Data comparative analysis method for intelligent steel rail damage judgment algorithm

Abstract

The invention discloses a data comparative analysis method for an intelligent steel rail damage judgment algorithm. Damage detection data analysis comprises automatically analyzing a flaw detection data file generated by flaw detection equipment through a computer, extracting important basic information in the data file, and analyzing flaw data echo intensity, position and angle information for confirmation. According to the method, historical flaw detection data can be effectively utilized, the historical development information of suspected flaws at the same position is obtained, the development law of the flaws is effectively judged, the influence caused by human factors is eliminated, and the accuracy and reliability of flaw judgment are improved.

Description

technical field [0001] The invention belongs to flaw detection of railway steel rails, in particular to a data comparison and analysis method for intelligent flaw judgment algorithms of steel rails. Background technique [0002] Flaw detection car is an important testing equipment used by railways for rail flaw detection to ensure the safe operation of railways. At present, flaw detection vehicles have been widely used in rail flaw detection in my country. However, the ultrasonic flaw detection equipment currently used by flaw detection vehicles does not have mature automation and intelligent technology for the identification and judgment of a large amount of detected data. Damage identification mainly relies on human eyes to view, identify, and extract possible defect points in the later stage. At present, we are facing: first, the labor intensity is high, and the degree of dependence on the skills of personnel is high; serious safety consequences. [0003] In order to ...

AI Technical Summary

Problems solved by technology

In the current flaw detection and judgment work, whether it is manually replaying the data collected by the flaw detection vehicle for damage judgment, or using computer intelligent recognition to automatically judge damage, there are technologies for viewing and comparing historical data of the same damage for the same location and damage. problem

Because the flaw detection vehicle runs at a certain speed when collecting flaw detection data, it is impossible to accurately record the mileage, and the error is often more than tens of meters; Viewing and comparing data of the same type of damage at the same location is the main difficulty in the industry at present

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