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Artificial Intelligence Application in Machine Condition Monitoring and Fault Diagnosis [chapter]

Yasir Hassan Ali
2018 Artificial Intelligence - Emerging Trends and Applications  
Artificial intelligence (AI) is a successful method of machine condition monitoring and fault diagnosis since these techniques are used as tools for routine maintenance.  ...  The subject of machine condition monitoring and fault diagnosis as a part of system maintenance has gained a lot of interest due to the potential benefits to be learned from reduced maintenance budgets  ...  Acknowledgements The author would like to thank Northern Technical University in Iraq through Professor Dr Mowafaq Y. Hamdoon, the Chancellor of the university for supporting this work.  ... 
doi:10.5772/intechopen.74932 fatcat:wuz6jnad4vff7bln4blfv3kwzm

The Role of Artificial Intelligence (AI) in Condition Monitoring and Diagnostic Engineering Management (COMADEM): A Literature Survey

B. K. Nagaraja Rao
2021 American Journal of Artificial Intelligence  
AI techniques such as, knowledge based systems, expert systems, artificial neural networks, genetic algorithms, fuzzy logic, casebased reasoning and any combination of these techniques (hybrid systems)  ...  , machine learning, biomimicry such as swarm intelligence and distributed intelligence. are widely used by multi-disciplinarians to solve a whole range of hitherto intractable problems associated with  ...  [86][82]introduces the principles and the algorithm model of the ant colony algorithm.Then the fault diagnosis system of neural network(NN)is established.ACA algorithm is used to train a NN for fault  ... 
doi:10.11648/j.ajai.20210501.12 fatcat:gvplqmpqubdw3pquik5eavux5u

A survey on artificial intelligence based techniques for diagnosis of hepatitis variants

Adetokunbo MacGregor John-Otumu, Godswill U. Ogba, Obi C. Nwokonkwo
2020 Journal of Advances in Science and Engineering  
aspect of integrating the major hepatitis variants into a single predictive model using effective intelligent machine learning techniques in order to reduce cost of diagnosis and quick treatment of patients  ...  This study reveals furthermore a serious gap in knowledge in terms of single hepatitis type prediction or diagnosis in all the papers considered, and recommends that the future road map should be in the  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.37121/jase.v3i1.83 fatcat:2kb3zwrpunejlcbw26x7xznj6m

Concurrent Fault Diagnosis for Rotating Machinery Based on Vibration Sensors

Qing-Hua Zhang, Qin Hu, Guoxi Sun, Xiaosheng Si, Aisong Qin
2013 International Journal of Distributed Sensor Networks  
Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment.  ...  It is important to enable reliable, safe, and efficient operation of large-scale and critical rotating machinery, which requires us to achieve accurate diagnosis of concurrent fault, for example, rolling  ...  Acknowledgments This work was partially supported by the NSFC under Grant 61174113 and the Natural Science Fund of Guangdong Province under Grant S2011020002735.  ... 
doi:10.1155/2013/472675 fatcat:kju5n5kty5grlm5bf4h7eft43e

Integration of ART-Kohonen neural network and case-based reasoning for intelligent fault diagnosis

Bo-Suk Yang, Tian Han, Yong-Su Kim
2004 Expert systems with applications  
This paper presents a new approach for integrating case-based reasoning (CBR) with an ART-Kohonen neural network (ART-KNN) to enhance fault diagnosis.  ...  When solving a new problem, the neural network is used to make hypotheses and to guide the CBR module in the search for a similar previous case that supports one of the hypotheses.  ...  The authors (Yang, Han, & An, 2003) proposed a fault diagnosis network (ART-Kohonen neural network, ART-KNN) which synthesizes the adaptive resonance theory (ART) (Carpenter & Grossberg, 1988) and  ... 
doi:10.1016/j.eswa.2003.09.009 fatcat:eecs76sxozfzdglp56q4dtom3u

A new cognitive-based massive alarm management system in electrical power administration

O. Aizpurua, R. Galan, A. Jimenez
2008 2008 7th International Caribbean Conference on Devices, Circuits and Systems  
Additionally, in this methodology, a rule based expert system is used to treat the alarms with a neural net based approach to treat the historical database of alarms and failures.  ...  Here, the integration is developed using the ontology of each system domains, i.e., the ontology corresponding to the alarms, controls, events, energy flow and trigger sequence.  ...  A typical "Fuzzy Cognitive Map Neural Network" (FCM) based on Nonlinear Hebbian Rule was implemented.  ... 
doi:10.1109/iccdcs.2008.4542607 fatcat:tcp3nto3zjhrfgzwmp4id5wg7a

Methodologies and Applications of Artificial Intelligence in Systems Engineering

Awatef K. Ali, MagdiSadek Mostafa Mahmoud
2022 International Journal of Robotics and Control Systems  
These are knowledge-based systems (KBS), artificial neural networks (ANN), and fuzzy logic and systems (FLS).  ...  To illustrate the concepts, merits, and demerits, a typical application is given from each methodology. The relationship between ANN and FLS is emphasized.  ...  planning system AIPS, and (application 3) the use and implementation of AI in VLSI design and verification, fault diagnosis, and test genera-tion.  ... 
doi:10.31763/ijrcs.v2i1.532 fatcat:nl5ylioc6vbu7iw6hjdvijvigi

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation [article]

