Research on communication process detection of automatic test system based on TextCNN: Communication process detection based on TextCNN
Zeyu Dou, Jincheng Wang · 2023
Anomaly detection in the communication process between devices is an important consideration dimension in the automatic test system. The execution sequence of the process affects the device status and test results. The current automatic test system for communication processes between devices is still in its infancy. This paper constructs a device communication process dataset of a certain scale by extracting the operation instructions and communication process information from the communication logs of the automatic test system. Based on this dataset, an automatic test system communication process anomaly detection model based on TextCNN is proposed. Each communication instruction is trained as a whole, and deep learning algorithm is used to achieve fault diagnosis of the system communication flow, further improving the accuracy of the system. Experimental results on the constructed dataset show that the model proposed in this article has an accuracy of 81.928% in process anomaly detection and an accuracy of 79.353% in identifying abnormal communication processes.