Research on Optical Fiber Vibration Identification Technology Based on Big Data Analysis in Optical Cable Operation and Maintenance Early Warning

This paper aims to develop an optical fiber vibration identification system based on big data analysis to realize the real-time monitoring and data analysis of the running state of optical cable. The goal is to reduce the impact of sudden failures on the network by accurately analyzing fiber vibration data. Big data technology is adopted to process and analyze fiber vibration data, and data-driven method is used to provide decision support, including collecting large amounts of fiber vibration data, applying data mining technology to identify vibration patterns, and using to make fault prediction with machine learning algorithms. The implementation effect of the system shows that through real-time data monitoring and analysis, the stability of the network can be effectively improved, the ledger management and query method can be improved, the network panorama presentation and real-time monitoring can be realized, and the impact of sudden faults on the network operation can be significantly reduced. Through these measures, the system not only improves the reliability of the network, but also optimizes the fault management and early warning mechanism, providing strong support for the network maintenance and operation.