Records with Subject: Process Control
Showing records 1 to 25 of 3434. [First] Page: 1 2 3 4 5 Last
Improved Time-Varying BLF-Based Tracking Control of a Position-Constrained Robot
Tan Zhang, Jinzhong Zhang
February 10, 2024 (v1)
Keywords: adaptive control, barrier Lyapunov function, constraint control, robot, tracking control
In this work, one improved symmetric time-variant logarithmic barrier, Lyapunov function (BLF), is developed for the first time to handle the state constraint problem of nonlinear systems. It is universal in the sense that the improved barrier function is a general one that can be used not only in systems with constrained requirements but also in systems without constrained requirements, without altering the designed controller. First of all, the n-link robotic system is transformed into a kind of multi-input and multi-output (MIMO) system. Then, a trajectory tracking control scheme is designed by combining the improved time-variant logarithmic BLF with the disturbance observer to solve the problems of model uncertainty and position constraint for the robotic system. We give that under the proposed controller, all the robotic system’s error vectors can trend to the equilibrium point asymptotically while the constraint conditions on the position are always met. Finally, the effectivenes... [more]
Anomaly Recognition, Diagnosis and Prediction of Massive Data Flow Based on Time-GAN and DBSCAN for Power Dispatching Automation System
Wenjie Liu, Pengfei Lei, Dong Xu, Xiaorong Zhu
February 10, 2024 (v1)
Keywords: DBSCAN, fault diagnosis, fault prediction, supervised learning, Time-GAN
Existing power anomaly detection is mainly based on analyzing static offline data. But this method takes a long time and has low identification accuracy when detecting timing and frequency anomalies, since this method requires offline screening, classification and preprocessing of the collected data, which is very laborious. Anomaly detection with supervised learning requires a large amount of abnormal data and cannot detect unknown anomalies. So, this paper innovatively proposes the idea of applying Time-series Generative Adversarial Networks (Time-GAN) in a dispatching automation system for the identification, diagnosis and prediction of massive data flow anomalies. First of all, regarding the problem of insufficient abnormal data, we use Time-GAN to generate a large number of reliable datasets for training fault diagnosis models. In addition, Time-GAN can ameliorate the imbalance between various types of data. Secondly, unsupervised learning methods such as Density-Based Spatial Clu... [more]
Novel Control Technology for Reducing Output Power Harmonics of Standalone Solar Power Generation Systems
Hwa-Dong Liu, Jhen-Ting Lin, Xin-Wen Lin, Chang-Hua Lin, Shoeb-Azam Farooqui
February 10, 2024 (v1)
Keywords: adjustable frequency and duty cycle, cake sweetness maximum power point tracking, standalone solar power system, total voltage harmonic distortion
This study presents a standalone solar power system that incorporates a photovoltaic (PV) module, a boost converter, an H-bridge inverter, a low-pass filter (LPF), and a microcontroller unit (MCU). A novel cake sweetness maximum power point tracking (CS MPPT) algorithm and adjustable frequency and duty cycle (AFDC) control strategy has been proposed and efficiently applied to the solar power system for optimizing the system efficiency and output power quality. The experimental results show that the proposed CS MPPT algorithm achieves an efficiency of 99% under both the uniform irradiance conditions (UIC) and partial shading conditions (PSC). Subsequently, the AFDC control strategy is applied to the H-bridge inverter which improves the output AC voltage and AC current and thereby improving the power quality. The system ensures a stable 110 Vrms/60 Hz AC output voltage with only 2% total voltage harmonic distortion of voltage (THDv), and produces a high-quality output voltage with reduce... [more]
Applying a Novel Image Recognition Curve-Fitting Control Strategy Combined with a Cloud Monitoring Technique into an Electric Self-Driving Vehicle (ESDV) to Improve Its Operation Efficiency
Hwa-Dong Liu, Ping-Jui Lin, Shan-Xun Lai, Chang-Hua Lin, Shoeb-Azam Farooqui
February 10, 2024 (v1)
Keywords: cloud monitoring technique, electric self-driving vehicle, Hough line detection method, image recognition curve-fitting control strategy
