第38 卷第3 期英文摘要

ResearchonCuttingForceModelingandSurfaceQualityintheTransitionAreaoftheMosaicMold

LIUXianli，GAOHaining，YUECaixu，JIANGNan
(School of Mechanical and Power Engineering, Harbin University of Science and Technology Harbin, 150080, China)

AbstractAiming at the problem of tool wear and breakage， the low accuracy of machined surface during the milling process of automobile panel splicing dies, the cutting force modeling of micro element is carried out. The cutting chip thickness of each cutting cycle is built as a function of the cutting angle and the shear force according to the different hardness of machining materials, and a plow force model are obtained under different cutting angles. By introducing a single-degree-of-freedom italic collision model, the Hopkinson test is used to obtain the elastic deformationδof the tool-workpiece impact under different spindle speeds, and then the impact force on the tool in the transition area is obtained. Combining above models together, the prediction model of milling force in the transition area can be obtained. Experiment and simulation results show a good consistency to prove the accuracy of the model. The surface quality under different feed directions is studied. From the analysis results of machined surface quality, surface roughness and height difference between workpieces, it is concluded that better surface quality can be obtained from high hardness and low hardness workpiece. The results provide theoretical support for the optimization of the milling process in the splicing die of the automobile panel.

Keywordssplicing die； impact force model； cutting force model； surface quality

GuidedWaveandEnhancedSplitMergeProbabilityModelBasedonDamageEvaluationMethod

QIULei,FANGFang,YUANShenfang,MEIHanfei
(State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics Nanjing, 210016, China)

AbstractIt′s well known that the environmental and operational variations during the service life of aircraft structure could easily introduce uncertainties to the guided wave features, making it difficult to interpret the changes of guided wave signals and leading to unreliable evaluations of the damage states. This problem has become one of the key problems that hinder the engineering applications of aeronautical structural health monitoring technology. To solve this problem, a damage monitoring method based on guided wave and enhanced split merge probability model is proposed. Firstly, a stable Gaussian mixture model (GMM) is established by an enhanced split merge modeling algorithm based on the guided wave features influenced by time-varying conditions. Then, the damage evaluation is realized by observing the cumulative migration trend of GMMs, which is measured by a best matching based Kullback-Leibler (KL) divergence. To validate the proposed method, an experiment is performed on an aircraft wing spar under changing structural boundary conditions. Experimental results show that this method can achieve stable and reliable monitoring of crack propagation under time-varying conditions. In addition, compared with the damage evaluation results based on guided wave damage index, the damage evaluation reliability is improved obviously by the proposed method.

Keywordsaircraft structure; structural health monitoring; guided wave; Gaussian mixture model; time-varying condition

AnImprovedGeneticAlgorithmforPedestalLoosenessParameterIdentificationinRotor-BearingSystems

CAOShuqian1,2,3,HUANGYaming1,2
(1.Department of Mechanics, Tianjin University Tianjin, 300072, China) (2.Tianjin Key Laboratory of Nonlinear Dynamics and Chaos Control Tianjin, 300072, China) (3.State Key Laboratory of Engines, Tianjin University Tianjin, 300072, China)

AbstractIn this paper, a non-linear dynamic equation of a rotor-bearing system with looseness between the pedestal and the casing is established. The non-linear parameters of the pedestal looseness fault are identified by means of the method of parameter optimization of genetic algorithm (GA), based on the displacement response signal in the vertical direction of the shaft end which has looseness. In view of the traditional genetic algorithm having problems of slow evolution and premature convergence, an improved method based on the genetic process of the traditional genetic algorithm is proposed. The method can take a greater mutation rate, restrain the premature convergence problem, and to speed up the evolution. Studies show that the improved method can effectively improve the efficiency of loosening parameters identification. The non-linear parameters of pedestal looseness fault are identified by the improved genetic algorithm, and the influence of mutation rate on recognition results is studied. Finally，the looseness parameters identification based on true measured signal is performed.

Keywordsrotor system; pedestal looseness; improved genetic algorithm; parameter identification; looseness fault experiment

StudyonthePeristalticFlowBasedonaModifiedImmersedBoundary-LatticeBoltzmannMethod

RENXiaofei1,WEIShoushui1,LIUFeifei1,ZHANGLing2,WANGShaowei3,XUMingtian3
(1.School of Control Science and Engineering, Shandong University Jinan, 250061, China) (2.School of Mathematics, Shandong University Jinan, 250061, China) (3.School of Civil Engineering, Shandong University Jinan, 250061, China)

AbstractIn this paper, peristaltic flow in a tube due to the waves of contraction is studied applying a modified immersed boundary-lattice Boltzmann method. The lattice Boltzmann method is used to describe the flow filed, and the modified immersed boundary method is used to couple the moving boundaries to the surrounding fluid. This method introduces the velocity induced by the flexible tube wall into the lattice Boltzmann equation, which replaces the conversion between the fluid velocity and the force induced by the deformation of the moving boundaries in the traditional immersed boundary-lattice Boltzmann method. We analyze the streamlines and velocity distribution, then systematically investigate the effects of variation of the relevant parameters such as the amplitude ratio and frequency of the traveling wave, viscosity of the fluid and wavenumber on the flow of the peristaltic tube. The comparison between the simulative and existing results shows that the method is reasonable and effective.

