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26th International Conference on Industrial Technology, ICIT 2025

作者： Yi, Kang Liu, Xin Hu, Wenkai Li, Yupeng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331521950

Accurately and promptly detecting the pipeline anomaly is crucial to the safe operation of pipeline systems, while a difficulty lies in that many existing methods require massive data for training models. However, pipelines are running under normal state for the most of the time, and labeled pipeline anomaly data is usually scarce. Among the commonly used sensors, vibration sensors are widely utilized in pipeline detection because of their advantages such as easy installation and high sensitivity. However, the vibration signal shows non-stationary characteristics when anomalies occur, and are contaminated by noises, making it difficult to represent the actual state with features extracted from either the time or frequency domain. Accordingly, this paper proposes a pipeline anomaly detection method based on the KPCA (kernel principal component analysis) and cosine distance prototypical network. First, features are extracted from original signals;then, the feature dimension is reduced by KPCA;last, the cosine distance is introduced to the prototypical network for anomaly detection. The effectiveness of the proposed method is demonstrated by case studies involving experimental data. © 2025 IEEE.

关键词： Frequency domain analysis

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Adaptive fixed-time anti-synchronization of neural networks: Potential application in active noise control

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IFAC-PapersOnLine 2023年第2期56卷 6400-6405页

作者： Haoyu Li Leimin Wang School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China

This paper discusses active noise control (ANC) through the dynamics analysis of neural networks. By designing an adaptive controller on the controlled neural network to generate a signal opposite to the noise source, the latter is considered neural networks with unknown parameters. To leave only the propagating signal sources in the channel, the controlled neural network is achieved the anti-synchronization with the unknown parameter neural network (fitted to noise source). Considering different noise environments, fixed-time control is introduced in ANC, i.e., the fixed-time stability of the error system is proved by the Lyapunov method. Since NNs-based ANC can directly obtain the anti-signal, our control scheme can significantly simplify the existing ANC scheme. Finally, a simulation example is provided to demonstrate the feasibility of the results in this paper.

关键词： Active noise control adaptive control fixed-time anti-synchronization Lyapunov methods

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Dual-mode FMF to SOI chip edge coupler

Dual-mode FMF to SOI chip edge coupler

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2021 Asia Communications and Photonics Conference, ACP 2021

作者： Zhang, Weilun Ye, Mengyuan Li, Yunlong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Dual-mode edge coupler for few mode fiber (FMF) to silicon chip is proposed. LP01 and LP11 modes could be efficiently coupled into TE0 and TE1 modes in waveguides via the proposed coupler in simulation. © Optica ...

ISBN: (纸本)9781957171005

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High Q silicon micro-ring resonator based on elliptical bending waveguides

High Q silicon micro-ring resonator based on elliptical bend...

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2021 Asia Communications and Photonics Conference, ACP 2021

作者： Li, Yunlong Ye, Mengyuan Zhang, Weilun Liu, Li School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

By adopting elliptical bending waveguides, a silicon micro-ring resonator with footprint ~ 440 μm and Q factor ~ 6.2×106 is proposed and demonstrated. © Optica Publishing Group 2021

ISBN: (纸本)9781957171005

By adopting elliptical bending waveguides, a silicon micro-ring resonator with footprint ~ 440 μm and Q factor ~ 6.2×106 is proposed and demonstrated. © Optica Publishing Group 2021

关键词： Waveguides

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Modeling of Steel Plate Temperature Field for Plate Shape control in Roller Quenching Process

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IFAC-PapersOnLine 2023年第2期56卷 6894-6899页

作者： Wen Zhang Min Wu Sheng Du Luefeng Chen Jie Hu Xuzhi Lai School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China

The temperature is of signification to control the plate shape during roller quenching process. The plate shape has an important influence on the use performance of steel plate. This paper presents a temperature field model, which can be used to control the plate shape. Firstly, the cooling mechanism during quenching is analyzed, and the heat transfer coefficients of each surface are obtained. Secondly, the temperature field model is established by using the heat conduction equation, and the cooling uniformity in the width and thickness directions is evaluated. Thirdly, based on the temperature field model and cooling uniformity, a typical plate shape control structure is designed. Finally, the temperature field model is verified, and the results show that this model can accurately simulate the temperature of steel plate.

关键词： Roller quenching process Temperature field model Cooling uniformity Plate shape control

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An Extended-Matrix-Separation-Based Summation Inequality on Stability of Discrete-Time Delayed Lur'e System*

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IFAC-PapersOnLine 2023年第2期56卷 6976-6981页

作者： Ke-You Xie Cui Zhu Wen-Hu Chen Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China

This paper investigates the stability of discrete-time Lur'e systems with a time-varying delay. Firstly, an extended-matrix-separated-based summation inequality is established to estimate the summation term containing the system state and the forward difference of the state. Then, an improved delay-product-type Lyapunov-Krasovskii functional (LKF) is proposed, which involves the characteristics of matrices refined and the information of delay squared. By using a quadratic function negative transformation lemma based on matrix-injection, a delay-dependent stability criterion is obtained. Finally, a numerical example demonstrates the advantages of the proposed criterion.