This study aims to develop an image recognition curve-fitting (IRCF) control strategy integrated with a cloud monitoring technique for application in electric self-driving vehicles (ESDVs) to improve their operation efficiency. The study focuses on an electric vehicle designed to reduce the carbon emissions and promote sustainability. The main camera, combined with the IRCF control strategy, was used to control the ESDV to enhance its operational efficiency. The proposed ESDV employs a pair of cameras to capture images and transmit them to the cloud-based web monitoring platform in real time. This allows the researchers to adjust the control parameters and promptly remove the road obstacles. The ESDV is equipped with a horn, two ultrasonic sensors, and an LED display, which can instantly detect the obstacles ahead of and behind the vehicle. When there are obstacles on the road, the vehicle will automatically stop, and the LED display will provide a visual representation of the obstacle... [more]
Mechanism and Main Control Factors of CO2 Huff and Puff to Enhance Oil Recovery in Chang 7 Shale Oil Reservoir of Ordos Basin
Tong Wang, Bo Xu, Yatong Chen, Jian Wang
February 10, 2024 (v1)
Keywords: Chang 7 shale oil reservoir, CO2 huff-n-puff, enhance oil recovery (EOR), heterogeneity
The Chang 7 shale oil reservoir has low natural energy and is both tight and highly heterogeneous, resulting in significant remaining oil after depletion development. CO2 huff and puff (huff-n-puff) is an effective way to take over from depletion development. Numerous scholars have studied and analyzed the CO2 huff-n-puff mechanism and parameters based on laboratory core sample huff-n-puff experiments. However, experimental procedures are not comprehensive, leading to more general studies of some mechanisms, and existing CO2 huff-n-puff experiments struggle to reflect the effect of actual reservoir heterogeneity due to the limited length of the experimental core samples. In this paper, CO2 huff-n-puff laboratory experiments were performed on short (about 5 cm) and long (about 100 cm) core samples from the Chang 7 shale oil reservoir, and the microscopic pore fluid utilization in the short samples was investigated using a nuclear magnetic resonance (NMR) technique. We then analyzed and... [more]
Design and Simulation of a Feedback Controller for an Active Suspension System: A Simplified Approach
Vasileios Provatas, Dimitris Ipsakis
February 10, 2024 (v1)
Keywords: active car suspension, controller performance criteria, model-based controller, modeling and simulation, optimal PID, PID controller, tuning methods
The concept of controlling vehicle comfort is a common problem that is faced in most under- and postgraduate courses in Engineering Schools. The aim of this study is to provide a simplified approach for the feedback control design and simulation of active suspension systems, which are applied in vehicles. Firstly, the mathematical model of an active suspension system (a quarter model of a car) which consists of a passive spring, a passive damper and an actuator is provided. In this study, we chose to design and compare the following controllers: (a) conventional P, PI and PID controllers that were tuned through two conventional methodologies (Ziegler−Nichols and Tyreus−Luyben); (b) an optimal PID controller that was tuned with a genetic algorithm (GA) optimization framework in terms of the minimization of certain performance criteria and (c) an internal model controller (IMC) based on the process transfer function. The controllers’ performance was assessed in a series of realistic scen... [more]
An Integrated Control Approach for Shifting Process of Single-Axis Parallel Hybrid Electric Vehicle with a Multi-Speed AMT Gearbox
Cheng Huang, Changqing Du
February 10, 2024 (v1)
Keywords: integrated multistage control, multi-speed AMT gearbox, parallel hybrid electric vehicle, robust control, shifting process
When a single-axis parallel hybrid electric vehicle (HEV) equipped with a multi-speed AMT gearbox is in its shifting process, the superposition of dynamic characteristics of multiple power sources and the intervention and withdrawal of AMT transmissions can easily cause significant vehicle longitudinal jerk. To achieve rapid and smooth output changes during the shifting process, this paper proposes an integrated multi-stage robust shifting control method for a single-axis parallel hybrid electric vehicles with a multi-speed AMT gearbox. First, models of key driveline components are constructed, and the shifting process is divided into five stages to provide a clear description of the control problem. Subsequently, we reproduce an integrated multistage robust control method to achieve favorable switching performance and control robustness under external disturbances. We propose a data-driven model predictive control strategy based on additional constraints in the torque unloading and re... [more]
Study on Flow Characteristics of a Single Blade Breakage Fault in a Centrifugal Pump
