Journal of Vibroengineering
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Research on blasting vibration effect and time-frequency characteristics of vibration signals in a road corridor at xianning nuclear power station
Full text linkDrill and blast is a major method for foundation excavation in nuclear power plant engineering. For transporting heavy components to engineering construction, the blast-induced vibration of foundation excavation in a road corridor may has a great influence on new pouring mass concrete and surrounding bedrock in Xianning Nuclear Power Station, which will affect the safety of the engineering construction. So it is necessary to monitor the process of blasting excavation and put forward effective control measures on blasting vibration effect, in which the peak particle velocity (PPV) attenuation law are investigated through regression analysis of practical field data by Duvall empirical formula and the time-frequency characteristics was analyzed by wavelet transform and wavelet package decomposition. By analyzing the velocity amplitude and power spectrum density amplitude of wavelet components, it shows the blast energy of original vibration signal is mainly within the frequency below 250 Hz and has three sub-band which varies from 10 Hz to 30 Hz, from 40 Hz to70 Hz and from 75 Hz to 125 Hz, respectively. Wavelet packet analysis indicates the energy of the signal in 0-125 Hz accounts for 94.25 % of the total signal. At the same time, for the sake of ensuring the safety of road corridor, Chinese admissibility standards (GB6722-2014) of blasting-induced vibration and the constants obtained from the regression were used to establish the maximum explosive charge per delay for an acceptable ground vibration level that would not cause damage for new pouring mass concrete and bedrock in road corridor. The safety criteria of particle vibration velocity for new pouring mass concrete and bedrock in road corridor could be both set as 5 cm/s, which show the remarkable effect on blasting damage control of the new pouring mass concrete and surrounding bedrock, the results demonstrate that controlling maximum explosive charge per delay methodology can be commendably applied to road corridor to control blasting-induced vibration effects
Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms
Full text linkFlexible beam structure is usually applied in various fields of engineering and industrial. There are few points of interest using flexible structure and one of the advantages is that its lighter compared to a rigid structure. Besides that, flexible beam also can save cost, reduce energy consumption, and improve operation safety. However, flexible beam structures are too sensitive and susceptible to with unwanted vibration that would cause damage or degradation to the structure system. Hence, to overcome the problem, appropriate modelling and controller for such systems should be developed. Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). Therefore, two type of algorithms was used in this work for modelling development of flexible beam structure, which are ant colony optimization (ACO) and cuckoo search algorithm (CSA). Based on the comparative results, CSA achieved the lowest mean square error (MSE) value of 6.1547×10-9 meanwhile ACO recorded a MSE of 1.0728×10-8. Moreover, CSA was deduced to be the best model for flexible beam structure because it achieved 95 % confidence level in correlation test and has excellent stability in pole-zero diagram system. Thus, CSA is a suitable algorithm to represent the real behavior of flexible beam structure in a system
Analysis model of restoring force of a rubber air spring
Full text linkNot only has the dynamic stiffness of a rubber air spring been inherited by effects of the compressed air, but it has also been affected by hysteresis behaviors caused by the friction, viscoelasticity of bellow material. Hence, this paper will analyze comprehensively the stiffness model of a commercial rubber air spring. One of the first works is to predict the structure parameters including effective area, volume and their change rate. Then, the restoring force generated by compressed air will be analyzed and built through the theory of thermodynamics. The hysteresis model of the rubber bellow will be obtained based on the Berg’s frictional model connecting in parallel with fractional Kelvin-Voigt model. Next, an experimental apparatus is set up to identify the parameters of this model as well as evaluate the proposed restoring force model of the rubber air spring. The study results show that the analysis model of the rubber air spring matches well the measured data. This work will offer a helpful insight in the design of the vibration isolation system using rubber air springs as elastic elements
Research on fan vibration fault diagnosis based on image recognition
Full text linkThe conventional methods for vibration fault detection and diagnosis relies on feature extraction from the waveforms of the vibration signals. This article exploits the scope of image recognition application for the detection and diagnosis of fan vibration faults. In this paper, a novel image recognition technique is proposed for vibration-based fault diagnosis using the spectrum images of the vibration signals. 1D vibration signal spectrum is initially computed using Fast Fourier Transform (FFT) and the FFT frequencies are adjusted such that it captures a vibration spectrum diagram as 2D image representation. FFT based vibration analysis is done and the image recognition concept is utilized for feature extraction and a machine learning classification module is used for fault analysis and diagnosis. Effective feature generation is done using Principal Component Analysis (PCA) by removing the redundancy from the feature vectors and machine learning classifiers are used to obtain improved image recognition and classification performance. Artificial Neural Network (ANN) classifier yields better performance in terms of various performance parameters and percentage improvement in terms of accuracy for ANN classification methods over Support Vector Machine (SVM), k-Nearest Neighbours (kNN) and Random Forest Ensemble (RFE) methods are 10.01 %, 4.51 % and 2.01 % respectively. Comparative scenarios are considered in this work for fan vibration fault detection as well as diagnosis based on the image features for various realistic vibration fault conditions. Effectiveness of the proposed image recognition-based technique is compared with the state-of-the-art methods, justifying its outperformance for fan fault detection and diagnosis using the combination of spectrum adjustment, PCA and ANN classification method
