Abstract: In view of the frequent failure of monitoring points and data anomalies, a monitoring data repairing method based on deep denoising autoencoder (DDAE) network is proposed. Firstly, the denoising auto-encoder (DAE) is used as the basic structural unit to construct the DDAE network. Then, the deep correlation of the data is extracted from the DDAE network, and the support vector regression (SVR) model is constructed to predict the monitoring data to be repaired. Experiments conducted on the airport noise data set demonstrate that the deep correlation can reconstruct the noise monitoring data very well. Compared with the traditional data repairing methods, the proposed data repairing method has better robustness and higher precision.