Journal of Vibroengineering
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Distribution of unsteady pressure in volute type axial flow pump
Get PDFIn order to study the distribution of unsteady pressure in volute type axial flow pump, the k-ε turbulence model was applied, and ANSYS CFX was provided for numerical simulation calculation. Experiments of external characteristics and pressure fluctuation have been done to verify the results of numerical simulation. The results show that under the design operating condition, the main fluctuation frequencies in the volute, at the inlet and outlet of the impeller are the blade passing frequency. The amplitudes of fluctuation at the inlet of the impeller decrease gradually from the rim to the hub, while those at the export decrease firstly and then increase, the amplitudes at the tongue are much higher than that at other sections of the volute. Under the off-design operating conditions, the main fluctuation frequency at the inlet and outlet of the impeller is still the blade passing frequency, while that at the tongue is between the twice shaft frequency and the blade passing frequency, fluctuation amplitudes are both larger than those under the design operating condition. Under the design operating condition, the radial force on the impeller is the minimum, however, the axial force increases with the increase of flow rate. The distributions of unsteady pressure in volute type axial flow pump are different with general centrifugal or axial flow pump
Fault diagnosis of rolling element bearing based on a new noise-resistant time-frequency analysis method
Get PDFWhen fault arises in the rolling element bearing, the time-domain waveform of fault vibration signal will take on the characteristic of cyclostationarity, and the spectral correlation (SC) or spectral correlation density (SCD) basing on second order cyclic statistic is an effective cyclostationarity signal processing method. However, when the fault signal is surrounded by strong background noise, the traditional signal processing methods such envelope demodulation analysis and SC would not work effectively. The paper improves the SC method and a new time-frequency analysis method naming improved spectral correlation (ISC) is proposed. The proposed method is much more noise-resistant than SC through the verification of simulation analysis results. Besides, it takes on modulation phenomenon usually when fault arises in the rolling element bearing and the aim of fault feature extraction is to extract the fault characteristic frequency only or cyclic modulation frequency and the modulated frequency or carrier frequency buried in the object vibration signal is neglected. So, the paper improves the ISC further and the improved ISC (IISC) is proposed. The IISC will extract the modulation frequency only and it has the advantages of much clearer expression effect and better extraction effect. The effectiveness and feasibility of the proposed method are verified through the three kinds of fault (inner race fault, outer race fault and rolling element fault) of rolling element bearing. Besides, the advantages of the proposed method over the other relative time-frequency analysis methods such as ensemble empirical mode decomposition (EEMD) and spectral kurtosis (SK) are also presented in the paper
Deep convolutional neural networks for Bearings failure predictionand temperature correlation
Get PDFRolling elements bearings (REBs) is one of the most sensitive components and the common failure unit in mechanical equipment. Bearings failure prognostics, which aims to achieve an effective way to handle the increasing requirements for higher reliability and in the same time reduce unnecessary costs, has been an area of extensive research. The accurate prediction of bearings Remaining Useful Life (RUL) is indispensable for safe and lifetime-optimized operations. To monitor this vital component and planning repair work, a new intelligent method based on Wavelet Packet Decomposition (WPD) and deep learning networks is proposed in this paper. Firstly, features extraction from WPD used as input data. Secondly, these selected features are fed into deep Convolutional Neural Networks (CNNs) to construct the Health Indicator (HI). This study focuses on analysing the relationships such as correlations between the HI and temperature. We develop a solution for the Connectiomics contest dataset of bearings under different operating conditions and severity of defects. The performance of the proposed method is verified by four bearing data sets collected from experimental setup called “PRONOSTIA”. The results show that the health indicator obtains fairly high monotonicity and correlation values and it is beneficial to bearing life prediction. In addition, it is experimentally demonstrated that the proposed method is able to achieve better performance than a traditional neural network based method
Improvement of vibration isolation performance of QZS platform in chaotic interval based on damping increase control method
