英文摘要

Advances in Coding Theory of Absolute Optical Encoders

ZHANG Jianhui，CHEN Zhenlin，ZHANG Fan
（School of Mechanical and Electrical Engineering，Guangzhou University Guangzhou，510006，China）

AbstractThe paper is an overview of the coding theory of the absolute photoelectric rotary encoders for angle measurement，including the absolute position coding methods and coding characteristics of reflective Gray codes，matrix codes，m-sequence codes and single-track Gray codes. The development of absolute position coding theory is based on two basic properties，uniqueness and mono-difference，and one goal to reduce the number of the tracks on the coding disc. The position coding methods introduced in this paper are reflective Gray codes withncode tracks，matrix code withn/3 tracks，m-sequence with two tracks and single-track Gray codes with only one track. However，the coding theory of single-track Gray code is not perfect，and it still relies on computer searching to obtain codes. Therefore，the fast construction method of single-track Gray codes is the development direction of absolute position coding theory in the future. Finally，the non-coding measurement method based on image sensor is introduced，which is a subversion of the traditional measurement method and is expected to become another development direction of photoelectric rotary encoders.

Keywordsangle measurement；rotary encoder；absolute position coding；image encoder

KSELF Dimension Reduction Method Based on Rotor Fault Data Set

HU Wengang，ZHAO Rongzhen
（College of Mechano-Electronic Engineering，Lanzhou University of Technology Lanzhou，730050，China）

AbstractAiming at the problem that the dimension of faulty data set with strong nonlinearity in fault diagnosis is too high and the sample of faulty label is insufficient，a kernel semi-supervised local Fisher discriminant analysis（KSELF）is proposed. The method first maps the original fault data set to a high-dimensional feature space by the kernel method，and then derives the projection transformation matrix based on the semi-supervised local Fisher discriminant analysis in the high-dimensional space. The proposed KSELF can effectively capture the nonlinear information of the data，and can fully utilize the fault information in a small number of label samples and a large number of unsigned fault samples，thereby avoiding over-learning problems. The proposed method is validated by the fault characteristic data set of a double-span rotor test bench. The results show thatthe KSELF method has stable dimensionality reduction ability，and can obtain better dimensionality reduction effect and higher classification accuracy，compared with other methods in the experiment.

Keywordsdimension reduction；kernel semi-supervised local Fisher discriminant analysis（KSELF）；kernel method；semi-supervised learning

Improved Feedforward Compensation Strategy for Electric Linear Loading Test System

PAN Weidong1，2，FAN Yuanxun1，LEI Jianjie1，3，CAO Dawei1
（1.School of Mechanical Engineering，Nanjing University of Science and Technology Nanjing，210094，China）（2.Shanghai Aerospace Control Technology Institute Shanghai，201109，China）（3.Shanghai Electro-Mechanical Engineering Institute Shanghai，201109，China）

AbstractIn order to solve the problem of the lower loading accuracy of electric linear loading test system（ELLTS）caused by the motion disturbance of linear actuators（problem of surplus force），an improved disturbance feedforward compensation strategy is proposed based on the analysis of traditional disturbance feedforward compensation. The strategy does not require the velocity feedback signal of the actuator，and only uses the displacement command signal and the force signal as the compensation term，which avoid the installation of a speed sensor. Furthermore，it is easy to use and flexible for applying. The surplus force of the proposed strategy is simulated using the SIMULINK software，and the rationality and feasibility of the proposed strategy are verified by the simulation results. Finally，many comparison experiments are implemented，whose results show that，the surplus force with the algorithm is well restrained within the dynamic loading frequency. In addition，the force output accuracy of ELLTS with the proposed strategy is further improved under typical loading conditions，which satisfies the "double ten index".

Keywordslinear actuator；electric linear loading test system（ELLTS）；surplus force；improved disturbance feedforward compensation；double ten index

Cutting Life Model of Hollow Shaft Based on Dual-frequency Vibration System

HUA Chunjian1，2，REN Haojing1，2，LU Yunjian1，2
（1.School of Mechanical Engineering，Jiangnan University Wuxi，214122，China）（2.Jiangsu Key Laboratory of Food Manufacturing Equipment Technology Wuxi，214122，China）

AbstractFor the study of hollow shaft cutting under compound frequency vibration，it is extremely important to establish the relationship among cutting life，geometry parameters of hollow shaft and loaded state. The stress intensity factor（SIF）is derived at the crack tip of a V-groove hollow shaft. Its dynamic model is established based on the built-in dual-frequency vibration system. So the constant amplitude nominal stress at the V-shaped incision is obtained plotting the stress spectrum，and the SIF value at the V-shaped incision of the hollow shaft under the compond frequency vibration is obtained. Based on the SIF superposition principle and the fatigue crack life formula，the cutting life model of the hollow shaft under the compound frequency is generalized.Analysis model and design the experiments，the experimental results are consistent with the model laws.

