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学者姓名：缪希仁
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Abstract ：
In nuclear power plants (NPPs), ex-core neutron detectors are deployed around reactor cores and are essential for reactor stability, but their deterioration and malfunction can cause misperceptions and misdiagnoses. Existing fault detection seldom accounts for global spatial-temporal coupling relationships implied among overall detectors and uncertainty under transient operations. Thus, we propose a novel detector-oriented fault detection scheme called the global-fused dynamic detection (GFDD) model, established by the global spatial-temporal graph (GSTG), moving-global graph convolution (MGGC), and uncertainty-quantified dynamic detection (UQDD). To enrich informational sources and disperse faulty propagation, we specifically design the GSTG for characterizing the spatial-temporal relationships among overall detectors and the MGGC for efficiently capturing global high-level features, further generating multidetector reconstructed signals and residuals. Through calculating dynamic statistics and quantifying uncertainty under varying operating conditions, the UQDD identifies faulty detectors and corrects erroneous signals. Experiments on steady and transient states from a real-world NPP with simulated faults validate that the GFDD model outperforms various state-of-the-art methods with regard to signal reconstruction and fault detection.
Keyword ：
Circuit faults Circuit faults Detectors Detectors Ex-core neutron detector Ex-core neutron detector fault detection fault detection Fault detection Fault detection Inductors Inductors Load modeling Load modeling Monitoring Monitoring Neutrons Neutrons nuclear power plant (NPP) nuclear power plant (NPP) Power system dynamics Power system dynamics Sensor phenomena and characterization Sensor phenomena and characterization spatial-temporal model spatial-temporal model Uncertainty Uncertainty uncertainty quantization uncertainty quantization
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| GB/T 7714 | Lin, Weiqing , Miao, Xiren , Chen, Jing et al. Fault Detection for Ex-Core Neutron Detectors in Nuclear Power Plants Using Global-Fused Dynamic Detection Model [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Lin, Weiqing et al. "Fault Detection for Ex-Core Neutron Detectors in Nuclear Power Plants Using Global-Fused Dynamic Detection Model" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Lin, Weiqing , Miao, Xiren , Chen, Jing , Duan, Pengbin , Ye, Mingxin , Xu, Yong et al. Fault Detection for Ex-Core Neutron Detectors in Nuclear Power Plants Using Global-Fused Dynamic Detection Model . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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Artificial intelligence has potential for forecasting reactor conditions in the nuclear industry. Owing to economic and security concerns, a common method is to train data generated by simulators. However, achieving a satisfactory performance in practical applications is difficult because simulators imperfectly emulate reality. To bridge this gap, we propose a novel framework called simulation-to-reality domain adaptation (SRDA) for forecasting the operating parameters of nuclear reactors. The SRDA model employs a transformer-based feature extractor to capture dynamic characteristics and temporal dependencies. A parameter predictor with an improved logarithmic loss function is specifically designed to adapt to varying reactor powers. To fuse prior reactor knowledge from simulations with reality, the domain discriminator utilizes an adversarial strategy to ensure the learning of deep domain-invariant features, and the multiple kernel maximum mean discrepancy minimizes their discrepancies. Experiments on neutron fluxes and temperatures from a pressurized water reactor illustrate that the SRDA model surpasses various advanced methods in terms of predictive performance. This study is the first to use domain adaptation for real-world reactor prediction and presents a feasible solution for enhancing the transferability and generalizability of simulated data.
