Industrial Process Fault Detection Method Based on Supervised Linear Dynamic System Model

Abstract

The invention discloses a supervision-based industrial process fault detection method of a linear dynamic system model, and is applied to fault detection under the condition of obtainable quality variables in an industrial process. By use of the linear dynamic system model and the quality variables, the linear dynamic system model with supervision is established, and the dynamics of a process and the randomness of data are taken into consideration. Compared to other conventional methods, the method provided by the invention not only improves the fault detection effect of the industrial process, but also enhances the grasp of process operators for process states, and enables industrial production to be safer and product quality to be more stable; and the reliance of the conventional fault detection method on process knowledge is improved to a quite large degree, and automatic implementation of the industrial process is better facilitated.

Description

technical field [0001] The invention belongs to the field of industrial process control, in particular to an industrial process fault detection method based on a supervised linear dynamic system model. Background technique [0002] In recent years, the problem of fault detection in industrial production process has been paid more and more attention by industry and academia. On the one hand, the actual industrial process is complex, has many operating variables, and has nonlinear, non-Gaussian, and dynamic stages. Under a single assumption, the detection effect of a certain method has great limitations. On the other hand, if the process is not well monitored and alarms are given for possible failures, operational accidents may occur, which may affect the quality of the product in the slightest, or cause loss of life and property in severe cases. Therefore, finding a better process fault detection method and timely and correctly alarming has become one of the research hotspot...

AI Technical Summary

Problems solved by technology

Although the unsupervised linear dynamic system model (LDS) is a probabilistic model and considers the serial correlation of process data, it does not utilize quality variables and ignores the important process information that may be implied by quality variables.

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