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Performance analyses of a novel finned parabolic trough receiver with inner tube for solar cascade heat collection

science China(Technological sciences) 2023年第5期66卷 1417-1434页

作者： LIU Peng REN TingTing GE YanLin LIU Wei CHEN LinGen Institute of Thermal Science and Power Engineering Wuhan Institute of TechnologyWuhan430205China School of Energy and Power Engineering Huazhong University of Science and TechnologyWuhan430074China School of Mechanical&Electrical Engineering Wuhan Institute of TechnologyWuhan430205China

Designing highly-efficient parabolic trough receiver(PTR)contributes to promoting solar thermal utilization and alleviating energy crisis and environmental problems.A novel finned PTR with inner tube(FPTR-IT),which can provide different grades of thermal energy with two heat transfer fluids(oil and water),is designed to improve thermal *** this FPTR-IT,an inner tube and straight fins are employed to respectively lessen heat loss at upper and lower parts of the *** on the design,a numerical model is developed to investigate its *** with other PTRs indicate that the FPTR-IT can combine the advantages of PTR with inner tube and finned PTR and obtain the best ***,performance evaluation under broad ranges of direct normal irradiances(300–1000 W/m^(2)),flow rates(50–250 L/min)and inlet temperatures(400–600 K)of oil as well as flow rates(3.6–10 L/min)and inlet temperatures(298.15–318.15 K)of water is *** with conventional PTR,heat loss is reduced by 20.7%–63.2%and total efficiency is improved by 0.03%–4.27%.Furthermore,the proportions of heat gains for water and oil are located in 8.3%–73.9%and-12.0%–64.3%,while their temperature gains are located in 11.6–37.9 K and-1.2–19.6 K,***,the proposed FPTR-IT may have a promising application prospect in remote arid areas or islands to provide different grades of heat for electricity and freshwater production.

关键词： finned parabolic trough receiver inner tube heat loss total efficiency solar cascade heat collection performance analyses

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Prediction and validation of parameters of multi-axis soil remediation equipment based on machine learning algorithms

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Particuology 2025年第3期98卷 41-55页

作者： Zhipeng Wang Yuhang Jiang Yaonan Zhu Feng Ma Youzhao Wang Chaoyue Zhao Xu Li Tong Zhu Institute of Process Equipment and Environmental Engineering School of Mechanical Engineering and AutomationNortheastern UniversityShenyang110819China The School of Engineering The University of TokyoTokyo113-8656Japan School of Environment and Resources Taiyuan University of Science and TechnologyTaiyuan030024China

To facilitate the recycling of polluted soils,the development of innovative multi-axial soil remediation machinery is essential for achieving a uniform blend of soil with remediation *** mean level of the steepest climb test was set using the mean level derived from the orthogonal test,and then the range of optimum values was determined based on the results of the steepest climb test,and the upper and lower bound intervals of the response surface test were set *** most optimal model is identified by applying machine learning algorithms to the response surface *** results show that the Decision Tree model outperforms Random Forest,SVR,KNN and XG Boost in terms of accuracy and stability in predicting dual *** of the decision tree model yields the following optimal parameter settings:homogenisation time of 1.7 s,homogenisation spacing of 181 mm,crusher spacing of 156 mm,and speed of 113 *** the final test prototype,the error rates of the machine learning prediction models were 3.01% and 3.88% *** experimental data confirms that the prediction accuracy reaches a satisfactory level after applying machine learning to optimise the *** study will provide a reference for the design and optimisation of new in situ multi-axial soil remediation devices.

