The invention discloses a
train operation fault automatic detection
system and method based on binocular stereoscopic vision, and the method comprises the steps: collecting left and right camera images of different parts of a
train based on a binocular stereoscopic
vision sensor; achieving the synchronous precise positioning of various types of target regions where faults are liable to happen based on the
deep learning theory of a multi-layer
convolution neural network or a conventional
machine learning method through combining with the left and right image consistency fault (no-fault) constraint of the same part; carrying out the preliminary fault classification and recognition of a positioning region; achieving the synchronous precise positioning of multiple parts in a non-fault region through combining with the priori information of the number of parts in the target regions; carrying out the
feature point matching of the left and right images of the same part through employing the technology of binocular stereoscopic vision, achieving the three-dimensional reconstruction, calculating a
key size, and carrying out the quantitative description of fine faults and gradually changing hidden faults, such as loosening or playing. The method achieves the synchronous precise detection of the deformation, displacement and falling faults of all big parts of the
train, or carries out the three-dimensional quantitative description of the fine and gradually changing hidden troubles, and is more complete, timely and accurate.