A new method based on variational mode decomposition （VMD） is proposed to distinguish between coal-rock fracturing and blasting vibration microseismic signals. First, the signals are decomposed to obtain the variati...A new method based on variational mode decomposition （VMD） is proposed to distinguish between coal-rock fracturing and blasting vibration microseismic signals. First, the signals are decomposed to obtain the variational mode components, which are ranked by frequency in descending order. Second, each mode component is extracted to form the eigenvector of the energy of the original signal and calculate the center of gravity coefficient of the energy distribution plane. Finally, the coal-rock fracturing and blasting vibration signals are classified using a decision tree stump. Experimental results suggest that VMD can effectively separate the signal components into coal-rock fracturing and blasting vibration signals based on frequency. The contrast in the energy distribution center coefficient after the dimension reduction of the energy distribution eigenvector accurately identifies the two types of microseismic signals. The method is verified by comparing it to EMD and wavelet packet decomposition.展开更多
Influences of large-scale climatic phenomena, such as the E1Nifio/La Nifia-Southem Oscillation （ENSO） and the Pacific Decadal Oscillation （PDO）, on the temporal variations of the annual water discharge at the Liji...Influences of large-scale climatic phenomena, such as the E1Nifio/La Nifia-Southem Oscillation （ENSO） and the Pacific Decadal Oscillation （PDO）, on the temporal variations of the annual water discharge at the Lijin station in the Huanghe （Yellow） River and at the Datong station in the Changjiang （Yangtze） River were examined. Using the empirical mode decomposition-maximum entropy spectral analysis （EMD- MESA） method, the 2- to 3-year, 8- to 14-year, and 23-year cyclical variations of the annual water discharge at the two stations were discovered. Based on the analysis results, the hydrological time series on the inter- annual to interdecadal scales were constructed. The results indicate that from 1950 to 2011, a significant downward trend occurred in the natural annual water discharge in Huanghe River. However, the changes in water discharge in Changjiang River basin exhibited a slightly upward trend. It indicated that the changes in the river discharge in the Huanghe basin were driven primarily by precipitation. Other factors, such as the precipitation over the Changjiang River tributaries, ice melt and evaporation contributed much more to the increase in the Changjiang River basin. Especially, the impacts of the inter-annual and inter-decadal climate oscillations such as ENSO and PDO could change the long-term patterns of precipitation over the basins of the two major rivers. Generally, low amounts of basin-wide precipitation on interannual to interdecadal scales over the two rivers corresponded to most of the warm ENSO events and the warm phases of the PDO, and vice versa. The positive phases of the PDO and ENSO could lead to reduced precipitation and consequently affect the long-term scale water discharges at the two rivers.展开更多
The gripper cylinder that provides braced force for Tunnel Boring Machine （TBM） might fail due to severe vibration when the TBM excavates in the tunnel. Early fault diagnosis of the gripper cylinder is important for...The gripper cylinder that provides braced force for Tunnel Boring Machine （TBM） might fail due to severe vibration when the TBM excavates in the tunnel. Early fault diagnosis of the gripper cylinder is important for the safety and efficiency of the whole tunneling project. In this paper, an online condition monitoring system based on the Empirical Mode Decomposition （EMD） method is estab- lished for fault diagnosis of the gripper cylinder while TBM is working. Firstly, the lumped mass parameter model of the gripper cylinder is established considering the influence of the variable stiffness at the rock interface, the equivalent stiffness of the oil, the seals, and the copper guide sleeve. The dynamic performance of the gripper cylinder is investigated to provide basis for its health condition evaluation. Then, the EMD method is applied to identify the characteristic frequencies of the gripper cylinder for fault diagnosis and a field test is used to verify the accuracy of the EMD method for detection of the characteristic frequencies. Furthermore, the contact stiff- ness at the interface between the barrel and the rod is calculated with Hertz theory and the relationship between the natural frequency and the stiffness varying with the health condition of the cylinder is simulated based on the dynamic model. The simulation shows that the character- istic frequencies decrease with the increasing clearance between the barrel and the rod, thus the defects could be indicated by monitoring the natural frequency. Finally, a health condition management system of the gripper cylin- der based on the vibration signal and the EMD method is established, which could ensure the safety of TBM.展开更多
To improve the accuracy of the stator winding fault diagnosis in induction motor,a new diagnostic method based on the Hilbert-Huang transform(HHT)was proposed.The ratio of fundamental zero sequence voltage to positive...To improve the accuracy of the stator winding fault diagnosis in induction motor,a new diagnostic method based on the Hilbert-Huang transform(HHT)was proposed.The ratio of fundamental zero sequence voltage to positive sequence voltage after switch-off was selected as the stator fault characteristic,which could effectively avoid the influence of the supply unbalance and the load fluctuation,and directly represent the asymmetry in the stator.Using the empirical mode decomposition(EMD)based on HHT,the zero sequence voltage after switch-off was decomposed and the fundamental component was extracted.Then,the fault characteristic can be acquired.Experimental results on a 4-kW induction motor demonstrate the feasibility and effectiveness of this method.展开更多
