The difficulty in online measurement of some thermal parameters in utility boilers restricts the boilers' efficient and economic operation.In this paper

the major models of soft measurement used in this field are firstly introduced briefly

including the method based on statistical analysis(like the principle component analysis(PCA)and partial least squares(PLS))

the artificial intelligence based artificial neural networks(ANN)

and the methods based on statistic studying theory(like the support vector machine(SVM)and fuzzy theory).Afterwards

various thermal parameters are treated as the research objects of soft measurement to summarize the modeling and simulation of soft measurement technology.The parameters include the coal characteristics

load and air flow of ball mill

air-coal ratio

oxygen content in flue gas

carbon content in fly ash

water level in the drum

main steam temperature

ash deposition on economizer and pollutant emission

and others.The results show that

for parameters showing nonlinear characteristics like the carbon content in fly ash

the soft measurement model established by the kernel principle component analysis(KPCA)method has well effect.For the parameters with high linear related degree between each other

the partial least square regression(PLSR)method is more efficient to build up the their soft measurement models.The model established by the ANN method has larger output errors when the actual sample space is out of the training sample space area.So during practical engineering process

the parameters of the model built by the ANN method should be corrected periodically.The SVM method still has no mature guidance to establish parameters soft measurement model

using the experiential data will affect the model accuracy significantly.Compared with the conventional SVM method

the least squares support vector machine(LS-SVM)method has shorter training time and more accurate results

which is more suitable for online modeling.For fuzzy theory method

the accurate mathematic model of the measured object is not necessary

but the fuzzy system has no learning function itself.If we combining the fuzzy theory with other artificial intelligence method like the ANN method

the soft measurement performance will be enhanced.Therefore

the application of soft measurement technology makes possible the effective measurement of thermal parameters.