Fault feature extraction method of diesel engine cylinder based on AWMMD

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (7) : 333-340.

WANG Min1, QIN Guojun1,2, LIAO Yifan1

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Abstract

Aiming at the noise interference problem in diesel engine cylinder fault diagnosis, an adaptive weighted multi-scale morphological decomposition (AWMMD) method was proposed to extract fault features from vibration signals of each cylinder head surface. Firstly, a new combined difference morphological filter was constructed based on three combination operators, which was used to decompose vibration signals in multi-scale. Secondly, a genetic algorithm based adaptive weight assignment algorithm for each scale morphological pattern component was designed with Teager energy kurtosis as the evaluation index, and a weighted multi-scale morphological decomposition method was proposed. Finally, the adaptive weight and the morphological mode components of multi-scale decomposition were combined to obtain the optimized fault feature extraction results. The results of simulation signal test and diesel engine fault simulation signal analysis show that the proposed method can effectively suppress noise interference and extract fault features.

Key words

diesel engine cylinder / vibration signal / feature extraction / multi-scale morphological decomposition / adaptive weighted

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WANG Min1, QIN Guojun1,2, LIAO Yifan1. Fault feature extraction method of diesel engine cylinder based on AWMMD[J]. Journal of Vibration and Shock, 2023, 42(7): 333-340

