Pressure pipeline damage prediction method based on sequential analysis

Abstract

The invention relates to a pressure pipeline damage prediction method based on sequential analysis. The pressure pipeline damage prediction method comprises the following steps: firstly, calculating afirst-order difference of a monitoring stress value; extracting stability information, combining an autoregressive moving average time sequence analysis ARMA model to predict stress value differencesin a plurality of days in the future, and then calculating stress values in the plurality of days in the future; and finally, using a weighted moving average (EWMA) method to analyze and predict thedevelopment trend of the stress values so as to carry out damage early warning. According to the invention, real-time early warning can be carried out on the running pipeline, and the pressure pipeline damage prediction method has the characteristics of timely and accurate early warning, so that technical support is provided for long-period safe running of the pipeline.

Description

technical field [0001] The invention belongs to the technical field of process industry safe operation assurance, and in particular relates to a pressure pipeline damage prediction method based on time series analysis. Background technique [0002] Pressure piping is an important part of the process industry, and its safe operation level directly determines the safe operation level of petrochemical enterprises. With the expansion of the scale of petrochemical enterprises, the limitations of conventional detection methods are becoming more and more obvious. For example, the daily consumption of manpower is too much, the special location is dangerous, and there are easy detection dead ends; the safety evaluation of equipment can only be based on the test in the shutdown state The data cannot reflect the real situation in the service state, and the real-time detection of the structural state of the equipment in service cannot be carried out. Whether the safety between the two i...

AI Technical Summary

Problems solved by technology

In actual engineering applications, the damage development trend of each position is different. Once the stress threshold is exceeded, the damage trend develops too fast, which often leads to the lack of time to prepare emergency plans.

Public information shows that relevant researchers use autoregressive moving average time series analysis method (ARMA(p,q)) to predict future stress values ​​based on monitoring data, but the steady fluctuation of stress values ​​caused by changes in pipeline conditions will lead to distortion of predicted values

Images