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5th International Conference on System Reliability and Safety engineering, SRSE 2023

作者： Zhang, Shijie Zhu, Guibing University of Electronic Science and Technology of China School of Aeronautics and Astronautics Chengdu China University of Electronic Science and Technology of China School of Automation Engineering Chengdu China Nottingham Electrification Centre Ningbo China

ISBN: (纸本)9798350305944

There are various of failure modes and operating conditions of an aero-engine gas path system. They are correlated with each other, making the fault diagnosis for aero-engine gas path difficult. This paper proposes a fault diagnosis method for aero-engine gas path considering operating condition. First, we develop a multilayer perceptron (MLP) model to identify the operating condition based on Mach number and altitude. Then, we adopt a Convolutional Bidirectional Long Short-Term Memory (CNN-BiLSTM) model to diagnose the failure mode under the corresponding operating condition based on monitoring parameters of each cross-section state. Finally, the effectiveness of the proposed gas path fault diagnosis method was validated by the simulation data generated by gas turbine simulation program (GSP). © 2023 IEEE.

关键词： Failure analysis

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Research on Machine Learning and Signal Processing of IQ Signals 16

Research on Machine Learning and Signal Processing of IQ Sig...

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16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023

作者： Yu, Xiaoyu Zeng, Hao Tian, Yu Guo, Lianping Ye, Peng Wang, Meng Liu, Chunming School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institute for Advanced Study UESTC Shenzhen China School of Automation Engineering UESTC Chengdu China CO. Ltd Department of Research and Development Dongguan China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350327144

IQ signals are a core technology of the zero-IF architecture in modern communication technology, but they are often unstable due to factors such as amplitude and phase imbalances. Utilizing the characteristics of IQ two-way signals, common IQ signal calibration algorithms use compensation, frequency domain calibration, etc. This article uses the characteristics of Machine Learning and Signal Processing to train the existing IQ signals and predict the signals based on the training set. Through simulation experiments and actual data measurement, it can be known that different prediction models will have different correction effects. Among them, the Neural Networks model, which is mainly adopted in this article, has a relatively ideal effect on signal processing and prediction, and can also significantly make the signal smoother. © 2023 IEEE.

关键词： Machine learning

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An optical electric field sensor using two cascaded LiNbO3 crystals with improved sensitivity

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IEEE Sensors Journal 2025年第12期25卷 21377-21385页

作者： Zhang, Jiahong Liu, Baoyong Liu, Xiaoming Li, Yingna Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Chengdu Technological University of China Chengdu China School of Information Engineering and Automation Kunming University of Science and technology China

Based on the Pockels effect of lithium niobate LiNbO3 crystals, a high-sensitivity electric field sensor utilizing a dual-crystal configuration of LiNbO3 was designed and fabricated. The sensor internally cascades a LiNbO3 crystal with light propagation along the x-axis and an electric field applied along the z-axis, and another crystal with light propagation along the x-axis and an electric field applied along the y-axis. By utilizing the large electro-optic coefficient γ33 of LiNbO3 along the z-axis, the sensor's sensitivity is significantly enhanced. Consequently, under the condition of identical crystal length, this sensor exhibits higher sensitivity compared to current electric field sensor that employ light propagation along the z-axis. Experimental results indicate that the sensor can accurately measure the time-domain waveforms of electromagnetic pulse (EMP) with rise time on the microsecond and nanosecond scales without distortion. The sensitivity of the sensor is 1.40 mV/(kVm-1), with the minimum and maximum measurable time-domain EMP being 3.6 kV/m and 320.1 kV/m, respectively. When the span of the spectrum analyzer is set to 10 kHz and the resolution bandwidth (RBW) is 10 kHz, the minimum detectable electric field is 2.2 V/m, corresponding to a linear dynamic range of 103.30 dB. Furthermore, from 5 °C to 40 °C, the static output optical power of the sensor fluctuates within ±0.28 dB. © 2001-2012 IEEE.

关键词： Spectrum analyzers

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An End-to-End Infrared and Visual Fusion Detection Framework for Near-Surface Defect in Moving Mode

An End-to-End Infrared and Visual Fusion Detection Framework...

