Assessment of Diesel Engine Valve Performance Degradation Status Based on Synchroextracting Enhanced Generalized S-transform

被引:0
|
作者
Liu Z. [1 ,2 ]
Bai Y. [1 ]
Li S. [1 ]
Zhang K. [3 ]
Liu M. [4 ]
Jia X. [1 ]
机构
[1] Shijiazhuang Campus, Army Engineering University of PLA, Hebei, Shijiazhuang
[2] Hebei Provincial Key Lab of Condition Monitoring and Assessment of Mechanical Equipment, Hebei, Shijiazhuang
[3] Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing
[4] Unit 96901 of PLA, Beijing
来源
Binggong Xuebao/Acta Armamentarii | 2024年 / 45卷 / 06期
关键词
diesel engine; MLPMixer; status assessment; synchroextracting enhanced generalized S-transform;
D O I
10.12382/bgxb.2023.0363
中图分类号
学科分类号
摘要
The operating status of diesel engine changes with the performance degradation of valve as the valve clearance gradually increases during operation. It is difficult to accurately assessment the performance degradation status of valve by traditional status assessment methods. A diesel engine valve performance degradation status assessment method based on synchroextracting enhanced generalized Stransform (SEEGST) is proposed. The vibration signal reflecting the status of diesel engine is collected by sensors. To solve the problems of low time-frequency resolution and weak energy aggregation in traditional signal time-frequency analysis methods, a SEEGST time-frequency analysis method is proposed based on the synchroextracting algorithm and generalized S-transform to convert the vibration signal into a two-dimensional time-frequency map. MLP-Mixer model is used to extract the time-frequency image features for training, thus realizing the assessment of diesel engine status. The proposed method is compared with five traditional methods, namely SSGST-MLPMixer, GST-MLPMixer, SEEGST-ViT, SEEGST-2DCNN and FFT spectrum-1DCNN, by conducting the valve performance degradation experiment on a diesel engine status monitoring test bench. The experimental results show that the overall assessment accuracy of the proposed method reaches 98. 96%, which can be effectively applied to the diesel engine valve performance degradation status assessment and provides a new idea for conducting the diesel engine valve performance degradation status assessment. © 2024 China Ordnance Industry Corporation. All rights reserved.
引用
收藏
页码:2003 / 2016
页数:13
相关论文
共 19 条
  • [1] LI L Y, SU T X, MA F K, Et al., Fault diagnosis method of high-pressure common rail system based on EEMD-SVM, Acta Armamentarii, 43, 5, pp. 992-1001, (2022)
  • [2] JI Y M, ZHANG W Z, YUAN Y P, Et al., Study of equivalent and influence laws of accelerated thermal fatigue life of aluminum alloy pistons in highly strengthened diesel engines, Acta Armamentarii, 43, 12, pp. 3008-3019, (2022)
  • [3] BI X B., Research on intelligent recognition method for diesel engine states based on vibration signal features, (2020)
  • [4] LIU Y S, KANG J S, WEN L, Et al., Health status assessment of diesel engine valve clearance based on BFA-BOA-VMD adaptive noise reduction and multi-channel information fusion, Sensors, 22, 21, pp. 8129-8153, (2022)
  • [5] KE Y, HU Y H, SONG E Z, Et al., A method for degradation features extraction of diesel engine valve clearance based on modified complete ensemble empirical mode decomposition with adaptive noise and discriminant correlation analysis feature fusion, Journal of Vibration and Control, 28, 19, pp. 2570-2584, (2022)
  • [6] XU Y G, WANG L, YU G, Et al., Generalized S-synchroextracting transform for fault diagnosis in rolling bearing [J], IEEE Transactions on Instrumentation and Measurement, 71, pp. 1-14, (2021)
  • [7] SHEN H, ZENG R L, YANG W C, Et al., Diesel engine fault diagnosis based on polar coordinate enhancement of time-frequency diagram, Journal of Vibration, Measurement & Diagnosis, 38, 1, pp. 27-33, (2018)
  • [8] MOU W J, SHI L S, CAI Y P, Et al., Diesel engine fault diagnosis based on the global and local features fusion of time-frequency image, Journal of Vibration and Shock, 37, 10, pp. 14-19, (2018)
  • [9] XU Y G, WANG L, HU A J, Et al., Time-extracting S-transform algorithm and its application in rolling bearing fault diagnosis, Science China Technological Sciences, 65, 4, pp. 932-942, (2022)
  • [10] WEI Z N, MAO Y X, YIN Z H, Et al., Fault detection based on the generalized Stransform with a variable factor for resonant grounding distribution networks, IEEE Access, 8, pp. 91351-91367, (2020)