Pressure vessel safety assessment method based on big data and multi-parameter coupling

Abstract

The invention belongs to the technical field of industrial data processing, and particularly relates to a pressure vessel safety assessment method based on big data and multi-parameter coupling. The method comprises the following steps: acquiring multi-dimensional monitoring data, including internal temperature and pressure data, external image data and equipment basic data, of the pressure vessel; performing time sequence analysis on the internal temperature and pressure data, and determining an internal safety mass score in combination with a synergistic factor; preprocessing an external image and extracting a scratch feature quantitative index and a shape integrity index to obtain an external safety quality score; performing weighted summation on the internal and external safety quality scores to obtain a safety quality score; correcting the initial safety evaluation threshold according to the thickness of the pressure vessel and the crack parameters, comparing the comprehensive score with the dynamic threshold, and judging the safety state of the pressure vessel. According to the invention, multi-dimensional comprehensive evaluation is realized, accuracy and real-time performance are improved, and reliable support is provided for safe operation of the pressure vessel.

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