Effect of mistuning parameters on dynamic characteristics of mistuned bladed disk
Full text linkThe aim of this paper is to study the nonlinear dynamics of the tenon and mortise of aero-engine compressor blades, based on lumped parameter model of tenon and mortise of blade disk system, considering the influence of gap and friction, The nonlinear vibration characteristics of mistuned bladed disk with different mistuning parameters are studied. The effects of tenon and mortise gap, dry friction, blade damping mistuning and tenon damping mistuning on the vibration characteristics of the mistuned bladed disk under strong coupling and weak coupling are obtained respectively. The results show that the gap and friction has little effect on the vibration response of the weakly coupled bladed disk, but the gap and friction has a great influence on the strongly coupled bladed disk, the larger the gap, the more complex the nonlinear dynamic characteristics of tenon. Under the same gap and coupling strength, the mistuning parameters have a certain influence on the vibration amplitude of the bladed disk
Active damping for vibration control based on the switched stiffness technique
Full text linkAn active damping controller based on the switched stiffness technique is developed and applied to vibration mitigation in a lightly damped structure. The controller either increases or decreases the system stiffness according to a state-dependent rule. A novel stability analysis based on the Floquet theory is proposed and employed to analyze the mathematical model of a one-degree-of-freedom system where the friction forces are taken into account. This novel analysis allows us to prove the exponential stability of the system origin, to establish a tuning procedure for the controller gain, to solve an optimization problem and to show the controller robustness against parameter uncertainties. Experimental verification is conducted to validate the effectiveness of the controller, and it is shown that the controller is feasible for vibration control problems
Vibration performance prediction and reliability analysis for rolling bearing
Full text linkThe bearing vibration signal is a rich dynamic symptom of bearing wear, and the vibration signal of rolling bearing presents chaotic characteristics. Input and output variables of vibration signal can be constructed through phase space reconstruction, the Input and output variables can be imported into the prediction model for prediction. The prediction accuracy of the extreme learning machine (ELM) model, Kriging model and RBF model are compared, the results show that ELM has higher accuracy, so ELM chaos model is used to predict the future vibration time series data, and the forecasting error can be obtained by comparing the prediction value with the actual values so as to verity the feasibility of the ELM model. The prediction results of the future state of the bearing are processed as the grey-bootstrap method, and the performance reliability prediction of the bearing is realized by the Poisson counting process. The experimental data show that with the deepening of the fault degree, the reliability performance decreases gradually. The reliability performance of the bearing without fault is 100 %, and the reliability performance is 47.56 % when the inner ring faulty size is 0.72 mm
Analysis on transformer vibration signal recognition based on convolutional neural network
Full text linkIn order to study the relationship between the transformer vibration and the operation state, the wavelet analysis method and the convolutional neural network method were used to analyze the transformer vibration signal. This paper proposes a transformer based on convolution neural network-based surface vibration signal feature extraction method. The result show that the convolution of neural network in different station transformer surface vibration signal classification has a lot of advantage, as the integration of feature extraction and classification recognition process together can effectively classify vibration signal recognition processing. This method is feasible for classification and identification by providing an accuracy value of 92.74 %. The future perspective of this research will focus on a generalized network model and parameters through experimentation for further investigation of accuracy and efficiency of this method
Analysis of transverse vibration of wire rope in flexible hoisting system
Full text linkTaking the flexible hoisting system as the research object, the transverse vibration mathematical model of the steel wire rope of the winding hoisting system is established, and the transverse vibration displacement, velocity and acceleration of the steel wire rope at 18 m away from one end of the wire rope under the sine excitation at other end is obtained through the comparison and verification of the results from the mathematical model, mechanical model and experiment. The results show that: for the length of the wire rope of 20 m, under the sine excitation at the end of amplitude of 0.002 m and frequency of 20 Hz, the transverse vibration displacement at 2 m from one end of the wire rope with length of 20 m is basically between –0.005 m and 0.005 m, the transverse vibration velocity at 2 m from one end of the wire rope is basically between –0.04 m/s and 0.04 m/s, and the transverse vibration acceleration of the wire rope is basically between –0.5 m/s2 and 0.5 m/s2. And the transverse vibration displacement decreases near the end, meanwhile the transverse vibration frequency increases with the reduction of length of vertical section of wire rope
Estimation of longitudinal excitation of propeller using a novel hybrid method
Full text linkDue to the limitation of working environment and structure conditions, it is difficult to directly measure the propeller excitation of ship propulsion shafting system. A method based on waveguide function and modal method combining with shafting vibration response measurement was proposed to estimate the propeller longitudinal excitation indirectly. Firstly, a waveguide transfer model for the general structure of the propulsion shafting is proposed that is suitable for estimating propeller excitation from shafting vibration response. Secondly, the longitudinal excitation of the propeller is calculated by measuring the waveguide coefficients of any shaft sections via the proposed hybrid method. Finally, the scheme is verified by a concrete example. The simulation results prove its feasibility and effectiveness for estimating propeller excitation by measuring the shafting vibration response, which provides a novel scheme for accurately grasping the propeller excitation and effectively controlling the vibration and noise of hull structure