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Condition Monitoring of Rotating Electrical Machines
Condition Monitoring of Rotating Electrical Machines
Knygos.lt klubas Knygos.lt nariams
195,01 €
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278,59 €
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Condition monitoring of engineering plants has increased in importance as engineering processes have become increasingly automated. However, electrical machinery usually receives attention only at infrequent intervals when the plant or the electricity generator is shut down. The economics of industry have been changing, placing ever more emphasis on the importance of reliable operation of the plants. Electronics and software in instrumentation, computers, and digital signal processors have impr…

Condition Monitoring of Rotating Electrical Machines (el. knyga) (skaityta knyga) | knygos.lt

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Condition monitoring of engineering plants has increased in importance as engineering processes have become increasingly automated. However, electrical machinery usually receives attention only at infrequent intervals when the plant or the electricity generator is shut down. The economics of industry have been changing, placing ever more emphasis on the importance of reliable operation of the plants. Electronics and software in instrumentation, computers, and digital signal processors have improved our ability to analyse machinery online. Condition monitoring is now being applied to a range of systems from fault-tolerant drives of a few hundred watts to machinery of a few hundred MW in major plants.

This book covers a large range of machines and their condition monitoring. This 3rd edition builds on the 2nd edition through a major revision, update of chapters and a comprehensive list of references & standards. Permanent magnet, switched reluctance and other types of machines are now covered, as well as variable speed drive machines and off-line techniques.

Contents cover an introduction to condition monitoring; rotating electrical machines; electrical machine construction, operation and failure modes; reliability of machines and typical failure rates; signal processing and instrumentation requirements; on-line temperature monitoring; on-line chemical monitoring; on-line vibration monitoring; on-line current, flux and power monitoring; on-line partial discharge (PD) electrical monitoring; on-line variable speed drive machine monitoring; off-line monitoring; condition-based maintenance and asset management; application of artificial intelligence techniques to CM; and safety, training and qualification.

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Condition monitoring of engineering plants has increased in importance as engineering processes have become increasingly automated. However, electrical machinery usually receives attention only at infrequent intervals when the plant or the electricity generator is shut down. The economics of industry have been changing, placing ever more emphasis on the importance of reliable operation of the plants. Electronics and software in instrumentation, computers, and digital signal processors have improved our ability to analyse machinery online. Condition monitoring is now being applied to a range of systems from fault-tolerant drives of a few hundred watts to machinery of a few hundred MW in major plants.

This book covers a large range of machines and their condition monitoring. This 3rd edition builds on the 2nd edition through a major revision, update of chapters and a comprehensive list of references & standards. Permanent magnet, switched reluctance and other types of machines are now covered, as well as variable speed drive machines and off-line techniques.

Contents cover an introduction to condition monitoring; rotating electrical machines; electrical machine construction, operation and failure modes; reliability of machines and typical failure rates; signal processing and instrumentation requirements; on-line temperature monitoring; on-line chemical monitoring; on-line vibration monitoring; on-line current, flux and power monitoring; on-line partial discharge (PD) electrical monitoring; on-line variable speed drive machine monitoring; off-line monitoring; condition-based maintenance and asset management; application of artificial intelligence techniques to CM; and safety, training and qualification.

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