The invention discloses a
soot blowing pipeline wall thickness online monitoring method based on temperature self-adaption, and relates to the technical field of industrial pipeline
nondestructive testing. The problems that in the prior art, a detection
signal is unstable in a high-temperature environment, and the micro
corrosion thinning recognition precision is insufficient can be at least partially solved. The method comprises the steps that the surface temperature of a pipeline is collected, and the force contribution ratio of
Lorentz force to
magnetostriction force is calculated; dynamically optimizing electromagnetic ultrasonic body wave excitation parameters according to the force contribution ratio;
body waves are excited point by point in the axial direction of the pipeline, and echo signals are collected; extracting bottom wave features by using empirical mode
decomposition and
wavelet threshold combined
noise reduction; calculating the wall thickness of each measuring point based on the
temperature correction sound velocity; and generating a B-scan image and carrying out grading evaluation according to the percentage of the
thinning amount. According to the method, the wall thickness is accurately measured under the high-temperature working condition,
signal stability is ensured through temperature self-adaptive parameter optimization, the
signal-to-
noise ratio is remarkably improved through combined
noise reduction, wall thickness distribution is visually presented through B scanning imaging, and reliable data support is provided for
safe operation and maintenance of a pipeline.