Method and system for filtering online monitored noise of steel rail cracks and judging cracks

Abstract

The invention discloses a method for filtering online monitored noise of steel rail cracks and judging the cracks. The method comprises the following steps: collecting steel rail sound signals by virtue of an acoustic emission sensor, and transferring the steel rail sound signals back to a monitoring terminal by virtue of a collection controller, and processing; carrying out hierarchical decomposition on the steel rail sound signals by virtue of a db6 wavelet, so as to obtain a wavelet packet reconstruction signal component, time, frequency and a wavelet coefficient; calculating a frequency band energy ratio, so as to eliminate high-frequency interference in the wavelet packet reconstruction signal component caused by striking; reconstructing the wavelet coefficient of the rest wavelet packet reconstruction signal component, so as to obtain reconstruction signals; carrying out classical acoustic emission parameter analysis on the reconstruction signals, so as to obtain acoustic emission parameters; and analyzing correlation diagrams and experience diagrams, so as to judge whether the cracks are expanded. By virtue of the method, noise interference signals in acoustic emission signals can be effectively removed, crack signals can be separated from the interference signals, and the separation precision is high; and the method can be used for processing smooth signals and has a local analysis function to non-smooth signals.

Description

technical field [0001] The invention belongs to the technical field of rail crack detection, and in particular relates to a rail crack online monitoring noise filtering and crack judgment method and system thereof. Background technique [0002] The increased carrying capacity of modern railways (faster operating speeds and greater axle loads) increases the dynamic load on the rails and increases the likelihood of line degradation. In the long-term operation process, due to the long-term extrusion deformation and rolling contact fatigue of the rail, cracks, fractures or other damages will occur on the surface and interior of the rail, and the crack expansion of the rail is the main cause of the rail fracture accident. In order to maintain a high level of safety in railway operations, real-time online detection of railway operating conditions is particularly important. Acoustic emission can detect whether crack growth is occurring in rails under traffic loads. The phenomenon...

AI Technical Summary

Problems solved by technology

[0005] Because the wavelet transform only further decomposes the low-frequency part of the signal, and does not continue to decompose the high-frequency part, that is, the detail part of the signal, so the wavelet transform can well characterize a large class of signals with low-frequency information as the main component, but It does not decompose and represent signals that contain a lot of detail information (tiny edges or textures) well

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