Get PDFIn order to further extend the effective isolation range of the quasi-zero stiffness (QZS) platform, the vibration isolation performance of the chaotic interval is improved. For a class of self-design quasi-zero-stiffness (QZS) vibration isolation platform, starting with chaotic motion of the non-linear vibration isolation system, the jumping interval is eliminated by means of transient chaos phenomena. The control method of damping increase is proposed in combination with the application of the Von der Pol Plane, which can make the jumping-down frequency to be decreased below the external excitation frequency, thus the effective isolation range of vibration isolation platform can be extended, and a lower isolation frequency can be obtained. Research shows that, when the solution of the motion equation of the platform system falls to resonant branch led by certain initial conditions, the resonant amplitude response will jump to the non-resonant branch by transient damping increase control method, which the removal time is determined by the Von der Pol Plane, hence making the platform system obtain the ideal vibration isolation performance. The research results have a significant importance for improving the low frequency and ultra-low frequency vibration isolation effect of such platforms, which lays a foundation for the popularization and engineering application, and can also provide a reference for control of other nonlinear vibration system
A study of a nonlinear magnetic vibration isolator with quasi-zero-stiffness
Get PDFA novel quasi-zero stiffness nonlinear magnetic isolator is designed by using magnetic springs in parallel with linear positive stiffness spring. Through the static analysis, the mathematical expressions of force-displacement-current and stiffness-displacement-current of the system are established, and the necessary conditions for the normal function and geometric parameters of the system are obtained. The nonlinear dynamic equations of the system under external excitation force are established. The amplitude and frequency characteristics of the system are deduced by harmonic balance method. The influence of system parameters and external excitation amplitude on the dynamic characteristics of the system is analyzed. Results showed that the vibration of the system can be controlled by controlling the electromagnet current or increasing the damping coefficient while the external excitation amplitude is kept in a certain of range. The researches provided a theoretical guidance for the design and application of the new quasi-zero stiffness nonlinear magnetic isolation system
Nonlinear robust adaptive NN control for variable-sweep aircraft
Get PDFIn this paper, we address the problem of altitude and velocity controllers design for variable-sweep aircraft with model uncertainties. The object is to maintain altitude and velocity during the wing transition process where mass distribution and aerodynamic parameters change significantly. Based on the functional decomposition, the longitudinal dynamics of the aircraft can be divided into altitude subsystem in non-affine pure feedback form and velocity subsystem. And then nonlinear robust adaptive NN velocity controller and altitude controller are designed with backstepping method to relax the prior requirements of aerodynamic parameters accuracy in linear LPV controller design. The method of filtered signal is used to circumvent the algebraic loop problem caused by the dynamics of non-affine pure feedback form. Dynamic surface control (DSC) and minimal learning parameters (MLP) techniques are employed to solve the problems of ‘explosion of complexity’ in the back-stepping method and the online updated parameters being too much. The robust terms have been introduced to eliminate the influences of approximation errors. According to the Lyapunov-LaSalle invariant set theorem, the semi-global boundedness and convergence of all the signals of the closed-loop system are proved. Simulation results are presented to illustrate the control algorithm with good performance
Creation of innovative earthquake resistant steel buildings by dividing the structure into inner and outer parts having interaction by hysteretic dampers
Get PDFIn conventional seismic design codes of building structures severe structural damage due to large earthquakes is accepted, provided that the structure does not collapse, and life safety of the residents is guaranteed. The extent of this allowed damage can be so high that after earthquake, demolition and reconstruction of the building becomes inevitable, particularly in near-fault areas. The idea followed in this study is to relocate the damage to some predetermined fuse elements, other than the main structural members, so that the building could be quickly and easily repaired, even after major earthquakes. For this purpose, dividing the building’s structure into two inner and outer parts with different dynamic characteristics, and creating dynamic interaction between them by using yielding plate or hysteretic dampers was investigated. At first, a 5-storey building model was developed and divided into two interactive parts using hysteretic dampers at roof level, and it was tried, by developing a code in MATLAB environment for