Huairui Li, Qian Huang, Sihan Li, Yunpeng Li, Qiang Fu, Rongsheng Zhu
February 10, 2024 (v1)
Keywords: blade breakage, centrifugal pump, fault diagnosis, flow characteristics, pressure pulsation
The precise identification of faults in centrifugal pumps is crucial for ensuring their safe and stable operation, given their significance as vital industrial equipment. This article aims to rigorously examine and analyze the flow characteristics of centrifugal pumps under two specific conditions: normal blade operation and a single blade breakage fault. Through systematic comparison and in-depth study, this article sheds light on distinguishing flow patterns exhibited by these pumps under both normal and fault scenarios. Utilizing validated numerical simulation methods, a thorough analysis is conducted to explore the flow condition and energy characteristics of the impeller channel following the breakage of a single blade. Additionally, the article investigates changes in the pressure pulsation characteristics of the pump volute as a result. The numerical simulation results reveal that the head of the centrifugal pump decreases at all flow points when a single blade breaks. However,... [more]
The Hydration Mechanisms of Co-Stabilization Saline Soils by Using Multiple Solid Wastes
Bolan Lei, Pingfeng Fu, Xiaoli Wang, Wen Ni, Siqi Zhang, Xiancong Wang, Jinjin Shi, Miao Xu
January 12, 2024 (v1)
Keywords: curing mechanism, industrial solid waste, saline soil, soil stabilizer
In this paper, an approach was employed to fabricate a curing agent using multiple solid wastes. To determine the optimal mixing ratio, orthogonal and compaction tests were initially conducted, followed by a comparative analysis of the excitation effects elicited by sodium silicate and NaOH. Remarkably, sodium silicate demonstrated superior suitability as an activator. The final composition was established as follows: 4% sodium silicate, 26% carbide slag, 25% granulated blast furnace (GBF) slag, 35% coal fly ash, and 10% flue gas desulphurization (FGD) gypsum. Under controlled conditions of 20% of curing agent content, the unconfined compressive strength of the solidified soil at 7 d attained 1.54 MPa, thereby satisfying the rigorous construction requirements for highways across all levels. XRD and SEM-EDS analyses revealed that the principal hydration products in the system consisted of ettringite, Friedel’s salt, and C-S-H gel. These products enveloped the soil particles, with ettrin... [more]
Classification and Evaluation of Tight Sandstone Reservoirs Based on MK-SVM
Xuefei Lu, Xin Xing, Kelai Hu, Bin Zhou
January 12, 2024 (v1)
Keywords: high-pressure mercury compression, lasso dimensionality reduction, MK-SVM model, reservoir classification, tight sandstone reservoirs
It is difficult to determine the main microscopic factors controlling reservoir quality due to the strong microscopic heterogeneity of tight sandstone reservoirs, which also makes it difficult to distinguish dominant reservoirs. At the same time, there are fewer experimental samples available, and data collected from relevant research are thus worth paying attention to. In this study, based on the experimental results of high-pressure mercury injection of 25 rock samples from Chang 6 reservoir in the Wuqi area, Lasso dimensionality reduction was used to reduce the dimensionality of 14 characteristic parameters to 6, which characterize the microscopic pore structure, while a combination of different kernel functions was used to construct the multi-kernel function of the multi-kernel model to be determined. A multi-kernel support vector machine (MK-SVM) model was established for unsupervised learning of microscopic pore structure characteristic parameters that affect reservoir quality. B... [more]
Active Steering Controller for Driven Independently Rotating Wheelset Vehicles Based on Deep Reinforcement Learning
Zhenggang Lu, Juyao Wei, Zehan Wang
January 12, 2024 (v1)
Keywords: active steering, Ape-X DDPG algorithm, deep reinforcement learning, independently rotating wheelsets
This paper proposes an active steering controller for Driven Independently Rotating Wheelset (DIRW) vehicles based on deep reinforcement learning (DRL). For the two-axle railway vehicles equipped with Independently Rotating Wheelsets (IRWs), each wheel connected to a wheel-side motor, the Ape-X DDPG controller, an enhanced version of the Deep Deterministic Policy Gradient (DDPG) algorithm, is adopted. Incorporating Distributed Prioritized Experience Replay (DPER), Ape-X DDPG trains neural network function approximators to obtain a data-driven DIRW active steering controller. This controller is utilized to control the input torque of each wheel, aiming to improve the steering capability of IRWs. Simulation results indicate that compared to the existing model-based H∞ control algorithm and data-driven DDPG control algorithm, the Ape-X DDPG active steering controller demonstrates better curving steering performance and centering ability in straight tracks across different running conditio... [more]
