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Keywords = bidirectional throttling

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20 pages, 17040 KiB  
Article
Study on Steady Flow Force of a Bidirectional Throttling Slide Valve and Its Compensation Optimization
by Qi Mao, Xinying Jia, Zhe Liu, Guang Li, Yichi Cao and Qingjun Yang
Appl. Sci. 2024, 14(23), 11037; https://doi.org/10.3390/app142311037 - 27 Nov 2024
Viewed by 776
Abstract
This paper focuses on a typical pressure-controlled slide valve, utilizing momentum analysis and computational fluid dynamics to simulate and analyze the asymmetry of steady flow force curves under bidirectional throttling patterns. The entropy production theory is employed to reveal the causes of nonlinearity [...] Read more.
This paper focuses on a typical pressure-controlled slide valve, utilizing momentum analysis and computational fluid dynamics to simulate and analyze the asymmetry of steady flow force curves under bidirectional throttling patterns. The entropy production theory is employed to reveal the causes of nonlinearity in the steady flow force of an inlet throttling slide valve. Based on flow field analysis, a flow force compensation scheme is proposed by adding a guiding shoulder and matching it with a suitably sized inner annular cavity. The study reveals that fluid momentum at the non-throttling valve port is the primary cause of the bidirectional throttling flow force difference, and under large-opening inlet throttling conditions, it may reverse the direction of the flow force. Vortex separation caused by turbulent pulsations is one of the intrinsic reasons for the nonlinearity of steady flow force. Full article
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25 pages, 8576 KiB  
Article
Fault Diagnosis of Hydraulic Components Based on Multi-Sensor Information Fusion Using Improved TSO-CNN-BiLSTM
by Da Zhang, Kun Zheng, Fuqi Liu and Beili Li
Sensors 2024, 24(8), 2661; https://doi.org/10.3390/s24082661 - 22 Apr 2024
Cited by 1 | Viewed by 1616
Abstract
In order to realize the accurate and reliable fault diagnosis of hydraulic systems, a diagnostic model based on improved tuna swarm optimization (ITSO), optimized convolutional neural networks (CNNs), and bi-directional long short-term memory (BiLSTM) networks is proposed. Firstly, sensor selection is implemented using [...] Read more.
In order to realize the accurate and reliable fault diagnosis of hydraulic systems, a diagnostic model based on improved tuna swarm optimization (ITSO), optimized convolutional neural networks (CNNs), and bi-directional long short-term memory (BiLSTM) networks is proposed. Firstly, sensor selection is implemented using the random forest algorithm to select useful signals from six kinds of physical or virtual sensors including pressure, temperature, flow rate, vibration, motor power, and motor efficiency coefficient. After that, fused features are extracted by CNN, and then, BiLSTM is applied to learn the forward and backward information contained in the data. The ITSO algorithm is adopted to adaptively optimize the learning rate, regularization coefficient, and node number to obtain the optimal CNN-BiLSTM network. Improved Chebyshev chaotic mapping and the nonlinear reduction strategy are adopted to improve population initialization and individual position updating, further promoting the optimization effect of TSO. The experimental results show that the proposed method can automatically extract fusion features and effectively utilize multi-sensor information. The diagnostic accuracies of the plunger pump, cooler, throttle valve, and accumulator are 99.07%, 99.4%, 98.81%, and 98.51%, respectively. The diagnostic results of noisy data with 0 dB, 5 dB, and 10 dB signal-to-noise ratios (SNRs) show that the ITSO-CNN-BiLSTM model has good robustness to noise interference. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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14 pages, 8936 KiB  
Article
Calculation and Analysis of Equilibrium Position of Aerostatic Bearings Based on Bivariate Interpolation Method
by Shuai Li, Yafu Huang, Hechun Yu, Wenbo Wang, Guoqing Zhang, Xinjun Kou, Suxiang Zhang and Youhua Li
Lubricants 2024, 12(3), 85; https://doi.org/10.3390/lubricants12030085 - 7 Mar 2024
Cited by 3 | Viewed by 1821
Abstract
The solution of equilibrium positions is a critical component in the calculation of the dynamic characteristic coefficients of aerostatic bearings. The movement of the rotor in one direction leads to bidirectional variations in the air film force, resulting in low efficiency when using [...] Read more.
