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- W2313363414 abstract "It is an important task to real-time monitor the water quality in the water distribution networks. But it is difficult to select the representative locations from the whole water distribution networks because of the dynamical hydraulic status in the water distribution networks. The Lagrange method was used to analysis the water dynamic quality path of every node in every water quality time step during the water quality simulation in the networks. An objective function based on the node demand factors and the water dynamic quality path was represented to evaluate the water quality importance of each node in every water quality time step. So the optimal nodes that adapted to be fixed the sensors were selected from the networks. Fast Fourier Transformation and convolution method were used to analysis the signals collected by the water quality on-line sensors. The contamination source can be traced because the sensors impulse reaction matrix can be defined by the water dynamic path analysis. Dynamic water qualify path was calculated out in an example water distribution networks. The optimal water quality sensors' locations were defined by the water quality path calculation and the contamination sources were distinguished in a hypothetical condition through the sensors' signals analysis. It shows that the water dynamic path analysis based on the dynamic node percent information is a useful tool to optimize the water quality sensors locations and the contamination source identification. This paper was presented at the 8th Annual Water Distribution Systems Analysis Symposium which was held with the generous support of Awwa Research Foundation (AwwaRF)." @default.
- W2313363414 created "2016-06-24" @default.
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- W2313363414 date "2008-03-13" @default.
- W2313363414 modified "2023-09-27" @default.
- W2313363414 title "Study of Water Quality Sensors Locations Optimization and Signals Analysis Based on Dynamic Water Quality Path" @default.
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- W2313363414 doi "https://doi.org/10.1061/40941(247)177" @default.
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