Keywordscomputational fluid dynamics; peristaltic flow; fluid-structure interaction; lattice Boltzmann method; immersed boundary method

TheVibrationsandEnergyAnalysisofDeployingCantileverBeam

LIUMing1，YANGXiaodong2，ZHANGWei2，QINChaohong3
(1.Institute of Advanced Structure Technology, Beijing Institute of Technology Beijing, 100081, China) (2.Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Engineering, Beijing University of Technology Beijing, 100124, China) (3.Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering Beijing, 100076, China)

AbstractThe deploying cantilever beam is a model of the typical time-varying structural system. The classical dynamic theory cannot be used to solve the vibration equations due to the changing of mass and stiffness. The vibrations and energy variations are studied based on the governing equations. The analytical expressions of the varying energy are obtained to show the characteristics of the vibration in the stable and unstable region of the system. Numerical method is employed to the vibration analysis and the variation diagrams of energy distributing among different modes in unstable state are discussed. The results show that the rule of energy distributing among the modes is quite different in the stable and unstable states.

Keywordstime-varying parameter; deploying cantilever beam; instability; energy analysis; mode

LambWavesDefectsImagingResearchBasedonPHMultiplierAlgorithmOptimization

LIPeijiang1,2,ZHUXiaojin1,YOUTing3,ZHANGHesheng1,FANGYubin1
(1.School of Mechatronics Engineering and Automation, Shanghai University Shanghai, 200072, China) (2.School of Information Engineering, Quzhou College of Technology Quzhou, 324000, China) (3.School of Electrical and Information Engineering, Quzhou College Quzhou, 324000, China)

AbstractThe detection technology of ultrasonic guided waves has a wide application prospect in structural health monitoring. In this paper, a kind of Lamb waves defect imaging method and its optimization based on envelope amplitude are proposed for detecting aluminum sheet. The sparse PZT array is used as a transmitting and receiving device to generate the excitation signal and acquire the Lamb waves for difference between the health signal and the defect signal, which contains defect position information. An appropriate penalty function is determined introducing the factors containing the position weight vector to highlight the characteristics of the defective pixel. It transforms the improved waveguide image quality problem into a series of solving unconstrained optimization problems，and the augmented objective function can be determined by means of PH multiplier algorithm, which makes the weight vector optimized and improves the image quality. Experimental results show that the positioning error about the algorithm is small, defect imaging of sheet is clear and can be intuitively recognized, and the optimal treatment of guided waves imaging is perfect.

KeywordsLamb wave; imaging; PH multiplier algorithm optimization; amplitude of the envelope

FeatureExtractionofRollingBearingBasedonAPLCD-WPT

ZHAOXiaoping1,2,ZHOUZixian1,2,WANGLihua3,ZHANGYonghong3,TAORunzhe3
(1.Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology Nanjing, 210044， China) (2.School of Computer & Software，Nanjing University of Information Science & Technology Nanjing, 210044, China) (3.School of Information and Control，Nanjing University of Information Science & Technology Nanjing, 210044, China)

AbstractIn order to extracting the characteristic frequency of rolling bearing signal, a feature extraction method based on adaptive partly-ensemble local characteristic-scale decomposition (APLCD) and wavelet package transform (WPT) is proposed, or APLCD-WPT for short. First, APLCD is employed to process vibration signals of rolling bearings, and it can add noise to improve the signal extreme-point distribution in extracting intrinsic mode component by changing the frequency variation. Then, WPT is used to trim less modal mixing problem, which can extract characteristic frequency signal of rolling bearing. Finally, the vibration signal of horizontal spiral centrifuge is analysed based on this method. The results show that APLCD-WPT can effectively suppress the mode mixing to accurately extract the characteristic frequency signal.

