Steel rail surface flaw detection system and method based on machine vision and pulse eddy currents

Abstract

The invention relates to a steel rail surface flaw detection system and method based on machine vision and pulse eddy currents. The system comprises a vision flaw detection subsystem, a pulse eddy current flaw detection subsystem, a data transmission subsystem and a data processing subsystem. The system and method are adopted, the detection system based on the machine vision and the pulse eddy currents is constructed through an embedded technology, by scanning and detecting a steel rail, the detection results of the machine vision and the pulse eddy currents are integrated, the size of a flawis judged in combination with characteristics of the flaw area, the length-width ratio and the like, and whether a defect exists or not on the surface of the steel rail is judged; an internet-of-things technology is introduced for wireless signal transmission, the functions of real-time detection, on-line locating, remote control and the like can be achieved, a 4G-LTE transmission function is added, Mobile, Unicom and Telecom 4G high-speed access is achieved, multi-system communication access is supported at the same time, the system and method have high stability, and flaw detection is conducted on the steel rail in real time at a super long distance; a pulse eddy current technology, a machine vision technology and the internet-of-things technology are utilized by the system and method, and the system and method have high application value.

Description

technical field [0001] The invention relates to the technical field of rail surface defect detection, in particular to a rail surface defect detection system and method based on machine vision and pulsed eddy current. Background technique [0002] In recent years, with the rapid development of my country's rail transportation industry, the demand for non-destructive testing of rails is getting higher and higher. Under the repeated friction, impact and extrusion of the wheel against the rail, it will cause damage to different positions of the rail. At present, the non-destructive testing of rails is mainly based on ultrasonic echo testing, which is suitable for the detection of internal defects, and has limited detection and detection capabilities for surface defects. However, surface defects of rails will cause the train to run unsteadily, accelerate the deepening of defects, and further affect the safety of trains; It will accelerate the wear of the wheels and reduce the s...

AI Technical Summary

Problems solved by technology

The eddy current detection signal is limited by the size and direction of the defect, and is greatly affected by external disturbances such as lift-off, and has limited detection capabilities for small defects; High false detection rate

Magnetic particle method and infiltration method need to add additional detection materials, which are not suitable for online real-time detection

[0004] In addition, most of the current flaw detection systems do not have online detection functions, and cannot detect the flaws of the rail surface in real time and efficiently

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