Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction

The bearing weak fault feature extraction is crucial to mechanical fault diagnosis and machine condition monitoring.Envelope analysis based on Hilbert transform has been widely used in bearing fault feature extraction. A generalization of the Hilbert transform, the fractional Hilbert transform is defined in the frequency domain, it is based upon the modification of spatial filter with a fractional parameter, and it can be used to construct a new kind of fractional analytic signal. By performing spectrum analysis on the fractional envelope signal, the fractional envelope spectrum can be obtained. When weak faults occur in a bearing, some of the characteristic frequencies will clearly appear in the fractional envelope spectrum. These characteristic frequencies can be used for bearing weak fault feature extraction.The effectiveness of the proposed method is verified through simulation signal and experiment data.

A Novel De-noising Method Based on Discrete Cosine Transform and Its Application in the Fault Feature Extraction of Hydraulic Pump

Aiming at the existing problems of discrete cosine transform(DCT) de-noising method, we introduce the idea of wavelet neighboring coefficients(WNC) de-noising method, and propose the cosine neighboring coefficients(CNC) de-noising method. Based on DCT, a novel method for the fault feature extraction of hydraulic pump is analyzed. The vibration signal of pump is de-noised with CNC de-noising method, and the fault feature is extracted by performing Hilbert-Huang transform(HHT) to the output signal. The analysis results of the simulation signal and the actual one demonstrate that the proposed CNC de-noising method and the fault feature extraction method have more superior ability than the traditional ones.

Fault diagnosis of rolling bearings with noise signal based on modified kernel principal component analysis and DC‐ResNet

In view of the influence of aliasing noise on the effectiveness and accuracy of bearing fault diagnosis,a bearing fault diagnosis algorithm based on the spatial decoupling method of modified kernel principal component analysis(MKPCA)and the residual network with deformable convolution(DC‐ResNet)is innovatively proposed.Firstly,the Gaussian noise with different signal‐to‐noise ratios(SNRs)is added to the data to simulate the different degrees of noise in the actual data acquisition process.The MKPCA is used to project the fault signal with different SNRs in the kernel space to reduce the data dimension and eliminate some noise effects.Finally,the DC‐ResNet model is used to further filter the noise effects and fully extract the fault features through the training of the preprocessed data.The proposed algorithm is tested on the Case Western Reserve University(CWRU)and Xi'an Jiaotong University and Changxing Sumyoung Technology Co.,Ltd.(XJTU‐SY)bearing data sets with different SNR noise.The fault diagnosis accuracy can reach 100%within 30 min,which has better performance than most of the existing methods.The experimental results show that the algorithm has an excellent effect on accuracy and computation complexity under different noise levels.

Geophysical Features of the Ore-Controlling Fault in the Chang'an Gold Deposit, Southern Yunnan Province

The Ailao Mountain is one of the most important metallogenic belts ofpolymetallic deposits in the Sanjiang region, southwestern China. Located in the southern segment of this metallogenic belt, the newly-discovered Chang＇an gold deposit is large in scale （Fig. 1A）, and has attracted much attention among geologists. The ore-hosted rocks in the district include the Late Ordovician Xiangyang Fm. sandstone and clastic rocks and the Early Silurian Kanglang Fm. dolomite. Affected by the multistage tectonic activities, stocks and dykes of lamprophyre, dolerite, syenite porphyry and orthoclasite are widely exposed, and the orebodies are in symbiosis with or crosscut the dyke rocks.

2D-HIDDEN MARKOV MODEL FEATURE EXTRACTION STRATEGY OF ROTATING MACHINERY FAULT DIAGNOSIS

A new feature extraction method based on 2D-hidden Markov model（HMM） is proposed. Meanwhile the time index and frequency index are introduced to represent the new features. The new feature extraction strategy is tested by the experimental data that collected from Bently rotor experiment system. The results show that this methodology is very effective to extract the feature of vibration signals in the rotor speed-up course and can be extended to other non-stationary signal analysis fields in the future.

