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Feature selection for ANNs using genetic algorithms in condition monitoring

Lindsay B. Jack, Asoke K. Nandi
1999 The European Symposium on Artificial Neural Networks  
This paper examines the use of a Genetic Algorithm GA to select the most signi cant input features from a large set of possible features in machine condition monitoring contexts.  ...  Arti cial Neural Networks ANNs can b eused successfully to detect faults in rotating machinery, using statistical estimates of the vibration signal as input features.  ...  Acknowledgements Thanks must b eexpressed to Weir Pumps for the loan of the machine set used in the experiments.  ... 
dblp:conf/esann/JackN99 fatcat:3or6myhbbbbbplgq4mk5tomq4y

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

Yasir Hassan Ali
2018 Artificial Intelligence - Emerging Trends and Applications  
However, the use of acoustic emission (AE) signal analysis and AI techniques for machine condition monitoring and fault diagnosis is still rare.  ...  Intelligent systems such as artificial neural network (ANN), fuzzy logic system (FLS), genetic algorithms (GA) and support vector machine (SVM) have previously developed many different methods.  ...  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

Acoustic Emission Signal Analysis and Artificial Intelligence Techniques in Machine Condition Monitoring and Fault Diagnosis: A Review

Yasir Hassan Ali, Roslan Abd Rahman, Raja Ishak Raja Hamzah
2014 Jurnal Teknologi  
However, the use of Acoustic Emission signal analysis and artificial intelligence techniques for machine condition monitoring and fault diagnosis is still rare.  ...  A recently developed method is by using artificial intelligence techniques as tools for routine maintenance.  ...  A simple problem of a roller with health monitoring was utilized to illustrate the effectiveness of GA in AE feature selection for fault classification by using ANNs.  ... 
doi:10.11113/jt.v69.3121 fatcat:zi2tpwcpb5fttgxurtpuzeduzq

Adaptive and Intelligent Systems for Generator Monitoring and Protection Purposes

Waldemar Rebizant, Janusz Szafran, Seung-Jae Lee, Sang-Hee Kang
2003 IFAC Proceedings Volumes  
As a result, the measurements can be performed with high accuracy in wide frequency band conditions, i.e. also for generator start-up, etc.  ...  New adaptive scheme for signal parameter measurement for generator monitoring and protection is presented.  ...  Selective frequency response of the filters and resulting selective features of estimators make them inadequate for application in off-nominal frequency conditions.  ... 
doi:10.1016/s1474-6670(17)34473-7 fatcat:szhfjntqffajniwejv75iyycqm

Rolling Element Bearing Condition Monitoring Based on Vibration Analysis Using Statistical Parameters of Discrete Wavelet Coefficients and Neural Networks

Vahid Kazemi Golbaghi
2017 International Journal of Automation and Smart Technology  
The ANN parameters were separately optimized using three optimization algorithms.  ...  These features were calculated in the time and wavelet domains and applied to Artificial Neural Networks (ANNs) as the feature vector to classify the condition of a bearing into one healthy and three faulty  ...  Statistical parameters are one of the most commonly used feature sets used in machine condition monitoring.  ... 
doi:10.5875/ausmt.v7i1.1201 fatcat:47fng5dewjhgjat7wlvyspm3u4

Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays

Eungyeong Kim, Seok Lee, Jae Kim, Chulki Kim, Young Byun, Hyung Kim, Taikjin Lee
2012 Sensors  
This was achieved using an odor monitoring system with a newly developed neural-genetic classification algorithm (NGCA). The system shows the enhancement in the sensitivity of the detected gas.  ...  Experiments showed that the proposed NGCA delivered better performance than the previous genetic algorithm (GA) and artificial neural networks (ANN) methods. We also used PCA for data visualization.  ...  The signals from multisensors were evaluated using principal components analysis (PCA) [20, 21] and artificial neural networks (ANNs), while the selection of possible features using a genetic algorithm  ... 
doi:10.3390/s121216262 pmid:23443378 pmcid:PMC3571782 fatcat:ihbtaj43h5cflhqvpmhbszntfa

Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems

Abhinav Saxena, Ashraf Saad
2007 Applied Soft Computing  
) for condition monitoring of mechanical systems.  ...  We show that a GA can be used to select a smaller subset of features that together form a genetically fit family for successful fault identification and classification tasks.  ...  the experimental data sets obtained for the work.  ... 
doi:10.1016/j.asoc.2005.10.001 fatcat:aaa67rwyjrgazecxmjvfemiu3y

Evolutionary feature selection applied to artificial neural networks for wood-veneer classification

Marco Castellani, Hefin Rowlands
2008 International Journal of Production Research  
Evolutionary feature selection applied to artificial neural networks for wood veneer classification.  ...  The novelty of the method lies in the implementation of the embedded approach in an evolutionary feature selection paradigm.  ...  The FeaSANNT (Feature Selection and ANN Training) algorithm uses the embedded approach for the selection of the data attributes for ANN systems.  ... 
doi:10.1080/00207540601139955 fatcat:227pnxaagrdmzko433u5irkerm

