For condensing turbine, steam exhaust point is in wet steam area. The exhaust steam humidity of steam turbine is difficult to get due to lacking of effective measuring method. Calculation of exhaust steam humidity has always been one of the key parts of the analysis of thermal power units. The main factors affecting exhaust steam humidity are turbine load and turbine exhaust pressure etc, and they are of non-linearity. This paper develops a calculation method to calculate exhaust steam humidity based on BP neural network. Taking a N1000-25/600/600 ultra-supercritical (USC) steam turbine as an example, the exhaust steam humidity is calculated and the results show that the method has a good accuracy to meet the needs of the engineering application.

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