Keywordscompound frequency vibration；dual-frequency vibration system；V-groove hollow shaft；stress intensity factor；the cutting life model

Fault Diagnosis of Spiral Bevel Gear Based on CEEMDAN Permutation Entropy and SVM

JIANG Lingli1，2，TAN Hongchuang1，LI Xuejun1，2，LEI Jiale1
（1.Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment，Hunan University of Science and Technology Xiangtan，411201，China）（2.School of Mechatronic Engineering and Automation，Foshan University Foshan，528225，China）

AbstractSpiral bevel gear is a basic transmission component and widely used in mechanical equipment，so it is important to monitor and diagnose its running state to ensure a safe operation. However，the vibration signals of spiral bevel gears are extremely complicated because of the changing number of meshing gear pairs，the position of meshing point and the transmission ratio，and the collisions between teeth during the meshing process. Especially，when the fault occurs，the vibration signals of spiral bevel gears present highly non-linear and non-stationary. This paper proposes a method for identifying the spiral bevel gear fault by using complete ensemble empirical mode decomposition with adaptive noise（CEEMDAN）permutation entropy as the sensitive features and support vector machines（SVMs）as the classifier. Firstly，the vibration signal is decomposed using CEEMDAN to obtain a series of internal modal functions（IMF）from a high frequency to a low frequency. The effective IMF components are optimized based on the correlation coefficient of each IMF component and the original signal，combining with the signal to noise ratio. Then，the permutation entropy values of the optimized IMFs are calculated. In order to obtain accuracy permutation entropy values，the overlapping parameter method is used to optimize the key parameters embedding dimension and delay time in the process of permutation entropy calculation. The eigenvectors are composed of the entropy values of the optimal IMFs，and the multi-class SVM is trained to identify the spiral bevel gear faults. The CEEMDAN permutation entropy method is applied to fault diagnosis of spiral bevel gears with three different fault states，and comparing with the method of EEMD permutation entropy and EMD permutation entropy. The results show that the fault diagnosis method based on CEEMDAN permutation entropy has a higher identification accuracy.

Keywordsspiral bevel gears；fault diagnosis；complete ensemble empirical mode decomposition with adaptive noise（CEEMDAN）；permutation entropy；support vector machine

Test and Analysis on Ride Comfort of All-Metal Wheel

ZHAO Zhenglong，SONG Bin，LÜ Jiangang，HE Zhongbo，DAI Zhiguang
（Department of Vehicle and Electrical Engineering，Shijiazhuang Campus，Army Engineering University Shijiazhuang，050003，China）

AbstractAn all-metal wheel based on spring-mesh structure is designed. The main and auxiliary springs of the metal wheel are interconnected with each other，which realizes the composite bearing capacity. In order to test the load-bearing and ride comfort of the spring tire，a ride comfort test system is built based on a 6×6 unmanned vehicle which is driven by 6 wheels and 6 motors. In view of the large amount of random noise and pulse interference noise in the vibration signal of the test results，the noise filtering is carried out by combining the morphological filtering and empirical mode decomposition（EMD）decomposition and reconstruction methods. Therefore，the effective vibration signal is obtained which can be directly used to analyze the ride comfort. In order to quantitatively analyze the vibration of metal wheel and inflatable rubber wheel，the weighted acceleration root mean square values of the test platform with different tires，different speeds and different locations are solved. The results show that the ride comfort performance of the metal wheel is slightly worse than that of the pneumatic rubber wheel with the same size，while it has a better grasping ability.Furthermore，a variety of wheel structural assemblies with spring mesh surface structure as the internal support，are proposed by adding a cladding layer with the material of rubber or crawler to the tread，in order to improve the vibration damping performance of metal wheels.

Keywordsall-metal wheel；ride comfort；real vehicle contrast test；filtering；optimization

Numerical Investigations and Experimental Verification on Rheological Characteristics of Reciprocating Seal

YUAN Xiang1，WANG Jun1，LIAN Zisheng1，WANG Guofa2，MA Lin3
（1.College of Mechanical and Vehicle Engineering，Taiyuan University of Technology Taiyuan，030024，China）（2.Coal Mining and Designing Department，Tiandi Science and Technology Co.，Ltd. Beijing，100013，China）（3.Research Center for Eco-Environmental Sciences in Shanxi Taiyuan，030024，China）

