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学者姓名：黄若辰
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Abstract ：
Eddy-current (EC) testing is one of the contactless nondestructive testing techniques for the physical property measurement (e.g., thickness, electrical conductivity, and magnetic permeability) of steel plates in various industrial applications. In this study, an estimation method of plate thickness and permeability is proposed using the triple-frequency coil inductance with probe lift-off. The functional relationship between the plate properties, probe lift-off, and characteristics of coil inductance is indicated by the simplified analytical model, which is employed for the initial guesses of optimization. The proposed method can decrease the influence of the local minimum on property estimation. Numerical simulations and experiments have been performed to evaluate the proposed method with various plate properties and probe lift-off. Compared with the estimation results without the appropriate initial guesses, the proposed method is more robust and accurate for various cases, with a relative estimation error smaller than 8%.
Keyword ：
Analytical model Analytical model Analytical models Analytical models eddy-current (EC) testing eddy-current (EC) testing Estimation Estimation Frequency estimation Frequency estimation Inductance Inductance Mathematical models Mathematical models Permeability Permeability permeability measurement permeability measurement probe lift-off probe lift-off Probes Probes thickness measurement thickness measurement
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| GB/T 7714 | Xia, Zihan , Huang, Ruochen , Lu, Mingyang et al. Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2024 , 73 . |
| MLA | Xia, Zihan et al. "Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 73 (2024) . |
| APA | Xia, Zihan , Huang, Ruochen , Lu, Mingyang , Yin, Wuliang . Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2024 , 73 . |
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Eddy -current (EC) testing is one of the contactless nondestructive testing techniques that has been frequently applied to evaluate the defects on metallic objects. In this paper, an estimation method of defect depth on metallic plates is proposed based on the approximate analytical model. An EC coil array sensitive to various defect orientation is designed to scan the plate surface. The independent inductance from various ferritecore coil pairs can be found by the approximate analytical model. The influence of defect on measurements, including depth and edges, is regarded as the variation of probe lift-off in the tested region, defined as the equivalent lift-off. Based on the approximate analytical model, when defect edges have relatively smaller influence, the defect depth on the plate surface can be approximately obtained by estimating the equivalent probe lift-off through optimization. In numerical simulations and experiments, the proposed method is evaluated by testing the aluminum and stainless -steel plates with cracks by the coil array. The reconstructed equivalent lift-off distribution closely relates to the position and dimensions of defects on plates.
Keyword ：
Analytical model Analytical model Defect testing Defect testing Eddy current testing Eddy current testing Metallic plate testing Metallic plate testing
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| GB/T 7714 | Xia, Zihan , Huang, Ruochen , Shao, Yuchun et al. Estimation of defect depth on plates by eddy-current coil array [J]. | SENSORS AND ACTUATORS A-PHYSICAL , 2024 , 369 . |
| MLA | Xia, Zihan et al. "Estimation of defect depth on plates by eddy-current coil array" . | SENSORS AND ACTUATORS A-PHYSICAL 369 (2024) . |
| APA | Xia, Zihan , Huang, Ruochen , Shao, Yuchun , Bai, Xue , Yin, Wuliang . Estimation of defect depth on plates by eddy-current coil array . | SENSORS AND ACTUATORS A-PHYSICAL , 2024 , 369 . |
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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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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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The use of renewable energy for power generation and hydrogen production can improve the economic efficiency of multi-energy coupled microgrids, as well as the capacity of renewable energy to be consumed. In this paper, a deep interactive dispatching strategy for multi-energy coupled microgrid is proposed. Firstly, a multi-energy coupled microgrid structure is built, incorporating an electric hydrogen production system on the load side. An economic analysis of the deep interaction of multiple energy sources is then conducted based on electricity to hydrogen energy consumption for dispatching decisions and supporting strategies. Simulation is also carried out for the verification of the deep interactive dispatching model. It proves the rationality and feasibility of the proposed model for scheduling energy use within a multi-energy system. © 2023 IEEE.
Keyword ：
Economic analysis Economic analysis Electric load dispatching Electric load dispatching Energy utilization Energy utilization Hydrogen production Hydrogen production
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| GB/T 7714 | Zhan, Yixiong , Yang, Yubin , Huang, Ruochen et al. A Deep Interactive Dispatching Strategy for Multi-energy Coupled Microgrid [C] . 2023 : 2054-2058 . |
| MLA | Zhan, Yixiong et al. "A Deep Interactive Dispatching Strategy for Multi-energy Coupled Microgrid" . (2023) : 2054-2058 . |
| APA | Zhan, Yixiong , Yang, Yubin , Huang, Ruochen , Yu, Xinhong , Dan, Zhimin , Lin, Qiongbin . A Deep Interactive Dispatching Strategy for Multi-energy Coupled Microgrid . (2023) : 2054-2058 . |
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Eddy-current testing technique has been extensively explored for estimating the electromagnetic property of steel plates in various industrial applications. In this article, a physics-guided deep learning (DL) method is proposed to estimate the permeability of plate in high thickness with probe liftoff. A simplified analytical model is derived, which realises the single to multiple frequency inductance transformation and calculates the related physical properties of the measurement configuration. A constant is found, which is a fundamental coefficient describing the first-order nature of the sensor response to a plate and it is insensitive to plate properties and probe dimensions. The nonlinear mapping from physical information, derived from the simplified analytical model, to plate permeability is constructed by the DL model based on the modified ResNet18-1D. Numerical simulations and experiments have been performed to evaluate the proposed method for permeability estimation with various plate materials and probe liftoff. The method achieves real-time accurate estimation of plate permeability with a relative error lower than 3%.
