Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Zhao, L.Y." wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-3 z 3
    Tytuł:
    An improved feature extraction method for rolling bearing fault diagnosis based on MEMD and PE
    Autorzy:
    Zhang, H.
    Zhao, L.
    Liu, Q.
    Luo, J.
    Wei, Q.
    Zhou, Z.
    Qu, Y.
    Powiązania:
    https://bibliotekanauki.pl/articles/259770.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    improved feature extraction method
    rolling bearing fault diagnosis
    MEMD
    PE
    Opis:
    The health condition of rolling bearing can directly influence to the efficiency and lifecycle of rotating machinery, thus monitoring and diagnosing the faults of rolling bearing is of great importance. Unfortunately, vibration signals of rolling bearing are usually overwhelmed by external noise, so the fault frequencies of rolling bearing cannot be readily obtained. In this paper, an improved feature extraction method called IMFs_PE, which combines the multivariate empirical mode decomposition with the permutation entropy, is proposed to extract fault frequencies from the noisy bearing vibration signals. First, the raw bearing vibration signals are filtered by an optimal band-pass filter determined by SK to remove the irrelative noise which is not in the same frequency band of fault frequencies. Then the filtered signals are processed by the IMFs_PE to get rid of the relative noise which is in the same frequency band of fault frequencies. Finally, a frequency domain condition indicator FFR(Fault Frequency Ratio), which measures the magnitude of fault frequencies in frequency domain, is calculated to compare the effectiveness of the feature extraction methods. The feature extraction method proposed in this paper has advantages of removing both irrelative noise and relative noise over other feature extraction methods. The effectiveness of the proposed method is validated by simulated and experimental bearing signals. And the results are shown that the proposed method outperforms other state of the art algorithms with regards to fault feature extraction of rolling bearing.
    Źródło:
    Polish Maritime Research; 2018, S 2; 98-106
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Identification of a linear epitope in the capsid protein of goose astrovirus with monoclonal antibody
    Autorzy:
    Dai, G.
    Huang, X.
    Liu, Q.
    Li, Y.
    Zhang, L.
    Han, K.
    Yang, J.
    Liu, Y.
    Xue, F.
    Zhao, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/16647377.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    epitope
    goose astrovirus
    capsid protein
    monoclonal antibody
    Opis:
    Goose astrovirus (GoAstV) is a novel avastrovirus that typically causes gosling gout and results in 2 to 20% mortality. GoAstV capsid protein is the sole structural protein, which is responsible for viral attachment, assembly, maturation as well as eliciting host antibodies. However, the epitopes within capsid protein have not been well studied. In this study, a monoclonal antibody, named 1D7, was generated against GoAstV capsid protein by hybridoma technology. Western blot results showed that this MAb could react with recombinant capsid protein expressed in E. coli. Also, it recognized the precursor of capsid protein, VP90 and VP70, in GoAstV-infected cells. Besides, excellent specificity of MAb 1D7 was further demonstrated in indirect immunofluorescence assay and immunohistochemical analysis. Epitope mapping results revealed that MAb 1D7 recognized the epitope 33QKVY 36 within Cap protein. Sequence alignment indicated that 33QKVY 36 is a conserved epitope among the isolates of goose astrovirus type 2 (GoAstV-2), suggesting the potential for its use in GoAstV-2 specific diagnostic assay. These findings may provide some insight into a function of the GoAstV capsid protein and further contribute to the development of diagnostic methods for GoAstV infection.
    Źródło:
    Polish Journal of Veterinary Sciences; 2022, 25, 4; 579-587
    1505-1773
    Pojawia się w:
    Polish Journal of Veterinary Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies