输送带
断层(地质)
反向散射(电子邮件)
状态监测
声发射
故障检测与隔离
实时计算
信号(编程语言)
结构健康监测
计算机科学
光纤
光纤传感器
分布式声传感
噪音(视频)
工程类
电子工程
声学
人工智能
电信
无线
电气工程
地震学
地质学
机械工程
物理
图像(数学)
执行机构
程序设计语言
作者
Qing Liu,Zhen Pan,Zhaojie Li,Binyang Yan,Kang Liu,Bojun Ai,Lang Xie
摘要
Distributed optical fiber acoustic sensing (DAS) can serve as an excellent tool for real-time condition monitoring of a variety of industrial and civil infrastructures. This paper presents a belt conveyor roller fault abnormal monitoring method based on DAS, for the low accuracy and efficiency of the existing belt conveyor rollers fault detection. This method uses the Rayleigh Backscatter of coherent pulsed light to detect and reconstruct the fault signal, and proposes a method based on the combination of power spectrum features and peak detection to recognize and locate abnormal signals under intense background noise. The field test verifies the effectiveness of the real-time monitoring scheme of the industrial conveyor belt system, with a detection accuracy rate of over 87% for simulated fault signals, and a location accuracy of ±2.5 m. It provides a new passive distributed monitoring method for the all-weather structural health monitoring of the rollers in the industrial belt conveyor systems.
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