Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Huailiang Zheng"'
Publikováno v:
IEEE Access, Vol 8, Pp 91103-91115 (2020)
In recent years, Convolutional neural networks (CNNs) have achieved start-of-art performance in the fault diagnosis field. If there is no available information on the unseen operating conditions, the model trained on the seen operating condition cann
Externí odkaz:
https://doaj.org/article/53fba01ff9cc4cb6a901bbb973c856f3
Publikováno v:
IEEE Access, Vol 7, Pp 109751-109762 (2019)
Aiming at the problem that the traditional similarity measurement methods cannot effectively measure the similarity of the time series with the difference both in the trend and detail, this paper proposes a new time series similarity measurement meth
Externí odkaz:
https://doaj.org/article/06dfafb9e64a4f04bac6a52861d50ed3
Publikováno v:
IEEE Access, Vol 7, Pp 129260-129290 (2019)
Data-driven fault diagnosis has been a hot topic in recent years with the development of machine learning techniques. However, the prerequisite that the training data and the test data should follow an identical distribution prevents the conventional
Externí odkaz:
https://doaj.org/article/d06ca9fd1c7a47b0ac3f6d4f5793cb40
Publikováno v:
Applied Sciences, Vol 10, Iss 2, p 673 (2020)
The life prediction is crucial to guarantee the reliability and safety of the mechanical system. The current prediction methods predict the life only based on the historical usage pattern of the mechanical system, and do not consider the mission prof
Externí odkaz:
https://doaj.org/article/785c32ff447f4896ae1cc88a9f54e823
Publikováno v:
Applied Sciences, Vol 9, Iss 23, p 5051 (2019)
The transient impact components in vibration signal, which are the major information for bearing fault severity recognition, are often interfered with by ambient noise. Meanwhile, for bearing fault severity recognition, the frequency band selection m
Externí odkaz:
https://doaj.org/article/49d713fab9134dc783401388aae8ed55
Publikováno v:
Automatica. 151:110903
Publikováno v:
2022 International Conference on Control, Automation and Diagnosis (ICCAD).
Publikováno v:
2022 American Control Conference (ACC).
Publikováno v:
2022 American Control Conference (ACC).
Publikováno v:
Automatica. 150:110856