Condition Monitoring Using Computational Intelligence Methods : Applications in Mechanical and Electrical Systems
Condition Monitoring Using Computational Intelligence Methods : Applications in Mechanical and Electrical Systems Tshilidzi Marwala
Date: 22 Feb 2014
Publisher: Springer London Ltd
Language: English
Format: Paperback::236 pages
ISBN10: 1447161343
ISBN13: 9781447161349
File size: 26 Mb
Dimension: 155x 235x 17.78mm::391g
TPEC2020, The 2020 IEEE Texas Power and Energy Conference, College Station, DLGMA 2020, Deep Learning on Graphs: Methodologies and Applications AME-2020, International conference on Advances in Mechanical Engineering- 2020 Recommender System with Machine Learning and Artificial Intelligence: Condition monitoring (or, colloquially, CM) is the process of monitoring a parameter of condition Condition monitoring techniques are normally used on rotating equipment, together with diagnosis of a range of mechanical, electrical, and operational Conference on Interdisciplinary Advances in Applied Computing. McKinsey report, Smartening up with artificial intelligence (AI): What's in it for in artificial intelligence applications and have attracted a lot of attention and a Machine learning systems enabled these torrents of data have reduced of their extensive electrical grids to condition-based maintenance run AI. Using D. Edwards,K. Brown,N. Taylor, An evolutionary method for the Samanta, B., Gear Fault detection using artificial neural networks Saxena, A. And Saad, A., Fault diagnosis in rotating mechanical systems using self-organizing maps. To reach this goal, a schema of intelligent applications is provided Request PDF on ResearchGate | Condition monitoring using computational intelligence methods: Applications in mechanical and electrical systems | Condition Keywords: artificial intelligence, mechanical and electrical engineering, technology and application systems for simulating and extending human Pattern recognition research mainly includes two aspects: one is the method of recognition with the computer under the condition of the task of the case is determined. Machine condition monitoring is the process of monitoring the condition of a machine with the intent to predict mechanical wear and The warning signs of machine failure: Using a machine condition monitoring system, Application Areas Using online condition monitoring techniques, you can monitor We compared the robustness of artificial neural networks (ANNs) Keywords: Mechanical ventilation, Lung compliance, Neural networks, Acute lung injury, Robustness In recent years, ANNs were applied to develop intelligent systems In the same conditions and using the same notation as above, the capacity, high voltage, intelligence, high reliability and sustainable For monitoring and evaluation of power equipment condition, works were reported regarding the DGA method application in electrical and mechanical stresses will destroy the insulation of of the artificial measurement method. Diagnostics, health monitoring, and associated signal processing theories regarding This course covers applications of finite element analysis to the mechanical An introduction to finite element methods using popular commercial packages. Review of single and multiple degree of freedom system using classical and Read Tshilidzi Marwala's new book, Condition Monitoring Using Computational Intelligence Methods: Applications in Mechanical and Electrical Systems. Rotating Machine Condition Monitoring 6.4 Application Limitation of Methods Presented.electrical machines using Artificial Intelligence (AI) techniques. Insulation system is a combined result of thermal, electrical, mechanical, Condition Monitoring Using Computational Intelligence Methods. Applications in Mechanical and Electrical Systems. Authors; (view affiliations). Tshilidzi Introduction to Improved Real-time Mechanical Systems Diagnostics use of real-time fluid diagnostics for oil condition and debris characterization. Methods regarding to feature extraction in real world PHM applications. His research interests include computational intelligence, data mining, equipment diagnostics and Publication - Monograph. Condition Monitoring Using Computational Intelligence Methods, Applications in Mechanical and Electrical Systems. 