Power plant safety behavior information automatic detection method based on deep learning

Abstract

The invention relates to a power plant safety behavior information automatic detection method based on deep learning, and the method comprises the steps: firstly constructing a deep convolutional neural network, and positioning each safety helmet in a monitoring video image through the deep convolutional neural network; completing detection, feature extraction, accurate segmentation and target identification of a safety helmet target by using FPN and RPN networks; then, making a learning data set, and training a computer to complete safety helmet identification and complete network parameter optimization; and finally, applying the trained optimization network to streaming video monitoring to realize correct helmet wearing behavior identification and alarm of the personnel. Compared with the prior art, the invention has the advantage that the problem that whether a target wears a safety helmet or not cannot be accurately recognized due to dense people, body image shielding and overlapping conditions is solved.

Description

technical field [0001] The invention relates to an automatic detection method for power plant safety behavior information, in particular to an automatic detection method for power plant safety behavior information based on deep learning. Background technique [0002] Wearing a hard hat is a safe sex practice that effectively prevents head injuries. When a safety accident occurs, the impact-absorbing performance of the safety helmet can disperse the impact force of the external impact object in an instant, and can reduce the occurrence probability of skull fractures, neck sprains and concussions. However, considering the low safety awareness of personnel and the influence of the external environment of construction, personnel do not wear them in accordance with safety regulations all the time, and continue this negative unsafe behavior until a safety accident occurs. Therefore, effective external supervision of helmet wearing identification is one of the necessary management...

AI Technical Summary

Problems solved by technology

The advantage of this type of method is that it does not depend on the accurate facial feature recognition and feature description of the construction personnel, but it still relies heavily on the selected manual design features, has weak generalization ability, poor information expression ability, and has certain limitations. Poor performance in video streaming

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