The solution of equilibrium positions is a critical component in the calculation of the dynamic characteristic coefficients of aerostatic bearings. The movement of the rotor in one direction leads to bidirectional variations in the air film force, resulting in low efficiency when using conventional calculation methods. It can even lead to iterative divergence if the initial value is improperly selected. This study concentrates on the orifice throttling aerostatic bearings and proposes a novel method called the bivariate interpolation method (BIM) to calculate the equilibrium position. The equilibrium equation for the rotor under the combined influence of air film forces, gravity, and external loads is established. A calculation program based on the finite difference method is developed to determine the equilibrium position. The process of solving the equilibrium position and the convergence is compared with the secant method and the search method. Furthermore, the variation trend of the equilibrium position and stiffness when the external loads changes are studied based on the BIM. Finally, the correctness of the BIM to solve the equilibrium position is proved by comparing it with the experiment results. The calculation results indicate that the BIM successfully resolves the problem of initial value selection and exhibits superior computational efficiency and accuracy. The equilibrium position initially moves away from the direction of the external load as the load increases, and then this gradually approaches the load direction. The main stiffness increases with increases in the external load, while the variation in cross stiffness depends on the direction of the external load. Full article
(This article belongs to the Special Issue Tribological Characteristics of Bearing System, 2nd Edition)
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12 pages, 408 KiB  
Article
Synthesizing Vehicle Speed-Related Features with Neural Networks
by Michal Krepelka and Jiri Vrany
Vehicles 2023, 5(3), 732-743; https://doi.org/10.3390/vehicles5030040 - 26 Jun 2023
Cited by 2 | Viewed by 1562
Abstract
In today’s automotive industry, digital technology trends such as Big Data, Digital Twin, and Hardware-in-the-loop simulations using synthetic data offer opportunities that have the potential to transform the entire industry towards being more software-oriented and thus more effective and environmentally friendly. In this [...] Read more.
In today’s automotive industry, digital technology trends such as Big Data, Digital Twin, and Hardware-in-the-loop simulations using synthetic data offer opportunities that have the potential to transform the entire industry towards being more software-oriented and thus more effective and environmentally friendly. In this paper, we propose generative models to synthesize car features related to vehicle speed: brake pressure, percentage of the pressed throttle pedal, engaged gear, and engine RPM. Synthetic data are essential to digitize Hardware-in-the-loop integration testing of the vehicle’s dashboard, navigation, or infotainment and for Digital Twin simulations. We trained models based on Multilayer Perceptron and bidirectional Long-Short Term Memory neural network for each feature. These models were evaluated on a real-world dataset and demonstrated sufficient accuracy in predicting the desired features. Combining our current research with previous work on generating a speed profile for an arbitrary trip, where Open Street Map data and elevation data are available, allows us to digitally drive this trip. At the time of writing, we are unaware of any similar data-driven approach for generating desired speed-related features. Full article
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19 pages, 43713 KiB  
Article
Automation and Remote Control of an Aquatic Harvester Electric Vehicle
by Emil Tudor, Mihai-Gabriel Matache, Ionuț Vasile, Ion-Cătălin Sburlan and Vasilica Stefan
Sustainability 2022, 14(10), 6360; https://doi.org/10.3390/su14106360 - 23 May 2022
Cited by 7 | Viewed by 4004
Abstract
Electric boats are evolving, following the trend of imposing electric powered vehicles in all transportation solutions. For a research project, a reed and aquatic weed harvester, the author’s goal is to develop an experimental electrical vehicle aimed at solving several particular problems such [...] Read more.
Electric boats are evolving, following the trend of imposing electric powered vehicles in all transportation solutions. For a research project, a reed and aquatic weed harvester, the author’s goal is to develop an experimental electrical vehicle aimed at solving several particular problems such as: small speed, big throttle, high maneuverability, big load capacity, small draught and affordable cost. The solution comprises of one electric motor powered by a converter supplied from Li-Ion batteries, which drives a hydraulic pump for simultaneous operation of two lateral-placed paddle wheels and one complex mechanism of cutter and conveyor. The control system of this vehicle consists of one remote controller, with bidirectional radio communication to three on-board controllers used for the management of the electro-hydraulic actuators, the electric motor and the battery storage system. The hardware and the software architectures are presented, underlining the automated operations designed to increase the safety, the maneuverability and the predictability of the vehicle. The advantages of the use of control electronics is the increasing operability of the vehicle by supervising the available stored energy and the predicted consumption of energy, the fast and remote assistance in case of operational failure using online diagnose and the operation optimization by selecting the best load profile for the cutter and for the paddles. The results of this research are the validation of the proposed hardware and software architectures used for the control of an electro-hydraulic vehicle and the feasibility of using radio communication and remote diagnose for vehicle control. Full article
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13 pages, 5403 KiB  
Article
Theoretical and Experimental Studies of a Switched Inertance Hydraulic System in a Four-Port High-Speed Switching Valve Configuration
by Min Pan, Andrew Plummer and Abdullah El Agha
Energies 2017, 10(6), 780; https://doi.org/10.3390/en10060780 - 6 Jun 2017
Cited by 21 | Viewed by 6118
Abstract
The switched inertance hydraulic system (SIHS) is a novel high-bandwidth and energy-efficient digital device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. An SIHS can provide an efficient [...] Read more.
The switched inertance hydraulic system (SIHS) is a novel high-bandwidth and energy-efficient digital device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. An SIHS can provide an efficient step-up or step-down of pressure or flow rate by using a digital control signal. In this article, analytical models of an SIHS in a four-port high-speed switching valve configuration are proposed, and the system dynamics and performance are investigated theoretically and experimentally. The flow responses, system characteristics, and power consumption can be predicted effectively and accurately by using the proposed models, which were validated by comparing with experiments and with numerical simulation. The four-port configuration is compared with the three-port configuration, and it is concluded that the former one is less efficient for valves of the same size, but provides a bi-direction control capability. As bi-direction control is a common requirement, this constitutes an important contribution to the development of efficient digital hydraulics. Full article
(This article belongs to the Special Issue Energy Efficiency and Controllability of Fluid Power Systems)
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