Aiming at the problems of low fault sensitivity and easy loss of some features in largescale fault data set detection based on convolutional neural network algorithm, a fault set detection scheme based on optimized capsule network algorithm was proposed. In the capsule network algorithm, multi neuron encapsulated capsule structure design was used, and multiple capsule layers were contained. So the algorithm had stronger fault data processing ability and generalization ability. The capsule vector extruded by squash function could be used to extract and describe fault features more accurately. More accurate fault score result could be gotten by improving capsule vector and based on feature coding and normalization class. The experimental results show that the optimized capsule network algorithm has stronger fault feature clustering performance and iterative operation performance, and the fault set detection accuracy is higher than that of convolution neural network algorithm.