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•A dynamic model of an axial piston pump is developed and experimentally validated.•Influences of operating conditions on the vibrations are studied.•Influences of stiffness and ...damping coefficients on the vibrations are studied.•The amplitude-frequency vibration responses and phase trajectory plots are analyzed.•Complex irregular motions occur under different working conditions.
A dynamic model with four masses and 19 degree of freedoms is proposed to investigate the vibration response characteristics of an axial piston pump. In the model, main parts are simplified by multiple lumped mass points connected with spring-damper elements. Experimental investigation is performed, and the discharge dynamic pressures and vibrations are measured to validate the dynamic model. Using the constructed model, influences of operating conditions (the discharge pressure, the rotational speed, and the displacement angle), and stiffness and damping coefficients between different contacting surfaces (the cylinder and valve plate, the piston and cylinder bore, and the slipper and swash plate) on the amplitude-frequency vibration responses and phase trajectory plots are analyzed. The findings showed that the vibration responses are significantly affected by the operating conditions, and are also considerably affected by the stiffness and damping coefficients. The rotational speed determines the fundamental frequency and its harmonics, and most of the harmonic vibration responses increase with increasing discharge pressure and displacement angle. The shape and the area defined by the phase trajectory are significantly changed by the operating conditions. The complex irregular motion might be changed into less irregular motion with decreasing discharge pressure, rotational speed and displacement angle.
Oil dampers have been used in recent years for passive structural control and shock mitigation in dynamic structural systems. However, machining technical and economic problems limit its application ...for new and existing buildings due to the necessary precision machining of incorporating shaft bearings and pressure sealings. A kind of nonlinear oil damper that is quite different from traditional oil damper is investigated and applied to a steel building. Vibration monitoring system was instrumented on the dampers to explore their actual performance and effectivity under strong earthquakes. Based on monitoring response of the nonlinear dampers under various excitations, Bayesian model selection is employed to analyze the most probable model class which can capture main dynamic characteristics of the nonlinear oil dampers and can also be used for predicting future response as well as reliability. Then, a particle filtering approach is proposed to identify the nonlinear model of the damper and quantify the model uncertainty. The developed particle filter is capable of re-parameterizing joint posterior distribution of states and parameters of the nonlinear oil damper without augmented state estimation, which combined with Markov chain Monte Carlo algorithm so as to be able to sample high-dimensional posterior distribution. The identified models and posterior distributions of parameters show that the developed particle filter approach can be appropriately used for nonlinear parameter identification without stuck to special particles. Furthermore, the dynamic properties of the nonlinear oil damper with respect to various excitations involving different spectral characteristics are discussed.
Hydraulic multi-way valves as core components are widely applied in engineering machinery, mining machinery, and metallurgical industries. Due to the harsh working environment, faults in hydraulic ...multi-way valves are prone to occur, and the faults that occur are hidden. Moreover, hydraulic multi-way valves are expensive, and multiple experiments are difficult to replicate to obtain true fault data. Therefore, it is not easy to achieve fault diagnosis of hydraulic multi-way valves. To address this problem, an effective intelligent fault diagnosis method is proposed using an improved Squeeze-Excitation Convolution Neural Network and Gated Recurrent Unit (SECNN-GRU). The effectiveness of the method is verified by designing a simulation model for a hydraulic multi-way valve to generate fault data, as well as the actual data obtained by establishing an experimental platform for a directional valve. In this method, shallow statistical features are first extracted from data containing fault information, and then fault features with high correlation with fault types are selected using the Maximum Relevance Minimum Redundancy algorithm (mRMR). Next, spatial dimension features are extracted through CNN. By adding the Squeeze-Excitation Block, different weights are assigned to features to obtain weighted feature vectors. Finally, the time-dimension features of the weighted feature vectors are extracted and fused through GRU, and the fused features are classified using a classifier. The fault data obtained from the simulation model verifies that the average diagnostic accuracy of this method can reach 98.94%. The average accuracy of this method can reach 92.10% (A1 sensor as an example) through experimental data validation of the directional valve. Compared with other intelligent diagnostic algorithms, the proposed method has better stationarity and higher diagnostic accuracy, providing a feasible solution for fault diagnosis of the hydraulic multi-way valve.
During high-pressure acid leaching, sulfuric acid slurry acts as the transportation medium in the withdrawal drum for acid pressure leaching. Over time, the metal-sealed float valve at the pipeline ...outlet may experience internal leakage. To address this issue, the Euler–Lagrange method for fluid dynamics is used to evaluate the corrosion wear characteristics of the valve in a three-phase flow. Specifically, we investigate the erosion and wear properties of the ball valve core as it opened and closed. To further understand how different ball valve openings impact erosion characteristics, we establish a correlation between the corrosion rate and the drag coefficient. Our research findings indicate that as the valve’s relative opening decreases from 80% to 20%, the corrosion wear rate gradually increases. In addition, the number of particles within the valve cavity also follows a similar trend. These erosion results highlight the significant influence that particle quantity has on erosion. Moreover, with an increase in particle size, both the erosion gradient range and maximum erosion rate decrease.
