Autor: Liu, An - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Dynamic load analysis of the connecting bolts in a universal joint
Autorzy:: An, Yuchen
Liu, Jing
Li, Zengguang
Powiązania:: https://bibliotekanauki.pl/articles/2087028.pdf
Data publikacji:: 2022
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:: dynamic loads
connecting bolts
universal joint
dynamic model
Opis:: Dynamic loads of the connecting bolts in a universal joint can greatly affect the bolt fatigue and fracture, as well as the machinery safety and stability. But few researches focused on those. To obtain the dynamic load characteristics of the connecting bolts in a universal joint, this paper established a flexible dynamic model for the connecting bolts. A multibody dynamic model of a universal joint is developed. The dynamic loads on the connecting bolts of the universal joint are analyzed. The influences of the preloads, speeds and loads are studied. The amplitude and frequency properities are obtained. The effect of the preload is small when the preload is in the range of 80%~120% of the standard value. The load and speed have great influence on the time- and frequency-domain dynamic loads of the bolts. The flexible dynamic model of the connecting bolt is closer to the actual situation than the rigid model since it can consider the preload and deformation of the bolts. This study can provide guidance for the fatigue life prediction of the universal shaft and its bolts.
Źródło:: Eksploatacja i Niezawodność; 2022, 24, 2; 211--225
1507-2711
Pojawia się w:: Eksploatacja i Niezawodność
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Camera-based PHM method in rotating machinery equipment micro-action scenarios
Autorzy:: Junfeng, An
Liu, Jiqiang
Zhen, Hao
Mengmeng, Lu
Powiązania:: https://bibliotekanauki.pl/articles/24200809.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:: deep learning
condition monitoring
Rmcad
anomaly detection
defect early warning
Opis:: The health operation of rotating machinery guarantees safety of the project. To ensure a good operating environment, current subway equipment inspections frequency is high, resulting in a waste of resources. Small abnormal changes in mechanical equipment will also contribute to the development of mechanical component defects, which will ultimately lead to the failure of the equipment. Therefore, mechanical equipment defects should be detected and diagnosed as soon as possible. Through the use of graphic processing and deep learning, this paper proposes Rmcad Framework with three aspects: condition monitoring, anomaly detection, defect early warning. Using a network algorithm, this paper proposes an improved model that has the characteristics of two-stream and multi-loss functions, which improves the accuracy of detection. Additionally, a defect warning method is constructed to improve the perception ability of equipment before failure occurs and reduce the frequency of frequent maintenance by detecting anomalies according to the degree of opening.
Źródło:: Eksploatacja i Niezawodność; 2023, 25, 1; art. no. 10
1507-2711
Pojawia się w:: Eksploatacja i Niezawodność
Dostawca treści:: Biblioteka Nauki

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