The invention discloses a
hydropower station dam
osmometer automatic reading method based on
machine vision and
deep learning, and relates to the technical field of dam safety management, and the method comprises the steps: carrying out the adaptive preprocessing of an
osmometer image; positioning a dial plate area and fitting a circle center; preliminarily identifying a pointer
line segment; a pre-trained YOLO model is adopted to accurately detect a pointer area, and the fitting circle center is combined to calibrate the actual circle center and the
tail end position of the pointer; dial scale characters are identified, the
centroid position and the
radian and distance relative to the actual circle center of the dial scale characters are calculated, a scale
data set is constructed, and abnormal data are filtered out through an isolated forest
algorithm; and finally, based on the
radian of the pointer and the optimized scale
data set, performing calculation through polar
coordinate mapping and an intelligent interpolation
algorithm to obtain a high-precision
osmotic pressure reading. According to the invention, full
automation, high precision and high robustness of reading of the
osmometer are realized, and the defects of low efficiency, large error and poor anti-interference capability of manual inspection and a traditional
image processing method are effectively overcome.