摘要
针对矿用钢丝绳断丝故障检测过程中,故障信号往往存在基线漂移和脉冲噪声,借鉴传统小波去噪的思想,提出了一种基于数学形态和提升小波分析算法的矿用钢丝绳断丝故障检测方法,论述了其检测原理和实现方法。仿真结果表明,该方法去噪效果明显,能明显提高对钢丝绳断丝故障判断的准确性。
Considering in the progress of the fault detection for mining steel rope broken wires, impulse noise and baseline drift always existing in the fault signal, using the idea of the traditional wavelet denoising for reference, this paper proposes a method of fault detection for mining steel rope broken wires based on mathematical morphology and lifting wavelet analysis algorithm, discussing its detection principle and realization method. According to the simulation results, the de-noising effect of this method is obvious, and it can significantly improve the accuracy of steel wire rope broken wires fault judgment.
出处
《煤矿机械》
北大核心
2014年第5期244-246,共3页
Coal Mine Machinery
基金
山东省自然科学基金(ZR2012EEM021)
山东省科技发展计划资助项目(2012G0020503)
山东科技大学学生专利研究及申请资助项目(201313019)
山东科技大学研究生科技创新基金(YC130328)
关键词
钢丝绳断丝故障
脉冲噪声
数学形态
提升小波
检测原理
steel rope broken wires fault
impulse noise
mathematical morphology
lifting wavelet
detection principle