关键词： Contaminated soil Mixing homogeneity Machine learning Steepest climb test Nine-axis

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t-SNVAE: Deep Probabilistic Learning With Local and Global Structures for Industrial Process Monitoring

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第6期6卷 1603-1613页

作者： Huang, Jian Liu, Zizhuo Yang, Xu Liu, Yupeng Lv, Zhaomin Peng, Kaixiang Ersoy, Okan K. University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Science and Technology Beijing Shunde Innovation School Foshan528399 China Shanghai University of Engineering Science School of Urban Railway Transportation Shanghai201620 China Purdue University Electrical and Computer Engineering West LafayetteIN47907 United States

Variational autoencoder (VAE) is a generative deep learning (DL) model with a probabilistic structure, which makes it tolerant to process uncertainties and more suitable for process monitoring. However, the probabilistic model may disrupt the topological structure of data and lead to the loss of neighborhood information. To address this issue, a process monitoring approach based on t-distributed stochastic neighbor variational autoencoder (t-SNVAE) is proposed to capture probabilistic features that elucidate both local and global structures within the raw data. Specifically, the distances between neighboring data points are transformed into joint probabilities by using t-SN embedding. Through minimizing the Kullback–Leibler divergence of joint probabilities between the original data and the reconstructed data, VAE learns Gaussian features containing both local and global neighborhood information. Finally, monitoring statistics are constructed for monitoring. The efficiency of the proposed approach is verified on a multiphase flow facility and a waste-water treatment process. © 2020 IEEE.

关键词： Embeddings

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Neural-Network-Based Adaptive Finite-Time Control for a Two-Degree-of-Freedom Helicopter System With an Event-Triggering Mechanism

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1754-1765页

作者： Zhijia Zhao Jian Zhang Shouyan Chen Wei He Keum-Shik Hong IEEE the School of Mechanical and Electrical Engineering Guangzhou UniversityGuangzhou 510006China the School of Intelligence Science and Technology the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Mechanical Engineering Pusan National UniversityBusan 46241South Korea the Institute for Future School of AutomationQingdao UniversityQingdao 266071China

Helicopter systems present numerous benefits over fixed-wing aircraft in several fields of *** control schemes for improving the tracking accuracy of such systems is *** paper proposes a neural-network(NN)-based adaptive finite-time control for a two-degree-of-freedom helicopter *** particular,a radial basis function NN is adopted to solve uncertainty in the helicopter ***,an event-triggering mechanism(ETM)with a switching threshold is proposed to alleviate the communication burden on the *** proposing an adaptive parameter,a bounded estimation,and a smooth function approach,the effect of network measurement errors is effectively compensated for while simultaneously avoiding the Zeno ***,the developed adaptive finite-time control technique based on an NN guarantees finitetime convergence of the tracking error,thus enhancing the control accuracy of the *** addition,the Lyapunov direct method demonstrates that the closed-loop system is semiglobally finite-time ***,simulation and experimental results show the effectiveness of the control strategy.

关键词： Adaptive neural-network control event-triggering mechanism(ETM) finite time two-degree-of-freedom helicopter

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Optimal zero-crossing group selection method of the absolute gravimeter based on improved auto-regressive moving average model

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Chinese Physics B 2023年第11期32卷 347-354页

作者：牟宗磊韩笑胡若 College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China National Institute of Metrology China Beijing 100029China

An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.

关键词： absolute gravimeter laser interference fringe Fourier series fitting honey badger algorithm mul-tiplicative auto-regressive moving average(MARMA)model

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Photothermal hygroscopic hydrogel for simultaneous generation of clean water and electricity

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science China(Technological sciences) 2023年第10期66卷 2958-2967页

作者： REN TingTing HUANG Lu XIE ShangZhen CHEN GuoPeng LIU Peng CHEN LinGen Institute of Thermal Science and Power Engineering Wuhan Institute of TechnologyWuhan 430205China School of Mechanical&Electrical Engineering Wuhan Institute of TechnologyWuhan 430205China