References

[1] 李环宇. 基于信息融合的柴油机故障诊断技术研究[D]. 大连: 大连海事大学, 2017.
LI Huan-yu. The study on diesel engine fault diagnosis based on information fusion[D]. Dalian: Dalian Maritime University, 2017.
[2] 高志龙, 霍柏琦, 唐松林, 等. 根据瞬时转速与冲击信号诊断柴油机故障的方法[J]. 噪声与振动控制, 2016, 36(4): 156-160.
GAO Zhi-long, HUO Bo-qi, TANG Song-lin, et al. Study on fault diagnosis method for diesel engines based on instantaneous speed and impact signal[J]. Noise and Vibration Control, 2016, 36(4): 156-160.
[3] SERRA J，VINCENT L. An overview of morphological filtering[J]. Circuits Systems and Signal Processing, 1992, 11(1): 47-108.
[4] MAROAGOS P, SCHAFER R W. Morphological filters, Part I: Their set-theoretic analysis and relations to linear shift-invariant filters[J]. IEEE Transactions on Acoustics Speech & Signal Processing, 1987, 35(8): 1153-1169.
[5] 付兴民, 潘宏侠. 基于AGMF和改进灰色关联度分析的柴油机故障诊断[J]. 噪声与振动控制, 2015, 35(5): 150-153.
FU Xing-min, PAN Hong-xia. Diesel engine fault diagnosis based on AGMF and improved grey correlation analysis[J]. Noise and Vibration Control, 2015, 35(5): 150-153.
[6] 董安. 基于形态滤波和灰色理论的柴油机故障诊断研究[D]. 太原: 中北大学, 2014.
DONG An. Diesel engine fault diagnosis based on morphological filter and grey theory[D]. Taiyuan: North University of China, 2014.
[7] 卢志才, 米东, 徐章遂, 等. 多尺度多元素形态滤波自适应降噪研究[J]. 河北科技大学学报, 2011, 32(3): 228-251.
LU Zhi-cai, MI Dong, XU Zhang-sui, et al. Research in application of multi-scale and multi-element morphological filtering in geomagnetic orientation[J]. Journal of Hebei University of science and technology, 2011, 32(3): 228-251.
[8] 胡爱军, 唐贵基, 安连锁. 基于数学形态学的旋转机械振动信号降噪方法[J]. 机械工程学报, 2006, 42(4): 127-130.
HU Ai-jun, TANG Gui-ji, AN Liang-suo. De-noising technique for vibration signals of rotating machinery based on mathematical morphology Filter[J]. Journal of Mechanical Engineering, 2006, 42(4): 127-130.
[9] 王霞. 非平稳信号特征提取方法研究及其在内燃机故障诊断中的应用[D]. 天津: 天津大学, 2015.
WANG Xia. Non-stationary signal feature extraction method and its Aapplication in internal combustion engine fault diagnosis[D], Tianjin: Tianjin University, 2015.
[10] GINOLHAC G, CHANUSSOT J. Morphological and statistical approaches to improve detection in the presence of reverberation[J]. IEEE Journal of Oceanic Engineering, 2005, 30(4): 881-899.
[11] 于宏志, 沈颖刚, 毕凤荣. EMD-Robust ICA在柴油机噪声源识别中的应用[J]. 噪声与振动控制, 2014, 34(1): 178-182.
YU Hong-zhi, SHEN Ying-gang, BI Feng-rong. Application of EMD-Robust ICA to noise sources identification of diesel engines[J]. Noise and Vibration Control, 2014, 34(1): 178-182.
[12] 刘敏, 李志宁, 张英堂, 等. 基于多尺度核独立成分分析的柴油机故障诊断[J]. 振动、测试与诊断, 2017, 37(5): 892-897.
LIU Ming, LI Zhi-ning, ZHANG Ying-tang, et al. Fault diagnosis of diesel engine based on multi-scale kernel independent component analysis[J]. Journal of Vibration,Measurement & Diagnosis, 2017, 37(5): 892-897.
[13] LI L, MA G, DU X. Edge Detection in Potential-field Data by Enhanced Mathematical Morphology Filter[J]. Pure and Applied Geophysics, 2013, 170(4): 645-653.
[14] DE I, CHANDA B. Multi-focus Image Fusion using a Morphology-based Focus Measure in a Quad-tree Structure[J]. Information Fusion, 2013, 14(2): 136-146.
[15] BAI X. Morphological Image Fusion using the Extracted Image Regions and Details Based on Multi-scale Top-hat Transform and Toggle Contrast Operator[J]. Digital Signal Processing, 2013, 23(2): 542-554.
[16] ZHAO Xiuliang, CHEN Yong. Combustion parameters identification and correction in diesel engine via vibration acceleration signal[J]. Applied Acoustics, 2017, 116: 205-215.
[17] 张朋波. 多尺度形态学在振动信号处理中的应用研究[D]. 北京: 华北电力大学, 2014.
ZHANG Peng-bo. Study on the application of multi-scale morphology in vibration signal processing[D]. Beijing: North China Electric Power University, 2014.
[18] 武哲, 杨绍普, 张建超. 基于LMD自适应多尺度形态学和Teager能量算子方法在轴承故障诊断中的应用[J]. 振动与冲击, 2016, 35(3): 7-13.
WU Zhe;YANG Shao-pu;ZHANG Jian-chao. Bearing fault feature extraction method based on LMD adaptive multiscale morphology and energy operator demodulating[J]. Journal of Vibration and Shock, 2016, 35(3): 7-13.
[19] 晏云海, 郭瑜, 伍星. 基于循环谱分析的鲁棒性滚动轴承故障特征提取方法[J]. 振动与冲击, 2022, 41(6): 1-7.
YAN Yun-hai, GUO Yu, WU Xing. Robust rolling bearing fault feature extraction method based on cyclic spectrum analysis[J]. Journal of Vibration and Shock, 2022, 41(6): 1-7.
[20] 王天金, 冯志鹏, 郝如江, 等．基于Teager能量算子的滚动轴承故障诊断研究[J]. 振动与冲击, 2012, 31(2): 1-5.
WANG Tian-jin;FENG Zhi-peng;HAO Ru-jiang, et al. Fault diagnosis of rolling element bearings based on teager energy operator[J]. Journal of Vibration and Shock, 2012, 31(2): 1-5.
[21] 陈鹏, 赵小强. 基于优化VMD与改进阈值降噪的滚动轴承早期故障特征提取[J]. 振动与冲击, 2021, 40(13): 146-153.
CHEN Peng, ZHAO Xiao-qiang. Early fault feature extraction of rolling bearing based on optimized VMD and improved threshold denoising[J]. Journal of Vibration and Shock, 2021, 40(13): 146-153.
[22] 裴迪, 岳建海, 焦静. 基于自相关与能量算子增强的滚动轴承微弱故障特征提取[J]. 振动与冲击, 2021, 40(11): 101-108.
PEI Di;YUE Jian-hai;JIAO Jing. Weak fault feature extraction of rolling bearing based on autocorrelation and energy operator enhancement[J]. Journal of Vibration and Shock, 2021, 40(11): 101-108.
[23] 崔宝珍. 自适应形态滤波与局域波分解理论及滚动轴承故障诊断[D]. 太原：中北大学, 2013.
CUI Bao-zhen. The Theory of adaptive morphological filter and local wave decomposition and roller bearings fault diagnosis[D]. Taiyuan: North University of China, 2013.
[24] 宋震. 柴油机典型故障特征提取与诊断研究[D]. 天津: 天津大学, 2012.
SONG Zheng. Feature extraction and fault diagnosis research on the diesel engine[J]. Tianjin: Tianjin University, 2012.