The invention discloses a cable accessory
nondestructive testing method based on image recognition, and relates to the technical field of data
encryption, and the method comprises the steps: extracting a
photon signal from an anti-
noise coding control template, generating an anti-interference
partial discharge light spot image in combination with a
compressed sensing reconstruction algorithm, and carrying out the alignment fusion of the anti-interference
partial discharge light spot image and
LiDAR point cloud data of a cable accessory, generating
spatial registration feature data; based on the neural
radiation field network, constructing a three-dimensional
radiation field model, inputting
spatial registration feature data, generating time-space domain deformation
field data and
partial discharge hot spot distribution data, and generating a defect candidate region by using a spatial weighted fusion
algorithm; a deep residual network is used as a framework, a transfer learning strategy is combined, a cable accessory defect model is constructed, a defect candidate area is input, and a cable accessory health state report is generated. According to the method, the three-dimensional
radiation field model is constructed by using the neural
radiation field network as a framework, accurate positioning and characterization of defects are realized, the detection reliability is improved, and the method is suitable for micro-defect identification.