变转速工况下液压泵故障振动信号的角域烈度特征提取方法

PDF(1127 KB)

振动与冲击 ›› 2020, Vol. 39 ›› Issue (17) : 142-149.

论文

刘思远1,2,3，王志伟1,2，姜万录1,2，李晓明4，卢明立3，卢正点3

作者信息 +

Angular domain intensity feature extraction method for fault vibration signals of hydraulic pump under variable rotating speed condition

LIU Siyuan1,2,3, WANG Zhiwei1,2, JIANG Wanlu1,2, LI Xiaoming4, LU Mingli3, LU Zhengdian3

Author information +

文章历史 +

摘要

提取对故障敏感的特征信息是提高液压泵状态评估准确性的关键；由于目前变转速工况下液压泵故障的敏感特征信息严重匮乏，导致评估准确率偏低；为此,针对液压泵滑靴磨损故障，提出角域烈度特征的新概念和新的特征提取方法。该方法利用阶比分析方法将时域非平稳振动信号转换成角域平稳信号,依据振动烈度的定义和频域计算方法,得出角域平稳振动信号的单边幅值谱和谐波频率,由此推导出三种振动信号类型(位移、速度和加速度)的角域烈度特征因子计算公式。以液压泵滑靴内边缘磨损故障为例，在变转速工况条件下提取故障振动信号的角域烈度特征因子,通过与阶次能量特征因子进行定性与定量分析比较，证实了角域烈度特征因子对滑靴磨损故障的劣化发展具有更强的敏感性。



Abstract

Extracting feature information sensitive to faults is the key to improve the correctness of hydraulic pump condition assessment, due to severe lack of sensitive feature information of hydraulic pump faults under variable rotating speed condition, the assessment correctness rate is much low. Here, a new concept of angular domain intensity feature and a new feature extraction method for hydraulic pump slipper wear faults were proposed. Non-stationary vibration signals in time domain were converted into stationary ones in angular domain with the order analysis method. According to the definition of vibration intensity and the calculation method in frequency domain, unilateral amplitude value spectra and harmonic frequencies of stationary vibration signals in angular domain were obtained, and then calculation formulas of angular domain intensity feature factors for three vibration signals including displacement, velocity and acceleration were derived. Taking inner edge wear fault of hydraulic pump slipper as an example, the angular domain intensity feature factor of fault vibration signals was extracted under variable rotating speed condition. Qualitative and quantitative contrastive analyses were performed for this feature factor and the order energy one. It was shown that the angular domain intensity feature factor is more sensitive to deterioration development of hydraulic pump slipper wear fault.

导出引用

刘思远1,2,3，王志伟1,2，姜万录1,2，李晓明4，卢明立3，卢正点3. 变转速工况下液压泵故障振动信号的角域烈度特征提取方法[J]. 振动与冲击, 2020, 39(17): 142-149

LIU Siyuan1,2,3, WANG Zhiwei1,2, JIANG Wanlu1,2, LI Xiaoming4, LU Mingli3, LU Zhengdian3. Angular domain intensity feature extraction method for fault vibration signals of hydraulic pump under variable rotating speed condition[J]. Journal of Vibration and Shock, 2020, 39(17): 142-149

