Abstract:In the process of beer fermentation

in order to establish the precise temperature sensor fault diagnosis model

on the basis of standard support vector machine (SVM)

We proposed piecewise least square support vector machine method

first using fuzzy c-means clustering (FCM) of the sample of poly class analysis to divide fermentation stage and the establishment of local model.Then the least square support vector machine (LS SVM) method is used for modeling of various types of samples.The experimental results show that the model has a high accuracy in the process of temperature fault diagnosis of beer fermentation process.After comparison

the proposed method establishes the model’s generalization ability better than other SVM methods to build the model.