Design and Research of a Field Bus Control System Laboratory for Metal Mining, Beneficiation and Metallurgy
Siyuan Wang, Jiugang Lei, Shan Hu, Guxiu Tang, Zhen Chen, Weiwei Yang, Yufeng Liu, Guofan Zhang
January 12, 2024 (v1)
Keywords: communication network, DCS, fieldbus, industrial process control, laboratory construction, mining and metallurgy, nonferrous metal
Fieldbus control systems play a pivotal role in industries such as mining, beneficiation, and metallurgy, facilitating precise process control. However, diverse process conditions and applications often lead to challenges during system implementation. The prevalence of process control projects underscores the need for dedicated control system laboratories to address these problems. Our research delves into the complexities of process control systems, focusing on mainstream brands such as Siemens, Rockwell, and Emerson, involving analysis of network architectures, software, and hardware configurations. Through rigorous testing of real equipment systems, we uncover prevalent issues in practical control system applications. These findings guide the resolution of technical challenges faced in project control, concurrently enhancing the design and debugging prowess of engineering professionals. We also anticipate the trajectory of intelligent manufacturing, embracing collaborative manufactu... [more]
Distribution of Hyperpycnal Flow Related Sandstone Deposits in a Lacustrine Shale System: Implication for Hydrocarbon Reservoir Exploration in the Chang 7 Oil Member of the Triassic Yanchang Formation, Ordos Basin, China
Pengyu Sun, Lixia Zhao, Qian Ma, Wei Zhang, Shun Zhang, Xiao Li, Juan Wen, Luxing Dou, Zhigang Wen
January 12, 2024 (v1)
Keywords: gravity flow, hyperpycnal flow, Ordos Basin, Triassic, Yanchang Formation
Gravity flow deposits are important hydrocarbon reservoirs in deep lacustrine deposits. Previous studies have paid much attention to the hydrocarbon reservoirs in those intrabasinal classic turbidite deposits. However, relatively little is known about the distribution of oil reservoirs in those extrabasinal hyperpycnal flow deposits. With the help of cores and wireline logging data, the present study undertakes a description and interpretation of subsurface shale oil reservoirs in the deep lake deposits in Chang 7 member, Yanchang Formation, Ordos Basin. Parallel bedded fine sandstone (Sh), massive bedded fine sandstone (Sm), massive bedded fine sandstone with mud clasts (Smg), deformed bedded siltstone (Fd), wave-lenticular bedded siltstone (Fh) and black shale (M) were found and interpreted in those deep lake deposits. The deposits were interpreted as hyperpycnal flow deposits which developed in channel, levee and deep lacustrine facies. The development of the Chang 7 sand body incre... [more]
An Electro-Hydraulic-Load-Sensitive System on the Basis of Torque Open-Loop Control
YanWen Li, Cong Yu, Gexin Chen, Mingkun Yang, Yuhang Zhang, Fei Wang
January 12, 2024 (v1)
Keywords: electric construction machinery, load sensitive, pressure control, torque control
Facing the development trend of electrification of construction machinery, in view of the drawbacks of the existing electro-hydraulic-load-sensitive system in terms of dynamic characteristics and usage of energy, based on the drive source of a servo motor-driven quantitative pump, an electro-hydraulic-load-sensitive system on the basis of torque open-loop control was proposed. Firstly, the working principle of the system was introduced and the system’s operating characteristics and energy consumption characteristics were theoretically analyzed. Secondly, in order to balance the system’s energy usage and maneuverability, a control strategy with a variable pressure margin was designed. Meanwhile, in order to solve the problem that the hydraulic pump’s mechanical efficiency causes system pressure control deviation, a torque compensation method based on offline data and speed prediction was proposed. Finally, simulation and testing were used to confirm the viability of the control strategy... [more]
A Timestep-Adaptive-Diffusion-Model-Oriented Unsupervised Detection Method for Fabric Surface Defects
Shancheng Tang, Zicheng Jin, Ying Zhang, Jianhui Lu, Heng Li, Jiqing Yang
January 12, 2024 (v1)
