钢绳芯输送带磁记忆检测信号小波分析方法研究  

Study on Detected Sign in Steel Cord Belts with Magnetic Memory Based on Wavelet Analysis

作　　者：乔铁柱[1] 马俊超[1] 赵永红[1] 

机构地区：[1]太原理工大学新型传感器与智能控制教育部重点实验室,太原030024

出　　处：《煤矿机械》2009年第11期246-248,共3页Coal Mine Machinery

基　　金：山西省科学技术发展计划项目(20080322020)

摘　　要：运用金属磁记忆检测技术对在役钢绳芯输送带中钢绳芯进行早期故障检测,利用小波分析对钢绳芯的异常应力集中区信号进行消噪处理和奇异性检测,消除了干扰信号,提高了信噪比,使故障点更加明显,经实验证明,该方法能够准确地检测出输送带内部钢绳芯发生抽动和断丝的位置。The metal magnetic memory technology （MMMT） was applied in the early fault diagnosis of steel-cord belts. And the malfunction signal of steel-cord belts was denoised and detected singularity by wavelet analysis. As a result, the interference signal was eliminated, Signal Noise Ratio （SNR） was improved and the malfunction points were clearer. The experiment proved that the method can accurately detect the malfunction places where occur the twitch of the joint and break of the steel-cord.

关 键 词：金属磁记忆 小波分析 钢绳芯输送带 故障检测 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]