T.Q. Yuan and Y.C. Soh (Singapore)
soft sensor, cooling tower,measurement, neural network.
Air flow data of cooling tower is very important in analyzing the performance of the cooling tower and optimizing the cooling tower energy consumption. In engineering, it’s very difficult to obtain because of the cooling tower structure and environment condition. In this paper, a soft-sensor was developed to estimate the air flow rates in the cooling tower system. Considering the complex nonlinear relationship between air flow rate and other variables, a neural network was used for the soft sensor model. The model has been evaluated on the off line laboratory test data set. The test results show that it is easy to be implemented and its measurement is reliable.
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