Temperature or flux sensors may be used in the the heat quality intensity analysis system for puddling furnace

RBF neural network is used to judge sensor fault for insureing the credibility of sensor data and the stability running of the heat quality intensity analysis system.The system is composed with computer

temperature and flux data acquire installation and sensor.Forecast model for every sensor using RBF neural network is found.The number of lately input signal for the net is n

the output of the net is the forecast value at n+1 occasion.The fault diagnosis of sensor is carried out by the on-line learning method.Emulation analysis shows forecast model for every sensor using RBF neural network can fulfil fault diagnosis and improve the diagnosis precision.