| Title | Research on Correlation Analysis of Vibration Signals at Multiple Measuring Points and Black Box Model of Flexible-DC Transformer |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Pan, Zhicheng, Deng, Jun, Chu, Jinwei, Zhang, Zhanlong, Dong, Zijian |
| Conference Name | 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2) |
| Date Published | oct |
| Keywords | “black box” model, Analytical models, Correlation, cyber physical systems, fault diagnosis, Flexible-DC transformer, Human Behavior, human factors, Metrics, multiple fault diagnosis, Neural networks, pubcrawl, resilience, Resiliency, system integration, Vibration detection, vibration measurement, Vibrations |
| Abstract | The internal structure of the flexible-DC transformer is complicated and the lack of a reliable vibration calculation model limits the application of the vibration analysis method in the fault diagnosis of the flexible-DC transformer. In response to this problem, this paper analyzes the correlation between the vibration signals of multiple measuring points and establishes a ``black box'' model of transformer vibration detection. Using the correlation analysis of multiple measuring points and BP neural network, a ``black box'' model that simulates the internal vibration transmission relationship of the transformer is established. The vibration signal of the multiple measuring points can be used to calculate the vibration signal of the target measuring point under specific working conditions. This can provide effective information for fault diagnosis and judgment of the running status of the flexible-DC transformer. |
| DOI | 10.1109/EI250167.2020.9347028 |
| Citation Key | pan_research_2020 |
Research on Correlation Analysis of Vibration Signals at Multiple Measuring Points and Black Box Model of Flexible-DC Transformer