参考文献

[1]孙健,李洪儒.一种基于复合谱与关联熵融合的特征提取方法[J]. 机械工程学报, 2017, 53(24):96-103.
SUN Jian, LI Hongru. Method on Feature Extraction Basd on Composite Spectrum and Relative Entropy Fusion[J]. Journal of Mechanical Engineering, 2017, 53(24):96-103.
[2] 姜万录，刘云杰，朱勇.小波脊线解调与两次EMD分解相结合的故障识别方法及应用研究[J]. 仪器仪表学报, 2013, 34(5):1131-1138.
JIANG Wanlu, LIU Yunjie, ZHU Yong. Resarch on Wavelet Demodulation and Twice EMD Based Fault Identification Method and Its Application[J]. Chinese Journal of Scientific Instrument,2013, 34(5):1131-1138.
[3] 刘玉娇, 姚恩涛, 徐红专. 基于粒子滤波和自回归谱的液压泵故障诊断[J]. 仪器仪表学报, 2012, 33(3):561-567.
LIU Yujiao, YAO Entao, XU Hongzhuan. Fault Diagnosis of Hydraulic Hump Based on Particle Filtering and Autoregressive Spectrum[J]. Chinese Journal of Scientific Instrument, 2012, 33(3):561-567.
[4] Tian Y, Lu C, Wang Z, et al. Fault Diagnosis Based on LMD-SVD and Information-geometric Support Vector Machine for Hydraulic Pumps[J]. Transactions of the Canadian Society for Mechanical Engineering, 2015, 39(3):569-580.
[5] Wang C, Wang Z, Ma J, et al. Fault Diagnosis for Hydraulic Pump Based on EEMD-KPCA and LVQ[J]. Vibroengineering Procedia, 2014, 4:188-193.
[6] 王天杨，李建勇，程卫东．基于瞬时故障特征频率趋势线和故障特征阶比模板的变转速滚动轴承故障诊断[J]. 振动工程学报, 2015, 28(6):1006-1014.
Wang Tianyang, Li Jianyong, Cheng Weidong. The Instantaneous Fault Characteristic Frequency and Fault Characteristic Order Template Based Fault Diagnosis Algorithm for Rolling Bearing under Time-varying Rotational Speed[J]. Journal of Vibration Engineering, 2015, 28(6):1006-1014.
[7] Yang Y, Wang H, Cheng J, et al. A Fault Diagnosis Approach for Roller Bearing Based on VPMCD under Variable Speed Condition[J]. Measurement, 2013, 46(8):2306-2312.
[8] Abboud D, Antoni J, Sieg-Zieba S, et al. Envelope Analysis of Rotating Machine Vibrations in Variable Speed Conditions: A comprehensive treatment[J]. Mechanical Systems & Signal Processing, 2017, 84:200-226.
[9] Tian Y, Ma J, Lu C, et al. Rolling Bearing Fault Diagnosis under Variable Conditions Using LMD-SVD and Extreme Learning Machine[J]. Mechanism & Machine Theory, 2015, 90:175-186.
[10] 赵明,林京.变转速下机械动态信息的自适应提取与状态评估[J]. 机械工程学报, 2015(8):89-89.
ZHAO Ming, LIN Jing. Adaptive Dynamic Information Extraction and State Evaluation for Machinery under Varying Speeds[J]. Journal of Mechanical Engineering, 2015(8):89-89.
[11] 刘坚, 彭富强, 于德介. 基于线调频小波路径追踪阶比跟踪算法的齿轮箱故障诊断研究[J].机械工程学报, 2009 , 45 (7) :81-86.
LIU Jian, PENG Fuqiang, YU Dejie. A New Order Tracking Method Based on Chirplet Path Pursuit and Its Application to Gearbox Fault Diagnosis[J]. Journal of mechinal Engineering, 2009, 45 (7) :81-86.
[12] Zhao M, Lin J, Xu X, et al. Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds[J]. Sensors, 2013, 13(8):10856-10875.
[13] Wang T, Ming L, Li J, et al. Rolling Element Bearing Fault Diagnosis Via Fault Characteristic Order (FCO) Analysis[J]. Mechanical Systems & Signal Processing, 2014, 45(1):139-153.
[14] 王况, 王科盛, 左明健. 基于阶次分析技术的行星齿轮箱非平稳振动信号分析[J]. 振动与冲击, 2016, 35(5):140-145.
WANG Kuang，WANG Keshang，ZUO Mingjian. Fault Diagnosis of a Planetary Gearbox Based on Order Tracking[J]. Journal of Vibration and Shock, 2016, 35(5):140-145.
[15] 樊新海, 李胜利, 安钢, 等. 装甲车辆传动装置振动烈度监测与评估[J]. 兵工学报,2009,30(3):272-275.
FAN Xinhai, LI Shengli, AN Gang, et al. Monitoring and Evaluation of Vibration Intensity of Armored Vehicle Transmission[J]. Journal of Ordnance, 2009,30 (3): 272-275.
[16] 樊新海, 赵智勇, 安钢, 等. 机械振动烈度的频域算法研究[J].装甲兵工程学院学报,2008,22(1):42-45.
FAN Xinhai, ZHAO Zhiyong, AN Gang, et al. Study on Frequency Domain Algorithm of Mechanical Vibration Intensity[J]. Journal of Armored Force Engineering Institute, 2008,22(1): 42-45.
[17] 马静云. 康复运动中表面肌电信号分析方法研究[D]. 燕山大学, 2015.
MA Jingyun. Research on Surface Electromyography Signal Analysis Method in Rehabilitation Exercise[D]. Yanshan
University, 2015.
[18] 李晓明.变转速液压泵多信息烈度特征状态评估方法研究[D].燕山大学,2018.
LI Xiaoming. Research on Multi-Information Intensity Characteristic Condition Evaluation of Variable Speed Hydraulic Pump[D]. YanShan University, 2018.
[19] 牛慧峰, 姜万录. 免疫支持向量机方法在液压泵故障诊断中的应用[J]. 中国机械工程, 2008, 19(14):0-1763.
NIU Huifeng, JIANG Wanlu. Application of Hybrid Approach Based on Immune Algorithm and Support Vector Machine for Fault Diagnosis of Hydraulic Pump[J]. China Mechanical Engineering, 2008, 19(14): 0-1763.
[20]李凌均, 张周锁, 何正嘉. 基于支持向量数据描述的机械故障诊断研究[J]. 西安交通大学学报, 2003, 37(9): 910-913.
LI Lingjun, ZHANG Zhousuo, HE Zhengjia. Research of Mechanical System Fault Diagnosis Based on Support Vector Data Description[J]. Journal of Xi'an Jiaotong University, 2003, 37(9): 910-913.