Research on Complex Association Network Model Based on LKJ Anomaly Data
Fault diagnosis of LKJ equipment based on its operation record data analysis is still based on manual work which is of low efficiency and error-prone. How to use LKJ operation record data to realize the exploration of equipment fault association through big data mining technology, and timely discove...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2020-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.06.013 |
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| Summary: | Fault diagnosis of LKJ equipment based on its operation record data analysis is still based on manual work which is of low efficiency and error-prone. How to use LKJ operation record data to realize the exploration of equipment fault association through big data mining technology, and timely discover LKJ potential fault hidden danger is an urgent problem to be solved. Based on the operation record data file of on board equipment for train operation control device (LKJ) , according to the complex network model, a complex association network model based on LKJ anomaly data was established. The model is used to analyze the association relationship and aggregation degree between different LKJ anomaly characteristic data, and to study the correlation between two groups of random variables. Simulation results show that the error of the model is about 5.2% and the model can be used to realize the correlation analysis of LKJ equipment fault diagnosis, which provides an effective method and basis for LKJ fault diagnosis and association analysis. |
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| ISSN: | 2096-5427 |