基于人工智能的输送装置故障诊断系统

Fault Diagnosis System of Conveyor Based on Artificial Intelligence Analysis

为了深入优化和改进带式输送机诊断、自查故障系统,结合企业安全生产管理规定,设计煤矿、洗选厂、电力企业等基于图像识别和AI算法的输煤皮带管控方案。文章通过引入人工智能控制技术,共建云系统解决方案和视频类技术服务共享,设计皮带撕裂检测算法模型、洒煤算法模型、异物检测算法模型,融合结构光、双目、TOF以及FPS统计分析,采用Fourier Descriptors数据提取和Back Propagation神经网络识别,实时分析研判输送装置故障诊断系统现状。

In order to further optimize and improve the belt conveyor diagnosis and self inspection fault system,combined with the enterprise safety production management regulations,the coal conveyor belt management and control scheme based on image recognition and AI algorithm is designed for coal mines,washing plants,electric power enterprises,etc.This paper introduces artificial intelligence control technology,co builds cloud system solutions and video technology service sharing,designs belt tear detection algorithm model,coal sprinkling algorithm model,foreign object detection algorithm model,integrates structured light,binoculars,TOF and FPS statistical analysis,uses Fourier Descriptors data extraction and Back Propagation neural network identification,and analyzes and judges the status quo of conveyor fault diagnosis system in real time.