کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7195106 | 1468193 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback
ترجمه فارسی عنوان
نگهداری مبتنی بر شرایط سیستم های نیروی دریایی: تجزیه و تحلیل داده ها با حداقل بازخورد
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
تحلیل داده ها، سیستم های نیروی دریایی، تعمیر و نگهداری مبتنی بر شرایط، نظارت بر یادگیری، یادگیری بی نظیر، تشخیص نوآوری، بازخورد حداقل
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی مکانیک
چکیده انگلیسی
The maintenance of the several components of a Ship Propulsion Systems is an onerous activity, which need to be efficiently programmed by a shipbuilding company in order to save time and money. The replacement policies of these components can be planned in a Condition-Based fashion, by predicting their decay state and thus proceed to substitution only when really needed. In this paper, authors propose several Data Analysis supervised and unsupervised techniques for the Condition-Based Maintenance of a vessel, characterised by a combined diesel-electric and gas propulsion plant. In particular, this analysis considers a scenario where the collection of vast amounts of labelled data containing the decay state of the components is unfeasible. In fact, the collection of labelled data requires a drydocking of the ship and the intervention of expert operators, which is usually an infrequent event. As a result, authors focus on methods which could allow only a minimal feedback from naval specialists, thus simplifying the dataset collection phase. Confidentiality constraints with the Navy require authors to use a real-data validated simulator and the dataset has been published for free use through the OpenML repository.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 177, September 2018, Pages 12-23
Journal: Reliability Engineering & System Safety - Volume 177, September 2018, Pages 12-23
نویسندگان
Francesca Cipollini, Luca Oneto, Andrea Coraddu, Alan John Murphy, Davide Anguita,