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Sewer Pipeline Operational Condition Prediction using Multiple Regression

机译:下水道管道运行条件预测使用多元回归

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One of the key factors for better performance of sewer pipeline networks is proper monitoring of existing operational or hydraulic condition of pipes. The hydraulic performance of sewer networks involves many uncertainties and is dependent upon vulnerability and retention capacity of each pipe segment in the concerned network. Random inspections of pipes are expensive. This paper suggests an objective methodology for evaluating operational condition of pipes. A multiple regression model is developed on the basis of historic condition assessment data for predicting existing operational condition rating of sewers. The regression model produces a most likely existing operational condition rating of pipes by utilizing simple inventory data. The developed model is intended to assist municipal engineers in identifying critical segments influencing overall hydraulic performance of the system.
机译:用于更好地性能的下水道管道网络的关键因素之一是对现有的管道运行或液压状况的正确监控。下水道网络的液压性能涉及许多不确定性,并且取决于每个管道段的脆弱性和保留能力。管道的随机检查是昂贵的。本文表明了评估管道运营状况的客观方法。基于历史性条件评估数据开发了多元回归模型,以预测下水道的现有操作条件等级。回归模型通过利用简单的库存数据产生管道最有可能的运行条件等级。开发的模型旨在帮助市政工程师识别影响系统整体水力性能的关键段。

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