Journal ArticleDOI
An overview of time-based and condition-based maintenance in industrial application
TLDR
It can be concluded that the application of the CBM technique is more realistic, and thus more worthwhile to apply, than the TBM one, however, further research on CBM must be carried out in order to make it more realistic for making maintenance decisions.About:
This article is published in Computers & Industrial Engineering.The article was published on 2012-08-01. It has received 729 citations till now. The article focuses on the topics: Condition-based maintenance & Predictive maintenance.read more
Citations
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Journal ArticleDOI
Condition monitoring of a wind turbine drive train based on its power dependant vibrations
TL;DR: In this article, an approach for condition health monitoring and fault diagnosis in wind turbine gearboxes and generators by means of analysing the power dependant vibrations gathered is presented, based on the establishment of the normal operation boundaries for carrying out the identification of deviations related to a defect.
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Multilayer Perceptron approach to Condition-Based Maintenance of Marine CODLAG Propulsion System Components
TL;DR: Using data available in UCI, online machine learning repository, MLPs for prediction of gas turbine (GT) and GT compressor decay state coefficients are designed and best results are achieved if MLP is designed with four hidden layers of 100, 50, 50 and 20 ANs, respectively.
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Predicting condition based on oil analysis : A case study
TL;DR: In this paper, the authors present and discuss a model for condition monitoring of diesel engines of a fleet of urban buses and develop a predictive maintenance policy for oil replacement based on the analysis of the oil condition.
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Degradation Prediction of Rail Tracks: A Review of the Existing Literature
TL;DR: A comprehensive review of rail degradation prediction models, their parameters, and the strengths and weaknesses of each model is provided in this paper, where a comparison of different models of degradation of rail tracks is also provided.
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Ensemble Machine Learning and Forecasting Can Achieve 99% Uptime for Rural Handpumps
TL;DR: This paper used sensor data from 42 Afridev-brand handpumps observed for 14 months in western Kenya to demonstrate how sensors and supervised ensemble machine learning could be used to increase total fleet uptime from a best-practices baseline of about 70% to >99%.
References
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Journal ArticleDOI
A review on machinery diagnostics and prognostics implementing condition-based maintenance
TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.
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Remaining useful life estimation - A review on the statistical data driven approaches
TL;DR: This paper systematically reviews the recent modeling developments for estimating the RUL and focuses on statistical data driven approaches which rely only on available past observed data and statistical models.
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Optimum Preventive Maintenance Policies
TL;DR: In this paper, two types of preventive maintenance policies are considered, and the optimum policies are determined, in each case, as unique solutions of certain integral equations depending on the failure distribution.
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Condition monitoring and fault detection of wind turbines and related algorithms: A review
TL;DR: In this article, the authors reviewed different techniques, methodologies and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns.
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Applications of maintenance optimization models : a review and analysis
TL;DR: An overview of applications of maintenance optimization models published so far and the role of these models in maintenance is analyzed and the factors which may have hampered applications are discussed.