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学者姓名：林琼斌
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Abstract ：
Eddy current testing (ECT), as a noncontact and nondestructive testing (NDT) technology, has been widely applied to various industrial fields for pipeline defect detection. In this article, a combined defect parameter estimation method using a novel arc-shaped differential probe with orthogonal receivers is proposed to detect circumferential defects in pipelines. The sensitivity between coils is analyzed to optimize the probe parameters. The scanning signals of defects on the complex plane are characterized by the shell curves (SCs), and a Lissajous curve (LC) model is employed for curve fitting. It is observed that a monotonous relationship holds between fitting parameters and defect dimensions. From the fit scanning curve, the defect depth and length can be estimated by employing the K-nearest neighbors (KNNs) algorithm. Experiments have been conducted to verify the proposed defect parameter estimation method by testing aluminum pipelines with cracks. The experimental results show that the estimation of defect parameters achieves an average accuracy (ACC) of more than 96.78% for various dimensions of cracks.
Keyword ：
Coils Coils Conductivity Conductivity Defect detection Defect detection Defect testing Defect testing eddy-current testing (ECT) eddy-current testing (ECT) estimation method estimation method Feature extraction Feature extraction Permeability Permeability pipeline inspection pipeline inspection Pipelines Pipelines Probes Probes Receivers Receivers Sensitivity Sensitivity sensor design sensor design Testing Testing
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| GB/T 7714 | Zeng, Huade , Huang, Ruochen , Xia, Zihan et al. A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Zeng, Huade et al. "A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Zeng, Huade , Huang, Ruochen , Xia, Zihan , Lin, Qiongbin , Yin, Wuliang . A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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Battery state-of-health (SOH) estimation is an effective approach to evaluate battery reliability and reduce maintenance costs for battery-based backup power supply systems. This paper proposes a novel SOH estimation method for batteries, which only uses the response characteristics of load surges and is, therefore, non-destructive to the estimated battery and its system. The discrete wavelet transform (DWT) method based on multi-resolution analysis (MRA) is used for wavelet energy features extraction, and the fuzzy cerebellar model neural network (FCMNN) is introduced to design the battery SOH estimator. The response voltage signals to load surges are used in the training and detection process of the FCMNN. Compared to conventional methods, the proposed method only exploits characteristics of online response signals to the inrush currents rather than injecting interference signals into the battery. The effectiveness of the proposed method is validated by detailed simulation analysis and experiments.
Keyword ：
dynamical battery state-of-health estimation dynamical battery state-of-health estimation fuzzy cerebellar model neural network fuzzy cerebellar model neural network non-invasive detection non-invasive detection response characteristic of load surges response characteristic of load surges wavelet transform wavelet transform
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| GB/T 7714 | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen . Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges [J]. | ENERGIES , 2024 , 17 (3) . |
| MLA | Fan, Yuhang et al. "Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges" . | ENERGIES 17 . 3 (2024) . |
| APA | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen . Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges . | ENERGIES , 2024 , 17 (3) . |
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Advanced wind power prediction technique plays an essential role in the stable operation of the grid with largescale grid integration of wind power. Most research focuses on distance-based static classification where the subjective nature of initial center selection increases the uncertainty of the prediction. And the data classification on a daily basis neglects the potentially significant climate changes at smaller time scales. To address these issues, the improved snake optimization-long short-term memory (ISO-LSTM) model with Gaussian mixture model (GMM) clustering is proposed to forecast wind power from an adaptive perspective. By exploiting the merits of the probabilistic classification, the K-means optimized GMM clustering enables an appropriate feature modelling for substantial climate changes at smaller time scales. Then the ISO algorithm exhibits higher search accuracy and is better suited for finding hyperparameter combinations for LSTM neural networks. The data from the National Aeronautics and Space Administration (NASA) of the US is used to validate the effectiveness of the proposed method. Compared to the traditional K-means clustering, the K-means optimized GMM clustering has increased accuracy by 2.63 %. Simultaneously, with the adoption of the enhanced ISO algorithm, the accuracy further increases by 7.27 %. Different existing models have also been tested; it shows that the proposed model demonstrates higher prediction accuracy.