AbstractAimed to improve the sealing performance of reciprocating seals，the rheological characteristics of the rod-seal interface in a sealing zone are investigated. Based on the theory of deformation，a numerical model of elastohydrodynamic lubrication under mixed lubrication is introduced to further reveal the sealing mechanism of reciprocating seals. The influences of working conditions such as different seal surface roughness，viscosities of hydraulic oil and rod velocities on friction，friction coefficient and leakage are analyzed by introducing fluid equations（considering cavitation），a micro contact model and a deformation model. The effectiveness of the method is verified by experiments，and a test rig is developed to validate the theoretical analysis.The results show a lower seal surface roughness yielding a larger friction force and leakage. The friction force decreases with the increase of the oil viscosity and the seal rod velocity，but the leakage presents an opposite trend. Therefore，a reasonable seal surface roughness and viscosity of hydraulic oil are of great significance to improve the anti-wear abilities of materials and reduce environmental pollution.

Keywordsreciprocating seals；elastohydrodynamic lubrication；surface roughness；viscosity

Simulation and Experiment of Streamlined Flow Tube Valveless Piezoelectric Pump

TANG Ming，BAO Qibo，ZHANG Jianhui，LAI Liyi，HUANG Zhi，YANG Guanyu，PAN Yinhao
（School of Mechanical and Electrical Engineering，Guangzhou University Guangzhou，510006，China）

AbstractValveless piezoelectric pumps have broad applications in the field of biomedicine. However，the existed valveless piezoelectric pumps have many fatal defects such as transporting failure and entanglemental loss，during the transportation of the living cells or long-chain functional polymers，which seriously restricts its application progress in the biomedical field. Therefore，this work proposed a streamlined flow tube valveless piezoelectric pump to alleviate or solve the above problems. The output performance of four groups of streamlined flow tube valveless piezoelectric pumps with different angles is studied. Firstly，the structure and working principle of the pump is explained，and the flow rate equation was established. Then，the internal flow-field dynamic mesh simulation of the four groups of valveless pumps（flow tube angles of 10°，15°，20° and 25°）is performed using a Fluent software. The results show that the flowing stability increses by decresing the tube's angle but the optimum flow rate inceses. Both the simulation rsults of the streamlined flow tube and the cone-shaped flow tube are cpmpared under the same differantial pressure，showing that there is an improvement in flowing stability by using the streamlined flow tube. Finally，the experiments to measure the flow rates of four groups of lead zirconate titanate piezoelectric ceramics pumps are carried out，whose results are compared with the simulation results. The experimental results of the optimal flow-rate trend and pumping direction are consistent with simulation ones. This work can futher promote the applications of the streamlined flow tube valveless piezoelectric pump in the field of micro-active material transportation and medical care.

Keywordsvalveless piezoelectric pump；finite element simulation；streamlined flow tube；flow rate

Rolling Bearing Fault Identification Based on Quantum-Behaved Particle Swarm Optimization and Multi-scale Permutation Entropy

WANG Wangwang1，DENG Linfeng1，2，ZHAO Rongzhen1，ZHANG Aihua2
（1.School of Mechanical and Electronical Engineering，Lanzhou University of Technology Lanzhou，730050，China）（2.School of Electrical and Information Engineering，Lanzhou University of Technology Lanzhou，730050，China）

AbstractIn order to accurately identify the different fault types of rolling bearings，a fault recognition method for rolling bearing based on quantum-behaved particle swarm optimization and multi-scale permutation entropy（QPSO-MPE）is proposed. Firstly，the original vibration signal of the rolling bearing is decomposed by ensemble empirical mode decomposition（EEMD），and a series of intrinsic mode functions（IMFs）and a trend term are obtained. The IMF component containing the main fault feature information is selected by kurtosis as the metric to reconstruct the vibration signal. Then，the key parameters of MPE are optimized by the QPSO algorithm，and the multi-scale permutation entropy of the reconstructed signals are calculated by the optimized MPE model to construct the multi-scale permutation entropy feature set of bearing faults. Finally，the fault feature set is input to GG（Gath-Geva）fuzzy clustering algorithm for clustering recognition. The experiment results show that the QPSO-MPE based fault recognition method can accurately identify the typical faults of rolling bearings and verify the effectiveness of QPSO-MPE in fault feature extraction.

