The Furnace Pollution On-line Monitoring Based On Acoustic Pyrometry And The Neural Network

The pollution of the boiler heating surface is one of the factor of the boiler operationing safety, the solution is on-line monitoring. For solving how to monitor the entire and multi-zone furnace heating surfaces, the text researches the furnace heating surfaces pollution of the coal-fired units. The text explains the acoustic temperature theory and its application particularly, meanwhile explains the theory, construction、training and simulation of the BP neural network which is applied widely in the neural network, the constructed BP neural network model predicts the furnace clean gas temperature according to the complexity of the boiler combustion and the multiformity of the power plant DAS database, and makes the furnace entire and multi-zone pollution on-line monitoring model according to the acoustic temperature device which is installed in different places, and makes use of the acoustic temperature device which measures the furnace actual gas temperature, and expresses the entire and multi-zone pollution based on the polluted coefficient of the temperature quotient, and proves the model by the off-line examination. To develop the furnace entire and multi-zone pollution on-line monitoring system based on the acoustic temperature and the neural network with making use of Matlab soft and SQL server datebase and BP neural network.