Fault Diagnosability Evaluation of Meta Actuation Units Based on SABO-VMD

doi:10.3969/j.issn.1004-132X.2025.08.013

Abstract

Abstract:

This paper introduced an evaluative approach to gauge the complexity of fault diagnosis within meta actuation units. The methodology commences with the decomposition of fault signals from these units， utilizing a VMD technique refined by SABO. The processes included the applications of a Kurtosis-based criterion to select pertinent intrinsic mode functions （IMFs）， culminating in the creation of a feature vector grounded in envelope entropy. The evaluative task then pivoted on employing Cosine distance as a measure of similarity， recasting the fault diagnosability problems into one of assessing the likeness of vibration signal feature vectors across varying fault conditions. A diagnosability evaluation matrix for the meta actuation units was formulated， which layed the foundation for a diagnostic index. It is concluded with an empirical validation using a worm gear-based meta actuation unit； the findings confirm the method’s efficacy in quantitatively gauging the diagnosability of diverse fault patterns.

Key words: meta actuation unit, fault diagnosability, subtraction-average-based optimizer （SABO）, variational mode decomposition （VMD）

摘要：

为了判断并量化元动作单元故障诊断的难度，提出一种元动作单元的故障可诊断性评价方法。利用减法平均优化算法（SABO）优化的变分模态分解（VMD）对元动作单元的故障信号进行分解，利用峭度准则筛选IMF分量，构建基于包络熵的元动作单元特征向量；以余弦距离作为相似性度量指标，将故障可诊断性定量评价问题转换为不同故障模式下振动信号特征向量的相似性度量问题；构建元动作单元故障可诊断性评价矩阵，从而建立元动作单元的故障可诊断性评价指标。最后以蜗轮元动作单元为例进行实验验证分析，结果表明所提方法能够实现元动作单元不同故障模式的可诊断性的定量评价。

关键词: 元动作单元, 故障可诊断性, 减法平均优化算法, 变分模态分解

CLC Number:

TH17

Hongyu GE, Zhan ZHAO, Anxiang GUO, Jiarui SUN. Fault Diagnosability Evaluation of Meta Actuation Units Based on SABO-VMD[J]. China Mechanical Engineering, 2025, 36(8): 1774-1783.

葛红玉, 赵展, 郭安祥, 孙佳瑞. 基于SABO-VMD的数控机床元动作单元故障可诊断性评价[J]. 中国机械工程, 2025, 36(8): 1774-1783.

Figures/Tables 18

Fig. 1 SABO-optimized VMD process flowchart

Fig. 2 Experimental platform

Fig. 3 Schematic diagram of various fault settings

Tab. 1 Worm gear meta actuation unit fault mode

故障状态编号	故障状态名称
t₀	正常
t₁	联轴器内接触面磨损
t₂	梅花星形弹性键形变
t₃	平键表面磨损
t₄	平键定位孔磨损
t₅	轴承装配间隙过大
t₆	轴承润滑不良
t₇	蜗杆轴线偏移

Fig. 4 Time-frequency domain signal of worm axis offset vibration

Fig. 5 Iterative process of SABO-optimized VMD

Fig.6 Time-frequency diagram of SABO-VMD decomposition results

Tab. 2 Local minimum envelope entropy，kurtosis and correlation coefficients

模态分量	IMF1	IMF2	IMF3	IMF4
局部最小包络熵	7.5455	7.0693	6.4656	6.4808
峭度值	4.778	3.6927	3.2509	3.9918
相关系数	0.718	0.413	0.284	0.528

Tab. 3 Types of experimental data

编号	故障类型	最佳参数（k，α）
t₀	正常	（5，1716）
t₁	联轴器内接触面磨损	（7，2115）
t₂	梅花星形弹性键形变	（3，258）
t₃	平键表面磨损	（7，2312）
t₄	平键定位孔磨损	（8，1895）
t₅	轴承装配间隙过大	（6，1058）
t₆	轴承润滑不良	（9，1127）
t₇	蜗杆轴线偏移	（4，864）

Fig. 7 Comparison between normal signal and fault signal

Fig. 8 Vibration image in normal state

Fig. 9 Vibration image of wear on the inner surface of the coupling

Fig. 10 Vibration image of deformed star-shaped elastic keys

Fig. 11 Vibration image of flat key surface wear

Fig. 12 Vibration image of wear of flat key positioning hole

Fig. 10 Vibration image with excessive bearing assembly clearance

Fig. 14 Vibration image of poor bearing lubrication

Fig. 15 Vibration image of worm axis offset

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