Harvesting water from the air using adsorbents and obtaining fresh water by solar-driven desorption is considered as one of the most effective ways to solve the freshwater crisis in arid and desert *** on a simple and low-cost photothermal hygroscopic hydrogel,a new strategy is proposed to boost solar energy efficiency by coupling solar-driven atmospheric water harvesting technology with thermoelectric power generation technology in this *** hygroscopic hydrogel ink PAM-CaCl_(2)is prepared by in situ polymerization using Acrylamide as monomer,Ammonium persulfate as thermal initiator and CaCl_(2)as hygroscopic *** the day,the photothermal hygroscopic hydrogel absorbs solar energy and evaporates its own internal water to obtain fresh ***,the residual waste heat is utilized to power the thermoelectric panel,which produces electricity based on Seebeck *** night,the hydrogel harvests water molecules in the air to achieve *** hybrid system can achieve a water production rate of 0.33 kg m^(-2)h^(-1)and an additional electrical energy gain of 124 mW m^(-2)at 1 kW m^(-2)solar *** model of the hybrid system is developed to understand the heat flow and thermoelectric generation *** results provide new insights into energy and freshwater replenishment options in arid or desert areas with abundant solar energy.

关键词： photothermal hygroscopic hydrogel atmospheric water harvesting solar steam generation thermoelectric power generation

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A Fault Diagnosis And Mechanism Identification Approach for Micro-short of Power Lithium Iron Phosphate Battery 3

A Fault Diagnosis And Mechanism Identification Approach for ...

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3rd New Energy and Energy Storage System Control Summit Forum, NEESSC 2023

作者： Wu, Chao Wang, Chao Lv, Shuyang Zhang, Kaixin Song, Yahao School of Electrical Engineering and Automation Institute of Science and Technology Henan Luoyang China

ISBN: (纸本)9798350309348

With the rapid development of power lithium-ion battery industry in recent years, its safety performance has gradually attracted widespread attention. This paper reports our research on micro-short fault of power lithium iron phosphate battery. Two different experiments which might induce micro-short were designed. According to the experiment results and external features of micro-short fault, a diagnostic approach based on module redundancy was proposed, which obtained the voltage correlation coefficient in serial module and temperature residual in parallel module to detect and locate the individual cell suffering micro-short in the module. Then the mechanism of micro-short fault was identified through variation tendency of incremental capacity curves. Post-mortem examination was carried out to validate the effectiveness of the proposed fault diagnosis and mechanism identification approach. ©2023 IEEE.

关键词： Failure analysis

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A Software Defect Prediction Method Using a Multivariate Heterogeneous Hybrid Deep Learning Algorithm

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Computers, Materials & Continua 2025年第2期82卷 3251-3279页

作者： Qi Fei Haojun Hu Guisheng Yin Zhian Sun College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China Information Technology Research Department Jiangsu Automation Research InstituteLianyungang222062China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen518055China

Software defect prediction plays a critical role in software development and quality assurance processes. Effective defect prediction enables testers to accurately prioritize testing efforts and enhance defect detection efficiency. Additionally, this technology provides developers with a means to quickly identify errors, thereby improving software robustness and overall quality. However, current research in software defect prediction often faces challenges, such as relying on a single data source or failing to adequately account for the characteristics of multiple coexisting data sources. This approach may overlook the differences and potential value of various data sources, affecting the accuracy and generalization performance of prediction results. To address this issue, this study proposes a multivariate heterogeneous hybrid deep learning algorithm for defect prediction (DP-MHHDL). Initially, Abstract Syntax Tree (AST), Code Dependency Network (CDN), and code static quality metrics are extracted from source code files and used as inputs to ensure data diversity. Subsequently, for the three types of heterogeneous data, the study employs a graph convolutional network optimization model based on adjacency and spatial topologies, a Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) hybrid neural network model, and a TabNet model to extract data features. These features are then concatenated and processed through a fully connected neural network for defect prediction. Finally, the proposed framework is evaluated using ten promise defect repository projects, and performance is assessed with three metrics: F1, Area under the curve (AUC), and Matthews correlation coefficient (MCC). The experimental results demonstrate that the proposed algorithm outperforms existing methods, offering a novel solution for software defect prediction.

