Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence - Couverture souple
Synopsis
Master's Thesis from the year 2017 in the subject Computer Sciences - Artificial Intelligence, grade: 9.00, Lovely Professional University, Punjab (Lovely professional university, Punjab), course: M.Tech, language: English, abstract: Residual life prediction is the technique which demonstrates how reliable a particular electronic system or component works under in specific operating conditions. The remaining useful life relies on the failure rate of a component and on the operating conditions of a device. This failure rate drifts for the duration of the life of the item with time. Life is an important aspect while choosing the electronic hardware. Residual life estimation and life prediction are two distinct terms. The importance of life estimation is to evaluate the remaining useful life of a specific component under the different stress parameters. As an increasing number of components are integrated on to a chip, the chances of failure increase, as the different parts have their own stress factors and different working conditions. So the condition monitoring strategies are utilized which enhances the reliability of a component and a suitable move to be made before any harmful breakdown happens. The electronic circuits need a failure estimation technique to protect the system from unavoidable failures. Residual life estimation of electronic components is an important fact these days as electronic components and devices becomes a great need of society. Residual life prediction is predicting the remaining useful life of a component or device based on various failure factors of any component and it also depends on the operating conditions. Many methods for predicting the life of electronic components have been developed. The life of electronic components can be predicted by creating an intelligent system for the failure analysis. The capability to predict the life of electronic components is a key to prevent the sudden costly failure and it will increase the overall performance and reliability of a system. So, remaining useful life prediction is an important factor for every active and passive electronic component such as resistor, capacitor and diode etc.
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Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence
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Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2017 in the subject Engineering - Artificial Intelligence, grade: 9.00, Lovely Professional University, Punjab (Lovely professional university, Punjab), course: M.Tech, language: English, abstract: Residual life prediction is the technique which demonstrates how reliable a particular electronic system or component works under in specific operating conditions. The remaining useful life relies on the failure rate of a component and on the operating conditions of a device. This failure rate drifts for the duration of the life of the item with time. Life is an important aspect while choosing the electronic hardware. Residual life estimation and life prediction are two distinct terms. The importance of life estimation is to evaluate the remaining useful life of a specific component under the different stress parameters. As an increasing number of components are integrated on to a chip, the chances of failure increase, as the different parts have their own stress factors and different working conditions. So the condition monitoring strategies are utilized which enhances the reliability of a component and a suitable move to be made before any harmful breakdown happens. The electronic circuits need a failure estimation technique to protect the system from unavoidable failures. Residual life estimation of electronic components is an important fact these days as electronic components and devices becomes a great need of society. Residual life prediction is predicting the remaining useful life of a component or device based on various failure factors of any component and it also depends on the operating conditions. Many methods for predicting the life of electronic components have been developed. The life of electronic components can be predicted by creating an intelligent system for the failure analysis. The capability to predict the life of electronic components is a key to prevent the sudden costly failure and it will increase the overall performance and reliability of a system. So, remaining useful life prediction is an important factor for every active and passive electronic component such as resistor, capacitor and diode etc. 116 pp. Englisch. N° de réf. du vendeur 9783668799134
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Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence
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GRIN Verlag, GRIN Verlag Okt 2018, 2018
ISBN 10 : 366879913X
ISBN 13 : 9783668799134
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Master's Thesis from the year 2017 in the subject Computer Sciences - Artificial Intelligence, grade: 9.00, Lovely Professional University, Punjab (Lovely professional university, Punjab), course: M.Tech, language: English, abstract: Residual life prediction is the technique which demonstrates how reliable a particular electronic system or component works under in specific operating conditions. The remaining useful life relies on the failure rate of a component and on the operating conditions of a device. This failure rate drifts for the duration of the life of the item with time. Life is an important aspect while choosing the electronic hardware. Residual life estimation and life prediction are two distinct terms. The importance of life estimation is to evaluate the remaining useful life of a specific component under the different stress parameters. As an increasing number of components are integrated on to a chip, the chances of failure increase, as the different parts have their own stress factors and different working conditions. So the condition monitoring strategies are utilized which enhances the reliability of a component and a suitable move to be made before any harmful breakdown happens. The electronic circuits need a failure estimation technique to protect the system from unavoidable failures. Residual life estimation of electronic components is an important fact these days as electronic components and devices becomes a great need of society. Residual life prediction is predicting the remaining useful life of a component or device based on various failure factors of any component and it also depends on the operating conditions. Many methods for predicting the life of electronic components have been developed. The life of electronic components can be predicted by creating an intelligent system for the failure analysis. The capability to predict the life of electronic components is a key to prevent the sudden costly failure and it will increase the overall performance and reliability of a system. So, remaining useful life prediction is an important factor for every active and passive electronic component such as resistor, capacitor and diode etc.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch. N° de réf. du vendeur 9783668799134
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Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2017 in the subject Engineering - Artificial Intelligence, grade: 9.00, Lovely Professional University, Punjab (Lovely professional university, Punjab), course: M.Tech, language: English, abstract: Residual life prediction is the technique which demonstrates how reliable a particular electronic system or component works under in specific operating conditions. The remaining useful life relies on the failure rate of a component and on the operating conditions of a device. This failure rate drifts for the duration of the life of the item with time. Life is an important aspect while choosing the electronic hardware. Residual life estimation and life prediction are two distinct terms. The importance of life estimation is to evaluate the remaining useful life of a specific component under the different stress parameters. As an increasing number of components are integrated on to a chip, the chances of failure increase, as the different parts have their own stress factors and different working conditions. So the condition monitoring strategies are utilized which enhances the reliability of a component and a suitable move to be made before any harmful breakdown happens. The electronic circuits need a failure estimation technique to protect the system from unavoidable failures. Residual life estimation of electronic components is an important fact these days as electronic components and devices becomes a great need of society. Residual life prediction is predicting the remaining useful life of a component or device based on various failure factors of any component and it also depends on the operating conditions. Many methods for predicting the life of electronic components have been developed. The life of electronic components can be predicted by creating an intelligent system for the failure analysis. The capability to predict the life of electronic components is a key to prevent the sudden costly failure and it will increase the overall performance and reliability of a system. So, remaining useful life prediction is an important factor for every active and passive electronic component such as resistor, capacitor and diode etc. N° de réf. du vendeur 9783668799134
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Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence
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Taschenbuch. Etat : Neu. Remaining Useful Life (RUL) Prediction of electrolytic Capacitor using Artificial Intelligence | Shivani Gulati (u. a.) | Taschenbuch | 116 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668799134 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 114859700
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