基于局域波降噪和双谱分析的自动机故障诊断研究

doi:10.3969/j.issn.1000-1093.2014.07.022

兵工学报 ›› 2014, Vol. 35 ›› Issue (7): 1077-1082.doi: 10.3969/j.issn.1000-1093.2014.07.022

基于局域波降噪和双谱分析的自动机故障诊断研究

潘宏侠，兰海龙，任海峰

（中北大学机械与动力工程学院，山西太原 030051）

收稿日期:2013-09-13 修回日期:2013-09-13 上线日期:2014-09-05
通讯作者: 潘宏侠 E-mail:panhx1015@163.com
作者简介:潘宏侠（1950—），男，教授，博士生导师
基金资助:
国家自然科学基金项目（51175480）

Fault Diagnosis for Automata Based on Local Wave Noise Reduction and Bispectral Analysis

PAN Hong-xia, LAN Hai-long, REN Hai-feng

(School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, Shanxi, China)

Received:2013-09-13 Revised:2013-09-13 Online:2014-09-05
Contact: PAN Hong-xia E-mail:panhx1015@163.com

摘要/Abstract

摘要： 特征提取是机械故障诊断的关键，能否准确地提取出反映机械设备工作状态的特征信息，直接影响到故障诊断的准确性和早期预报的可靠性。自动机表面的振动信号成分复杂，除了含有丰富的零部件运动状态信息外，也存在着大量的噪声成分。只有有效地去除干扰信息，才能对信号做出正确地评估和分析。自动机表面的振动信号具有明显的短时冲击特性，是一种典型的非高斯、非线性信号。高阶谱分析，特别是双谱分析，在处理非高斯信号和识别非线性系统故障等方面具有一定的优越性。将局域波理论和双谱分析相结合，对自动机振动信号进行降噪处理和分析，结果表明其应用在自动机故障诊断中具有较好的识别效果。

关键词: 振动与波, 局域波, 降噪, 双谱分析, 自动机

Abstract: Feature extraction is a key of mechanical fault diagnosis, which directly affects the accuracy of fault diagnosis and the reliability of early prediction. The vibration signal components of automata surface are complex, including rich information on the motion states of components and parts, and a lot of noise components. Interference information should be effectively removed in order to make a correct assessment and analysis of the signal. The vibration signal of automata surface has obvious short impact characteristics, and is a typical non-Gaussian, nonlinear signal. Bispectral analysis has certain advantages especially in dealing with non-Gaussian signal and identifying nonlinear system failures. Automata vibration signal is noise-reduced and analyzed by the local wave theory and the Bispectral analysis.

Key words: oscillation and wave, local wave, noise reduction, bispectral analysis, automata

中图分类号:

TK42

潘宏侠，兰海龙，任海峰. 基于局域波降噪和双谱分析的自动机故障诊断研究[J]. 兵工学报, 2014, 35(7): 1077-1082.

PAN Hong-xia, LAN Hai-long, REN Hai-feng. Fault Diagnosis for Automata Based on Local Wave Noise Reduction and Bispectral Analysis[J]. Acta Armamentarii, 2014, 35(7): 1077-1082.

参考文献

［1］胡红英, 马孝江. 基于局域波分解的信号降噪算法［J］. 农业机械学报, 2006,37(1): 118-120.
HU Hong-ying, MA Xiao-jiang. Signal denoising based on local-wave decomposing method［J］. Transactions of the Chinese Society for Agricultural Machinery, 2006, 37(1): 118-120. (in Chinese)
[2] 赵慧敏, 梅检民, 肖云魁，等. 基于双谱和变精度粗糙集理论的柴油机故障特征自动提取［J］. 振动与冲击, 2011,30(6):223-228.
ZHAO Hui-min, MEI Jian-min, XIAO Yun-kui, et al. Automatic extraction of fault features for diesel engine based on bispectrum approach and variable precision rough set theory［J］. Journal of Vibration and Shock, 2011, 30(6): 223-228. (in Chinese)
[3] 盖强, 马孝江, 张海勇, 等．几种局域波分解方法的比较研究［J］．系统工程与电子技术, 2002, 24(2): 57-59.
GAI Qiang, MA Xiao-jiang, ZHANG Hai-yong, et al. Comparing study for decomposing methods using local wave method［J］. Systems Engineering and Electronics, 2002, 24(2): 57-59 . (in Chinese)
[4] 黄晋英, 潘宏侠, 毕世华,等. 基于双谱熵型的故障模式识别［J］. 兵工学报, 2012,33(6):718-722.
HUANG Jin-ying, PAN Hong-xia, BI Shi-hua, et al. Fault pattern recognition based on bispectrum entropy model［J］. Acta Armamentarii, 2012,33(6):718-722. (in Chinese)
[5] Huang Jinying, Pan Hongxia, Bi Shihua. Bispectrum entropy feature extraction and its application for fault diagnosis of gearbox[C]∥IEEE International Conference on Fuzzy Systems. Barcelona, Spain: IEEE, 2010.
[6] Gu F, Shao Y, Hu N, et al. Electrical motor current signal analysis using a modified bispectrum for fault diagnosis of downstream mechanical equipment［J］. Mechanical Systems and Signal Processing, 2011, 25(1):360-372.
[7] 李军伟, 韩捷. 小波包-双谱分析和Hilbert-双谱分析的滚动轴承故障诊断方法对比研究［J］. 中国工程机械学报, 2005,3(3): 297-301.
LI Jun-wei, HAN Jie. Contrast research of the method for the fault diagnosis of rolling bearing based on wavelet packet bispectrum analysis and Hilbert-bispectrum analysis［J］. Chinese Journal of Construction Machinery, 2005, 3(3): 297-301. (in Chinese)

