Journal Article10.1016/J.YMSSP.2005.09.012
A review on machinery diagnostics and prognostics implementing condition-based maintenance
4.4K
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.
read more
About: This article is published in Mechanical Systems and Signal Processing. The article was published on 01 Oct 2006. The article focuses on the topics: Condition-based maintenance & Prognostics.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Deep learning and its applications to machine health monitoring
TL;DR: The applications of deep learning in machine health monitoring systems are reviewed mainly from the following aspects: Auto-encoder and its variants, Restricted Boltzmann Machines, Convolutional Neural Networks, and Recurrent Neural Networks.
2.2K
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.
2K
Artificial intelligence for fault diagnosis of rotating machinery: A review
TL;DR: This paper attempts to present a comprehensive review of AI algorithms in rotating machinery fault diagnosis, from both the views of theory background and industrial applications.
1.8K
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
TL;DR: A review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction, which provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.
1.5K
Rotating machinery prognostics: State of the art, challenges and opportunities
TL;DR: In this article, the authors synthesize and place these individual pieces of information in context, while identifying their merits and weaknesses, and discuss the identified challenges, and in doing so, alerts researchers to opportunities for conducting advanced research in the field.
1.1K
References
Optimal Replacement In The Proportional Hazards Model
Viliam Makis,Andrew K.S. Jardine +1 more
TL;DR: The form of the optimal replacement policy is found and an algorithm based on a recursive computational procedure is presented which can be used to obtain the optimal policy and the optimal expected average cost.
218
A Control-Limit Policy And Software For Condition-Based Maintenance Optimization
TL;DR: The analysis of a preventive replacement policy of the control-limit type for a deteriorating system subject to inspections at discrete points of time is presented, using Cox’s PHM with a Weibull baseline hazard function and time dependent stochastic covariates.
207
Simulation modelling of repairable multi-component deteriorating systems for ‘on condition’ maintenance optimisation
TL;DR: This work model continuously monitored deteriorating systems by using Monte Carlo simulation and embedding the resulting model within an ‘on condition’ maintenance optimisation scheme that aims at minimising the expected total system cost over a given mission time.
202
Mathematical modelling and computer simulations as an aid to gearbox diagnostics
TL;DR: In this article, the results of computer simulations and results obtained by laboratory rigs and field practice are compared, and different factors are taken into consideration: design factors, production technology factors, operational factors and change of condition factors.
193
•Book
Mechanical fault diagnosis and condition monitoring
Ralph A. Collacott
- 01 Jan 1977
TL;DR: In this article, the authors present a model for failure detection in a marine engine and show that it is possible to detect the failure of a flywheel bearing in a steam turbine by measuring the transverse vibrations of the bearing.
189