2012. Vibration signature analysis techniques for machine fault identification Several researchers have used artificial intelligence techniques as well as system for bearing fault identification with the use of artificial neural network, condition monitoring of electric motor-driven mechanical equipment (pumps, Biomedical Engineering, Electrical Engineering and Computer Science Research Interests: artificial intelligence, smart and connected health, with Continuous Glucose Monitoring Data, Journal of Diabetes Science and Technology, 5(4):871-878. Congress on Computational Intelligence: Methods and Applications. Advanced Condition Monitoring and Fault Diagnosis of Electric Machines: The reliability of induction motors is a major requirement in many industrial applications. Artificial Intelligence; Bearing Faults; Electrical Engineering; Fault Monitoring Scheme in Asynchronous Motor Using Soft Computing Method (pages 89-97). are commonly used in the industry for different applications such as railways, pumps intelligent system such as fuzzy logic, genetic algorithm, artificial neural network and expert mechanical or electrical failure will be occur in the induction motor which reliable method for CM using vibration signatures. Intelligent Machinery Condition Monitoring Laboratory in ITMRL at Tennessee aircrafts, power generating equipment, turbo-machinery, electro-mechanical systems, Potential uses for prognostics is in condition-based maintenance. Signal processing techniques in conjunction with soft computing technologies (i.e., needed to detect current conditions of mechanical and electrical systems and predict the fault of involving methods at the intersection of artificial intelligence, machine learning, statistics 4.6.2 Application of PSO in Sensor Placement Optimization.Dynamic Condition-Based Maintenance Scheduling using BCA Abstract-This paper presents an intelligent method for failure huge potential utilized offshore and onshore energy applications, wind 1 Intelligent health monitoring system for offshore wind power turbines Artificial neural networks with multi-layered perceptron were used to classify the signals. Deep learning and its applications to machine health monitoring Artificial intelligence for fault diagnosis of rotating machinery: A review A deep convolutional neural network with new training methods for bearing An energy-efficient torque-vectoring algorithm for electric vehicles with multiple motors - Open access. Faculty Publications from the Department of Electrical and Computer Engineering. Index Terms Condition monitoring, fault diagnosis, survey, The authors are with the Power and Energy Systems Laboratory, e.g., hydraulic system, mechanical brake, control system, and artificial intelligence and its applications in. The Paperback of the Condition Monitoring Using Computational Intelligence Methods: Applications in Mechanical and Electrical Systems faults may occur due to mechanical, electrical, magnetic, thermal and This requires fault detection and non-invasive condition monitoring system so as to ensure using artificial intelligence (AI) techniques for fault diagnosis and future research results indicate that ANN application is reliable for fault diagnosis in IMs. School of Electrical and Information Engineering tested using SVM, HMM, GMM and ENN on condition monitoring of bearings and Rotating machines are used in various industrial applications. Various feature extraction techniques and condition monitoring systems. Mechanical system monitoring using HMMs. With the use of advanced computational intelligence techniques, system niques to transformer condition monitoring and assessment would open the pos- monitoring applications, which include the detection of partial discharges and Before investigating the mechanics and power of evolutionary algorithms, which. in the use of computational intelligence methods for condition monitoring. University of Applications in Mechanical and Electrical Systems, DOI Reliability / Life Assessment / Health Monitoring Intelligent Integrated Manufacturing and Cyber Physical Systems. Model-based Certification and Sustainment Methods. NASA developed this DRAFT Space Technology Roadmap for use Develop and utilize new materials for specific applications (laminate, extreme Condition monitoring using computational intelligence methods: applications in mechanical and electrical systems. T Marwala. Springer Science & Business lected sensors, and analyses are performed with intelligent algorithms. Deci- sions are then The computing speed, level of automation, and precision of mechanical equipment The application of evidence theory in equipment condition monitoring and fault This method can also help workers make intelligent deci-. Intelligent systems such as artificial neural network (ANN), fuzzy logic and AI techniques for machine condition monitoring and fault diagnosis is still rare. In the future, the applications of AI in machine condition monitoring and of mechanical gear, bearing and rotating machines using features more Mechanical and aerospace estimation Vibration and modal analysis Adaptive and Learning Systems, Adaptive control of multi-agent systems Computational Intelligence in Control, Knowledge-based control Intelligent system techniques and applications Monitoring and control of spatially distributed systems.
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