Keywordsrolling bearing fault recognition；quantum-behaved particle swarm optimization（QPSO）；multiscale permutation entropy（MPE）；ensemble empirical mode decomposition（EEMD）；GG fuzzy clustering

Transfer Path Modeling for Door Glass Vibration and Optimization Analysis

LIU Zhe，GAO Yunkai，XU Xiang，SHI Wang，WANG Honglong
（School of Automobile，Tongji University Shanghai，201804，China）

AbstractThe transfer path analysis（TPA）of the abnormal vibration guides to a two-level TPA model of a closing door's glass-the lock，weather-strip and glass at the first level and the rail junction and glass at the second. Based on the model，the operating load and path contribution，which determine the causes of the abnormal vibration，derive from the response of the testing points when the door is closed at 1.5 m/s（the speed at normal situations）.An improved scheme considering the reasons reduce the abnormal vibration of the door glass．

Keywordsdoor noise；noise vibration harshness（NVH）；frequency-domain transfer path analysis；two-level transfer path analysis；load identification；contribution analysis

Real-Time Online Automatic Bridge Modal Identification

LIANG Peng1，2，HE Min1，ZHANG Yang1，YE Chunsheng1，LI Linguo1
（1.School of Highway，Chang'an University Xi'an，710064，China）（2.Engeeirng Reacher Center for Large Highway Structure Safety of Ministry of Education，Chang'an University Xi'an，710064，China）

AbstractThe online real-time analysis framework combing the updated fuzzy C-means（FCM）method identifies the automatic bridge modal. The improved FCM algorithm derives the cumulative adjacency matrix from different maximum clustering numbers and the graph-segmentation algorithm solves the matrix for the optimal clustering number to automatically identify the stable graphs. The framework guarantees the online data processing by integrating the acquisition，transmission and analysis into the identification system. An adjustable sliding data window ensures the automatically real-time identification. In experiments，the possibility of applying the proposed framework on an arch bridge model is verified. The improved FCM algorithm automatically optimizes the number of clusters with default parameters. The proposed framework including the sliding data window identifies the real-time modal parameters.

Keywordsmodal identification；stabilization diagram；fuzzy C-means（FCM）method；real-time online automatic modal identification；modal identification system；extensible sliding data window

Aero-engine Fault Diagnosis Based on Deep Self-Coding Network

CUI Jianguo1，LI Guoqing1，JIANG Liying1，YU Mingyue1，WANG Jinglin2
（1.School of Automation，Shenyang Aerospace University Shenyang，110136，China）（2.Aviation Key Laboratory of Science and Technology on Fault Diagnosis and Health Management Shanghai，201601，China）

AbstractThe fault diagnosis of an aero-engine always plagues the industry due to its complex internal structure.In light of this problem，this paper proposes a fault diagnosis method based on the deep self-coding network.First，the monitoring data is preprocessed，and the structure of the network is constructed according to the data's features. Then，the unlabeled data samples train the network for the initial values of its parameters，and the labeled samples work for a slight adjustment. Thus，the aeroengine fault diagnosis model based on deep self-encoding neural network is established. Finally，the proposed model presents its advantages over common fault diagnosis methods，including back propagation neural network and radial basis neural network，in accuracy according to the tested of labeled samples.

Keywordsdeep self-encoding network；aero engine；fault diagnosis；neural network

Experimental Identification and Active Vibration Controlof Piezoelectric Flexible Manipulator

KANG Jianyun，BI Guo，SU Shibo
（School of Aerospace Engineering，Xiamen University Xiamen，361005，China）

AbstractThe modeling and active vibration control of a piezoelectric flexible manipulator system are presented，taking the Euler-Bernoulli cantilever as an example. Considering the non-linearity and complexity of a flexible system，the transfer function combining the input voltage of the actuator and the output voltage of the sensor arises from the experimental identification. Aiming at the elastic vibration，the weighted matrix of the model based on the linear quadratic regular（LQR）theory，which is difficult to solve，is optimizaed by the genetic algorithm. On this basis，the experimental platform is construacted and the control program is compiled for the vibration control test of a flexible manipulator. The results show that the proposed method suppresses the vibration of the flexible manipulator both under free attenuation and continuous excitation as demanded.

Keywordsflexible manipulator；system identification；genetic algorithms；vibration control

Hybrid Adaptive Algorithm for Active Micro-vibration Control Under Multiple Narrowband Disturbances

FANG Yubin，ZHU Xiaojin，GAO Zhiyuan，ZHANG Hesheng，MIAO Zhonghua
（School of Mechatronics Engineering and Automation，Shanghai University Shanghai，200072，China）

AbstractIn light of the frequency mismatch in active structural vibration control under multi-frequency narrowband excitation，a hybrid adaptive active vibration control method is proposed based on the parallel-form filteredx least mean square（FxLMS）algorithm. In the proposed algorithm，multiple bandpass filters in feedforward paths decouple reference signal into multiple narrowband signals. Thus，the multi-frequency narrowband active vibration control is transformed into multiple narrowband active vibration control to speed up the convergence.Besides，the feedback path improves the robustness against time-varying and broadband noise disturbance.Then，the analysis of the proposed algorithm uncovers the conditions demanded for its stability and convergence. Finally，the effectiveness of the proposed algorithm is verified by a Adams-Simulink simulation system and active micro-vibration control experiments. The results show that the proposed algorithm can suppress micro-vibration of multi-frequency narrowband disturbances and exhibit better robustness in the condition of disturbance frequencies mismatch and broadband noise.