Keyword ：
Gaussian mixture model Gaussian mixture model Improved snake optimization Improved snake optimization K -means algorithm K -means algorithm Long short-term memory network Long short-term memory network Probabilistic classification Probabilistic classification
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| GB/T 7714 | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin et al. Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
| MLA | Zhou, Yu et al. "Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 157 (2024) . |
| APA | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin , Chai, Qinqin , Wang, Wu . Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
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Bi-directional DC-AC converters are widely used in the field of electric vehicle-to-grid. However, the inductance of the grid-side interface filter is affected by the length of the grid connection and the power level, which presents nonlinear characteristics. This poses challenges for high-performance grid waveform control. In this paper, a modeling method for bi-directional DC-AC grid-connected converters based on type-II T-S fuzzy models is proposed, and the corresponding type-II T-S fuzzy control strategy is designed to address the parameter uncertainty and non-linearity issues. Simulation results show that type-II T-S fuzzy control offers superior control performance and better current waveform quality compared to type-I T-S fuzzy control under uncertainty parameter conditions. The effectiveness of the proposed strategy is further validated through a 1 kW prototype of a bi-directional DC-AC converter.
Keyword ：
DC-AC inverters DC-AC inverters dual-buck bi-directional inverter dual-buck bi-directional inverter model building model building nonlinear inductance nonlinear inductance type-II T-S fuzzy model type-II T-S fuzzy model
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| GB/T 7714 | Chen, Zhihua , Huang, Ruochen , Lin, Qiongbin et al. Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter [J]. | ELECTRONICS , 2024 , 13 (9) . |
| MLA | Chen, Zhihua et al. "Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter" . | ELECTRONICS 13 . 9 (2024) . |
| APA | Chen, Zhihua , Huang, Ruochen , Lin, Qiongbin , Yu, Xinhong , Dan, Zhimin . Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter . | ELECTRONICS , 2024 , 13 (9) . |
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The optimal capacity of energy storage facilities is a cornerstone for the investment and low-carbon operation of integrated energy systems (IESs). However, the intermittence of renewable energy and the different operating characteristics of facilities present challenges to IES configuration. Therefore, a two-stage decision-making framework is developed to optimize the capacity of facilities for six schemes comprised of battery energy storage systems and hydrogen energy storage systems. The objectives considered are to minimize the levelized cost of electricity (LCOE), power abandonment rate (PAR) and maximize self-sufficiency rate (SSR) simultaneously. In the first stage, each scheme is solved using NSGA-II. In the second stage, the weights of objective function are determined by entropy weight method, while the optimal individual is selected from the Pareto solutions by the technique for order preference by similarity to ideal solution approach. Life models of battery, fuel cell, and electrolyzer are introduced to quantify device replacement costs. Meanwhile, carbon trading mechanisms and time-of-use tariffs are considered to assess environmental and economic benefits. The results show that the hydrogen-electric coupling scheme demonstrated superior performance, with LCOE, SSR, and PAR of 0.6416 & YEN;/kWh, 48.9 %, and 1.96 %, respectively, and the hydrogen storage tank is closely related to LCOE and PAR.
Keyword ：
Battery energy storage system Battery energy storage system Configuration optimization Configuration optimization Entropy weight method Entropy weight method Hydrogen energy storage system Hydrogen energy storage system ideal solution ideal solution Non-dominated sorting genetic algorithm-II Non-dominated sorting genetic algorithm-II Technique for order preference by similarity to Technique for order preference by similarity to
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| GB/T 7714 | Lin, Liangguang , Ou, Kai , Lin, Qiongbin et al. Two-stage multi-strategy decision-making framework for capacity configuration optimization of grid-connected PV/battery/hydrogen integrated energy system [J]. | JOURNAL OF ENERGY STORAGE , 2024 , 97 . |
| MLA | Lin, Liangguang et al. "Two-stage multi-strategy decision-making framework for capacity configuration optimization of grid-connected PV/battery/hydrogen integrated energy system" . | JOURNAL OF ENERGY STORAGE 97 (2024) . |
| APA | Lin, Liangguang , Ou, Kai , Lin, Qiongbin , Xing, Jianwu , Wang, Ya-Xiong . Two-stage multi-strategy decision-making framework for capacity configuration optimization of grid-connected PV/battery/hydrogen integrated energy system . | JOURNAL OF ENERGY STORAGE , 2024 , 97 . |
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When high power density of electric vehicle (EV) charging load connected to the microgrids in expressway service areas, the stability of the system is affected. Long-distance transmission or transformer expansion can be costly and difficult to maintain, therefore, this research proposed a dynamic capacity expansion method. Combined with the energy storage system, through the most economic operation, aiming for strong microgrid independence and minimum power fluctuation, a multi-objective model is established to pursue the optimal dispatch scheme by integration of power assets using the Nondominated Sorting Genetic Algorithm II (NSGA-II). To address insufficient diversity for evolutionary operators and slow speed of the original NSGA-II, improvements are made based on the initial dataset optimization and differential evolution. Verified by the simulating results, the proposed method dynamically expands the capacity of the microgrid, thus mitigates the impact of heavy charging load. © 2024 IEEE.