Keywordsrolling bearing; feature extraction; model mixing; adaptive partly-ensemble local characteristic-scale decomposition (APLCD); wavelet package transform (WPT)

ANewAlgorithmforT-LineFaultLocationBasedonWaveletEnergySpectrum

WANGMei1,ZHULiang1,ZHANGGuoqiang1,WANGLiang1,LIUChi2
(1.Institute of Electrical and Control Engineering, Xi′an University of Science and Technology Xi′an, 710054, China) (2.School of Software, Beijing Institute of Technology Beijing, 100081, China)

AbstractConsidering the fault dead time problem of transmission lines with T type branches, a new algorithm based on wavelet energy spectrum for T transmission line location is proposed to achieve fault precision location. The cubic B-spline algorithm of wavelet transform modulus maxima is applied to extract the fault feature. In the non-dead zone, the three-terminal location method is used to accurately complete the fault location. In the dead time range, the wavelet energy spectrum algorithm judges the fault branch, and then the three terminal fault location method is used to complete the fault location. The simulation results show that the proposed method can meet the requirements of T-line fault location. The algorithm proposed in this paper is not only affected by the fault type and transition impedance, but also appropriate to solve the difficult problem of measuring the blind area in anOarea.

KeywordsT line; wavelet transform; energy spectrum; fault location

IdentificationofNon-uniformStiffnessDegradationinStructureBasedontheChangeRateofFrequency

ZHANGJiabin,TANGCui,WANGLei,ZHANGJianren
(School of Civil Engineering and Architecture, Changsha University of Science & Technology Changsha, 410114, China)

AbstractTo study on non-uniform stiffness degradation in structure caused by adverse environmental effects and damage, an identification method for stiffness degradation is proposed based on the change rate of frequency using bending beam model, which considers the variation of modal deflection curvature and natural frequency before and after damage. Firstly, modal deflection curvature is derived through a flexibility matrix, and the damage area and location are determined through the variation of modal deflection curvature before and after damage. Then, the damage area is divided into segments, after that the matrix function of damage extent, location parameters of damage area and natural frequency is established according to the vibration theory of Euler-Bernoulli beam. It can directly assess the damage degree of different segments through the change rate of frequency. The results show that the method can precisely identify the location and extent of the local damage, and has advantages in assessment of the non-uniform stiffness degradation in structure.

Keywordsconcrete component； local stiffness； natural frequency； flexibility matrix； modal deflection curvature

CompoundControlforaPiezoelectricMicro-manipulationStage

HUJunfeng,YANGMingli,ZHENGChanghu
(School of Mechanical & Electrical Engineering, Jiangxi University of Science and Technology Ganzhou,341000, China)

AbstractThe nonlinear characteristics of micro-manipulation stage may occurrs due to the hysteresis of piezoelectric actuator，which has seriously affected the motion precision and repeated positioning accuracy of the stage. In order to solve the problem，a compound control algorithm of feedforward compensation combined with feedback is proposed. The theoretical model reflecting the hysteresis phenomenon is established by combining discrete Preisach model and support vector machine. The inverse model of discrete Preisach is obtained by adopting the iterative search method based on the hysteresis model. The feedforward compensation of the stage is carried out based on the inverse model. In order to correct the deviation without eliminating by feedforward compensation and the error caused by the model′s uncertainty, proportion integration differentiation (PID) control is used to feedback regulation. In order to illustrate the feasibility of the proposed control method，an experimental comparative analysis of the composite control, feedforward control and PID control is carried out. The results show that the proposed method has better control accuracy and fast response.

Keywordsmicro-manipulation stage; piezoelectric actuator; inverse Preisach model; compound control; support vector machine

InvestigationonFaultClassificationBasedonNon-subsampledContourletTransform

LIHongkun1,CUIMingli1,YANGRui1,ZHANGZhixin2,WANGFengtao1
(1.School of Mechanical Engineering, Dalian University of Technology Dalian, 116024, China) (2.School of Mechanical Engineering, Dalian University Dalian, 116622, China)

AbstractIn this research, a new method of time-frequency image feature extraction is proposed. It is based on the multi-scale and multi-direction decomposition of the non-subsampled contourlet transform. Firstly, the vibration signals are transformed into a time-frequency image which is then converted into a gray image based on the contourlet transform. Then, the coefficients at high and low frequency are calculated based on the gray image. Different feature extraction methods are investigated in details. In this paper, the energy at the high-frequency, the mean and standard deviation at the low-frequency are calculated as characteristic parameters. Finally, the data of different conditions from a gearbox and rolling bearing are classified and tested by support vector machine (SVM). The results show that the proposed method is effective in determining the characteristic value of a time-frequency image for the condition identification.