Keyword ：
Domain adaptation Domain adaptation Forecasting Forecasting Knowledge transfer Knowledge transfer Nuclear power plant (NPP) Nuclear power plant (NPP) Pressurized water reactor (PWR) Pressurized water reactor (PWR) Transformer Transformer
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| GB/T 7714 | Lin, Wei-Qing , Miao, Xi-Ren , Chen, Jing et al. Simulation-to-reality transferability framework for operating-parameter forecasting in nuclear reactors using domain adaptation [J]. | NUCLEAR SCIENCE AND TECHNIQUES , 2025 , 36 (5) . |
| MLA | Lin, Wei-Qing et al. "Simulation-to-reality transferability framework for operating-parameter forecasting in nuclear reactors using domain adaptation" . | NUCLEAR SCIENCE AND TECHNIQUES 36 . 5 (2025) . |
| APA | Lin, Wei-Qing , Miao, Xi-Ren , Chen, Jing , Ye, Ming-Xin , Xu, Yong , Jiang, Hao et al. Simulation-to-reality transferability framework for operating-parameter forecasting in nuclear reactors using domain adaptation . | NUCLEAR SCIENCE AND TECHNIQUES , 2025 , 36 (5) . |
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In the field of multi-style textile defect detection, a common challenge is the difficulty of adapting the inherent detection model to different styles of textile defects. Changes in the color or style of the textile often result in a decrease in the accuracy of defect detection. Relying solely on the model for fine-tuning inspections can lead to catastrophic forgetting, which significantly impacts the performance of the textile defect detector. To address these challenges, a multi-task correlation distillation (MTCD) anomaly detection method based on knowledge distillation and representative sampling is proposed to detect multi-style textile defects. To enable MTCD to detect defects of new-style textiles while maintaining the detection of old-style textiles, two main modules are introduced. The distillation adaptation module (DAM) explores the intra-feature correlation in the feature space of the target detector, allowing the student model to acquire knowledge of new-style textile defect detection while inheriting the teacher model's detection ability for old-style textile defects. The representative sampling module (RSM) stores representative knowledge of textile defect detection for old-style textiles, facilitating the transfer of knowledge learned from detecting new-style textile defect styles and maintaining the ability to detect defects in old-style textiles. This increases the detection accuracy of the student model for new-style textile defects. The results show that the proposed MTCD method can adapt to the new textile defect detection while maintaining the accuracy of the old textile defect detection and avoiding the problem of catastrophic forgetting. Furthermore, it offers a better balance between stability and plasticity, making it a promising solution for defect detection of multi-style textiles in industrial production environments. © 2024 SPIE and IS&T.
Keyword ：
Anomaly detection Anomaly detection Defects Defects Distillation Distillation Knowledge management Knowledge management Textiles Textiles
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| GB/T 7714 | Jiang, Hao , Huang, Shicong , Jin, Zhiheng et al. Multi-style textile defect detection using distillation adaptation and representative sampling [J]. | Journal of Electronic Imaging , 2024 , 33 (3) . |
| MLA | Jiang, Hao et al. "Multi-style textile defect detection using distillation adaptation and representative sampling" . | Journal of Electronic Imaging 33 . 3 (2024) . |
| APA | Jiang, Hao , Huang, Shicong , Jin, Zhiheng , Zhang, Minggui , Chen, Jing , Miao, Xiren . Multi-style textile defect detection using distillation adaptation and representative sampling . | Journal of Electronic Imaging , 2024 , 33 (3) . |
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Sensor faults in nuclear power plants (NPPs) have the potential to propagate negative impacts on system stability, leading to false alarms and accident misdiagnosis. Existing methods seldom concurrently consider complex spatial–temporal correlations among multi-type sensors in the primary circuit. This study presents a novel sensor fault detection and isolation scheme named the knowledge-guided spatial–temporal model (KGSTM), using the knowledge-guided recurrent unit (KGRU) and the concurrent detection strategy. To organically express part and whole interdependencies from inherent sensor layout, several graphs are specifically designed with pertinent domain knowledge. KGRU consists of the multi-graph convolutional network (MGCN) for fusing various spatial information and the gate recurrent unit (GRU) for extracting dynamic temporal features, further obtaining precise reconstructed signals and residuals. The concurrent detection strategy can explicitly quantify abnormal behaviors to detect and isolate faulty sensors by characterizing spatial–temporal signal variation. Numerical results on two real-world datasets from a pressurized water reactor (PWR) with simulated faults illustrate that the KGSTM has superior performance over various state-of-the-art methods in terms of signal reconstruction and fault detection. © 2024 Elsevier B.V.
