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In view of the fact that a large number of signals generated in the process of complex system development and operation can represent the time sequence health state of system operation, a time sequence feature recognition method based on data visualization and convolutional neural networks (CNN) intelligent recognition is proposed. This method uses data visualization technology to map the time sequence features of the signal to the image, and uses the trained feature recognition model to recognize the time sequence features of the signal visualization image, which can realize the real-time intelligent state monitoring of the system. The normal and abnormal characteristics of three typical signals are selected. Through model construction and test analysis, it is verified that the method has good recognition effect on the time sequence characteristics of complex system signals, and can be applied to condition monitoring and fault diagnosis of complex systems with high time sequence requirements.