Keywordsactive micro-vibration control；multi-frequency narrowband disturbance；hybrid adaptive control；parallel-form FxLMS

Fault Diagnosis for Rolling Bearing Based on EMD Binarization Image and CNN

GU Yuhai，ZHU Tengeng，RAO Wenjun，HUANG Yanting
（Key Laboratory of Modern Measurement& Control Technology Ministry of Education，Beijing Information Science& Technology University Beijing，100192，China）

AbstractThe traditional fault diagnosis methods show low accuracy and poor generalization ability in identification，and the methods based on deep learning need huge amounts of training data. In light of these shortcomings，this paper proposes an intelligent rolling bearing fault diagnosis method based on the empirical mode decomposition（EMD）and convolution neural network（CNN）. The bearing vibration data are decomposed by EMD. The intrinsic mode function（IMF）component with the largest correlation coefficient are analyzed for spectral images，which are compressed into characteristic binarization images to feed in the CNN training.Then，CNN yields a model that is used to classify and identify various faults based on the compressed images both under normal and various fault conditions . The experimental results show that the presented method surpasses traditional fault diagnosis methods when the accuracy rate of the bearing fault diagnosis with less training data increased to 97.61%，which is much larger than that of the BP neural network and probabilistic neural network method. Besides，the method presents stronger generalization ability and better anti-noise performance with an accuracy rate of 96.19% when the original signals is superposed with a 6 dB white noise.

Keywordsempirical mode decomposition；convolution neural network；rolling bearing；fault diagnosis

Analysis of Thermohydrodynamic Characteristics of Liquid Film Seals Based on Cavitation

SUN Xinhui1，YAN Fangqi1，HAO Muming1，LI Ning2，WENG Zewen2，YUAN Junma2
（1.College of New Energy，China University of Petroleum（East China） Qingdao，266580，China）（2.AECC Hunan Aviation Powerplant Research Institute Zhuzhou，412002，China）

AbstractThe dynamic Reynolds equations and liquid film energy equations are deduced and solved by finite element method. The thermoshydrodynamic characteristic model of liquid film seal considering the cavitation is established. On this basis，the influence of groove number，groove depth，rotational speed and pressure on the stiffness and damping of liquid film is analyzed：considering the cavitation and thermal viscosity，the interaction between the two orthogonal angular coefficients is weak，and the coupling angular coefficient is smaller than those of the orthogonal angular and the axes；the absolute value of stiffness coefficients increases with the increase of groove number，groove depth，rotational speed and pressure；The absolute value of damping coefficients increase with the increase of rotational speed and pressure，and decrease slightly with the increase of groove number and groove depth. The anti-perturbation ability of the liquid film shares the same rules with the absolute value of stiffness coefficients.

Keywordsliquid film seal；dynamic characteristics；thermal viscosity；cavitation；stiffness；damping

Topology Optimization Research and Vibration Characteristics Analysis of the Floating Raft Isolation System

CUI Hongyu1，ZHU Haitao1，2
（1.School of Naval Architecture & Ocean Engineering，Dalian University of Technology Dalian，116024，China）（2.CRRC Qingdao Sifang Rolling Stock Research Institute Co.，Ltd. Qingdao，266031，China）

AbstractThe intermediate raft is key to a floating raft vibration isolation system due to the influences of its mass distribution and size on the performance of the system. In light of this situation，the topological optimization method and power flow are introduced to optimize the raft structure by decreasing its weight，and uncover the vibration transfer characteristics of the system respectively. To study the optimized raft structure，the experimental model of floating raft isolation system is built from an air spring isolator，and the isolation performance of floating raft system is analyzed based on the vibration level drops. The simulation shows that the optimized raft structure maintains the desired performance when the weight is greatly reduced. The experiments present a close relation between the vibration isolation results of the air spring and its stiffness，and reinforce the advantages of the improved floating raft vibration isolation system.