关键词： Discrete-time system Lur'e system stability time-varying delay summation inequality delay-product-type LKF

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Knowledge transfer for tuning microwave filters with unknown individual differences

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IFAC-PapersOnLine 2023年第2期56卷 10180-10185页

作者： Linwei Guo Weihua Cao Leyu Bi Wenkai Hu Yan Yuan Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China

Improving the production efficiency of Microwave Filters (MFs) is of great practical significance for constructing modern communication systems. The characteristics of MFs are with various degrees of individual differences caused by materials. The most tuning techniques have to start from scratch for tuning different MFs, which is time-consuming. The knowledge from previous tuning processes can be used in the current tuning due to the relevance of MFs. Motivated by this, a knowledge transfer method for tuning MFs with unknown individual differences is proposed. The main contributions are threefold: 1) An Knowledge Transfer technique for Optimization Tuning (KTOT) is created to tune various MFs efficiently; 2) an Evaluation mechanism of Difference Degree (EDD) is proposed to guide transfer; 3) a Guiding strategy of Knowledge Transfer Intensity (KTIG) in accordance with the difference degree is presented to reuse knowledge reasonably. The high-efficiency of KTOT and the effectiveness of KTIG based on EDD are demonstrated.

关键词： Knowledge transfer difference degree evaluation microwave filters tuning processes intelligent optimization

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Anti-sway control of Crane Based on Equivalent-Input-Disturbance Method and Feedback Linearization

Anti-sway Control of Crane Based on Equivalent-Input-Disturb...

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第42届中国控制会议

作者： Shuhan He Gang Yu Yongbo Li Fengyu Zhang Wangyong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation Complex Systems Huaxin Cement Technology Management (Wuhan) Co. Ltd

The anti-sway issue with crane systems is discussed in this essay. Because cranes are undriveable and nonlinear,implementing anti-sway controllers becomes much more challenging. This work suggests a crane anti-sway controller that uses feedback linearization(FL) in conjunction with the Equivalent-Input-Disturbance(EID) technique to address the issues. to reduce the problem that the feedback linearization largely relies on the model's *** crane system is first treated as a linear system, after which the unmodeled disturbances, nonlinear components, and external disturbances of the system are treated as the total disturbances of the system, and the effects of these disturbances are then compensated for using disturbance estimation. Finally, simulation experiments confirm that the maximum steady-state fluctuations of the position and angle of the anti-sway controller based on the equivalent input disturbance method and the feedback linearization method are 14 and 6.85percent, respectively, of those estimated without *** demonstrates the potency of this approach.

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Stabilization of Stochastic Linear Systems via Path-dependent Feedback control

Stabilization of Stochastic Linear Systems via Path-dependen...

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Industrial Cyber-Physical Systems (ICPS)

作者： Ruizhe Yu Xiaofeng Zong Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China

This paper aims to investigate the stabilization problem of stochastic linear system via path-dependent state-feedback control. For the given stochastic linear system, a novel feedback control is designed with the path-dependent information of the system states, and the control gains are determined by the stochastic algebraic Riccati equation. To prove that path-dependent control can drive the stochastic linear system to be exponentially stable, a novel Lyapunov function is proposed. Combined with the general theory on stability of stochastic system, it is shown that stochastic system will be stabilized in mean-square via path-dependent control.

关键词： Linear systems Wireless sensor networks Stochastic systems Riccati equations Filling Feedback control Synchronization

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Landslide Sensitivity Mapping Based on One-Dimensional Residual Convolutional Neural Networks

Landslide Sensitivity Mapping Based on One-Dimensional Resid...

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2022 Chinese automation Congress, CAC 2022

作者： Ke, Yougang Lu, Chengda Wu, Min Yu, Wanke Niu, Ruiqing School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Institute of Geophysics and Geomatics China University of Geosciences Wuhan China

ISBN: (纸本)9781665465335

Landslide is a common geological disaster. Landslide sensitivity mapping (LSM) is the key technology for landslide monitoring, early warning and risk assessment. Deep learning shows good performance in feature extraction. This paper proposes a one-dimensional residual convolution neural network (1DRCNN), which takes Yunyang County, Chongqing City, China, located in the Three Gorges Reservoir area as the research area. Extracting 12 evaluation factors from multi-source remote sensing data and building a training set. The spatial probability of landslide occurrence is quantitatively predicted by the proposed model, and finally, the landslide sensitivity mapping is generated. Compared with the common machine learning models SVM and logistic regression, the results show that the AUC (area under curve) and accuracy of 1D-RCNN are 0.9860 and 93.38%, respectively, which proving that this method is effective and can provide a reference for disaster prevention and reduction. © 2022 IEEE.

关键词： Landslides

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