Intellectualized Data Collection and Fault Diagnosis for Ships Information System
Song Gao, Chuanxu Yan, Zhenchong Liu · 2019
As the level of intelligent ships has been increasing rapidly, the amount information which is transmitted among systems can be quite extensive. The probability of malfunctions occurring or going to happen goes up during information transit. Therefore, the demand for fault diagnosis and fault prediction in information system would definitely grow gradually. In this paper, aimed to meet the above demand, we developed a data acquisition device based on various interfaces. The device can collect the data from ships information system and provide an excellent platform for data processing and data analysis. Combining with fault feature library and using big data mining and machine learning, it can predict and diagnose faults automatically. This device provides daily reliable protection for the system.