Keyword ：
Analytical model Analytical model eddy current testing eddy current testing electromagnetic sensing electromagnetic sensing permeability measurement permeability measurement
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| GB/T 7714 | Xia, Zihan , Meng, Tian , Huang, Ruochen et al. Physics-Guided Deep Learning for Plate Permeability Estimation With Single to Multiple Frequency Transformation of Eddy-Current Testing [J]. | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 20 (4) : 6109-6118 . |
| MLA | Xia, Zihan et al. "Physics-Guided Deep Learning for Plate Permeability Estimation With Single to Multiple Frequency Transformation of Eddy-Current Testing" . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 20 . 4 (2023) : 6109-6118 . |
| APA | Xia, Zihan , Meng, Tian , Huang, Ruochen , Fletcher, Adam , Shao, Yuchun , Lu, Mingyang et al. Physics-Guided Deep Learning for Plate Permeability Estimation With Single to Multiple Frequency Transformation of Eddy-Current Testing . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 20 (4) , 6109-6118 . |
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This article proposed a method to simultaneously estimate the permeability, conductivity, thickness, and lift-off of metallic plates using sweep frequency eddy current measurement combined with machine learning (ML). The whole processing was mainly divided into characteristic extractions and a data-driven machine learning model. According to the classical Dodd and Deeds analytical solution, the characteristic value of mutual inductance signal related to metallic plate parameters is extracted based on theoretical derivation. The parameters of metallic plates are inherently coupled together; thus, the parameters of metallic plates cannot be directly and accurately obtained using only characteristic information. In this article, the machine learning modeling combining the extracted features is established to achieve decoupling and high-precision inversion. The data required for model training comes from the customized fast finite element method (FEM) solver and analytical solution. While the experiment data act as the test set to verify the performance of the proposed method. The results show the proposed method can be applied to accurately estimate the parameters of metallic plates, and the relative errors of inverted parameters are within 3.5%.
Keyword ：
Characteristic extraction Characteristic extraction machine learning (ML) model machine learning (ML) model parameters decoupling parameters decoupling sweep frequency eddy current measurement sweep frequency eddy current measurement
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| GB/T 7714 | Huang, Pu , Bao, Zhenyu , Huang, Ruochen et al. Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
| MLA | Huang, Pu et al. "Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 72 (2023) . |
| APA | Huang, Pu , Bao, Zhenyu , Huang, Ruochen , Jia, Jieshu , Liu, Kuanyao , Yu, Xing et al. Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
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Steel microstructure determines the mechanical properties of steel such as hardness and tensile strength. To monitor steel microstructure evolution during thermal processing such as hot rolling, online measurement of microstructure is vital to steel quality control. Previous studies using multifrequency eddy-current testing to monitor the change in electromagnetic properties and infer steel microstructures have achieved remarkable success, yet due to the high-frequency excitation signal, the inspected thickness of steel microstructures is constrained on the surface due to the skin effect. This study introduces the pulsed eddy-current (PEC) method to characterize the electromagnetic property profile along the depth of thick steel plates. The low-frequency square-wave signal enables PEC to reflect multilayer characteristics in a single measurement with good penetration ability. An explicit analytical equation for calculating the time-domain PEC response is derived for the first time which shows advantages in terms of speed and gaining in-depth physical insights. A custom PEC system has been designed and built with a tunnel magneto-resistance (TMR) sensor as the receiver. Theoretical and numerical analyses are performed. A time-domain intersection point on the Tau curve is found to be a useful indication of the properties of a planar structure. Experimental results on layered planar structures of various electromagnetic properties are analyzed and validated.
Keyword ：
hardware development hardware development Index Terms- Analytical model Index Terms- Analytical model pulsed eddy-current (PEC) testing pulsed eddy-current (PEC) testing steel microstructure steel microstructure thickness inspection thickness inspection
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| GB/T 7714 | Xiong, Lei , Xia, Zihan , Huang, Ruochen et al. Through Thickness Inspection of Layered Magnetic Material Using Pulsed Eddy-Current Testing [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
| MLA | Xiong, Lei et al. "Through Thickness Inspection of Layered Magnetic Material Using Pulsed Eddy-Current Testing" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 72 (2023) . |
| APA | Xiong, Lei , Xia, Zihan , Huang, Ruochen , Wang, Shupei , Zheng, Xinnan , Shen, Jialong et al. Through Thickness Inspection of Layered Magnetic Material Using Pulsed Eddy-Current Testing . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
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To reduce the current stress in the whole operating area and improve the dynamic performance switching between different operating points of the dual-active-bridge (DAB) converter, a bidirectional power control (BPC-GCSO) scheme based on the global current stress optimization is proposed in this paper. The global current stress optimal solution (GCSO) set is first derived for the DAB converter, which enables the DAB converter to realize the minimum current stress at any operating point. Then, a virtual direct power control method is introduced based on the GCSO scheme and a bidirectional power control (BPC) strategy is designed. To validate the proposed scheme, a simulation experimental environment is built on the MATLAB/Simulink platform, and the simulation results prove the feasibility of the proposed method. © 2023 IEEE.
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| GB/T 7714 | Gong, Xingyang , Fu, Xiaofeng , Cai, Fenghuang et al. A Bidirectional Power Control Scheme Based on Global Current Stress Optimization for Dual Active Bridge DC-DC Converters [C] . 2023 : 865-870 . |
| MLA | Gong, Xingyang et al. "A Bidirectional Power Control Scheme Based on Global Current Stress Optimization for Dual Active Bridge DC-DC Converters" . (2023) : 865-870 . |
| APA | Gong, Xingyang , Fu, Xiaofeng , Cai, Fenghuang , Huang, Ruochen . A Bidirectional Power Control Scheme Based on Global Current Stress Optimization for Dual Active Bridge DC-DC Converters . (2023) : 865-870 . |
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