Keywordsnon-subsampled contourlet; time-frequency image; support vector machine (SVM); condition identification

ResearchonIdentificationofPickAlloyHead′sFailureModeBasedonBPNeuralNetwork

ZHANGQiang1,2,3，LIUZhiheng1，WANGHaijian1，TIANYing1，NGUYENVietTuyen1,4
(1.College of Mechanical Engineering, Liaoning Technical University Fuxin, 123000, China ) (2.State key Laboratory of Mineral Processing Science and Technology Beijing, 100160, China) (3.Engineering Research Center for Safe Exploitation and Clean Utilization of Coal Resources, Liaoning Technical University Fuxin, 123000, China) (4.Vietnam Coal Mine Machinery Energy Research Institute Hanoi, 100000, Vietnam)

AbstractIn order to monitor and identify the failure mode of the alloy head of the pick-cutting, a method based on BP neural network is proposed to deal with the multi- feature signals. The chapped, off, chipping and serious wear alloy head are tested in cutting process to extract the maximum, mean and variance of the three directional vibration characteristic signals and current signal of the cutting motor. The BP neural network is learned and trained by multi-feature signals to establish the recognition model and monitor and identify the failure mode on-line. The experimental results show that the results of BP neural network are consistent with the actual failure mode of the test samples. It provides new methods to realize online monitoring and identification of failure mode for shearer picks.

Keywordspick; BP neural network; alloy head′s failure mode; vibration signal; current signal

AnalysisoftheAbnormalChangeofIsolatedStructureModalParametersUnderHealthyConditionBasedonLong-TermMonitoringData

DUYongfeng1,2，ZHUQingxin1，LIWanrun1,2，ZHUQiankun1,2
(1.Institute of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology Lanzhou, 730050, China) (2.Western Center of Disaster Mitigation in Civil Engineering of Ministry of Education Lanzhou, 730050, China)

AbstractDue to its excellent damping effect, seismic isolation technology is widely used in the lifeline engineering such as school, hospital and etc. A set of long-time structural health monitoring system is designed and installed in a teaching building to test the isolation design and ensure its safety. This system can record the structural response to common environmental factors and different loads. Based on the collected data of the structural acceleration response, the improved Morlet wavelet modal parameter identification method is used to analyze and process the data in real time, identify structural modal parameters under different conditions, and analyze the impact on the law from the environmental factors and human activities. The result indicates that the changes of personnel activities and environment temperature have great influence on the dynamic characteristics of the isolated structure, which should be considered in the design. Finally, two seismic response data collected by the structural health monitoring system are analyzed, and the structure characteristics′ variation law of the isolated structure under earthquake is concluded.

Keywordsbase isolation；structural health monitoring；wavelet transform; ambient excitation; earthquake excitation；modal parameter

LowEnergyImpactLocalizationofCompositeMaterialsBasedonResistanceStrainGauge

ZHAOGang1,2,3,LIShuxin1,3,LIULisheng3,LIKun1,2
(1.State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology Wuhan, 430070,China) (2.School of Mathematics and Information Sciences, Nanchang Hangkong University Nanchang, 330063, China) (3.School of Science, Wuhan University of Technology Wuhan, 430070, China)

AbstractAccording to the requirements of the impact and vibration testing for carbon fiber reinforced plastics (CFRP) used in aircraft structures, the method of achieving impact localization with resistance strain gauge is proposed. First, the dynamic strain signal is received from the resistance strain gauge. Then, the wavelet transform is applied to extract the arrival time of the signal. The wave velocity is calculated based on Mindlin plate theory. Finally, the coordinate of the impact source can be obtained by the localization algorithm proposed in this paper. Experiments are carried out on a carbon fiber laminate plate with the size of 400mm×400mm×2mm.The experimental results show that the error is less than 10mm. Thus, this paper provides a feasible approach to achieve structural health monitoring of aircraft structures.

Keywordslow energy impact; resistance strain gauge; wavelet transform; localization; carbon fiber reinforced plastics (CFRP)

DynamicsAnalysisofMillingMulti-hardnessMosaicHardenedSteel

YUECaixu,FENGLei,GAOHaining,ZHULei,ZHANGHaitao,LIUXianli
(School of Mechanical and Power Engineering, Harbin University of Science and Technology Harbin, 150080, China)

AbstractChatter is a strong self-excited vibration phenomenon which is produced by the interaction between the tool and workpiece in the metal cutting process. It can reduce the surface quality of the workpiece and tool life when increase the cutting force amplitude increase and cause strong fluctuation. First, the dynamic milling force system is designed based on the stability prediction analysis. The chatter stability in the milling process is simulated after the study of multi-hardness mosaic hardened steel for its lobes figure. Then, the influence of modal parameters on the shape of lobes figure is analyzed. The forecast accuracy of stability lobe figure is validated by the study of time domain analysis, tool wear and surface topography. The result provides reasonable processing parameters for milling multi-hardness mosaic hardened steel and theoretical basis and technical guidance for the selection of processing parameters in milling automobile cover mold.