Keyword ：
Convolution Convolution Domain Knowledge Domain Knowledge Fault detection Fault detection Nuclear energy Nuclear energy Nuclear fuels Nuclear fuels Nuclear power plants Nuclear power plants Numerical methods Numerical methods Pressurized water reactors Pressurized water reactors Signal reconstruction Signal reconstruction System stability System stability
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| GB/T 7714 | Lin, Weiqing , Miao, Xiren , Chen, Jing et al. Fault detection and isolation for multi-type sensors in nuclear power plants via a knowledge-guided spatial–temporal model [J]. | Knowledge-Based Systems , 2024 , 300 . |
| MLA | Lin, Weiqing et al. "Fault detection and isolation for multi-type sensors in nuclear power plants via a knowledge-guided spatial–temporal model" . | Knowledge-Based Systems 300 (2024) . |
| APA | Lin, Weiqing , Miao, Xiren , Chen, Jing , Ye, Mingxin , Xu, Yong , Liu, Xinyu et al. Fault detection and isolation for multi-type sensors in nuclear power plants via a knowledge-guided spatial–temporal model . | Knowledge-Based Systems , 2024 , 300 . |
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Safety monitoring of power operations in power stations is crucial for preventing accidents and ensuring stable power supply. However, conventional methods such as wearable devices and video surveillance have limitations such as high cost, dependence on light, and visual blind spots. WiFi-based human pose estimation is a suitable method for monitoring power operations due to its low cost, device-free, and robustness to various illumination conditions. In this paper, a novel Channel State Information (CSI)-based pose estimation framework, namely PowerSkel, is developed to address these challenges. PowerSkel utilizes self-developed CSI sensors to form a mutual sensing network and constructs a CSI acquisition scheme specialized for power scenarios. It significantly reduces the deployment cost and complexity compared to the existing solutions. To reduce interference with CSI in the electricity scenario, a sparse adaptive filtering algorithm is designed to preprocess the CSI. CKDformer, a knowledge distillation network based on collaborative learning and self-attention, is proposed to extract the features from CSI and establish the mapping relationship between CSI and keypoints. The experiments are conducted in a real-world power station, and the results show that the PowerSkel achieves high performance with a PCK@50 of 96.27%, and realizes a significant visualization on pose estimation, even in dark environments. Our work provides a novel low-cost and high-precision pose estimation solution for power operation. IEEE
Keyword ：
channel state information channel state information deep learning deep learning Electric power operation safety Electric power operation safety Feature extraction Feature extraction human pose estimation human pose estimation Monitoring Monitoring Pose estimation Pose estimation Power generation Power generation Safety Safety Sensors Sensors WiFi sensing WiFi sensing Wireless fidelity Wireless fidelity
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| GB/T 7714 | Yin, C. , Miao, X. , Chen, J. et al. PowerSkel: A Device-Free Framework Using CSI Signal for Human Skeleton Estimation in Power Station [J]. | IEEE Internet of Things Journal , 2024 , 11 (11) : 1-1 . |
| MLA | Yin, C. et al. "PowerSkel: A Device-Free Framework Using CSI Signal for Human Skeleton Estimation in Power Station" . | IEEE Internet of Things Journal 11 . 11 (2024) : 1-1 . |
| APA | Yin, C. , Miao, X. , Chen, J. , Jiang, H. , Yang, J. , Zhou, Y. et al. PowerSkel: A Device-Free Framework Using CSI Signal for Human Skeleton Estimation in Power Station . | IEEE Internet of Things Journal , 2024 , 11 (11) , 1-1 . |
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In the optimization design of the electromagnetic repulsion mechanism in finite element simulation, there are problems of high computational cost and long optimization time. To shorten the development cycle of the prototype and improve the efficiency of optimization, an optimization algorithm based on the Hybrid Infill Criterion and Kriging Surrogate Model (HIC-KSM) is proposed by organically combining the Expected Improvement (EI) infill criterion and the Pareto front infill criterion to make full use of the performance of parallel computation and to accelerate the convergence speed of the algorithm. The proposed algorithm is compared with the other optimization algorithms, the optimization results of five multi-objective test functions are compared to verify the efficiency of the proposed algorithm, and the algorithm is applied to the parameter optimization of the electromagnetic repulsion mechanism. © 2024 Published under licence by IOP Publishing Ltd.
