HYDRAULIC PRESSURE SIGNAL DENOISING USING THRESHOLD SELF-LEARNING WAVELET ALGORITHM-中国期刊网

摘要 Apre-filtercombinedwiththresholdself-learningwaveletalgorithmisproposedforhydraulicpressuresignalsdenoising.Thedenoisingthresholdisself-learntinthesteadyflowstate,andthenmodifiedunderagivenlimittomakethemeansquareerrorsbetweenreconstructionsignalsanddesirableoutputsminimum,sothecorrespondingoptimaldenoisingthresholdinasingleoperatingcasecanbeobtained.Theseoptimalthresholdsareusedforthewholesignaldenoisingandaredifferentinvariouscases.Simulationresultsandcomparativestudiesshowthatthepresentapproachhasanobviouseffectofnoisesuppressionandissuperiortothoseoftraditionalwaveletalgorithmsandback-propagationneuralnetworks.Italsoprovidestheprecisedataforthenextstepofpipelineleakdetectionusingtransienttechnique.

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HYDRAULIC PRESSURE SIGNAL DENOISING USING THRESHOLD SELF-LEARNING WAVELET ALGORITHM

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HYDRAULIC PRESSURE SIGNAL DENOISING USING THRESHOLD SELF-LEARNING WAVELET ALGORITHM

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