Keywordsmulti-hardness mosaic mold; milling stability; Lobes figure; surface topography; tool wear

FaultDiagnosisofRollingBearingBasedonk-OptimizedVMD

WANGFengtao,LIUChenxi,ZHANGTao,DUNBosen,HANQingkai,LIHongkun
(School of Mechanical Engineering, Dalian University of Technology Dalian, 116024, China)

AbstractIn the light of extracting fault features of a rolling bearing in early failure period, an incipient fault feature extraction method based onk-optimized variational mode decomposition (VMD) and kurtogram is proposed, wherekvalue is selected based on energy criteria. First, the vibration signals are decomposed by VMD, the energy of intrinsic mode function components is summed under differentkvalues. Based on the energy criterion, the bestkvalue is determined, which is used as the parameter of VMD in decomposing the signals. The reconstructed signals are demodulated at last. The simulated and measured signals of fault bearing are analyzed by this method, which can effectively extract the weak inner ring fault feature. The result shows that the method can determine the incipient fault feature with the bestkvalue, which is significantly valuable in applications.

Keywordsrolling bearing; variational mode decomposition(VMD); kurtogram; fault diagnosis; fault feature extraction

VibrationandShockTestingforEmbeddedMEMSSensorforIntelligentAero-engineApplications

SHAOJing1，DUANLi2，HUMinkai2，DINGGuifu2，MAOChenglong3，SHENJie3，JINGBo4
(1.AECC Commercial Aircraft Engine Co., Ltd Shanghai, 200241, China) (2.Electronic Information and Electrical Engineering, Shanghai Jiao Tong University Shanghai, 200240, China) (3.Suzhou TST Control Technology Co., Ltd Suzhou, 215164, China) (4.Mechanical Engineering, Shanghai Jiao Tong University Shanghai, 200240, China)

AbstractIntelligent aero-engines and other mechanical systems require the vibration- and shocking-resistant embedded sensors, which also has to endure the tough requirements such as high temperature, high shocking, and high vibration strength. In this paper, a high temperature embedded sensor by the aid of micro-electro-mechanical-system (MEMS) technology is integrated into the aero-engine turbine blade. High temperature characterization and a series of vibrational and shocking tests are conducted to verify the functionality of the sensor system in order to stand for the tough working environment of the sensor system including the attaching-ability of MEMS thin film as well as the joint strength of the connection cables to the sensor. The sensor system is capable of sensing up to 800℃ high temperature and stand for up to 40gvibration and 100gshocking.

Keywordsvibration test； shocking test； micro-electro-mechanical-system (MEMS) micro-fabrication； embedded integration

NoiseReductionMethodofVibrationSignalBasedonSingularValueandSingularVector

ZHANGXiaotao1，LIWeiguang2
(1.School of Automotive,Guangdong Mechanical & Electronical College of Technology Guangzhou, 510515, China) (2.School of Mechanical and Automotive Engineering, South China University of Technology Guangzhou, 510640, China)

AbstractIn the light of coexistence of random noise and power interference noise in rotor vibration signals, the noise reduction method based on the combination of singular value and singular vector is proposed. First, the signals processed with signal value decomposition (SVD) method, the effective order of singular value can be obtained from singular value spectrum, in this way the random noise can be reduced. From the relationship between singular value and singular vector we can get the corresponding singular vectors. Then, these singular vectors are calculated with fast Fourier transformation (FFT). The singular vectors corresponding to the power interference are filtered based on the FFT amplitude spectrum feature. Finally, the time-domain signal with all the other singular values and singular vector are reconstructed to reduce the random noise and power interference noise in the target signals. Simulation experimental results demonstrate that the proposed method can effectively reduce the random noise and power interference noise, which is obviously superior to the notch filter method.

Keywordssingular value decomposition; singular value; singular vector; power interference

FuzzyC-meansBasedHealthAssessmentMethodforSpaceMechanismShafting

LIUHongxing,QINGTao,WANGHong,ZHOUNingning
(Beijing Key Laboratory of Long-Life Technology of Precision Rotation and Transmission Mechanism, Beijing Institute of Control Engineering Beijing，100094，China)

AbstractA health assessment method for space mechanism shafting based on fuzzy C-means clustering is proposed in the light of applying the existing health assessment methods to space mechanism shafting. First, a new parameter named characteristic frequencies′ distinctness is defined. Then, the fuzzy C-means clustering model is trained by the kurtosis and characteristic frequencies′ distinctness of fine and faulted shafts. Finally, the health index is constructed according to the membership related to the fine shafting cluster. With the proposed method, the shafts can be sorted correctly according to the health state, and the reliable health index can be obtained at high rotation speeds. The practicability and effectiveness of the approach proposed have been demonstrated.