[1]	秦国华，高杰，叶海潮，姜国杰，黄帅，赖晓春. 基于融合评价指标和神经网络的刀具磨损预测[J]. 兵工学报, 2021, 42(9): 2013-2023.
[2]	李静, 刘哲, 黄文准. 基于快速非局部均值和超分辨率重建的图像降噪算法[J]. 兵工学报, 2021, 42(8): 1716-1727.
[3]	赵屹东, 陈慧岩, 胡家铭. 双侧独立电驱动履带车辆自动机械变速器线控换挡控制方法[J]. 兵工学报, 2021, 42(3): 459-467.
[4]	王健，秦春霞，杨珂，任萍. 基于导向重构与降噪稀疏自编码器的合成孔径雷达目标识别[J]. 兵工学报, 2020, 41(9): 1861-1870.
[5]	李东瑾，杨瑞娟，李晓柏，朱晟坤，费太勇. 基于栈式降维与字典学习的辐射源调制识别[J]. 兵工学报, 2020, 41(10): 2023-2032.
[6]	任海锋，潘宏侠. 基于多分形特征的枪械自动机裂纹故障诊断[J]. 兵工学报, 2018, 39(3): 457-462.
[7]	宫鹏涵，周克栋，赫雷，陆野. 形态滤波方法在抵肩力信号降噪中的应用研究[J]. 兵工学报, 2017, 38(7): 1416-1421.
[8]	李子高，李淑秋，闻疏琳. 一种基于独立成分分析的水下宽带信号波达方位估计方法[J]. 兵工学报, 2017, 38(1): 114-122.
[9]	戴涌，钱林方，吴晓金，徐亚栋. 某火炮自动机高速机构的热-结构耦合效应仿真分析[J]. 兵工学报, 2016, 37(9): 1738-1743.
[10]	齐玉辉，徐诚. 全射弹寿命过程中的大口径机枪自动机磨损和性能衰减趋势研究[J]. 兵工学报, 2016, 37(8): 1359-1364.
[11]	李晖，张林林，常永乐，闻邦椿. 约束层阻尼对薄壁圆柱壳模态参数的影响研究[J]. 兵工学报, 2016, 37(7): 1337-1344.
[12]	孙宝，孙大刚，李占龙，燕碧娟，王军. 粘弹结构模态损耗因子分析的修正模态应变能法[J]. 兵工学报, 2016, 37(1): 155-164.
[13]	刘海鸥，晋磊，董诗瑾，苗成生. 重型自动机械变速车辆换挡序列优化[J]. 兵工学报, 2015, 36(8): 1377-1383.
[14]	邹衍，徐诚，张克. 5.8mm/7.62mm模块化步枪运动特性匹配分析[J]. 兵工学报, 2015, 36(7): 1356-1362.
[15]	苗成生，刘海鸥，赵亦农，岳甫营，陈慧岩. 基于离合器接合速度的重型越野车辆起步控制研究[J]. 兵工学报, 2015, 36(5): 769-776.

基于局域波降噪和双谱分析的自动机故障诊断研究

Fault Diagnosis for Automata Based on Local Wave Noise Reduction and Bispectral Analysis

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价