A sparse causal analysis method for industrial control multi-loop oscillation behavior

Abstract

The invention discloses a sparse causal analysis method of industrial control multi-loop oscillation behaviors. The method includes: collecting the process output time sequence signal of each to-be-analyzed control loop; performing cosine-removing trend preprocessing on each process output time sequence signal to obtain a corresponding sub-signal; building a sparse multi-variable vector autoregression model for the sub-signal of each control loop; performing Granger causality analysis on the basis of the sparse multi-variable vector autoregression models to obtain the Granger causality index between optional two control loops; performing statistical significance judgement on the Granger causality index, and determining that the causal relationship between the corresponding control loops indicated by the Granger causality index is established under the corresponding significance level if the result is significant. By the sparse causal analysis method, a multi-oscillation-loop oscillation source can be positioned, an oscillation propagation path can be detected, and effective reference can be provided for the diagnosing and checking of oscillation faults.

Description

technical field [0001] The invention relates to the field of fault diagnosis in industrial control, in particular to a sparse causal analysis method for industrial control multi-loop oscillation behavior. Background technique [0002] Common industrial chemical processes are composed of thousands of highly coupled loops, and the process equipment has the characteristics of large scale, many variables, high comprehensiveness, and long-term operation under closed-loop control. However, due to the over-tuning of the controller in the control loop, the nonlinearity of the process, the valve viscosity and external disturbances, the control loop will oscillate, or even the global oscillation of the control loop, which greatly affects the stability of industrial process equipment. sex and productivity. [0003] The causal analysis of the oscillation circuit of the industrial process, including the detection of the oscillation source and the analysis of the propagation path, is an ...

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Problems solved by technology

[0005] However, the limitations of the above methods are as follows: the principle-based analysis method has poor universality and low analysis efficiency; while the method based on spectral principal component analysis can only determine the source of the oscillation, but cannot know the propagation path of the oscillation; For causal analysis, due to the large number of loops and strong coupling, the calculation efficiency of the algorithm is low, and the calculation results are complex. The cosine trend in the data of the oscillation loop makes the loops highly similar and repeatable, which affects the accuracy of the final analysis results.

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