Keyword ：
Electric load dispatching Electric load dispatching Microgrids Microgrids Multiobjective optimization Multiobjective optimization
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| GB/T 7714 | Gao, Sheng , Wang, Zheng , Shen, Yu-Long et al. Dynamic Capacity Expansion Strategy for Expressway Service Area Based on I-NSGA-II Algorithm [C] . 2024 : 324-329 . |
| MLA | Gao, Sheng et al. "Dynamic Capacity Expansion Strategy for Expressway Service Area Based on I-NSGA-II Algorithm" . (2024) : 324-329 . |
| APA | Gao, Sheng , Wang, Zheng , Shen, Yu-Long , Lin, Qiongbin . Dynamic Capacity Expansion Strategy for Expressway Service Area Based on I-NSGA-II Algorithm . (2024) : 324-329 . |
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The material quality of metallic cylinders including microstructure is reflected in their physical properties. Eddy current testing techniques play an important role in the measurement of metallic cylinder measurement. In this paper, a cylinder radius and permeability estimation method is proposed based on the combined analytical and optimisation method. The Dodd and Deeds analytical model has been first simplified, which suggests an approximate linear relationship between the cylinder radius, permeability and coil inductance. Based on the proposed relation, the pre-estimated radius and permeability are used as the initial guess for the modified Newton-Raphson algorithm to solve the least squares problem between the measured and calculated coil inductance spectra. This method avoids the local minimum issue that occurs otherwise, to some extent. The effectiveness of the proposed method has been evaluated by numerical simulations and experiments, which indicates that fast estimation can be achieved with high accuracy.
Keyword ：
Cylinder measurement Cylinder measurement Eddy current testing Eddy current testing Electromagnetic sensing Electromagnetic sensing
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| GB/T 7714 | Huang, Ruochen , Xia, Zihan , Lu, Mingyang et al. Model-based cylinder radius and permeability estimation using eddy current testing [J]. | MEASUREMENT , 2023 , 220 . |
| MLA | Huang, Ruochen et al. "Model-based cylinder radius and permeability estimation using eddy current testing" . | MEASUREMENT 220 (2023) . |
| APA | Huang, Ruochen , Xia, Zihan , Lu, Mingyang , Zhang, Zili , Lin, Qiongbin , Yin, Wuliang . Model-based cylinder radius and permeability estimation using eddy current testing . | MEASUREMENT , 2023 , 220 . |
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Accurate estimation of the state of health (SOH) of lithium-ion batteries is an important guarantee to ensure safe and reliable operation of lithium-ion battery systems. However, the complex aging mechanism inside the battery makes it difficult to measure the battery SOH directly. In this paper, a SOH estimation method based on a novel dual-stage attention-based recurrent neural network (DARNN) and health feature (HF) extraction from time varying charging process is proposed. Firstly, the constant current charging time, the maximum temperature time, the isochronous voltage difference, and the isochronous current were extracted as lithium-ion battery HFs, and their correlations with SOH are verified by spearman correlation coefficient. Secondly, the DARNN is proposed to capture the time-dependent and temporal features of the input sequence and to accurately predict SOH. Finally, the proposed estimation method is validated on the NASA battery dataset. The results show that the method can accurately estimate SOH for lithium-ion batteries. The mean square error and the mean absolute percentage error of the method are <0.5 %.