Keywordsfuzzy C-means； health assessment； space mechanism shafting； characteristic frequencies′distinctness； health index

FaultDiagnosisMethodforAutomataMachineBasedonMultipleScaleSampleEntropyandVPMCD

WANGFei,FANGLiqing,QIZiyuan
(First Department, Shijiazhuang Campus of the Army Engineering University Shijiazhuang, 050003, China)

AbstractAs the characteristics of presents the fault features of vibration signals are hard to extract due to its nonlinearity, no-stationary and aperiodicity. In the light of the low fault recognition rate in an automata machine for this reason, a new approach is proposed which combines multiple scale sample entropy and variable predictive model based on the class discriminate (VPMCD). First, wavelet threshold noise reduction is applied to the collected signals. Then, the vibration signals are decomposed into several signals in different scales, the sample entropy of different signals are calculated and the sensitivity to fault characteristics are selected to constitute the fault features. Finally, the VPMCD is establishedbased on the fault features to recognize and classify the automata faults. The experimental results show that this method can accurately distinguish several typical fault forms of automata.

Keywordsautomata machine; wavelet packet analysis; sample entropy; feature extraction; variable predictive model based class discriminate (VPMCD); fault diagnosis

DirectDriveMotorSensorFaultDiagnosisBasedonOptimalUnknownInputObserverforElectricVehicle

XUXing1,2,CHENTe1,CHENLong1,2
(1.School of Automotive and Traffic Engineering, Jiangsu University Zhenjiang, 212013, China) (2.Research Institute of Automotive Engineering, Jiangsu University Zhenjiang, 212013, China)

AbstractUsing direct driven in-wheel motor as the driving system of distributed driven electric vehicle，the power distribution of each driving wheel can be realized quickly and accurately. Aiming at the matter of current sensor fault and rotational speed sensor fault in distributed driven electric vehicle, the robust fault detection and location method is studied. Considering the unknown input and noise in motor model, decoupling the unknown input via the method of system order reduction, using Kalman filter (KF) to filter the white noise of the decoupled subsystem, the optimal unknown input observer (UIO) is designed to realize the system state estimation, and a robust residual generator is obtained. At the same time, the generalized likelihood ratio (GLR) method is used to evaluate the residual signals and determine the threshold value, a sensor fault location method is proposed. Bench experiment results show that the sensor fault diagnosis method based on optimal UIO realizes the sensor fault diagnosis and location of the direct driven in-wheel motor system.

Keywordselectric vehicle; direct drive motor; sensor; fault diagnosis; unknown input observer; Kalman filte

ShakingTableTestonSeismicResponseofRockSlope

FENGXixia,JIANGQinghui,ZHANGHuichao,JIANGJinlin,PENGZhihao,JIANGWeihua
(School of Civil Engineering, Wuhan University Wuhan, 430072, China)

AbstractIn order to study the dynamic response of anti-dip layered rock slope models, one 2D physical model of anti-dip layered rock slope containing two groups of rock joints is designed for the shaking table test. The influence of different dynamic parameters including wave type, amplitude and frequency on the dynamic response of the slope model is considered. The research results reveal that the amplification coefficient of peak ground acceleration(PGA)increases with increasing the relative elevation, which is basically showed the non-linearly amplification characteristics, and this amplification trend is obvious near the slope top. With the increase of acceleration amplitude, PGA amplification coefficients rise on the whole, but it is influenced by rock structure and wave type. PGA amplification coefficients increase with the increase of frequency, and the growth trend become stronger near the slope top. The slope model under seismic loads mainly presents that shear cracks and tension cracks extend, connect and from step-type fractures. The failure of the slope is mainly caused by bending crack along joint surfaces. The study has theoretical and practical significance.

Keywordsrock slope; shaking table test; peak ground acceleration(PGA) amplification coefficient; seismic response; failure mechanism

InfluenceofPlateauLocomotiveSuspensionStructureonVehicleVibrationCharacteristics

WANGChen1，LUOShihui1,FANHui2,DUZhongyuan2,MAWeihua1,XUZiqiang1
(1.Traction Power State Key Laboratory, Southwest Jiaotong University Chengdu, 610031, China) (2.Dalian Locomotive and Rolling Stock Co.,Ltd Dalian, 116022, China)

AbstractBased on the multi-body system dynamics theory, a plateau locomotive dynamic model is established with two kinds of different suspension schemes. The effects ofμon the acceleration of bogie, carbody and vertical wheel rail force are analyzed. It is pointed that with the increase ofμ, ranging from 0.5 to 3, the vertical acceleration of frame and vertical wheel rail force climb up to 11.24% and 12.2%; the vertical riding quality and acceleration of carbody go down by 11.3% and 15%. Then the influence of different suspension stiffness distribution schemes on vehicle/track vibration characteristics is investigated. The results indicate that the selection of a larger secondary suspension stiffness deteriorate vehicle sperling index. While a smaller primary suspension stiffness can reduce the vertical impact between wheel and rail caused by track irregularity. Especially, the low frequency vibration is inhibited, which do damage to the foundation under rail. The influence of locomotive on ballast and subgrade is decreased during the running process and the subgrade settlement is improved.