Keywords: computer vision, deep-learning-based unsupervised detection method, denoising diffusion probabilistic model, fabric defect detection, image repair
Defect detection is crucial in quality control for fabric production. Deep-learning-based unsupervised reconstruction methods have been recognized universally to address the scarcity of fabric defect samples, high costs of labeling, and insufficient prior knowledge. However, these methods are subject to several weaknesses in reconstructing defect images into defect-free images with high quality, like image blurring, defect residue, and texture inconsistency, resulting in false detection and missed detection. Therefore, this article proposes an unsupervised detection method for fabric surface defects oriented to the timestep adaptive diffusion model. Firstly, the Simplex Noise−Denoising Diffusion Probabilistic Model (SN-DDPM) is constructed to recursively optimize the distribution of the posterior latent vector, thus gradually approaching the probability distribution of surface features of the defect-free samples through multiple iterative diffusions. Meanwhile, the timestep adaptive mo... [more]
Encrypted Model Predictive Control of a Nonlinear Chemical Process Network
Yash A. Kadakia, Atharva Suryavanshi, Aisha Alnajdi, Fahim Abdullah, Panagiotis D. Christofides
January 5, 2024 (v1)
Keywords: cybersecurity, encrypted control, Model Predictive Control, process control, quantization, semi-homomorphic encryption
This work focuses on developing and applying Encrypted Lyapunov-based Model Predictive Control (LMPC) in a nonlinear chemical process network for Ethylbenzene production. The network, governed by a nonlinear dynamic model, comprises two continuously stirred tank reactors that are connected in series and is simulated using Aspen Plus Dynamics. For enhancing system cybersecurity, the Paillier cryptosystem is employed for encryption−decryption operations in the communication channels between the sensor−controller and controller−actuator, establishing a secure network infrastructure. Cryptosystems generally require integer inputs, necessitating a quantization parameter d, for quantization of real-valued signals. We utilize the quantization parameter to quantize process measurements and control inputs before encryption. Through closed-loop simulations under the encrypted LMPC scheme, where the LMPC uses a first-principles nonlinear dynamical model, we examine the effect of the quantization... [more]
Experimental Study on HMCVT Adaptive Control of Cotton Pickers
Huajun Chen, Wenqing Cai, Meng Wang, Xiangdong Ni, Yongqiang Zhao, Wenlong Pan, Yuangang Lin
January 5, 2024 (v1)
Keywords: adaptive control, cotton picker, HMCVT, test
Aiming at the stability of the output speed and the poor adaptability of the transmission system during the operation of a cotton picker, a control strategy of hydro-mechanical continuously variable transmission (HMCVT) for cotton pickers based on gray prediction and fuzzy PID is proposed. Firstly, the hardware and software of the existing hydraulic mechanical coupling transmission test-bed of cotton pickers are designed, and the HMCVT human-computer interaction measurement and control system is built by using LABVIEW 2020 software. Then, combined with the transmission theory, the control strategy and gray prediction model are designed. Finally, the continuity test, transmission efficiency test, and adaptive control verification test are carried out. The results show that as the input speed increases, the peak time of the pump motor output speed is prolonged, while the overall speed regulation process is smoother, and the output speed process of the HMCVT system is continuous. As the d... [more]
Research on Path Tracking and Yaw Stability Coordination Control Strategy for Four-Wheel Independent Drive Electric Trucks
Feng Gao, Fengkui Zhao, Yong Zhang
January 5, 2024 (v1)
Keywords: four-wheel independent drive, fractional order sliding mode control, linear quadratic regulator, path tracking, yaw stability control
Achieving accurate path tracking and vehicle stability control for four-wheel independent drive electric trucks under complex driving conditions, such as high speed and low adhesion, remains a major challenge in current research. Poor coordination control may cause the vehicle to deviate from its intended path and become unstable. To address this issue, this article proposes a coordinated control strategy consisting of a three-layer control framework. In the upper layer controller design, establish a linear quadratic regulator (LQR) path tracking controller to ensure precise steering control by eliminating steady-state errors through feedforward control. The middle layer controller utilizes the fractional order sliding mode control (FOSMC) yaw moment controller to calculate the additional yaw moment based on the steering angle of the upper input, utilizing the error of yaw rate and sideslip angle as the state variable. To collectively optimize the control system, establish a coordinate... [more]