This work presents an advanced mathematical tool applicable to the recognition and classification of power system transients and disturbances. Disturbances without a periodic pattern or with a non-linear pattern requi...This work presents an advanced mathematical tool applicable to the recognition and classification of power system transients and disturbances. Disturbances without a periodic pattern or with a non-linear pattern require a more suitable tool than the Fourier series （Fast Fourier or Windowed Fourier Transforms）. To overcome these drawbacks, other tools have been broadly used, such as the wavelet transform. However, the wavelet transform also has some drawbacks such as the lack of adaptivity or interpretation of nonlinear phenomena that the Hilbert and Hilbert Huang Transform techniques could mitigate. The Hilbert techniques transform a time domain function into a space representation both in time and frequency. In the paper, the technique is applied to analyse several short-term and steady events, like a short circuit, a capacitor-switching transient, or a line energisation, showing the abilities of the Hilbert-based transforms.展开更多
A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to pro...A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to produce the representation of the signal. This methodallows the decomposition of one-dimensional signals into intrinsic mode functions (IMFs) usingempirical mode decomposition and the calculation of a meaningful multi-component instantaneousfrequency. Applied to fault signals , it provides new time-frequency attributes. Then the momentsand margins of the time-frequency spectrum are calculated as the feature vectors. The probabilisticneural network is used to classify different fault modes. The accuracy and robustness of theproposed methods is investigated on signals obtained during the different fault modes (early rub,loose, misalignment of the rotor).展开更多
基金This work was supported by the National Key Research and Development program of China （No. 2016YFC0801406）, Shandong Key Research and Development program （Nos. 2016ZDJS02A05 and 2018GGX 109013） and Shandong Provincial Natural Science Foundation （No. ZR2018MEE008）.
文摘A new method based on variational mode decomposition （VMD） is proposed to distinguish between coal-rock fracturing and blasting vibration microseismic signals. First, the signals are decomposed to obtain the variational mode components, which are ranked by frequency in descending order. Second, each mode component is extracted to form the eigenvector of the energy of the original signal and calculate the center of gravity coefficient of the energy distribution plane. Finally, the coal-rock fracturing and blasting vibration signals are classified using a decision tree stump. Experimental results suggest that VMD can effectively separate the signal components into coal-rock fracturing and blasting vibration signals based on frequency. The contrast in the energy distribution center coefficient after the dimension reduction of the energy distribution eigenvector accurately identifies the two types of microseismic signals. The method is verified by comparing it to EMD and wavelet packet decomposition.
基金Supported by the National Basic Research Program of China(973 Program)(No.2010CB951202)the National Natural Science Foundation of China(Nos.41376055,41030856)
文摘Influences of large-scale climatic phenomena, such as the E1Nifio/La Nifia-Southem Oscillation （ENSO） and the Pacific Decadal Oscillation （PDO）, on the temporal variations of the annual water discharge at the Lijin station in the Huanghe （Yellow） River and at the Datong station in the Changjiang （Yangtze） River were examined. Using the empirical mode decomposition-maximum entropy spectral analysis （EMD- MESA） method, the 2- to 3-year, 8- to 14-year, and 23-year cyclical variations of the annual water discharge at the two stations were discovered. Based on the analysis results, the hydrological time series on the inter- annual to interdecadal scales were constructed. The results indicate that from 1950 to 2011, a significant downward trend occurred in the natural annual water discharge in Huanghe River. However, the changes in water discharge in Changjiang River basin exhibited a slightly upward trend. It indicated that the changes in the river discharge in the Huanghe basin were driven primarily by precipitation. Other factors, such as the precipitation over the Changjiang River tributaries, ice melt and evaporation contributed much more to the increase in the Changjiang River basin. Especially, the impacts of the inter-annual and inter-decadal climate oscillations such as ENSO and PDO could change the long-term patterns of precipitation over the basins of the two major rivers. Generally, low amounts of basin-wide precipitation on interannual to interdecadal scales over the two rivers corresponded to most of the warm ENSO events and the warm phases of the PDO, and vice versa. The positive phases of the PDO and ENSO could lead to reduced precipitation and consequently affect the long-term scale water discharges at the two rivers.
