Research On Method For Direct Air-cooled Condenser Fault Diagnosis

As a water-saving technology, direct air-cooling system has been rapidly developed in recent years. Due to the direct air-cooling system uses air as cooling source, the size of the entire cooling system is very large, the back pressure of the condenser is very sensitive to the changes of environment, and there are more failures during operation. It is very necessary to study the failure mechanism and methods of monitoring. The main contents of this paper is divided into three parts:the study for back pressure forecasting of direct air-cooling condenser, the study for monitoring method of ash deposition, and the study for monitoring method of condenser freezing. The back pressure is a very important factor to judge whether there are some failure or type of failure. Due to the back pressure of direct air-cooling system affected by many factors and the comparability of back pressure under different conditions is very poor., in order to judge if the back pressure is normal, we need to know the back pressure under different conditions. In this paper, the author study the factors that affect the back pressure firstly, based on this, the author design a BP neural network. Through the application of the neural network, we can get a series of back pressure value under different conditions. The study for monitoring method of ash deposition part based on the back pressure forecasting part, in this part, the author propose a method to determine the severity of ash deposition by studying the relationship between actual back pressure and normal back pressure. In the study for monitoring method of condenser freezing part, the author study the freezing mechanism of condenser firstly, based on this, the author design a BP neural network. Through the application of the neural network, we can monitor the freezing condition of the condenser accurately.