Tarek R. Besold, Artur d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro Domingos, Pascal Hitzler, Kai-Uwe Kuehnberger, Luis C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon (+1 others)
2017 arXiv   pre-print
Such systems have shown promise in a range of applications, including computational biology, fault diagnosis, training and assessment in simulators, and software verification.  ...  The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas.  ...  An example of a neural-symbolic system that is already providing a contribution of this type to problems in bioinformatics and fault diagnosis is the Connectionist Inductive Learning and Logic Programming  ... 
arXiv:1711.03902v1 fatcat:3fod6z4oevhplpv2hzlkguyqiu

An Overview of Neuromorphic Computing for Artificial Intelligence Enabled Hardware-based Hopfield Neural Network

Zheqi Yu, Amir M. Abdulghani, Adnan Zahid, Hadi Heidari, Muhammad A. Imran, Qammer H. Abbasi.
2020 IEEE Access  
Inspired by biology, this novel system has implemented the theory of human brain modeling by connecting feigned neurons and synapses to reveal the new neuroscience concepts.  ...  Towards the end, we conclude with a broad discussion and a viable plan for the latest application prospects to facilitate developers with a better understanding of the aforementioned model in accordance  ...  ACKNOWLEDGMENT Authors would like to thank Sultan Qaboos University (Government of the Sultanate of Oman) for supporting Dr. A. M. Abdulghani.  ... 
doi:10.1109/access.2020.2985839 fatcat:mclixaatyzbk7kn4lvshxw7aie

Early Detection Of Abnormal Emergent Behaviour

Lambert Spaanenburg
2007 Zenodo  
Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007  ...  Faults are modelled separately and Fault Diagnosis and Isolation (FDI) is based on classifying machine behaviour as normal or having a known and characterized fault [1] , [2] .  ...  The number of possible states and state-interactions explodes with increased freedom in local throughput and local control & calibration, and a global model of the emergent behaviour of a system using  ... 
doi:10.5281/zenodo.40559 fatcat:owf6ndiyzfb5pduyqpq7nvunnq

Potential, Challenges and Future Directions for Deep Learning in Prognostics and Health Management Applications [article]

Olga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe
2020 arXiv   pre-print
, diagnosing and predicting faults of complex industrial assets has been limited.  ...  The current paper provides a thorough evaluation of the current developments, drivers, challenges, potential solutions and future research needs in the field of deep learning applied to Prognostics and  ...  Acknowledgment The contributions of Olga Fink and Qin Wang were funded by the Swiss National Science Foundation (SNSF) Grant no. PP00P2 176878.  ... 
arXiv:2005.02144v1 fatcat:wxm3dstogjfkhbcu6aueyaddja

Spectrum Enhanced Fault Localization with Artificial Intelligence Paradigm for Software Diagnosis

P. Merlin
2019 International Journal for Research in Applied Science and Engineering Technology  
The proposed approach based neural network was used to find the results on the given public dataset.  ...  The application of hybrid artificial neural network (ANN) and Quantum Particle Swarm Optimization (QPSO) [7] were investigated in software fault-proneness prediction.  ...  Barinel is a combination of model-based diagnosis (MBD) and spectrumbased fault localization (SFL).  ... 
doi:10.22214/ijraset.2019.1036 fatcat:llekbzr5ivfydl7s76td4dpoqe

Modeling the faulty behaviour of digital designs using a feed forward neural network approach

Zeynab Mirzadeh, Jean-Francois Boland, Yvon Savaria
2015 2015 IEEE International Symposium on Circuits and Systems (ISCAS)  
Finally, neural network and its advantage with regard to fault diagnosis and fault clustering are discussed.  ...  Dataset generation A neural network needs a relevant dataset for proper training.  ...  It is computed by using outputs from the neural network based model of circuit C17. , is the probability of having error type when the input of the model is . for(int i = 0; i < actual.rows ; i ++) { for  ... 
doi:10.1109/iscas.2015.7168934 dblp:conf/iscas/MirzadehBS15 fatcat:lljjcbpgynd77ogojbohmrjxfi

Potential, challenges and future directions for deep learning in prognostics and health management applications

Olga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe
2020 Engineering applications of artificial intelligence  
Not all of the signals contain information on a specific fault type since different fault types are affecting different signals and the correspondence is generally not one-to-one.  ...  , diagnosing and predicting faults of complex industrial assets has been limited.  ...  Acknowledgements The contributions of Olga Fink and Qin Wang were funded by the Swiss National Science Foundation (SNSF) Grant no. PP00P2_176878.  ... 
doi:10.1016/j.engappai.2020.103678 fatcat:6heplbhuozautml5p7pzwrlfvq

A Plausibility-based Fault Detection Method for High-level Fusion Perception Systems

Florian Geissler, Alexander Unnervik, Michael Paulitsch
2020 IEEE Open Journal of Intelligent Transportation Systems  
Similar to the reasoning of human intuition, the final outcome of a complex black-box procedure is verified against given expectations of an object's behavior.  ...  In this article, we apply and evaluate collaborative, sensor-generic plausibility checking as a mean to detect empirical perception faults from their statistical fingerprints.  ...  We test our plausibility-based fault diagnosis in simulation, using the injection of typical perception faults as identified from real-world infrastructure experiments.  ... 
doi:10.1109/ojits.2020.3027146 fatcat:iajki3vpezcbzajmlsul7mpkr4
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