Keywordsfloating raft；vibration isolation；topology optimization；power flow；vibration level drops

A Method of Mechanical Fault Diagnosis Based on Locality Margin Discriminant Projection

SHI Mingkuan，ZHAO Rongzhen
（School of Mechanic & Electrical Engineering，Lanzhou University of Technology Lanzhou，730050，China）

AbstractA locality margin discriminant projection（LMDP）algorithm is proposed to reduce the dimension of the fault feature set．The algorithm defines the local intra-class similarity and the local inter-class similarity to separate the neighboring samples of different classes and join those in the same class. Then，the time-domain and frequency-domain statistical characteristics of rotor vibration signals are extracted to form the original fault feature set. The LMDP algorithm fuse the feature set to select a low-dimensional sensitive feature subset that contains the most intrinsic information. Finally，the K-nearest neighbor（KNN）classifier trains the subset and classify the faults. The vibration signal seta of two different double-span rotor systems verify the effectiveness of the proposed method.

Keywordsfault diagnosis；dimensionality reduction；manifold learning；rotor system

Rolling Bearing Fault Diagnosis Based on DS-VMD and Correlated Kurtosis

SHI Wenjie1，HUANG Xin1，WEN Guangrui1，2，ZHANG Zhifen1
（1.School of Mechanical Engineering，Xi'an Jiaotong University Xi'an，710049，China）（2.School of Mechanical Engineering，Xinjiang University Urumqi，830047，China）

AbstractIn order to adaptively determine the parameters of variational mode decomposition（VMD）and reduce the dependence on prior knowledge in signal processing，a parameter optimization-based VMD and signal reconstruction methods by correlated kurtosis indicators is proposed to extract the fault characteristics of rolling bearings. Firstly，the DS algorithm is used to optimize the parameter combination of the VMD，after which the vibration signal is decomposed to obtain the intrinsic mode function（IMF）. Then the correlation kurtosis of each IMF is calculated and used to reconstruct the vibration signal. Finally，the envelope spectrum analysis of the reconstructed signal is performed to extract bearing fault features. The proposed method is compared with empirical mode decomposition（EMD）and conventional VMD method，and both the simulation signal and vibration signal show that the proposed method can effectively identify the fault characteristic frequency of the rolling bearing. Furthermore，compared with the widely used fast kurtogram method，the proposed method also shows better results.

Keywordsvariational mode decomposition；differential search；correlated kurtosis；rolling bearing；fault diagnosis

Dynamic Performance of Cast-in-Place Steel Spring Floating Slab Track in Urban Express Rail Transit

LI Ping1，LUO Xinwei1，ZHU Wenhai2
（1.Guangzhou Metro Design & Research Institute Co.，Ltd. Guangzhou，510000，China）（2.Gerb（Qingdao）Vibration Control Co.，Ltd. Qingdao，266108，China）

AbstractTo verify the applicability of 25 m cast-in-place steel spring floating slab track in urban express rail transit，the vehicle-track coupled dynamics model and numerical method of CRH6 and cast-in-place steel spring floating slab are established based on the vehicle-track coupled dynamics theory. Through simulation calculation，the coupled dynamics performance of cast-in-place floating slab track bed and train under fast driving conditions is simulated，-and the safety，comfort and stability of 25 m cast-in-place steel spring floating slab track bed are evaluated.The effect of cast-in-place floating slab length，thickness and support damping on the dynamic performance of the system is studied. The research results show that：The denser the vibration isolators are，the better the stability of the track bed itself；The variation of the thickness of the cast-in-place steel spring floating slab bed on the operational safety indicators and ride comfort indicators of the intercity electric multiple units are not large；increasing the thickness of the floating slab can slightly improve the running stability of the vehicle；When the intercity electric multiple units is running，the stability indicators，the comfort rate and other indicators all meet the limit，that is，the cast-in-place floating slab track can meet the requirements of urban express rail transit. The research results can provide support for the dynamic design of the cast-in-place steel spring floating slab track with a speed of 160 km and above.

Keywordsurban express rail transit；cast-in-place steel spring floating slab track；dynamic performance；vehicle-track coupled dynamics

Experimental Study on Improving Tensile Properties of FFF Thin Plate by Vibration

JIANG Shijie，DONG Tiankuo，CHEN Pifeng，SUN Mingyu，DAI Weibing
（School of Mechanical Engineering & Automation，Northeastern University Shenyang，110004，China）

AbstractThe fused filament fabrication（FFF）technology has become the most popular rapid prototyping technology due to its simple operation，low cost and friendly environment. However，due to the manufacturing process of layer by layer deposition，the quality of its products is difficult to match that of the parts obtained by traditional processing methods. In this paper，for the first time，piezoelectric ceramic and the FFF rapid prototyping equipment are combined to improve the mechanical properties of printed products by using vibration. Firstly，the ordinary FFF rapid prototyping equipment is converted into vibration FFF rapid prototyping equipment by piezoelectric ceramics.Then，the tensile specimens before and after vibration input are prepared and the tensile experiment is completed. By comparing and analyzing the stress-strain relationship of different parts，the influence rule of the applied vibration on the tensile performance of the FFF products is clarified. The results show that vibration can significantly improve the tensile strength and elastic-plastic property of FFF products，and effectively reduce its anisotropy.

