Fault Recognition of Gear Pump Based on EMD Neural Network
Aim at the non-stationary and time-variation characteristic of the gear-pump fault signal, proposing a condition recognition method for gear pump based on EMD and neural network. Take the vibration acceleration of case as the analysis object. Firstly,deal the signal with EMD, extract the main IMF co...
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Veröffentlicht in: | Applied Mechanics and Materials 2013-07, Vol.333-335, p.1635-1639 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | Aim at the non-stationary and time-variation characteristic of the gear-pump fault signal, proposing a condition recognition method for gear pump based on EMD and neural network. Take the vibration acceleration of case as the analysis object. Firstly,deal the signal with EMD, extract the main IMF components, containing the main information components. And then calculate its energy, and use the energy ratio to compose the feature vectors , which is used for BP neural network to identify the gear pump working state. The result reveals the EMD neural network method can recognize the working conditions of mesh-type high-pressure gear pump CB-KP63. |
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ISSN: | 1660-9336 1662-7482 1662-7482 |
DOI: | 10.4028/www.scientific.net/AMM.333-335.1635 |