抓取项目建设进度图像,自动提取电网基建特征。结合区块链分布式、防篡改、可追溯的技术特点,自动生成统计指标,通过智能合约上运行的规则触发对投资进度执行偏差的监测和预警。案例研究结果表明,基于图像特征的目标图像识别方法的平均绝对误差为4.32%,进线预测精度优于工程土建和变电站。基于智能合约的投资统计预警模型能够自动监测投资进度并生成预警,为投资计划的动态调整提供依据,有效提高了电网基建投资项目的精细化管理水平。
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