Active Feature of the Ganzi-Yushu Fault Zone in the Late Quaternary

Based on regional geological mapping results and interpretation of satellites images and areophotos in combination with detailed field study,this paper gives the spatial distribution of recent surface activity of the Ganzi-Yushu fault zone(GYF).According to faulted landform as well as deformation and displacement of young deposit layers,the slip rates of GYF since the late Quaternary are briefly studied,combined with the results of geological chronology(14C and Thermoluminescene dating).The result shows that the average slip rates of GYF is differentiate along different segments:Ganzi segment:horizontal rate is 3.4±0.3 mm/a,vertical rate is 2.2±0.1 mm/a;Manigange segment:horizontal rate is 7.0±0.7 mm/a;Denke segment:horizontal rate is 7.2±1.2 mm/a;Dangjiang segment:horizontal rate is 7.3±0.6 mm/a.

Component fault diagnosis for nonlinear systems

In the field of fault diagnosis, the state equation of nonlinear system, including the actuator and the component, has been established. When the faults in the system appear, it is difficult to observe the fault isolation between the actuator and the component. In order to diagnose the component fault in the nonlinear systems, a novel strategy is proposed. The nonlinear state equation with only the component system is built on mathematical equations. The nonlinearity of the component equation is expanded and estimated with Taylor series. If the actuator is perfect, the anomaly of the state equations reflects the component fault. The fault feature index is defined to detect the component fault and the initial fault. The numerical examples of the component faults are simulated for multiple-input multiple-output(MIMO)nonlinear systems. The results show that the component faults,as well as the incipient faults, can be detected. Furthermore, the effectiveness of the proposed strategy is verified. This method can also provide a foundation for the component fault reconfiguration control.

AUTO-EXTRACTING TECHNIQUE OF DYNAMIC CHAOS FEATURES FOR NONLINEAR TIME SERIES

The main purpose of nonlinear time series analysis is based on the rebuilding theory of phase space, and to study how to transform the response signal to rebuilt phase space in order to extract dynamic feature information, and to provide effective approach for nonlinear signal analysis and fault diagnosis of nonlinear dynamic system. Now, it has already formed an important offset of nonlinear science. But, traditional method cannot extract chaos features automatically, and it needs man＇s participation in the whole process. A new method is put forward, which can implement auto-extracting of chaos features for nonlinear time series. Firstly, to confirm time delay r by autocorrelation method; Secondly, to compute embedded dimension m and correlation dimension D; Thirdly, to compute the maximum Lyapunov index λmax; Finally, to calculate the chaos degree Dch of Poincare map, and the non-circle degree Dnc and non-order degree Dno of quasi-phase orbit. Chaos features extracting has important meaning to fault diagnosis of nonlinear system based on nonlinear chaos features. Examples show validity of the proposed method.

Simulation analysis of wear characteristics of connecting rod bearing bush based on improved mixed lubrication model

The failure rate of crankpin bearing bush of diesel engine under complex working conditions such as high temperature,dynamic load and variable speed is high.After serious wear,it is easy to deteriorate the stress state of connecting rod body and connecting rod bolt,resulting in serious accidents such as connecting rod fracture and body damage.Based on the mixed lubrication characteristics of connecting rod big endbearing shell of diesel engine under high explosion pressure impact load,an improved mixed lubrication mechanism model is established,which considers the influence of viscoelastic micro deformation of bearing bush material,integrates the full film lubrication model and dry friction model,couples dynamic equation of connecting rod.Then the actual lubrication state of big end bearing shell is simulated numerically.Further,the correctness of the theoretical research results is verified by fault simulation experiments.The results show that the high-frequency impact signal with fixed angle domain characteristics will be generated after the serious wear of bearing bush and the deterioration of lubrication state.The fault feature capture and alarm can be realized through the condition monitoring system,which can be applied to the fault monitoring of connecting rod bearing bush of diesel engine in the future.

Investigation of Bearing Fault Diagnosis Based on Explicit Dynamics Analysis in ANSYS/LS-DYNA

In this paper, deep grove ball bearing GB6206 has been chosen as research object, and the explicit dynamics analysis method in ANSYS/LS-DYNA has been used to study features of fault bearing which with a tiny pit in the inner ring raceway. In the process of building this bearing FEM, the following parameters have been well considered, such as boundary conditions, friction, contaction, loads and so on. Through simulation, the corresponding equivalent stress nephograms and acceleration of nodes on the inner ring raceway has been obtained. According to features of acceleration which occurs neighbor to fault pit, bearing＇s fault diagnosis has been realized. This paper provides a new way in monitoring bearing status and diagnosing fault of bearing.