Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Zongzhen Zhang"'
Publikováno v:
Sensors, Vol 24, Iss 12, p 3833 (2024)
In a diesel engine, piston slap commonly occurs concurrently with fuel combustion and serves as the main source of excitation. Although combustion pressure can be measured using sensors, determining the slap force is difficult without conducting test
Externí odkaz:
https://doaj.org/article/b6dc0b091e394950921a1343b84f3aa3
Publikováno v:
Sensors, Vol 24, Iss 1, p 169 (2023)
Due to the superior robustness of outlier signals and the unique advantage of not relying on a priori knowledge, Convolution Sparse Filtering (CSF) is drawing more and more attention. However, the excellent properties of CSF is limited by its inappro
Externí odkaz:
https://doaj.org/article/6024ead16dd449a6af359beaf0a19e07
Publikováno v:
IEEE Access, Vol 8, Pp 92407-92417 (2020)
Sparse representation is the important principle of unsupervised learning method. In order to accurately identify the fault condition of machines, the desired feature distribution should show population sparsity and lifetime sparsity. In this paper,
Externí odkaz:
https://doaj.org/article/8834c0c744ff4902b8418d3647bc59e5
Multidimensional Blind Deconvolution Method Based on Cross-Sparse Filtering for Weak Fault Diagnosis
Publikováno v:
IEEE Access, Vol 8, Pp 209415-209427 (2020)
Fault diagnosis and condition monitoring of rotating machinery has drawn considerable attention. The complex structure of rotating machinery and poor working conditions cause two challenges: weak signature detection (WSD) and weak compound fault sepa
Externí odkaz:
https://doaj.org/article/957d3c9bda8d455b9d4e1f787275bfbe
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 2857 (2023)
Existing generative adversarial networks (GAN) have potential in data augmentation and in the intelligent fault diagnosis of bearings. However, most relevant studies only focus on the fault diagnosis of rotating machines with sufficient fault-type sa
Externí odkaz:
https://doaj.org/article/09aeae251a1c43fc9c60305e0c44d9c7
Publikováno v:
IEEE Access, Vol 7, Pp 65150-65162 (2019)
Identifying impact fault features from fault vibration signal is significantly meaningful for the fault diagnosis and condition monitoring of rotating machinery. Given defects and the working conditions, impact features are covered by background nois
Externí odkaz:
https://doaj.org/article/f04224040aac49e48a65584c7e7d9a5b
Publikováno v:
Entropy, Vol 23, Iss 8, p 1052 (2021)
The domain adaptation problem in transfer learning has received extensive attention in recent years. The existing transfer model for solving domain alignment always assumes that the label space is completely shared between domains. However, this assu
Externí odkaz:
https://doaj.org/article/53af97d6b0dc47588d56f988fa632778
Publikováno v:
Entropy, Vol 23, Iss 8, p 1075 (2021)
Fault diagnosis of mechanical equipment is mainly based on the contact measurement and analysis of vibration signals. In some special working conditions, the non-contact fault diagnosis method represented by the measurement of acoustic signals can ma
Externí odkaz:
https://doaj.org/article/09925668d52b42cca1eb87c3d03f7020
Publikováno v:
Chinese Journal of Aeronautics. 35:266-276
Due to the strong background noise and the acquisition system noise, the useful characteristics are often difficult to be detected. To solve this problem, sparse coding captures a concise representation of the high-level features in the signal using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a612fc0953864af0d94b612ab6827cd
https://doi.org/10.1016/j.cja.2021.04.012
https://doi.org/10.1016/j.cja.2021.04.012
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 71:1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9c1bc67d660c1086558ae80d016060c
https://doi.org/10.1109/tim.2022.3178488
https://doi.org/10.1109/tim.2022.3178488