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| GB/T 7714 | Xie, H. , Miao, X. . Optimal design of electromagnetic repulsion mechanism based on hybrid infill criterion and kriging surrogate model [未知]. |
| MLA | Xie, H. et al. "Optimal design of electromagnetic repulsion mechanism based on hybrid infill criterion and kriging surrogate model" [未知]. |
| APA | Xie, H. , Miao, X. . Optimal design of electromagnetic repulsion mechanism based on hybrid infill criterion and kriging surrogate model [未知]. |
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Due to the limitation of a single short-circuit detection feature, the short-circuit protection method of a low-voltage AC system based on the over-current principle has been unable to meet the requirements of operation protection under complex working conditions. With the availability of flexible technologies such as distributed photovoltaic and energy storage, low-voltage protection technology has faced new hurdles. Therefore, a node-autonomous fast short circuit protection method for distributed photovoltaic low-voltage AC systems is proposed. Firstly, the characteristics of the branch state are constructed using the instantaneous amplitudes of short-circuit current and voltage, and the early detection technique of short-circuit state is investigated. Secondly, the polarity information of the short-circuit current in each branch of the same node is introduced, and the short circuit branch protection decision mechanism based on the direction correlation identification of the short-circuit current is designed. Finally, the protection experiment of the low voltage physical experiment system and its simulation model are carried out. The experimental results show that the short circuit of both the traditional and photovoltaic branches can be detected within 0.5 ms. The protection response ranges between different nodes are reasonably matched, and for the short circuit at the near end of the outlet of the same node, whether the protection is triggered can be accurately determine in each branch within 1 ms of the short circuit, thus achieving selective protection. The protection method does not malfunction under the disturbance of various source load operating conditions. The research results have high theoretical and engineering value. © 2024 Power System Technology Press. All rights reserved.
Keyword ：
distributed photovoltaic distributed photovoltaic early detection of short circuit status early detection of short circuit status low-voltage system low-voltage system protection decision mechanism protection decision mechanism short circuit fault short circuit fault
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| GB/T 7714 | Zhuang, S. , Miao, X. , Guo, M. . Fast Short-circuit Protection Method for Low-voltage AC System With Distributed Photovoltaic; [含分布式光伏低压交流系统短路快速保护方法] [J]. | Power System Technology , 2024 , 48 (12) : 5138-5148 . |
| MLA | Zhuang, S. et al. "Fast Short-circuit Protection Method for Low-voltage AC System With Distributed Photovoltaic; [含分布式光伏低压交流系统短路快速保护方法]" . | Power System Technology 48 . 12 (2024) : 5138-5148 . |
| APA | Zhuang, S. , Miao, X. , Guo, M. . Fast Short-circuit Protection Method for Low-voltage AC System With Distributed Photovoltaic; [含分布式光伏低压交流系统短路快速保护方法] . | Power System Technology , 2024 , 48 (12) , 5138-5148 . |
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Aiming at the problem that the users’ phase sequence is difficult to identify accurately due to the connection of high proportion of distributed photovoltaic to low-voltage transform district, a phase sequence identification method for users in low-voltage transform district with photovoltaic based on maximal information coefficient(MIC) is proposed, relying on power consumption data obtained by the advanced metering infrastructure. According to the topology structure of the low-voltage transform district with photovoltaic, the spatial characteristics of power consumption information are analyzed, and the deep interconnection information of the users’ phase sequence is mined based on the mathematical expression determined by the user’s voltage. Combined with the actual engineering practice, the time series screening mechanism is used to select the users’voltage sequence and the three-phase current sequence on the low-voltage side of the distribution transformer district with photovoltaic, so as to construct the phase sequence identification features of the users in the low-voltage transform district with photovoltaic. In view of the shortcomings of traditional correlation characterization methods, the MIC is introduced to measure the three-phase correlation degree of phase sequence identification features, and the users’ phase sequence is distinguished according to the value of MIC. The validity and reliability of the proposed method are verified by the example analysis based on the actual data of low-voltage transform district with photovoltaic. © 2024 Electric Power Automation Equipment Press. All rights reserved.
