Large-scale process pipeline defect detection method

Abstract

The invention discloses a method for detecting the defects of a large process pipeline. The method comprises the following steps: establishing a three-dimensional data model of a to-be-detected large process pipeline and setting the sizes of character grids, then dividing the three-dimensional data model according to the set sizes of the character grids and extracting grid division points so as to form a standard point cloud figure of the pipeline; drawing a plurality of sections along a direction perpendicular to the axis of the standard point cloud figure of the pipeline, then extracting the point cloud sections and separately recording the point cloud sections as 1, 2, 3, ..., n; carrying out image acquisition on the to-be-detected large process pipeline by using an X-ray imaging device and carrying out signal enhancement so as to obtain an enhanced image signal; acquiring the point cloud figure of the enhanced image signal; subjecting the point cloud figures of the sections and the point cloud figure of the enhanced image signal to fusion and comparison; and subjecting non-coincidence points to fitting and determining the locations and graphic information of the defects of the large process pipeline. The method can greatly improve the detection efficiency of the defects of the large process pipeline.

Description

technical field [0001] The invention relates to a large-scale process pipeline defect detection method, in particular to a large-scale oil and gas transmission pipeline defect detection method in marine engineering. Background technique [0002] In offshore engineering, large-scale process pipelines are the link of offshore oil and gas transportation, and their safety and reliability play an important role in the process of offshore oil and gas transportation. Due to the fact that large-scale process pipelines are prone to surface defects, small cracks and other problems during the production process, which brings serious safety hazards to the offshore oil and gas transportation process, it is necessary to carry out defect detection on large-scale process pipelines. Most of the traditional pipeline detection is manual. Observation, ultrasonic flaw detection and magnetic induction principle are used for detection. Manual observation can only detect surface defects of pipeline...

AI Technical Summary

Problems solved by technology

Due to the fact that large-scale process pipelines are prone to surface defects, small cracks and other problems during the production process, which brings serious safety hazards to the offshore oil and gas transportation process, it is necessary to carry out defect detection on large-scale process pipelines. Most of the traditional pipeline detection is manual. Observation, ultrasonic flaw detection and magnetic induction principle are used for detection. Manual observation can only detect surface defects of pipelines, but it is difficult to detect small cracks inside pipelines. Ultrasonic flaw detection and magnetic induction detection cannot clearly show the form of defects, so they are not suitable for Inspection and repair work of large process pipelines

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