Research on Oil and Gas Pipeline Vibration Detection Based on Distributed Fiber Optic Phase-Sensitive Signal Classification
Addressing the challenge of manual inspection difficulties for trans-crossing oil and gas pipelines,this paper employs distributed fiber optics for real-time monitoring of pipeline conditions,classifying vibration signals to identify the sources of pipeline vibrations.An improved Bald Eagle Search algorithm and a method for extracting features from fiber optic vibration signals are proposed.Furthermore,distributed fiber optic phase-sensitive signals are classified and recognized based on neural networks.Experimental results demonstrate that the proposed Ct-GBES-BPNN classification model achieves excellent performance in classification and recognition,providing support for ensuring the safety of trans-crossing oil and gas pipelines.
Distributed fiber opticsPhase-sensitive signalsOil and gas pipelinesFeature extractionVibration recognition
万方数据
维普
