Control Valve Viscous Detection Method

Abstract

The method discloses a control valve adhesion detecting method. The method comprises the following steps that it is assumed that the linear random process corresponding to a data series of a loop to be tested is the null hypothesis; a plurality of sets of surrogate data corresponding to original data are generated based on the surrogate data generating algorithm; the test statistics of the original data and the surrogate data is calculated; if the test statistics of the original data and the test statistics of the surrogate data are obviously different, it is proved that the nonlinearity component exists in the original data series, and a valve of a corresponding control loop probably has the adhesion; or otherwise, the valve of the control loop does not have the adhesion. According to the control valve adhesion detecting method, the nonlinearity detection of the data series is carried out through the statistics or detecting indexes, and then whether the adhesion exists in the control valve or not is judged; the control valve adhesion detecting method can be complementary with an existing detecting method, and therefore the effects of expanding the effective adhesion character detecting condition range and improving the adhesion character detection rate are achieved.

Description

technical field [0001] The invention belongs to the technical field of a control circuit performance monitoring system, and in particular relates to a method for detecting a sticking fault in a pneumatic control valve. Background technique [0002] The method for detecting the stickiness of the pneumatic control valve proposed in the prior art uses a substitute data method based on the nonlinear prediction error index to check whether the original time series contains nonlinearity, and then make a judgment on whether the control valve is sticky. However, due to the complex factors such as a large amount of noise in the actual field data used for the above analysis and calculation, and the interference of the "non-linear prediction error" index detection results, some actually have sticky situations, but the existing methods are very sticky result that does not exist. Moreover, through simulation research, it is found that under the condition of interference, the non-linear ...

AI Technical Summary

Problems solved by technology

However, due to the complex factors such as a large amount of noise in the actual field data used for the above analysis and calculation, and the interference of the "non-linear prediction error" index detection results, some actually have sticky situations, but the existing methods are very sticky non-existent result

Moreover, through simulation research, it is found that under the condition of interference, the non-linear prediction error index method proposed by the prior art to detect the stickiness of the pneumatic control valve cannot correctly detect the stickiness of the pneumatic control valve under many conditions

Images