| [1] |
YUAN S F, CHU F L. Support vector machines-basedfault diagnosis for turbo-pump rotor [J]. MechanicalSystems and Signal Processing, 2006, 20(4): 939-952.
|
| [2] |
WANG J P, HU H T. Vibration-based fault diagnosisof pump using fuzzy technique [J]. Measurement, 2006,39(2): 176-185.
|
| [3] |
DU J, WANG S P, ZHANG H Y. Layered clusteringmulti-fault diagnosis for hydraulic piston pump[J]. Mechanical Systems and Signal Processing, 2013,36(2): 487-504.
|
| [4] |
ZHAO Z, JIA M X, WANG F L, et al. Intermittentchaos and sliding window symbol sequence statisticsbasedearly fault diagnosis for hydraulic pump on hydraulictube tester [J]. Mechanical Systems and SignalProcessing, 2009, 23(5): 1573-1585.
|
| [5] |
HUANG N E, SHEN Z, LONG S R, et al. The empiricalmode decomposition and the Hilbert spectrumfor nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal society of London, 1998,454(1): 903-955.
|
| [6] |
DYBAJ, ZIMROZ R. Rolling bearing diagnosingmethod based on empirical mode decomposition of machinevibration signal [J]. Applied Acoustics, 2014, 77:195-203.
|
| [7] |
YAN J H, LU L. Improved Hilbert-Huang transformbased weak signal detection methodology and its applicationon incipient fault diagnosis and ECG signalanalysis [J]. Signal Processing, 2013, 98: 74-87.
|
| [8] |
GEORGOULAS G, LOUTAS T, STYLIOS C D, etal. Bearing fault detection based on hybrid ensembledetector and empirical mode decomposition [J]. MechanicalSystems and Signal Processing, 2013, 41(1/2):510-525.
|
| [9] |
BIN G F, GAO J J, LI X J, et al. Early fault diagnosisof rotating machinery based on wavelet packetsempiricalmode decomposition feature extraction andneural network [J]. Mechanical Systems and SignalProcessing, 2012, 27: 696-711.
|
| [10] |
ZHENG Y, SUN X F, CHEN J, et al. Extracting pulsesignals in measurement while drilling using optimumdenoising methods based on the ensemble empiricalmode decomposition [J]. Petroleum Exploration andDevelopment, 2012, 39(6): 798-801.
|
| [11] |
CHEN Y L, ZHANG P L, XU C, et al. Fault diagnosisof rolling bearing based on DCT and EMD [J]. ElectronicMeasurement Technology, 2012, 35(2): 121-125(in Chinese).
|
| [12] |
ZANG H G, LI Q Z, WANG S Y, et al. Bearing faultdiagnosis based on improved DCT and EMD [J]. Bearing,2013(3): 53-56 (in Chinese).
|
| [13] |
BOUCHIKHI A, BOUDRAA A O. Multi-componentAM-FM signals analysis based on EMD-B-splines ESA[J]. Signal Processing, 2012, 92: 2214-2228.
|
| [14] |
LI J, PAN M C, TANG Y, et al. Analysis and preprocessingof geomagnetic signals based on morphologicalfilter and Hilbert-Huang transform [J]. Chinese Journalof Scientific Instrument, 2012, 33(10): 2175-2180(in Chinese).
|
| [15] |
ROMA N, SOUSA L. A tutorial overview on the propertiesof the discrete cosine transform for encoded imageand video processing [J]. Signal Processing, 2011,91: 2443-2464.
|
| [16] |
SOON I Y, KOH S N, YEO C K. Noisy speech enhancementusing discrete cosine transform [J]. SpeechCommunication, 1998, 24: 249-257.
|
| [17] |
JADHAV D V, HOLAMBE R S. Radon and discretecosine transforms based feature extraction and dimensionalityreduction approach for face recognition [J].Signal Processing, 2008, 88: 2604-2609.
|
| [18] |
SIGNES M T, GARC′IA J M, MORA H. Improvementof the discrete cosine transform calculation by meansof a recursive method [J]. Mathematical and ComputerModelling, 2009, 50: 750-764.
|
| [19] |
CHEN Y L, ZHANG P L, WU D H, et al. Weak faultsignal extraction and identification based on DCT [J].Noise and Vibration Control, 2012(1): 133-136 (in Chinese).
|
| [20] |
CHEN Y L, ZHANG P L, LI B, et al. Combined bearingfault diagnosis method based on energy aggregation[J]. Noise and Vibration Control, 2013(1): 191-196(in Chinese).
|
| [21] |
CAI T T, SILVERMAN B W. Incorporating informationon neighboring coefficients into wavelet estimation[J]. Sankhya Series B, 2001, 63(2): 127-148.
|
| [22] |
YANG Y, WEI Y S. Neighboring coefficients preservationfor signal denoising [J]. Circuits Syst Signal Process,2012, 31: 827-832.
|
| [23] |
HE W P, ZI Y Y, CHEN B Q, et al. Tunable Qfactorwavelet transform denoising with neighboringcoefficients and its application to ratating machineryfault diagnosis [J]. Science China Technological Sciences,2013, 56(8): 1956-1965.
|
| [24] |
YANG S P, ZHAO Z H. Improved waveletdenoisingusing neighboring coefficients and its application tomachinery fault diagnosis [J]. Journal of MechanicalEngineering, 2013, 49(17): 137-141 (in Chinese).
|
| [25] |
SU W S, WANG F T, ZHANG Z X, et al. Applicationof EMD and spectral kurtosis in early fault diagnosis ofrolling element bearings [J]. Journal of Vibration andShock, 2010, 29(3): 18-21 (in Chinese).
|
