A novel multi-channel CNN-LSTM and transformer-based network for diesel engine misfire diagnosis under different noise conditions
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11431-023-2698-2.pdf
Reference10 articles.
1. Qin C, Jin Y, Zhang Z, et al. Anti-noise diesel engine misfire diagnosis using a multi-scale CNN-LSTM neural network with denoising module. CAAI Trans Intel Tech, 2023, 8: 963–986
2. Zhang P, Gao W, Li Y, et al. Misfire detection of diesel engine based on convolutional neural networks. Proc Inst Mech Eng Part D-J Automob Eng, 2021, 235: 2148–2165
3. Liu Y, Kang J, Bai Y, et al. A novel adaptive fault diagnosis algorithm for multi-machine equipment: Application in bearing and diesel engine. Struct Health Monit, 2023, 22: 1677–1707
4. Song Q, Gao W, Zhang P, et al. Detection of engine misfire using characteristic harmonics of angular acceleration. Proc Inst Mech Eng Part D-J Automob Eng, 2019, 233: 3816–3823
5. Qin C, Jin Y, Tao J, et al. DTCNNMI: A deep twin convolutional neural networks with multi-domain inputs for strongly noisy diesel engine misfire detection. Measurement, 2021, 180: 109548
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