The invention discloses a welding simulator virtual weld defect detection method based on deep learning. A convolutional neural network CNN is used to realize virtual weld defect detection, the convolutional neural network CNN comprises an input layer, a convolutional layer, an excitation layer, a pooling layer and a full connection layer from top to bottom, an output value of an upper layer between two adjacent layers is used as an input value of a lower layer, and the invention belongs to the technical field of weld joint detection, and provides the welding simulator virtual weld joint defect detection method based on deep learning. The method comprises the following steps: firstly, on the basis of analyzing and collecting data characteristics, designing an identification algorithm of awelding seam image, performing graying processing and segmentation processing on the image, and remarkably separating a welding seam region from a non-welding seam region; secondly, constructing a deep learning network and expanding the collected data set; and finally, performing recognition training on the defect features by using a training learning framework.