solving the nonlinear equations of motion, to find the optimal values of the initial stiffness and the yielding strength of dampers, assuming their behavior to be elastic-perfectly plastic. The results of nonlinear time history analyses (NLTHA), by using a set of selected earthquakes accelerograms, showed that by using appropriate initial stiffness and yield strength, the inert-story drifts of both inner and outer structures can be significantly reduced. Then, 5-, 8- and 11-story steel braced buildings were designed by ETABS, and were divided into inner and outer substructures, and then were modeled in PERFORM-3D software using hysteretic dampers with optimal stiffness and strength, obtained from the MATLAB program, and the seismic responses were compared. Final results of the NLTHA show that the inter-story drift values of outer and inner substructures decreases in average by 20 % and 65 %, respectively, comparing to the original structure. This drift reduction leads to decrease of the damage indices of outer and inner substructures by almost 20 % and 80 %, respectively, comparing to the original structure, making it possible in most cases to have an easily repairable structure
Adaptive Neuro Fuzzy Inference System control of active suspension system with actuator dynamics
Get PDFA hybrid intelligent control technique based on combination of neural network and fuzzy logic will be proposed for hydraulic actuated active suspension system. A half car model will be used for design of Adaptive Neuro Fuzzy Inference System (ANFIS) controller for hydraulic actuated active suspension. The nonlinear behavior of hydraulic system and uncertain parameters in active suspension has increased the difficulty of creating mathematical model for active suspension system. The performance of most of the classical controller depends on nature of mathematical model of system. Hence it is very difficult to create classical controller without mathematical model of a system. Fuzzy logic controller has ability to predict the behavior of system without the need of mathematical model of a system. In this paper, ANFIS controller proposed for active suspension due to its ability to handle actuator dynamics and parameter uncertainty in hydraulic actuator. The simulation carried out for sinusoidal road profile in order to measure the performance of proposed controller. The result of simulation indicates performance of the ANFIS controller for active suspension with actuator dynamics
In-plane vibration analysis of heavy-loaded radial tire utilizing the rigid-elastic coupling tire model with normal damping
Get PDFTheoretical modeling, parameters identification and vibration characteristic of heavy-loaded radial tire is investigated with rigid-elastic coupling model with normal damping. The normal damping, including structural damping of flexible carcass and proportion damping of distributed sidewall element is added to enrich the flexible beam on modified elastic foundation tire model. The rigid-elastic coupling tire model with normal damping is investigated and derived with finite difference method. The mass, stiffness and damping matrixes of the proposed tire model are analytically related with the structural and geometrical parameters of heavy-loaded radial tire. Taking the error between the analytical and experimental transfer function as the object value, Genetic Algorithm (GA) is utilized to identify the damping coefficients of flexible carcass and distributed sidewall element. The influence of modal order and tire damping parameters on the in-plane transfer function is discussed. The theoretical and experimental results show that the rigid-elastic coupling tire model with normal damping can achieve the sectional feature of in-plane transfer function resulting from the coupling characteristic between the flexible carcass and distributed sidewall element within the frequency band of 300 Hz
Knock detection in spark ignition engines based on complementary ensemble improved intrinsic time-scale decomposition (CEIITD) and Bi-spectrum
Get PDFEngine knock limits the thermal efficiency improvement of spark-ignition (SI) engines. Thus, the extract research of the knock characteristics has a great significance for the development of gasoline engines. The research proposes a novel knock detection and diagnosis method in SI engines using the CEIITD (Complementary Ensemble Improved Intrinsic time-scale decomposition) and Bi-spectrum algorithm. The CEIITD algorithm is used to extract the knock characteristics. The results show that the CEIITD algorithm can effectively and clearly extract the knock shock characteristics (including light knock) through the vibration signals. A Bi-spectrum analysis can further distinguish between the light knock signal and normal combustion signal. The Bi-spectrum results also show that knock characteristic has a strong non-Gaussian property. At last, the Band pass filter and Improved ITD method were employed to identify the knock characteristics from these cylinder block vibration signals. The comparison result shows that the CEIITD method proposed in this paper is more suitable to detect the knock characteristic