Keywordsfused filament fabrication；piezoelectric ceramics；using vibration；tensile strength；elastic-plastic property

Novel Method of Real-Time Remaining Useful Life Prediction for Wind Turbine Bearings

LÜ Mingzhu1，2，SU Xiaoming1，LIU Shixun3，CHEN Changzheng1
（1.School of Mechanical Engineering，Shenyang University of Technology Shenyang，110870，China）（2.School of Automatic Control Engineering，Liaoning Equipment Manufacturing Vocational and Technical College Shenyang，110161，China）（3.China Quality Certification Center（Shenyang）North laboratory Shenyang，110164，China）

AbstractDue to the lack of sensitivity and robustness to periodic fault shocks，the traditional degradation indicators are unable to track the degradation process of wind turbine bearings timely and predict remaining useful life accurately. In this paper，a real-time remaining useful life prediction method for wind turbine bearings based on the combination of envelope harmonic-to-noise ratio（EHNR）and unscented particle filter（UPF）is proposed.Firstly，the early degradation starting point of the bearing is detected by calculating the EHNR of the vibration signal and the trend characteristic of the EHNR is extracted as the novel degradation indicator. Secondly，the degradation model of bearing is constructed on the basis of historical data，and then the UPF algorithm is used to update the model parameters in order to realize the tracking and prediction of the bearing degradation stage.Finally，the actual monitoring data of wind turbine bearings is taken as an example to validate the proposed method，the results show that this method can start the life prediction mechanism in time and effectively solve the problem of particle degradation in traditional particle filter algorithm. Compared with commonly used support vector regression（SVR）and back propagation neural network（BPNN）prediction methods，it has higher prediction accuracy，and provides a reference for health management and reliability evaluation of large wind turbines.

Keywordswind turbine；bearings；envelope harmonic-to-noise ratio （EHNR）；unscented particle filter（UPF）；remaining useful life prediction

Optimization of Quality Compensation Strategy for On-Line Dynamic Balance of Spindle System

WANG Zhan1，2，ZHANG Bo1，ZHANG Ke2
（1.School of Mechanical Engineering，Shenyang Jianzhu University Shenyang，110168，China）（2.National and Regional Joint Engineering Laboratory of High-Grade Stone NC Processing Equipment and Technology Shenyang，110168，China）

AbstractOn-line dynamic balancing is the main method to solve the spindle system unbalance failure and reduce the spindle vibration. In order to improve the balancing accuracy and efficiency of the on-line dynamic balancing device，an optimization model of the spindle system dynamic balancing quality compensation strategy based on genetic algorithm is proposed. The model takes the residual unbalanced force as the optimization objective and the rotation phase of the mass block of the balancing device as the optimization variable. Then the phase is calculated by genetic algorithm. The on-line dynamic balance test platform of the spindle system is built to carry out the comparison and optimization experiment of the dynamic balance strategy under different rotating speeds，and the residual unbalanced force after the balance is greatly reduced. The experimental results show that after the optimization of the mass compensation strategy，the vibration of the spindle decreases by an average of 20.60%，and the balance time decreases by an average of 34.67%. It can be seen that the optimization model of the quality compensation strategy of the spindle system based on genetic algorithm can further improve the quality and efficiency of the spindle on-line dynamic balance and improve the operating performance of the equipment.

Keywordsgenetic algorithm；spindle；quality compensation；on-line dynamic balance

Method for Determining Optimal Analysis Length of Vibration Data

ZHANG Jianwei1，2，3，LI Yang1，2，3，MA Xiaojun1，2，3，CHENG Mengran1，2，3
（1.School of Water Conservancy，North China University of Water Resources and Electric Power Zhengzhou，450046，China）（2.Collaborative Innovation Center of Water Resources Efficiency and Protection Engineering Zhengzhou，450046，China）（3.Henan Provincial Hydraulic Structure Safety Engineering Research Center Zhengzhou，450046，China）

AbstractThe selection of data analysis length is the key to extracting structural vibration characteristic information，and the artificial selection of the data length for signal analysis will cause certain errors in the calculation results. To reduce the influence of subjective factors，an improved multi-scale permutation entropy（IMPE）method is proposed to analyze the length of vibration data. IMPE method has a strong advantage in dealing with nonlinear and non-stationary signals，so the vibration measurement data of the measured structure can be obtained by placing sensors. For the obtained vibration signal，the one-dimensional time series data is multi-scaled and then coarse-grained to determine its phase space reconstruction parameters. The vibration data with different lengths is selected and the multi-scale permutation entropy（MPE）entropy value is calculated respectively. It is found that the entropy value is sensitive to the change of the data length，changes with the increase of the data length，and finally it is going to stabilize. Here，the stable value is defined as a standard entropy value，and the entropy value satisfying standard entropy value of 97% is used as the effective entropy value. The entropy value that meets the accuracy requirements is selected，and its corresponding shortest data length is defined as the optimal data analytical length of the vibration data. This method is applied to the selection of the optimal data length of the simulation signal and the vibration signal of discharge engineering，and the accurate data analysis length can be selected for structure monitoring，and it has good universality.