Adomian Decomposition, Firing Change Process Analysis and Synchronous Control of Fractional-Order Hindmarsh−Rose Neurons in Electromagnetic Field
Tengfei Lei, Haiyan Fu, Hongyan Zang, Lili Huang, Wenqiang Sun
November 30, 2023 (v1)
Keywords: firing, fractional-order HR neurons, ISI bifurcation diagram, synchronous control
In this paper, based on integer-order Hindmarsh−Rose (HR) neurons under an electric field, the fractional-order model is constructed, and the nonlinear term is decomposed by the Adomian decomposition method, and the numerical solution of the system is obtained. The firing behavior of the neuron model is analyzed by using a phase diagram, interspike interval (ISI) bifurcation diagram, sample entropy (SE) complexity, and largest Lyapunov exponent (LLE). Based on the sliding mode control theory, a chaos synchronization controller of the system is designed. Matlab simulation results show that the controller is realizable and effective, and also has the characteristic of fast response, which provides a reference for the control and application of a memristor neural network system.
Investigating the Mechanism of Continuous−Discrete Coupled Destabilization of Roadway-Surrounding Rocks in Weakly Cemented Strata under Varying Levels of Moisture Content
Lihui Sun, Zhixin Jiang, Yaxin Long, Qingfeng He, Haiyang Zhang
November 30, 2023 (v1)
Keywords: anchorage failure mechanism, continuous–discrete, destabilization mechanism, moisture content, weakly cemented rock
This study examines frequent disasters, including large-scale deformation and collapse, caused by underground mining in weakly cemented strata in Western China. The weakly cemented rock’s unique characteristics, including low strength and easy disintegration, demonstrate a different damage pattern than that traditionally seen in the central and eastern regions. Using Fast Lagrangian Analysis of Continua-Particle Flow Code (FLAC2D-PFC2D) coupling, we model the strata, focusing on the 3-1 coal seam roadway at Hongqinghe mine. This study investigates the damage−rupture−destabilization progression in the peripheral rock under varying levels of moisture content. Our findings indicate that a water content of ω = 5.5% is the threshold for roadway damage, and moisture content 5.5% abruptly increases cracks and shifts the rock’s force chain, causing significant deformation and affecting the ceiling the most. Moreover, higher levels of moisture content weaken the anchor solid’s performance, with... [more]
Discrete-Element-Method-Based Determination of Particle-Level Inputs for the Continuum Theory of Flows with Moderately Cohesive Particles
Kevin M. Kellogg, Peiyuan Liu, Christine M. Hrenya
November 30, 2023 (v1)
Keywords: cohesion, continuum theory, discrete element method, particle flows
In this work, the cohesion-specific inputs for a recent continuum theory for cohesive particles are estimated for moderately cohesive particles that form larger agglomerates via discrete element method (DEM) simulations of an oscillating shear flow. In prior work, these inputs (critical velocities of agglomeration and breakage and collision cylinder diameters) were determined for lightly cohesive particles via the DEM of simple shear flow—i.e., a system dominated by singlets and doublets. Here, the DEM is again used to extract the continuum theory inputs, as experimental measurements are infeasible (i.e., collisions between particles of a diameter of <100 μm). However, simulations of simple shear flow are no longer feasible since the rate of agglomeration grows uncontrollably at higher cohesion levels. Instead, oscillating shear flow DEM simulations are used here to circumvent this issue, allowing for the continuum theory inputs of larger agglomerate sizes to be determined efficient... [more]
Decentralized Control Strategy for Participation of Electric Vehicles in Distribution Voltage Control
Xin Fang, Juan Li, Yubo Yuan, Xiaodong Yuan
November 30, 2023 (v1)
Keywords: decentralized voltage control, electric vehicle, electric vehicle charging station, rolling optimization