Keyword ：
advanced metering infrastructure advanced metering infrastructure low-voltage transform district with photovoltaic low-voltage transform district with photovoltaic maximal information coefficient maximal information coefficient phase sequence identification phase sequence identification
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| GB/T 7714 | Zheng, K. , Miao, X. , Lin, Y. et al. Phase sequence identification method for users in low-voltage transform district with photovoltaic based on maximal information coefficient; [基于最大互信息系数的低压光伏台区用户相序辨识方法] [J]. | Electric Power Automation Equipment , 2024 , 44 (12) : 108-114 . |
| MLA | Zheng, K. et al. "Phase sequence identification method for users in low-voltage transform district with photovoltaic based on maximal information coefficient; [基于最大互信息系数的低压光伏台区用户相序辨识方法]" . | Electric Power Automation Equipment 44 . 12 (2024) : 108-114 . |
| APA | Zheng, K. , Miao, X. , Lin, Y. , Huang, C. . Phase sequence identification method for users in low-voltage transform district with photovoltaic based on maximal information coefficient; [基于最大互信息系数的低压光伏台区用户相序辨识方法] . | Electric Power Automation Equipment , 2024 , 44 (12) , 108-114 . |
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针对分布式电源大规模接入低压台区后传统低压配电网出现的电压越限、台区负载不平衡、变压器容量分配不均衡等问题,基于柔性互联装置的功率调控能力构建多台区互联架构,并提出一种计及变压器功率损耗的负荷调控策略,实现互联台区间有功互济、负荷均衡.首先,介绍加入电容电流反馈有源阻尼环节的柔性互联装置控制策略,为确保后续负荷调控策略的有效实施打下基础;其次,提出计及变压器功率损耗的负荷调控策略,以生成柔性互联装置功率指令;最后,仿真结果表明所提策略可以灵活控制各端口传输功率并保持母线电压稳定,且相比于传统负荷调控策略可以有效降低系统损耗.
Keyword ：
变压器 变压器 控制策略 控制策略 柔性互联装置 柔性互联装置 柔性台区 柔性台区
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| GB/T 7714 | 林雨润 , 缪希仁 . 计及变压器功率损耗的多台区柔性互联协调控制研究 [J]. | 电器与能效管理技术 , 2024 , (9) : 15-23 . |
| MLA | 林雨润 et al. "计及变压器功率损耗的多台区柔性互联协调控制研究" . | 电器与能效管理技术 9 (2024) : 15-23 . |
| APA | 林雨润 , 缪希仁 . 计及变压器功率损耗的多台区柔性互联协调控制研究 . | 电器与能效管理技术 , 2024 , (9) , 15-23 . |
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The converter station based on a half-bridge sub-module has poor tolerance to dc short-circuit faults, which puts forward higher requirements for the detection and breaking performance of dc circuit breakers (DCCBs). To this end, this paper proposes a Capacitance-Resistance hybrid fault current limiter (CRHCL) that can be integrated with DCCBs. The proposed CRHCL realizes the fast switching of the current limiting resistor through the thyristor and the pre-charged capacitor. The working principle and parameter configuration principle of CRHCL are described, and the theory and performance verification are carried out in the single-ended equivalent system simulation. The results show that compared with the traditional scheme of DCCB direct breaking, the proposal has a lower breaking current and breaking voltage, which effectively reduces the demand of DCCB for device number and breaking performance. © Published under licence by IOP Publishing Ltd.
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| GB/T 7714 | Fu, M. , Miao, X. . A capacitance-resistance hybrid fault current limiter based on thyristor [未知]. |
| MLA | Fu, M. et al. "A capacitance-resistance hybrid fault current limiter based on thyristor" [未知]. |
| APA | Fu, M. , Miao, X. . A capacitance-resistance hybrid fault current limiter based on thyristor [未知]. |
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