A novel multiobjective adaptive surrogate model is employed for the prediction of full-film lubrication performance of surface texture profile for thrust bearings in axial piston pumps. At present, a ...surface texture optimization design of thrust bearing in axial piston pump has not been provided based on a unique design solutions. In this study, multi-objective adaptive surrogate-based optimization (MO-ASMO) algorithm was used for solving both the mechanical and volumetric losses performance design of surface texture. The non-dominated sorting genetic algorithm (NSGA-II) formed part of the developed multi-objective optimization model, having three competing design objectives which mainly include load capacity, friction torque and leakage rate. A comparative study of two models with accuracy analysis of each case was performed. The results show that the MO-ASMO has the best performance among the different surrogate models. Comparing with the NSGA-II model, the improvement of the leakage rate and the load carrying force made by MO-ASMO are higher about 16.12% and 3.67%, respectively. In other words, multi-objective optimization is capable of enhancing textured slipper bearing performance using MO-ASMO method. The optimal texture radius and texture depth are chosen to minimize the leakage rate and texture bearing capacity.
•Evidential UQ to determine uncertainties of the metal fatigue crack growth was proposed.•DE based interval optimization improves the practical utility of evidential UQ.•Aluminum alloy CCT data are ...used to demonstrate the effectiveness presented method.
Uncertainties originate from physical variability, data uncertainty, and modeling errors in the fatigue crack growth prediction analysis. This study presents an evidential uncertainty quantification (UQ) approach for determining uncertainties involved in revealing the material constants of the metal fatigue crack growth model with imprecise uncertainty information (i.e., epistemic uncertainty). The parameters in fatigue crack growth model are obtained by fitting the available sparse experimental data, and then the uncertainties in these parameters are considered. To alleviate the computational difficulties in the UQ analysis based on evidence theory, an interval optimization method based on differential evolution is used in finding the propagated belief structure. The overall procedure is demonstrated using the results of several replicated experiments on aluminum alloy CCT specimens.
Inspired by the working principle that there is no throttling loss (theoretically) in the fully open and fully closed states of high-speed on–off valves, a high-frequency two-dimensional rotary valve ...is proposed to generate fluid pulse width modulation waves to control and distribute the flow rate of the hydraulic system in an energy-saving manner. The mechanism has been designed, so the aim of this paper is to develop detailed research on the characteristics of the high-frequency two-dimensional rotary valve as a new hydraulic component. The mathematical model of the rotary valve is established, and influences of key parameters on its characteristics are analyzed. Then, the static and dynamic characteristics of the rotary valve are simulated including valve coefficients, leakage, dynamic response and efficiency. Finally, a prototype of the two-dimensional rotary valve is designed and the testing system is built, and its pressure loss characteristics and energy efficiency characteristics were tested experimentally. The experiment results show that the valve is able to reduce throttling losses and improve the overall energy efficiency in the hydraulic system compared with the traditional throttling control. It can be used as a new variable mechanism, combined with a quantitative pump, to provide a way of forming a variable or load sensitive or bidirectional variable function of the pump system.
•Fuzzy entropy assisted improved SSD denoising method is developed.•Secondary screening decreases the interference of natural periodic impulses.•Soft threshold technique is applied to further ...suppress the residual noise.•Simulation and experiment verify the superiority of the presented approach.
The fault feature of vibration signal is always submerged in heavy interference noise and strong pumping impulses in axial piston pump bearings. A fuzzy entropy assisted singular spectrum decomposition denoising method is introduced to extract bearing fault in axial piston pump. The raw measured data is adaptively decomposed to singular spectrum components. The fuzzy entropy of singular spectrum components is used to screen the component with critical information and remove the unrelated components. The remaining singular spectrum components are conducted for the secondary screening to decrease impulse interference based on the prior knowledge. Simulation results of signals with different noise intensity thoroughly validate performance. This method is applied to process practical engineering signals and the characteristic frequency intensity coefficient is taken as the evaluation index in the field. The experimental results show that the evaluation index of the presented technique are increased by 80%, 56% and 40%, respectively.
The dynamic vibration characteristics of multibody system in axial piston pump is studied based on a lumped parameter model. The model is used to predict the vibration responses of the rotor assembly ...and the separator assembly based on Runge-Kutta method. The built model is verified by comparing the theoretical frequencies and experimental results. The developed model is used to investigate the effect of operating circumstances and coefficients of stiffness and damping on the amplitude-frequency vibration response and phase trajectory diagram. The results demonstrated that the frequency simulated by the model is similar to that measured by the experiment, and the error is 8.85%. The frequency of the harmonic is related to the excitation force period and the rotational speed of the axial piston pump. Higher harmonic vibration frequencies are integer multiples of the pump rotation frequency and the inherent flow pulsation frequency. The frequency of pistons impulse is twice that of the rotation. The frequency diagram and phase trajectory diagram are affected by various operating conditions as well as stiffness and damping factors.
The underlying study investigates single valued neutrosophic entropy based adaptive sensitive frequency band selection for variational mode decomposition (VMD) for the purpose of identifying ...defective components in an axial pump. The proposed methodology is applied in the following steps. First, VMD is applied for decomposing vibration signals into various frequency bands, called as modes. After computing energy of each VMD, the lower (minimum) and upper (maximum) bounds from these energy readings are extracted for defect conditions, such as outer race, inner race, worn piston, faulty cylinder and valve plate, and blocked hole of the piston. Thereafter, energy interval ranges are obtained and further converted into the form of single valued neutrosophic sets (SVNSs). Then, the proposed neutrosophic entropy measure is deployed for quantifying the non-linear connection between each bearing defect conditions and various frequency bands. The mode having maximum neutrosophic entropy value is designated to the “most sensitive” frequency band. Thereafter, envelope demodulation is applied to the most sensitive selected frequency band for finding defective components. The proposed neutrosophic entropy and VMD based methodology is effective in providing a better insight for selecting suitable frequency band for carrying out envelope demodulation in comparison to existing methods.
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