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Conditional inference trees for knowledge extraction from motor health condition data

Alexis Sardá-Espinosa, Subanatarajan Subbiah, Thomas Bartz-Beielstein
2017 Engineering applications of artificial intelligence  
In this paper, a specific kind of decision tree algorithm, called conditional inference tree, is used to extract relevant knowledge from data that pertains to electrical motors.  ...  The obtained knowledge is organized in a structured way and then analyzed in the context of health condition monitoring.  ...  Because of these properties, conditional inference trees were chosen as the modeling tool for the analysis of health condition from motors and generators.  ... 
doi:10.1016/j.engappai.2017.03.008 fatcat:f6n6chybsngfrljlbd22okhvb4

Health Monitoring of Bearing and Gear Faults by Using a New Health Indicator Extracted From Current Signals

Moncef Soualhi, Khanh T.P. Nguyen, Abdenour Soualhi, Kamal Medjaher, Kamel Eddine Hemsas
2019 Measurement (London)  
This method is based on a new indicator extracted from electrical signals.  ...  Therefore, it is necessary to perform Prognostics and Health Management (PHM) for these systems.  ...  From data to features extraction and health indicators construction This subsection deals with the extraction of a new health indi cator from the three phase current signals.  ... 
doi:10.1016/j.measurement.2019.03.065 fatcat:ajoznczsr5cx7g72d2d5sdjzka

Intelligent Fault Diagnosis of Synchromesh Gearbox Using Fusion of Vibration and Acoustic Emission Signals for Performance Enhancement

T Praveenkumar, M Saimurugan, K I Ramachandran
2019 International Journal of Prognostics and Health Management  
Then the statistical features are extracted from vibration and AE signals and then the prominent features are selected using J48 decision tree algorithm respectively.  ...  In this paper, vibration and acoustic emission signals are acquired under various simulated gear and bearing fault conditions from the synchromesh gearbox.  ...  SENSOR FUSION TECHNIQUE Data mining and machine learning are the techniques which infer knowledge from raw data and then analyze the data, which gives a way for automated interpretation of the sensor data  ... 
doi:10.36001/ijphm.2019.v10i2.2738 fatcat:owb5gtkedfb7zknpn23ai7gzwi

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

Contreras-Valdes, Amezquita-Sanchez, Granados-Lieberman, Valtierra-Rodriguez
2020 Applied Sciences  
The reason for this enthusiasm derives from the remarkable benefits of its usefulness, such as the exploitation of large databases and the use of the information extracted from them in an intelligent way  ...  through the analysis and discovery of knowledge.  ...  Kantardzic [7] calls DM to the process of applying a computer-based methodology for discovering knowledge from data.  ... 
doi:10.3390/app10030950 fatcat:bgp74acuvjd6fmzffyvkrbks2m

Prediction of the voltage status of a three-phase induction motor using data mining algorithms

Aderibigbe Israel Adekitan, Ademola Abdulkareem
2019 SN Applied Sciences  
This creates a platform for developing embedded systems that are trained using knowledge acquired from data mining for performance monitoring of induction motors.  ...  For comparative analysis, the Tree Ensemble, Decision Tree, Random Forest and Support Vector Machine (SVM) were deployed for the voltage prediction.  ...  Knowledge acquired from the data mining model can be deployed as a predictive model markup language (PMML) file for training intelligent modules for performance monitoring of induction motors.  ... 
doi:10.1007/s42452-019-1720-9 fatcat:bokizwctffdvpovmnbdxoqasuu

Machine Fault Diagnosis and Prognosis: The State of The Art

Tran Van Tung, Bo-Suk Yang
2009 International Journal of Fluid Machinery and Systems  
upon the evaluation of on-line monitored data according to a rule set which is determined by expert knowledge.  ...  Machine fault diagnostic and prognostic techniques have been the considerable subjects of condition-based maintenance system in the recent time due to the potential advantages that could be gained from  ...  Data mining techniques were also applied to KBS as tools extracted diagnosis knowledge from data base.  ... 
doi:10.5293/ijfms.2009.2.1.061 fatcat:btjf42m6mbd33aszky7i4tukrq

Computer based pedestrian landscape design using decision tree templates

Baranidharan Raman, Jody R. Naderi
2006 Advanced Engineering Informatics  
Decision trees extracted from the knowledge base were used in the design of pedestrian landscapes, which were tested in a transportation simulator.  ...  In this paper, we demonstrate the application of a decision tree learning algorithm for designing pedestrian landscapes that encourage walking for health.  ...  Fig. 2 . 2 Decision tree extracted from the pedestrian post-occupancy evaluation surveys: (a) use-specific decision trees for health wakers and commuters, (b) sitespecific decision tree for different types  ... 
doi:10.1016/j.aei.2005.08.002 fatcat:et2qjxh3prb3ljksbedlg7hn34

Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification

Adrienn Dineva, Amir Mosavi, Mate Gyimesi, Istvan Vajda, Narjes Nabipour, Timon Rabczuk
2019 Applied Sciences  
In this research, the Electrical Signature Analysis as well as traditional vibration data have been considered for modeling.  ...  The contribution of this work is to propose a novel methodology for multi-label classification for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions.  ...  After, the filtered signal is used for extracting the fault features affecting the machine health.  ... 
doi:10.3390/app9235086 fatcat:3nl3t4w45bbillr6x43zl6lydq

An intelligent condition-based maintenance platform for rotating machinery

Van Tung Tran, Bo-Suk Yang
2012 Expert systems with applications  
This strategy commonly consists of sequent modules such as data acquisition, signal processing, feature extraction and feature selection, condition monitoring, etc.  ...  For these reasons, an intelligent algorithm based CBM platform is proposed in this paper to be applied for rotating machinery easily and effectively.  ...  Acknowledgments The authors gratefully acknowledge the support of Brain Korea 21 Project and The Vietnam National Foundation for Science and Technology Development (NAFOSTED) for this study.  ... 
doi:10.1016/j.eswa.2011.08.159 fatcat:cnfrwvzckjgmxfxhshydonci4u

TKGS: Tourist Keeping and Guiding System

Narjes Davari, Amir Masoud Rahmani, Sanaz Teimuri
2012 International Journal of Computer Applications  
It considers tourist's physiological condition, priorities, location and visit histories in order to offer best services.  ...  Nowadays rapid grows of information technology affected the way of our life and tourism as a part of this revolution benefits from its advantages.  ...  It is responsible for information management and information inferring in/from knowledge base.  ... 
doi:10.5120/7511-0556 fatcat:e2ldiefamfghlf7jveerk6vt54

Cognitive Training and Stress Detection in MCI Frail Older People through Wearable Sensors and Machine Learning

F. Delmastro, F. Di Martino, C. Dolciotti
2020 IEEE Access  
Therefore, we propose a mobile system architecture for online stress monitoring able to infer the stress level during a session.  ...  INDEX TERMS Cognitive training, m-health, physiological data analysis, stress detection, wearable sensors, decision support system, machine learning.  ...  inference engine to learn from the data it is modeling.  ... 
doi:10.1109/access.2020.2985301 fatcat:mzg2bjhgp5dh7enn26uxibtgba

A Decision Support System for Changes in Operation Modes of the Copper Heap Leaching Process

Manuel Saldaña, Purísima Neira, Víctor Flores, Pedro Robles, Carlos Moraga
2021 Metals  
This task involves considering mineral resources and operating conditions to provide an optimal and realistic copper extraction and processing strategy.  ...  In this work, a knowledge-based decision support system for managing the operating mode of the copper heap leaching process is presented. The domain was modeled using an ontology.  ...  This work was conducted using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health.  ... 
doi:10.3390/met11071025 fatcat:jwcqzv4hz5htvifqcfh3gpgjxy

Multi-label Classification for Fault Diagnosis of Rotating Electrical Machines [article]

Adrienn Dineva, Amir Mosavi, Mate Gyimesi, Istvan Vajda
2019 arXiv   pre-print
by using large amounts of sensory data.  ...  The contribution of this work is to propose a novel methodology using multi-label classification method for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions  ...  After, the filtered signal is used for extracting the fault features affecting the machine health.  ... 
arXiv:1908.01078v1 fatcat:exs65e24mvffpmmn2k567gyvqi

Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Wan Zhang, Min-Ping Jia, Lin Zhu, Xiao-An Yan
2017 Chinese Journal of Mechanical Engineering  
This review may be considered as a useful guidance for researchers in selecting a suitable method for a specific situation and pointing out potential research directions.  ...  However, only few comprehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition monitoring and fault diagnosis.  ...  DNN can adaptively mine representative information from the original data without the need for prior knowledge because of the depth structure.  ... 
doi:10.1007/s10033-017-0150-0 fatcat:7e7qq3xewzhqtdvb2np6q3ftv4

Predictive Maintenance: A Novel Framework for a Data-Driven, Semi-Supervised, and Partially Online Prognostic Health Management Application in Industries

Francesca Calabrese, Alberto Regattieri, Marco Bortolini, Mauro Gamberi, Francesco Pilati
2021 Applied Sciences  
Prognostic Health Management (PHM) is a predictive maintenance strategy, which is based on Condition Monitoring (CM) data and aims to predict the future states of machinery.  ...  It was conducted on data collected from a test rig and shows the potential of the proposed framework in terms of the ability to detect changes in the operating conditions and abrupt faults and storage  ...  Sci. 2021, 11, x FOR PEER REVIEW 15 of 28 latter deals with the extraction of component-level features that can reveal the health condition of the components.  ... 
doi:10.3390/app11083380 fatcat:3s7bstt4mjforexdt4uzjfg3g4
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