KeywordsQinghai-Tibet railway; locomotive; suspension stiffness; vibration characteristic; dynamic performance

BearingFaultDiagnosisBasedonARModelFilteringinAngleDomain

CHENGWeidong,LIUDongdong,ZHAODezun
(School of Mechanical Electronic and Control Engineering， Beijing Jiaotong University Beijing, 100044, China)

AbstractThe algorithm of employing order tracking based on the time-frequency representation is limited in rolling bearing fault diagnosis under a variable rotational speed and gear vibration noise, because of the lack of extractable rotational frequency components. The algorithm of angle domain resampling based on fault characteristic frequency can extract the bearing fault characteristics, however the location of the fault cannot be found and error may occur in this algorithm. The method is proposed in this paper based on auto regressive (AR) model filtering in angle domain to solve this problem. To estimate the rotational speed, the gear instantaneous meshing frequency is extracted from the down sampling mixed signal using chirplet path pursuit algorithm. The mixed signal is re-sampled by a constant angular interval based on the estimated rotational speed. The gear noise is removed in the angle domain signal used AR model. Finally, the fault diagnosis is completed by observing the order spectrum gotten by Hilbert transformation and FFT. The effectiveness of the method is tested by the analysis of the simulation signal and experimental signal.

Keywordsgear vibration noise; variable rotational speed; fault diagnosis; chirplet; gear instantaneous meshing frequency (GIMF); AR model

BearingFaultDiagnosisBasedonVariationalModalDecompositionCombinedwithEnvelopeofSpectrum

BOLin,TANGZhi,XUGuanji
(The State Key Laboratory of Mechanical Transmission, Chongqing University Chongqing, 400044, China)

AbstractAiming at the problem of early fault diagnosis of rolling bearing, it is pointed out that the empirical mode decomposition (EMD) has poor anti-noise effect and the limitation of end effect. Variational modal decomposition (VMD), principal component analysis (PCA) and entropy bearing fault diagnosis are put forward based on cepstral envelope. Firstly, it takes VMD to decompose the bearing vibration signal of rolling; secondly, the components are handled by PCA. Then, it computes the entropy of the components and choses whose entropy of components is less than the average to reconstruct. Finally, the reconstructed signal is analyzed by cepstral envelope. Experimental results show that the method can effectively extract the rolling bearing fault frequencies, and judge damage position of the rolling bearing, it has a good anti-noise ability.

Keywordsvariational modal decomposition (VMD)； principal component analysis (PCA)；entropy；cepstral envelope

DesignandExperimentofTrackMechanism-SoilInteractionSystem

TANGLiwei1,SUNZhongxing1,WANGWei1,SUNYezun2
(1.Department of Artillery Engineering, Shijiazhuang Campus of the Army Engineering University Shijiazhuang, 050003, China) (2.Representative Organization of Factory 247 Taiyuan, 030000, China)

AbstractThe experimental system of track mechanism-soil interaction is designed and constructed according to the new test system of soil bin developed by the Key Laboratory of Bionic Engineering in Ministry of Education, which is composed of soil trough and track-type trolley device as well as its supporting driving element and real-time test system through which can obtain parameters such as driving moment of the motor, horizontal displacement of trolley, sinkage in the traveling process of the trolley, inclined angle of the vehicle body, and motor speed, as well as the variation from the start to the smooth operation of the trolley device. Laser range finder is constructed with turnplate to realize the stage extraction of the track shape, which is not in contact with a road wheel. The vehicle load, track width and slip rate are taken as the experimental factors, the mechanism sinkage is taken as the experimental index, and orthogonal experiment design method is adopted. The experiments are carried out in three different Tightness degrees of the track, where sinkages and dipangles are obtained. The three regression equations of the sinkage on the vehicle body load, track width and slip rate are obtained by regression analysis, whose fitting effect is good, confidence is 0.99, and correlation coefficient is not less than 0.9. The average relative error between the test value and the calculated value of the regression equation is less than 10%. The results can be used to predict the stress distribution of flexible track and provide data support and important reference for the ground of soft soil.