Keywordsdam vibration；data analysis length；improved multi-scale permutation entropy；signal analysis；white noise

Safety and Optimization of Vertical Pump Gate

SHI Xianrui1，2，3，YAN Genhua1，3，DONG Jia1，2，3，YANG Yu1
（1.Nanjing Hydraulic Research Institute Nanjing，210029，China）（2.College of Water Conservancy and Hydropower Engineering，Hohai University Nanjing，210098，China）（3.State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering Nanjing，210029，China）

AbstractThe pump gate is a new type of water environment management equipment with compact device and novel structure. However，as this equipment is a combination of hydraulic plate and axial-flow pump，the weak boundary constraint and complex flow are easy to induce the vibration of the pump gate. Therefore it is necessary to carry out systematic research on the hydraulics and power safety of the pump gate before widespread application. In this study，the hydrostatic properties，hydrodynamic and flow-excited vibration characteristics of the vertical pump gate are studied systematically. It is conducted when the equipment under different operating conditions. The research methodology includes numerical simulation，hydrodynamic and hydroelastic vibration experiments. As a result，the problem of large vibration is revealed when the pump gate is operating. The Hilbert-Huang transformation method is used to analyze the data. On the basis of this，the modified and optimized design of the pump gate is carried out. The achievement indicates that the connection between components should be enhanced. After a great deal of effort，the final optimization scheme effectively controls the structural vibration and the optimization effect is significant，which provided a great reference for the design of similar projects.

Keywordsflow-excited vibration；numericalt analysis；vibration optimization；vertical pump gate；time-frequency analyses

Guided-Wave Based Damage Diagnosing Method with Energy Spectrum and Siamese Network

WANG Binwen，LÜ Shuaishuai，YANG Yu
（Aircraft Strength Research Institute of China Xi'an，710065，China）

AbstractCarbon fiber reinforced polymer（CFRP）has been widely used in the primary structures of aircraft.Guided-wave-based damage diagnosis has a good prospect in the field of CFRP damage monitoring，but it is confined by structural uncertainty and expertise dependence. An innovative strategy incorporating energy spectrum and siamese convolutional neural network（CNN）is proposed. The method of energy spectrum can not only eliminate the high dependence of expertise，but also collect richer information for the deep learning model. The CNN can effectively reduce the quantity of model parameters and consequently alleviate the phenomenon of over-fitting. The accuracy of damage recognition and localization achieve 88% and 85%，respectively. Furthermore，no personal expertise is involved through the entire process，thus the capability of damage recognition can be more robust.

Keywordscomposite material；damage diagnosis；guided wave；convolutional neural network；siamese network

Analysis of Natural Vibration Characteristics of Corrugated Web Steel Box-Concrete Composite Girder Bridge

JI Wei，LUO Kui，YAN Linjun
（College of Civil Engineering，Lanzhou Jiaotong University Lanzhou，730070，China）

AbstractIn order to find a simplified calculation method for the vibration frequency of the corrugated web steel box-concrete composite girder bridge，firstly，based on the comprehensive consideration of the shear lag effect of the box girder and the influence of the shear deformation of the corrugated steel web，the element stiffness matrix of the corrugated web steel box-concrete composite girder bridge is derived by the potential energy variation principle. Secondly，according to the derived element stiffness matrix and element mass matrix，the Matlab software is used to compile the calculation program of the vibration frequency calculation of the corrugated web steel box-concrete composite girder bridge. Finally，the convergence speed and computational efficiency of the vibration frequency solving program are analyzed. The results show that the frequency value obtained by the vibration frequency solving program agrees well with the ANSYS spatial finite element value and the measured value.The calculation of the frequency by the vibration frequency solver requires only a small number of units to achieve high calculation accuracy. The calculation time of the vibration frequency is greatly shortened，the calculation efficiency is improved，the complexity of the establishment and solution of the ANSYS spatial finite element model is avoided，and a simple method for analyzing the natural vibration characteristics of this type bridge in the engineering is provided.

Keywordscorrugated steel web；vibration frequency；element stiffness matrix；composite girder bridge；finite element analysis