Keyword ：
Dual -stage attention -based recurrent neural Dual -stage attention -based recurrent neural Lithium-ion battery Lithium-ion battery network network State of health State of health
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| GB/T 7714 | Hong, Jiangnan , Chen, Yucheng , Chai, Qinqin et al. State-of-health estimation of lithium-ion batteries using a novel dual-stage attention mechanism based recurrent neural network [J]. | JOURNAL OF ENERGY STORAGE , 2023 , 72 . |
| MLA | Hong, Jiangnan et al. "State-of-health estimation of lithium-ion batteries using a novel dual-stage attention mechanism based recurrent neural network" . | JOURNAL OF ENERGY STORAGE 72 (2023) . |
| APA | Hong, Jiangnan , Chen, Yucheng , Chai, Qinqin , Lin, Qiongbin , Wang, Wu . State-of-health estimation of lithium-ion batteries using a novel dual-stage attention mechanism based recurrent neural network . | JOURNAL OF ENERGY STORAGE , 2023 , 72 . |
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The wide use of Li-ion batteries in various industrial applications has led to a focus on their health status. This paper proposes a novel fast SOH estimation method by combining the response characteristics and the Genetic Algorithm-Extreme Learning Machine (GA-ELM) model. Based on the theoretical manipulations, the dynamic response due to the inrush current has been derived and shows that the response curve due to the inrush current contains information related to the battery SOH. Since there is no explicit relation, GA-ELM with the wavelet transform method is used to extract effective dynamic response voltage data features to estimate SOH without manually adjusting parameters. Experiment results validate that the fast estimation of the battery SOH can be achieved by using the proposed method with a resolution accuracy of 3% in any state of charge (SOC). Compared with other models by the crossover analysis, the method is efficient for feature extraction while providing better performance. This paper aims to highlight the use of load surges response characteristics-to estimate SOH with no additional sensors. It shows the application has a good prospect in the electric vehicles (EVs). © 2023 IEEE.
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| GB/T 7714 | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen et al. Fast Battery SOH Estimation Based on Response Characteristics of Load Surges and GA-ELM [C] . 2023 . |
| MLA | Fan, Yuhang et al. "Fast Battery SOH Estimation Based on Response Characteristics of Load Surges and GA-ELM" . (2023) . |
| APA | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen , Lin, Yufeng , Wang, Jia , Huang, Qingrong . Fast Battery SOH Estimation Based on Response Characteristics of Load Surges and GA-ELM . (2023) . |
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During the planning and construction process of a multi-energy coupled microgrid, various risks may be encountered. Conducting a reasonable risk analysis and evaluation for its planning and construction can help avoid unnecessary losses. This article first provides a detailed analysis of the risks faced in the planning and construction of multi-energy coupled microgrids and establishes a risk assessment index system. Then, it proposes an evaluation method for the planning risks of multi-energy coupled microgrids. This method calculates the weights of risk indicators using the analytic hierarchy process (AHP). Via the risk matrix method combined with Delphi method, the comprehensive risk value can be calculated for the planning and construction of multi-energy coupled microgrids. With the proposed method, comprehensive risk assessments are performed on two case studies to demonstrate the feasibility of the method. By comparing the risk indicator scoring results of the two planned cases, the characteristics of multi-energy coupled microgrids are revealed. © 2023 IEEE.
Keyword ：
Analytic hierarchy process Analytic hierarchy process Decision making Decision making Risk analysis Risk analysis Risk assessment Risk assessment
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| GB/T 7714 | Yang, Yubin , Lin, Qiongbin , Huang, Ruochen et al. Risk Analysis and Assessment for Multi-Energy Coupled Microgrid Planning [C] . 2023 . |
| MLA | Yang, Yubin et al. "Risk Analysis and Assessment for Multi-Energy Coupled Microgrid Planning" . (2023) . |
| APA | Yang, Yubin , Lin, Qiongbin , Huang, Ruochen , Li, Yi , Liu, Jie , Liu, Changsha . Risk Analysis and Assessment for Multi-Energy Coupled Microgrid Planning . (2023) . |
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