关键词： Software defect prediction multiple heterogeneous data graph convolutional network models based on adjacency and spatial topologies CNN-BiLSTM TabNet

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Event-Triggered Extended Dissipative FTB for T-S Fuzzy Switched Systems With Mismatched Phenomena and Deception Attacks: A Multidomain Framework

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IEEE Transactions on Cybernetics 2024年第9期54卷 4928-4938页

作者： Chen, Haiyang Zong, Guangdeng Su, Shun-Feng Gao, Fangzheng Tiangong University School of Control Science and Engineering Tianjin300387 China Nanjing Institute of Technology School of Automation Jiangsu Collaborative Innovation Center for Smart Distribution Network Nanjing211167 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Nanjing Institute of Technology School of Automation Nanjing211167 China

This article investigates the extended dissipative finite-time boundedness (ED-FTB) problem for fuzzy switched systems under deception attacks. To improve the network resource efficiency, a multidomain probabilistic event-triggered mechanism (MDPETM) is proposed. The mode mismatched phenomenon is modeled based on the switching delay information between the controller mode and the system mode. To extract the true signal generated by the MDPETM, a virtual delay concept is developed. The constraint that the controller and the system must have the same premise variables is removed. Based on the MDPETM, mismatched fuzzy state feedback controllers are first devised which may not share the same modes with the system. Then, by establishing fuzzy basis and controller mode-dependent Lyapunov functionals, sufficient criteria free of nonlinear terms existing in the literature are derived, which ensure the ED-FTB of the closed-loop system under admissible delays and deception attacks. Finally, an application-oriented one-link robotic arm system is utilized to validate the theoretical results. © 2013 IEEE.

关键词： Controllers

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Multi-objective constructal design for quadrilateral heat generation body based on thermal-entransy theory and NSGA-Ⅱ

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science China(Technological sciences) 2024年第9期67卷 2777-2786页

作者： CHEN LinGen ZHU HongWei GE YanLin SHI ShuangShuang FENG HuiJun Institute of Thermal Science and Power Engineering Wuhan Institute of TechnologyWuhan 430205China Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment Wuhan 430205China School of Mechanical Electrical EngineeringWuhan Institute of TechnologyWuhan 430205China

Based on thermal-entransy theory, the multi-objective constructal design of quadrilateral heat generation body(HGB) with similar shapes of leaves is studied further. The relationship between the aspect ratio of quadrilateral HGB and average temperature difference based on thermal-entransy dissipation is compared with that between the aspect ratio of quadrilateral HGB and the maximum temperature difference(MTD). The relationship between a composite function, consisting of linear weighting sum of the average temperature difference and MTD, and aspect ratio is obtained, and the optimal aspect ratios under minimum composite function with different weighting coefficients are obtained. Using the NSGA-Ⅱ algorithm, the Pareto frontier containing a series of compromise results of average temperature difference and MTD is obtained, and optimization results are compared using the deviation index. There is no aspect ratio to make both MTD and average temperature difference reach the minimum, and the optimal aspect ratio under the minimum MTD is smaller than that under the minimum average temperature difference. The optimal aspect ratio is obtained by making the composite function reach the minimum, and the optimal aspect ratios obtained by minimizing the composite function with different weighting coefficients are different. Compared with the construct of the initial design, the value of the composite function with optimal construct decreases by 1.9%, and the aspect ratio of the quadrilateral HGB decreases by 9.1%. The average temperature difference with the optimal construct increases by 2.1%, and the MTD with the optimal construct decreases by 5.6%. The deviation index under multi-objective optimization is smaller than that under single-objective optimization, and the obtained construct has better comprehensive thermal conductivity. Compared with TOPSIS and LINMAP decision-making methods, the average temperature difference with composite function optimization increases by 0.5

关键词： thermal-entransy theory constructal theory heat conduction quadrilateral heat generation body composite function NSGA-Ⅱ

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