Keywordstrack mechanism-soil interaction; track shape; sinkage; load; track width; slip rate

VibrationModalMeasurementofHoneycombSandwichPanels

BasedonLaserInterferometry

TAONan,MAYinhang,JIANGYijun,YANGFujun,HEXiaoyuan
(Department of Engineering Mechanics, Southeast University Nanjing, 210096, China)

AbstractVibration characteristics of cantilevered honeycomb sandwich panels with local damage are studied by use of electronic speckle pattern interferometry (ESPI). By comparing with the results of finite element modeling simulation on cantilevered aluminum plate, the viewpoint of the homogeneous characteristics of honeycomb sandwich structures can be verified. The first fourteen out-of-plane resonant mode shapes of an intact plate are obtained by experimental method. The experimental results show that comparing with those of intact one, resonant frequencies of the honeycomb sandwich panels will become lower with the structural damage appearance, and the resonant mode shapes also change with the damage location and orientation. Veering in the mode shapes can be observed when the damaged structures vibrate at higher order resonant modes.

Keywordslaminated honeycomb sandwich; mode shape; veering in the mode shapes; electronic speckle pattern interferometry (ESPI)

ArcMechanismandParameterPredictionofVacuumArcBrazingEquipment

LIUZhixiang1,2，XIEChunxue1,2，MAOJun2，XIEMiao1,2，LUJinnan2
(1.Research Institute of Technology and Equipment for the Exploitation and Utilization of Mineral Resources, Liaoning Technical University Fuxin, 123000, China) (2.School of Mechanical Engineering, Liaoning Technical University Fuxin, 123000, China)

AbstractIn the current research of vacuum arc brazing technology, there are problems that the key factors of arc ignition process are not clearly defined and the value of the factors is adjusted mostly based on experience. In this paper, the influencing factors of arc ignition process of vacuum arc brazing equipment are studied. To quickly build arc and get stable arc current, argon flow, breakdown voltage, breakdown distance and tantalum tube diameter cited various influential factors in the process of arc are analyzed one by one from the establishment of the basic mechanism. The optimal parameter prediction model is established based on adaptive neural network based fuzzy interference system(ANFIS) model. The argon flow, vacuum degree, the breakdown distance and the diameter of the tantalum tube as the prediction model input are used to predict the breakdown voltage optimal value. Through the field experiment, the theoretical research and the prediction performance of the parameter prediction model studied in this paper are verified and improved. The results show that the arc current in arc ignition process of vacuum arc brazing equipment is stable, which uses the parameters obtained from prediction model, and results meet process requirements.

Keywordsvacuum arc welding; arc mechanism; parameter prediction; adaptive neural network based fuzzy interference system (ANFIS)

FaultDiagnosisforSteamTurbineRotorbyUsingSupportVectorMachineBasedonCS-BBOOptimizationAlgorithm

SHIZhibiao,GEChunxue
(School of Mechanical Engineering, Northeast Dianli University Jilin, 132012, China)

AbstractTo improve the accuracy and efficiency of turbine rotor fault diagnosis, a new method of fault diagnosis based on the biogeography-based optimization with chaos (CS-BBO) and support vector machine (SVM) is introduced. Firstly, the chaos theory is introduced into the biogeography-based optimization algorithm (BBO), the CS-BBO algorithm is obtained. Then, the optimal parameters of the SVM diagnostic model are obtained through the CS-BBO algorithm, and optimization model enhances the learning ability and generalization ability of SVM. Finally, the validity of the optimization model is verified by the experimental data of 4 kinds of states from ZT-3 rotor test bench to simulate the turbine rotor fault. The results show that the optimized model of SVM obtained by CS-BBO algorithm can be used to diagnose the fault of the steam turbine rotor accurately and efficiently. Compared with the optimized SVM model, which is obtained by the biogeography-based optimization algorithm, the accuracy and efficiency of fault diagnosis of this method is higher.

Keywordssupport vector machine; parameter optimization; biogeography-based optimization with chaos; fault diagnosis; steam turbine rotor

PowerTransformerVibrationCharacterizationAnalysisbyVectoringFittingMethod

HUMin1,3,PENGWei2,JINZhijian3,YUANGuogang4
(1.Shanghai Jiulong Electric Power (Group) Co., Ltd Shanghai, 200436, China ) (2.Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Company Shanghai, 200437, China) (3.School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University Shanghai, 200240, China) (4.Shanghai Rhythm Electronic Technology Co., Ltd Shanghai, 201108, China)

AbstractVibration characterization of power transformer is an import key to reliability and trouble shooting, The vector fitting (VF)method is used to analysis vibration test data of power transformer surface. The VF is compared with PolyLSCF method and the experimental data of power transformer is analyzed. It can be found that the 100 Hz operation frequency causes harmonic response, and the vibration level of the transformer bottom is much higher and local mode is checked after sole analysis. The analysis result will provide advice on optimization of measurement point locations and failure recognition.

Keywordstransformer; vector fitting; vibration characteristic； modal analysis