To address the problems that the existing 1DCNN method for aero-engine fault diagnosis lacks the multi-scale feature extraction capability of fault frequency and the insufficient extraction of time-domain features of the original vibration signal, improved 1DCNN aero-engine fault diagnosis method is proposed by fusing embedded multiscale layers to dual-channel 1DCNN. The method of amplitude change rate is proposed for the time domain feature enhancement of vibration signals, and the amplitude change channel is added as the second channel on the basis of single-channel 1DCNN to build a dual-channel 1DCNN to strengthen the time domain feature extraction capability of 1DCNN, then the multi-scale module is improved to an embedded multi-scale layer and applied to the first channel of 1DCNN to extract multi-scale features of aero-engine fault frequency. Finally, the improved 1DCNN is applied to the diagnosis of aero-engine transient static rubbing, blade fracture and other faults, and the superiority, noise resistance, generalization of the improved 1DCNN detection and the feasibility of the improvement points are proved through comparative experiments.