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Saima Bhatti, Asif Ali Shaikh, Asif Mansoor and Murtaza Hussain
Machinery components undergo wear and tear over time due to regular usage, necessitating the establishment of a robust prognosis framework to enhance machinery health and avert catastrophic failures. This study focuses on the collection and analysis of v...
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Syed Safdar Hussain and Syed Sajjad Haider Zaidi
This study introduces a novel predictive methodology for diagnosing and predicting gear problems in DC motors. Leveraging AdaBoost with weak classifiers and regressors, the diagnostic aspect categorizes the machine?s current operational state by analyzin...
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Meng Ma, Zhirong Zhong, Zhi Zhai and Ruobin Sun
There are hundreds of various sensors used for online Prognosis and Health Management (PHM) of LREs. Inspired by the fact that a limited number of key sensors are selected for inflight control purposes in LRE, it is practical to optimal placement of redu...
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Ruosen Qi, Jie Zhang and Katy Spencer
This paper presents an up-to-date review of data-driven condition monitoring of industrial equipment with the focus on three commonly used equipment: motors, pumps, and bearings. Firstly, the general framework of data-driven condition monitoring is discu...
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Kang Wang, Zhi-Jiang Xu, Yi Gong and Ke-Lin Du
Vibration signal analysis is the most common technique used for mechanical vibration monitoring. By using vibration sensors, the fault prognosis of rotating machinery provides a way to detect possible machine damage at an early stage and prevent property...
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Elena Quatrini, Francesco Costantino, Xiaochuan Li and David Mba
In the industrial panorama, many processes operate under time-varying conditions. Adapting high-performance diagnostic techniques under these relatively more complex situations is urgently needed to mitigate the risk of false alarms. Attention is being p...
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Kerelous Waghen and Mohamed-Salah Ouali
This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset and...
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Riham Ginzarly, Ghaleb Hoblos and Nazih Moubayed
Due to the accelerating pace of environmental concerns and fear of the depletion of conventional sources of energy, researchers are working on finding renewable energy sources of power for different axes of life. The transportation sector has intervened ...
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Andrea Nesci, Andrea De Martin, Giovanni Jacazio and Massimo Sorli
Recent trend in the aeronautic industry is to introduce a novel prognostic solution for critical systems in the attempt to increase vehicle availability, reduce costs, and optimize the maintenance policy. Despite this, there is a general lack of literatu...
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Chinedu I. Ossai
Prognosis and remaining useful life (RUL) estimation of components and systems (C&S) are vital for intelligent asset-integrity management. The implementation of the traditional multi-level particle filter (TRMPF) has improved prognosis when compared ...
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