With the accelerating transportation electrification, increasing numbers of electric vehicles (EVs) are connected to distribution networks via electric vehicle charging stations (EVCSs). Due to the uncertain charging behaviors of EV users, concentrated high-power EV charging during peak hours can result in significant undervoltage issues, affecting the regular operation of distribution networks and having detrimental effects on regular EV charging. Conventional EV charging scheduling methods are conducted in a centralized way, requiring extensive investment in communication infrastructure and intensive computing power. Accordingly, this paper proposes a novel decentralized voltage control scheme with the participation of EVs and EVCSs. The proposed control scheme first divides the distribution network into clusters based on a modified modularity index. Then, it applies the rolling optimization-based control of the EVs and EVCSs within each cluster to solve the regional voltage problems... [more]
Multi-Sized Granular Suspension Transport Modeling for the Control of Lost Circulation and Formation Damage in Fractured Oil and Gas Reservoirs
Jinhua Liu, Yayun Zhang, Dujie Zhang, Fan Li, Hexiang Zhou, Chengyuan Xu, Weiji Wang
November 30, 2023 (v1)
Keywords: fractured reservoir, gas and geothermal resources, multi-sized granule retention, oil, permeability damage, production enhancement, suspended granule transport
Transport and retention of multi-sized suspended granules are common phenomena in fracture media of oil, gas and geothermal reservoirs. It can lead to severe permeability damage and productivity decline, which has a significant impact on the efficient development of underground resources. However, the granule transport and retention behaviors remain not well understood and quantified. The novel stochastic model is proposed for the multi-sized suspended granule transport in naturally fractured reservoirs accounting for granule retention and fracture clogging kinetics. A percolation fracture network is proposed considering fracture connectivity evolution during suspended granule transport. Granule retention and fracture clogging dynamics equations are proposed to account for incomplete fracture clogging by retained granules. The microscale stochastic model is allowed for upscaling to predict the multi-sized granule transport behavior in naturally fractured reservoirs. The model solution... [more]
An Improved Fault Diagnosis Approach for Pumps Based on Neural Networks with Improved Adaptive Activation Function
Fangfang Zhang, Yebin Li, Dongri Shan, Yuanhong Liu, Fengying Ma
November 30, 2023 (v1)
Keywords: adaptive activation function, deep learning, fault diagnosis, pumping unit
Due to the complex underground environment, pumping machines are prone to producing numerous failures. The indicator diagrams of faults are similar to a certain degree, which produces indistinguishable samples. As the samples increase, manual diagnosis becomes difficult, which decreases the accuracy of fault diagnosis. To accurately and quickly judge the fault type, we propose an improved adaptive activation function and apply it to five types of neural networks. The adaptive activation function improves the negative semi-axis slope of the Rectifying linear unit activation function by combining the gated channel conversion unit to improve the performance of the deep learning model. The proposed adaptive activation function is compared to the traditional activation function through the fault diagnosis data set and the public data set. The results show that the activation function has better nonlinearity and can improve the generalization performance of the deep learning model and the ac... [more]
Review of Recent Advances in the Drive Method of Hydraulic Control Valve
Yanchao Li, Ruichuan Li, Junru Yang, Xiaodong Yu, Jikang Xu
November 30, 2023 (v1)
Keywords: displacement accuracy, drive performance, hydraulic control valve, response speed, spool drive
Hydraulic control valves are widely used in industrial production, agricultural equipment, construction machinery, and other large power equipment for controlling the pressure and flow of fluids in hydraulic systems. The driving method has a significant impact on the response and control accuracy of hydraulic valves. This paper reviews the driving methods of spools from five aspects: solenoid drive, material expansion drive, motor drive, hydraulic valve drive, and another drive. It summarizes the various schemes currently available for spool drive and analyzes each of them. After optimizing the driving method of the valve core, the control accuracy can reach 3%, and the minimum response time is 7 ms. According to the characteristics of the different drive methods, the differences between them are compared, the advantages and disadvantages of each drive method are analyzed, and the application scenarios for each drive method are identified. Solutions to the drawbacks of the existing dri... [more]
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