Fault Diagnosis of Polymerization Kettle Chemical Process Based on LE-ISTOA-SVM
Polymerization kettle is the most important equipment for preparing polymer compounds.Its stable operation is related to the quality of products and the safety of personnel and equipment.However,the modern chemical production process is very complex,and the chemical process diagnosis data has the characteristics of high-dimensional nonlinearity.This paper proposes a fault diagnosis method based on LE-ISTOA-SVM.Firstly,the Laplace feature mapping algorithm is used to reduce the dimension of fault data.Then,the improved stooty tern optimization algorithm is used to optimize the pa-rameters of SVM to improve its performance.Finally,the experimental data of the polymerizer is used for simulation test.The test results show that the diagnosis effect of this method is good.
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