Design and implementation of an automatic condition‐monitoring expert system for ball‐bearing fault detection

A. Hajnayeb, S.E. Khadem, M.H. Moradi
2008 Industrial Lubrication and Tribology  
Research limitations/implications -The method can be used for other machinery condition-monitoring systems which are based on ANN.  ...  Design/methodology/approach -An algorithm is used to select the best subset of features to boost the success of detecting healthy and faulty ball.  ...  So, feature selection methods have been recently used in condition monitoring systems (Matsuura, 2004; .  ... 
doi:10.1108/00368790810858395 fatcat:qujufdp3zvdbpk6litusuggtza

Intelligent fault diagnosis of rotating machine elements using machine learning through optimal features extraction and selection

Syed Muhammad Tayyab, Eram Asghar, Paolo Pennacchi, Steven Chatterton
2020 Procedia Manufacturing  
Importance of feature selection for optimal performance of KNN in defect classification is studied by selecting most important and useful features using Genetic Algorithm (GA).  ...  Results show the ability of KNN classifier in combination with GA for correct and confident fault diagnosis of rotating machine elements in case of proper selection of parameters for features extraction  ...  Genetic Algorithm (GA) is used for effective feature selection for isolating the best features evaluated through fitness criteria.  ... 
doi:10.1016/j.promfg.2020.10.038 fatcat:cxrrvckslfbytjxplwdttjtywi

A New Method for Mechanical Fault Recognition of Extra-high Voltage Circuit Breaker

Dongyan Li, Mingzhe Rong, Ting Wang, Xiaohua Wang
2012 Physics Procedia  
It is of important to recognize the mechanical fault for extra-high voltage Circuit Breakers (CBs) in GIS, when the condition monitoring of CBs is realized.  ...  The algorithm of LibSVM is improved by using Genetic Algorithm (GA), and the GA-LibSVM can obtain high recognition accuracy than usual LibSVM for mechanical fault recognition of CB.  ...  Reference [5] provided a method to obtain the mechanism dynamic features for the CB, and proposed an ANN algorithm for condition recognition of CB.  ... 
doi:10.1016/j.phpro.2012.02.058 fatcat:jnjgt3muengjvdn5xtz5ohmla4

A Parallel Evolutionary Computing-Embodied Artificial Neural Network Applied to Non-Intrusive Load Monitoring for Demand-Side Management in a Smart Home: Towards Deep Learning

Yu-Hsiu Lin
2020 Sensors  
This work addresses NILM by a parallel Genetic Algorithm (GA)-embodied Artificial Neural Network (ANN) for Demand-Side Management (DSM) in a smart home.  ...  Therefore, in this work, a parallel GA has been conducted and used to integrate meta-heuristics (evolutionary computing) with an ANN (neurocomputing) considering its evolution in a parallel execution relating  ...  Acknowledgments: The author would like to sincerely thank the reviewers for their valuable comments and suggestions on this work.  ... 
doi:10.3390/s20061649 pmid:32188065 fatcat:onqwjrmk7rhddbvln5lwrtjfdi

Compressor fault diagnosis based on SVM and GA

Milad Golmoradi, Ebrahim Ebrahimi, Mohamad Javidan
2017 Vibroengineering PROCEDIA  
Kernel function used here in the support vector machine is RBF in which the parameters of support vector machine were optimized using Genetic Algorithm for better performance to increase the accuracy of  ...  Great attention has been paid to the condition monitoring and fault diagnosis of the Compressor by the field engineers and technicians.  ...  Some functions used in condition monitoring and extraction of features are represented in Table 2 .  ... 
doi:10.21595/vp.2017.18392 fatcat:6g2t5f4qdfaanilbmyfoz3zt5q

A survey on ecg signal monitoring through sensor and prediction of heart attack with the help of optimized neural network using genetic algorithm

2016 International Journal of Latest Trends in Engineering and Technology  
This system calculates the number of hidden nodes for neural network which train the network with proper selection of neural network architecture and uses the global optimization of genetic algorithm for  ...   Feature Extraction: This includes operations for representing the data appropriately and selecting specific features from this representation.  ... 
doi:10.21172/1.81.019 fatcat:7i26g3ga5bectgjx3jq5wf4jku

Bearing Fault Detection Using Artificial Neural Networks and Genetic Algorithm

B Samanta, Khamis R Al-Balushi, Saeed A Al-Araimi
2004 EURASIP Journal on Advances in Signal Processing  
The characteristic parameters like number of nodes in the hidden layer of MLP and the width of RBF, in case of RBF and PNN along with the selection of input features, are optimized using genetic algorithms  ...  For each trial, the ANNs are trained with a subset of the experimental data for known machine conditions. The ANNs are tested using the remaining set of data.  ...  The authors would also like to thank the reviewers for their suggestions that helped revising the paper to its present form.  ... 
doi:10.1155/s1110865704310085 fatcat:ti3nl7yg5rhgbhc4p4n5wtfzf4
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