基金Supported by National Basic Research Program of China(Grant No.2013CB035403)National Natural Science Foundation of China(Grant No.51375297)Program of Shanghai Subject Chief Scientist of China(Grant No.14XD1402000)
文摘The gripper cylinder that provides braced force for Tunnel Boring Machine （TBM） might fail due to severe vibration when the TBM excavates in the tunnel. Early fault diagnosis of the gripper cylinder is important for the safety and efficiency of the whole tunneling project. In this paper, an online condition monitoring system based on the Empirical Mode Decomposition （EMD） method is estab- lished for fault diagnosis of the gripper cylinder while TBM is working. Firstly, the lumped mass parameter model of the gripper cylinder is established considering the influence of the variable stiffness at the rock interface, the equivalent stiffness of the oil, the seals, and the copper guide sleeve. The dynamic performance of the gripper cylinder is investigated to provide basis for its health condition evaluation. Then, the EMD method is applied to identify the characteristic frequencies of the gripper cylinder for fault diagnosis and a field test is used to verify the accuracy of the EMD method for detection of the characteristic frequencies. Furthermore, the contact stiff- ness at the interface between the barrel and the rod is calculated with Hertz theory and the relationship between the natural frequency and the stiffness varying with the health condition of the cylinder is simulated based on the dynamic model. The simulation shows that the character- istic frequencies decrease with the increasing clearance between the barrel and the rod, thus the defects could be indicated by monitoring the natural frequency. Finally, a health condition management system of the gripper cylin- der based on the vibration signal and the EMD method is established, which could ensure the safety of TBM.
基金Project (No. 50677060) supported by the National Natural ScienceFoundation of China
文摘To improve the accuracy of the stator winding fault diagnosis in induction motor,a new diagnostic method based on the Hilbert-Huang transform(HHT)was proposed.The ratio of fundamental zero sequence voltage to positive sequence voltage after switch-off was selected as the stator fault characteristic,which could effectively avoid the influence of the supply unbalance and the load fluctuation,and directly represent the asymmetry in the stator.Using the empirical mode decomposition(EMD)based on HHT,the zero sequence voltage after switch-off was decomposed and the fundamental component was extracted.Then,the fault characteristic can be acquired.Experimental results on a 4-kW induction motor demonstrate the feasibility and effectiveness of this method.
文摘This work presents an advanced mathematical tool applicable to the recognition and classification of power system transients and disturbances. Disturbances without a periodic pattern or with a non-linear pattern require a more suitable tool than the Fourier series （Fast Fourier or Windowed Fourier Transforms）. To overcome these drawbacks, other tools have been broadly used, such as the wavelet transform. However, the wavelet transform also has some drawbacks such as the lack of adaptivity or interpretation of nonlinear phenomena that the Hilbert and Hilbert Huang Transform techniques could mitigate. The Hilbert techniques transform a time domain function into a space representation both in time and frequency. In the paper, the technique is applied to analyse several short-term and steady events, like a short circuit, a capacitor-switching transient, or a line energisation, showing the abilities of the Hilbert-based transforms.
文摘A new method of fault analysis and detection by signal classification inrotating machines is presented. The Local Wave time-frequency spectrum which is a new method forprocessing a non-stationary signal is used to produce the representation of the signal. This methodallows the decomposition of one-dimensional signals into intrinsic mode functions (IMFs) usingempirical mode decomposition and the calculation of a meaningful multi-component instantaneousfrequency. Applied to fault signals , it provides new time-frequency attributes. Then the momentsand margins of the time-frequency spectrum are calculated as the feature vectors. The probabilisticneural network is used to classify different fault modes. The accuracy and robustness of theproposed methods is investigated on signals obtained during the different fault modes (early rub,loose, misalignment of the rotor).
