Abnormity detection method for natural gas purification process based on analysis of independent component of dynamic kernel

Abstract

The invention discloses an abnormity detection method for natural gas purification process based on analysis of an independent component of a dynamic kernel. The diagnosis method comprises the following steps: determining technical parameters in a monitored purification and desulfuration production process for natural gas with high sulfur content; carrying out data acquisition on the purification and desulfuration production process for the natural gas with high sulfur content; preprocessing data; analyzing an autoregressive model of the data, and determining a dynamic lag order of the model to obtain a dynamic expansion matrix; carrying out whitening processing on the expansion matrix in a kernel principal component space, extracting a principal component, and analyzing and estimating an independent element by an independent component; calculating an SPE statistical magnitude and a T2 statistical magnitude corresponding to the independent element, analyzing whether the statistical magnitudes are overproof or not, determining that an abnormal working condition happens if the statistical magnitudes are overproof, otherwise, determining that the working condition is normal, and carrying out abnormal working condition parameter tracing by a T2 contribution figure method. According to the method, a failure can be detected in time, and a failure reason resulting in the technical operation parameter is traced back, so that a decision-making reference basis is provided for system failure elimination and recovery.

Description

technical field [0001] The invention belongs to the fault detection and diagnosis technology of high-sulfur natural gas desulfurization production process, and relates to a natural gas purification process abnormal detection method based on dynamic nuclear independent component analysis. Background technique [0002] The industrial process of purification and desulfurization of high-sulfur natural gas is complex, with many process parameters, which are affected by uncertain factors such as temperature, pressure, flow rate, equipment aging and raw gas processing capacity. It is a typical chemical system with complex nonlinear dynamic characteristics. The purification and desulfurization process of high-sulfur natural gas mainly includes the following parts: the main absorption tower MDEA solution absorbs the acid component H 2 S and CO 2 , the hydrolysis reactor removal (COS), the cyclic regeneration of the MDEA solution in the regeneration tower and the heat exchange proces...

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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiency that the existing technology cannot detect the occurrence of faults in time, and provide a method for detecting abnormalities in the natural gas purification process based on dynamic kernel independent component analysis, which can detect the occurrence of faults in time, and trace back the cause of the fault caused by the process operation parameters , so as to provide decision-making reference for system troubleshooting and recovery

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