Application of a New Enhanced Deconvolution Method in Gearbox Fault Diagnosis

[1]  Robert B. Randall,et al.  The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis , 2007 .

[2]  Wenhua Du,et al.  Research and application of improved adaptive MOMEDA fault diagnosis method , 2019, Measurement.

[3]  Christopher J Hardy,et al.  Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes , 2016, Magnetic resonance in medicine.

[4]  Yi Qin,et al.  Kurtogram manifold learning and its application to rolling bearing weak signal detection , 2018, Measurement.

[5]  Xiaodong Jia,et al.  A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery , 2017 .

[6]  Peter W. Tse,et al.  Order spectrogram visualization for rolling bearing fault detection under speed variation conditions , 2019, Mechanical Systems and Signal Processing.

[7]  Wenhua Du,et al.  A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network , 2019, Complex..

[8]  Wenhua Du,et al.  Research on Novel Bearing Fault Diagnosis Method Based on Improved Krill Herd Algorithm and Kernel Extreme Learning Machine , 2019, Complex..

[9]  Qing Zhao,et al.  Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection , 2017 .

[10]  Minqiang Xu,et al.  A fault diagnosis scheme for planetary gearboxes using adaptive multi-scale morphology filter and modified hierarchical permutation entropy , 2018 .

[11]  Xiai Chen,et al.  Incipient fault diagnosis of limit switch based on a ARMA model , 2019 .

[12]  Jiawei Xiang,et al.  Kernel regression residual decomposition-based synchroextracting transform to detect faults in mechanical systems. , 2019, ISA transactions.

[13]  Xianzhi Wang,et al.  Entropy Based Fault Classification Using the Case Western Reserve University Data: A Benchmark Study , 2020, IEEE Transactions on Reliability.

[14]  Jiawei Xiang,et al.  A data indicator-based deep belief networks to detect multiple faults in axial piston pumps , 2018, Mechanical Systems and Signal Processing.

[15]  Bo Peng,et al.  The FERgram: A rolling bearing compound fault diagnosis based on maximal overlap discrete wavelet packet transform and fault energy ratio , 2019, Journal of Mechanical Science and Technology.

[16]  Xiaolong Wang,et al.  Weak fault diagnosis of rolling bearing under variable speed condition using IEWT-based enhanced envelope order spectrum , 2019, Measurement Science and Technology.

[17]  Jiawei Xiang,et al.  Minimum entropy deconvolution based on simulation-determined band pass filter to detect faults in axial piston pump bearings. , 2019, ISA transactions.

[18]  Changqing Shen,et al.  A coarse-to-fine decomposing strategy of VMD for extraction of weak repetitive transients in fault diagnosis of rotating machines , 2019, Mechanical Systems and Signal Processing.

[19]  Wenhua Du,et al.  A Novel Fault Diagnosis Method of Gearbox Based on Maximum Kurtosis Spectral Entropy Deconvolution , 2019, IEEE Access.

[20]  Bin Li,et al.  Study on Slurry Noise of Electromagnetic Flowmeter Based on ARMA Power Spectrum Estimation , 2015 .

[21]  Shi Li,et al.  A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals , 2019, Comput. Ind..

[22]  Kun Yu,et al.  A Combined Polynomial Chirplet Transform and Synchroextracting Technique for Analyzing Nonstationary Signals of Rotating Machinery , 2020, IEEE Transactions on Instrumentation and Measurement.

[23]  Kai Ding,et al.  An enhanced multipoint optimal minimum entropy deconvolution approach for bearing fault detection of spur gearbox , 2019, Journal of Mechanical Science and Technology.

[24]  Robert B. Randall,et al.  Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter , 2007 .

[25]  Haiyang Pan,et al.  Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines , 2017 .

[26]  Jin Chen,et al.  Spectral kurtosis based on AR model for fault diagnosis and condition monitoring of rolling bearing , 2012 .

[27]  Wenhua Du,et al.  Application of Parameter Optimized Variational Mode Decomposition Method in Fault Diagnosis of Gearbox , 2019, IEEE Access.

[28]  Yonghao Miao,et al.  Detection and recovery of fault impulses via improved harmonic product spectrum and its application in defect size estimation of train bearings , 2016 .

[29]  Zhijian Wang,et al.  Application of an Improved Multipoint Optimal Minimum Entropy Deconvolution Adjusted for Gearbox Composite Fault Diagnosis , 2018, Sensors.

[30]  Chao Wu,et al.  Identification of Multiple Faults in Gearbox Based on Multipoint Optional Minimum Entropy Deconvolution Adjusted and Permutation Entropy , 2018, Entropy.

[31]  Changqing Shen,et al.  A new l0-norm embedded MED method for roller element bearing fault diagnosis at early stage of damage , 2018, Measurement.

[32]  Wenhua Du,et al.  Research on Fault Extraction Method of Variational Mode Decomposition Based on Immunized Fruit Fly Optimization Algorithm , 2019, Entropy.

[33]  Heimo Ihalainen,et al.  Adaptive Autoregressive Model for Reduction of Noise in SPECT , 2015, Comput. Math. Methods Medicine.

[34]  Peng Chen,et al.  Step-by-Step Fuzzy Diagnosis Method for Equipment Based on Symptom Extraction and Trivalent Logic Fuzzy Diagnosis Theory , 2018, IEEE Transactions on Fuzzy Systems.

[35]  Yuling He,et al.  Weak Fault Feature Extraction and Enhancement of Wind Turbine Bearing Based on OCYCBD and SVDD , 2019, Applied Sciences.

[36]  Huaqing Wang,et al.  A Novel Feature Enhancement Method Based on Improved Constraint Model of Online Dictionary Learning , 2019, IEEE Access.

[37]  Steven Y. Liang,et al.  Incipient Fault Feature Extraction for Rotating Machinery Based on Improved AR-Minimum Entropy Deconvolution Combined with Variational Mode Decomposition Approach , 2017, Entropy.

[38]  Jun Ma,et al.  MVMD-MOMEDA-TEO Model and Its Application in Feature Extraction for Rolling Bearings , 2019, Entropy.

[39]  Minping Jia,et al.  Research on an enhanced scale morphological-hat product filtering in incipient fault detection of rolling element bearings , 2019 .

[40]  Wenhua Du,et al.  Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis , 2019, Complex..

[41]  Arcangelo Pellegrino,et al.  Design of Delivery Valve for Hydraulic Pumps , 2018, Machines.

[42]  R. Wiggins Minimum entropy deconvolution , 1978 .

[43]  Xianzhi Wang,et al.  Early fault diagnosis of rolling bearings based on hierarchical symbol dynamic entropy and binary tree support vector machine , 2018, Journal of Sound and Vibration.

[44]  Minping Jia,et al.  A Feature Selection Framework-Based Multiscale Morphological Analysis Algorithm for Fault Diagnosis of Rolling Element Bearing , 2019, IEEE Access.

[45]  Francesco Villecco,et al.  On the Evaluation of Errors in the Virtual Design of Mechanical Systems , 2018, Machines.

[46]  Fengshou Gu,et al.  A novel procedure for diagnosing multiple faults in rotating machinery. , 2015, ISA transactions.

[47]  Xue Wei,et al.  An online damage identification approach for numerical control machine tools based on data fusion using vibration signals , 2015 .