Non-linear procedure failure testing method based on two-dimensional dynamic kernel principal component analysis

Abstract

Disclosed is a non-linear process fault detection method based on two-dimensional dynamic kernel principal component analysis, belonging to the fault detection technical field; the method comprises the following steps: the first step is to determine the sampling parameters, namely, to judge the execution process, determine the sampling parameters, select the data parameters which affect the fault, and then judge whether to carry through training or testing; the second step is training, that is, to collect the data of normal work, pick up the non-linear principal component of the training data through two-dimensional dynamic kernel principal component analysis, calculate the square prediction error of the training data and determine the control limit; the third step is testing, that is, to collect the online observation data, pick up the non-linear principal component of the online observation data through two-dimensional dynamic kernel principal component analysis, calculate the square prediction error of the real-time online observation data, compare the control limit of the square prediction error of the real-time online observation data with the control limit of the square prediction error of the training data, display and gives an alarm if the control limit of the former exceeds that of the latter. The invention can timely detect the fault in the production process and reduce losses in the industrial production process.

Description

Nonlinear Process Fault Detection Method Based on 2D Dynamic Kernel Principal Component Analysis technical field The invention belongs to the technical field of fault detection, in particular to a non-linear process fault detection method based on two-dimensional dynamic kernel principal component analysis (2D-DKPCA, TwoDimensionalDynamicKernelPrincipalComponentsAnalysis). Background technique With the continuous development of the economy, the number of industrial enterprises is increasing, and the competition among production departments is becoming increasingly fierce. To improve the efficiency of enterprises, it is necessary to improve product quality and reduce the number of substandard products. In addition to the higher and higher requirements for the production process of products, the requirements for the ability of fault detection methods in the production process are also higher and higher. This is because some failures are unavoidable in complex nonlinear prod...

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Problems solved by technology

Step 1: Determine sampling parameters

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