基于小波时频图与Swin Transformer的柴油机故障诊断方法

doi:10.12305/j.issn.1001-506X.2023.09.40

摘要/Abstract

摘要：

针对用传统的故障诊断方法难以对非线性非平稳的柴油机故障信号进行准确高效诊断的问题, 提出基于小波时频图与Swin Transformer的柴油机故障诊断方法。该方法可以有效结合小波时频分析在处理非线性非平稳信号方面的优势和Swin Transformer强大的图像分类能力, 通过连续小波变换将原始信号表示为小波时频图, 将小波时频图作为特征图输入到Swin Transformer进行训练, 实现柴油机故障状态识别。实验结果表明, 与对比方法相比, 所提方法具有较好的故障识别精度及稳定性, 在公开数据集和实验室实测数据中的整体故障诊断准确率分别达到100%和98.88%, 为柴油机故障诊断提供了一种新的思路。

关键词: 连续小波变换, 小波时频图, Swin Transformer, 柴油机, 故障诊断

Abstract:

In view of the problem that it is difficult to accurately and efficiently diagnosis the nonlinear and non-smooth diesel engine fault signals by traditional fault diagnosis methods, a diesel engine fault diagnosis method based on wavelet time-frequency diagram and Swin Transformer is proposed. The method can effectively combine the advantages of wavelet time-frequency analysis in processing nonlinear non-stationary signals and the powerful image classification capability of Swin Transformer, represent the original signals as wavelet time-frequency diagrams through continuous wavelet transform, and input the wavelet time-frequency diagrams as feature maps to Swin Transformer for training to achieve diesel engine fault status identification. The experimental results show that the proposed method has better fault identification accuracy and stability compared with the comparison methods, and the overall fault diagnosis accuracy reaches 100% and 98.88% in the public data set and the laboratory measured data respectively, which provides a new idea for diesel engine fault diagnosis.

Key words: continuous wavelet transform, wavelet time-frequency diagram, Swin Transformer, diesel engine, fault diagnosis

中图分类号:

TK428

刘子昌, 白永生, 李思雨, 贾希胜. 基于小波时频图与Swin Transformer的柴油机故障诊断方法[J]. 系统工程与电子技术, 2023, 45(9): 2986-2998.

Zichang LIU, Yongsheng BAI, Siyu LI, Xisheng JIA. Diesel engine fault diagnosis method based on wavelet time-frequency diagram and Swin Transformer[J]. Systems Engineering and Electronics, 2023, 45(9): 2986-2998.

图/表 24

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阶段	输出大小	Swin Transformer
阶段1	56×56	$\text{concat} 4 \times 4, 96-\mathrm{d}, \mathrm{LN}\\\left\{\begin{array}{l}\text { window size }: 7 \times 7 \\\operatorname{dim} 96, \text { heads }: 3\end{array}\right\} \times 2 $
阶段2	28×28	$ \text{concat} 4 \times 4, 192-\mathrm{d}, \mathrm{LN}\\\left\{\begin{array}{l}\text { window size: } 7 \times 7 \\\operatorname{dim} 192 \text {, heads: } 6\end{array}\right\} \times 2$
阶段3	14×14	$ \text{concat} 4 \times 4, 384-\mathrm{d}, \mathrm{LN}\\\left\{\begin{array}{l}\text { window size: } 7 \times 7 \\\operatorname{dim} 384, \text { heads }: 12\end{array}\right\} \times 6$
阶段4	7×7	$\text{concat} 4 \times 4, 768-\mathrm{d}, \mathrm{LN}\\\left\{\begin{array}{l}\text { window size }: 7 \times 7 \\\operatorname{dim} 768 \text {, heads }: 24\end{array}\right\} \times 2$

状态序号	故障位置	故障直径/ mm	电机载荷/ hp	电机转速/(r/min)
1	正常	-	0	1 797
2	内圈故障	0.177 8	0	1 797
3	内圈故障	0.355 6	0	1 797
4	内圈故障	0.544 3	0	1 797
5	外圈故障	0.177 8	0	1 797
6	外圈故障	0.355 6	0	1 797
7	外圈故障	0.544 3	0	1 797
8	滚动体故障	0.177 8	0	1 797
9	滚动体故障	0.355 6	0	1 797
10	滚动体故障	0.544 3	0	1 797

模型	准确率/%		损失值
模型	训练集	验证集	训练集	验证集
小波时频图- Swin Transformer	100.00	100.00	4.17e-05	1.01e-04
短时傅里叶变换- Swin Transformer	100.00	100.00	7.36e-05	3.57e-04
小波时频图-ViT	100.00	99.32	1.42e-04	2.82e-02
小波时频图-2DCNN	99.89	99.83	9.83e-03	9.02e-03

项目	指标
类型	四冲程、直列、水冷、高压共轨
尺寸/mm	1 330×970×1 005
缸径×行程/mm	107×125
型号	锡柴CA6DF3-20E3
共轨系统	BOSCH电控共轨
净功率/kW	147
额定功率/kW	155
净重/kg	700(不含离合器、中冷器)
额定转速/(r/min)	2 300
进气形式	增压中冷
单缸气门数/个	2
点火顺序	1-5-3-6-2-4
压缩比	17.4
总排量/L	6.7
最大扭矩/NM	760
最大马力/ps	200
全负荷最低燃油功率/(g/kW·h)	≤205
适配范围	8.5~11 m公路大中型人员运输车、12 t以上中重型载重运输车

状态序号	故障模式
1	正常状态
2	一缸失火
3	二缸失火
4	空气滤清器堵塞
5	一缸失火和二缸失火
6	空滤堵塞和一缸失火
7	空滤堵塞和二缸失火