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- W2364176759 abstract "The hydraulic system of variable frequency fault detection problem accurately.The hydraulic system of variable frequency control signal complex,fault detection of the data collected huge amount,often appear fault detection data crosstalk noise and not clear increase.The traditional frequency hydraulic system fault detection rely mainly on the subjective experience and parameters measurement of the methods for fault diagnosis,these methods of data crosstalk,the impact of not remove,often appear misdiagnosis and virtual diagnosis phenomenon.Therefore put forward a kind of PSO-BP frequency hydraulic system fault detection method,variable frequency hydraulic control system fault input parameters through the optimized to the neural network fault diagnosis model training,overcome fault data crosstalk fuzzy not clear faults.Experiments show that after the optimal neural network model variable frequency hydraulic system can be the fault detection accuracy greatly improved,the actual hydraulic system production is of guiding significance." @default.
- W2364176759 created "2016-06-24" @default.
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- W2364176759 date "2013-01-01" @default.
- W2364176759 modified "2023-09-26" @default.
- W2364176759 title "Frequency Conversion of Hydraulic System Failure Detection Based on PSO-BP" @default.
- W2364176759 hasPublicationYear "2013" @default.
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