Repository logo
    Info Pages
    Content PolicyCopyright & Access InfoDepositing to MRODeposit LicenseDeposit License SummaryFile FormatsTheses FAQDoctoral Thesis Deposit
    Communities & Collections
    All of MRO
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register using a personal email and password.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Cao X"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Item
    Human-Machine Function Allocation Method for Submersible Fault Detection Tasks
    (MDPI (Basel, Switzerland), 2024-11-19) Yang C; Pang L; Wu W; Cao X; Lu B; Piao M
    The operation and support (OS) officer is responsible for buoyancy regulation and fault detection of onboard equipment in the civil submersible. The OS officer carries out the above tasks through the human-machine interface (HMI) of a submersible buoyancy regulation and support (SBRS) system. However, the OS officer often faces uneven task frequency produced by fault tasks, which leads to an unbalanced mental workload and individual failures. To address this issue, we proposed a human-machine function allocation method based on level of automation (LOA) taxonomy and submersible task complexity (STC), aimed at improving human-machine cooperation in submersible fault detection tasks. Based on this method, we identified the LOA2 as the optimal human-computer function allocation scheme. In this study, three measurement techniques (subjective scale, work performance, and physiological status) were used to test 15 subjects to validate the effectiveness of the proposed optimal human-machine function allocation scheme. The GAMM test results also indicate that the proposed optimal human-machine function allocation scheme (LOA2) can improve the work performance of the operating system officials under low or high workloads and reduce the subjective workload.

Copyright © Massey University  |  DSpace software copyright © 2002-2026 LYRASIS

  • Contact Us
  • Copyright Take Down Request
  • Massey University Privacy Statement
  • Cookie settings
Repository logo COAR Notify