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2023 IEEE Far East NDT New technology and Application Forum, FENDT 2023

作者： Li, Jiacheng Gao, Bin Xu, Jieyi Liu, Lei Zeng, Yu Ru, Gaige Tian, Gui Yun University of Electronic Science and Technology of China School of Automation Engineering Chengdu China Newcastle University School of Electrical and Electronic Engineering United Kingdom

ISBN: (纸本)9798350303544

Traditional infrared thermal testing (IRT) is susceptible to surface conditions such as variation of surface emissivity, which may lead to false detection and has high requirements for the flatness and cleanliness of the sample. Traditional visual testing (VT) could capture surface texture information with high resolution but lacks the ability to detect sub-surface defects. This paper proposes a multispectral fusion detection framework in moving mode combines the advantages of IRT and VT for real-time detection and classification of both surface defects and sub-surface defects. The designed multispectral fusion detection system can adjust the trajectory and speed for different materials and shapes of specimens and collect time-synchronized infrared and visible image pairs for further processing. The proposed algorithmic framework enables real-time end-to-end fusion detection by fast coarse registration and late fusion. Comparative experiments have been conducted on four standard and natural samples of different materials and shapes to validate the reliability and efficiency of the proposed framework. © 2023 IEEE.

关键词： Object detection

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Application of Fuzzy BP Neural Network to Evaluate Effectiveness of Curriculum Teaching Reform of Nuclear Radiation Detection technology 5

Application of Fuzzy BP Neural Network to Evaluate Effective...

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5th IEEE Eurasian Conference on Educational Innovation, ECEI 2022

作者： Jiang, Jianfeng Li, Fei Gu, Yi Gu, Zhixing Ge, Liangquan Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province Chengdu Chengdu China

ISBN: (纸本)9781665433181

In the context of curriculum teaching reform, it is of great significance to evaluate its effectiveness. In the paper, the teaching reform of the nuclear radiation detection technology curriculum is studied and analyzed by using the fuzzy BP neural network model. According to the investigation of the evaluation factors of education reform, four primary evaluation indexes and nine corresponding secondary indexes are selected: teaching ability, classroom order, after school learning, and teaching effectiveness. The preliminary data set is obtained in the form of a questionnaire. The fuzzy theory and analytic hierarchy process are used to construct and calculate the evaluation index to provide samples for the learning of neural networks. On this basis, the fuzzy BP neural network model is constructed by combining BP neural network with a fuzzy system. After testing, the relative error of the output prediction score is less than 0.0002, which well predicts the evaluation results and provides an effective method for the evaluation of curriculum teaching reform. © 2022 IEEE.

关键词： Fuzzy neural networks

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Adaptive Containment Control for Fractional-Order Nonlinear Multi-Agent Systems With Time-Varying Parameters

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1627-1638页

作者： Yang Liu Huaguang Zhang Yingchun Wang Hongjing Liang the College of Information Science and Engineering Northeastern UniversityShenyang 110004China the State Key Laboratory of Synthetical Automation for Process Industries and also with the School of Information Science and EngineeringNortheastern UniversityShenyang 110004China the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and *** using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is *** command filter is introduced to solve the complexity problem inherent in adaptive backstepping ***,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is ***,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the *** on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic ***,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.

关键词： Adaptive backstepping control command filter fractional-order multi-agent system time-varying parameters

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Scaled IoT Intrusion Detection Model based on Improved PSO Algorithm Optimization 5

Scaled IoT Intrusion Detection Model based on Improved PSO A...

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5th International Conference on Electronic engineering and Informatics, EEI 2023

作者： Wang, Yongrui Yang, Han Liu, He Dang, Haoyang Institute of Systems Engineering Academy of Military Sciences Beijing China School of Automation Engineering University of Electronic Science and Technology Chengdu China

ISBN: (纸本)9798350327076

An improved convolutional nveural network intrusion detection training model is proposed to address the issues of slow convergence and low accuracy that may arise from the large randomness of initial parameters in traditional neural network intrusion detection models. The proposed approach utilizes an enhanced particle swarm optimization (PSO) algorithm to optimize the convolutional neural network intrusion detection model, thereby improving its global search capability. The improved PSO algorithm is employed to optimize the neural network hyperparameters, with the loss function used as the population location. Once the optimal parameters are obtained, a scaled convolutional neural network is constructed, and the model is trained using backpropagation. The initial model defaults to using the Gram's corner field method to transform the data into three-dimensional format, incorporating a softpool pooling layer to enhance feature extraction. Additionally, a scaled neural network structure is employed to maximize the perceptual field, and the CUDA parallel computing method is utilized to accelerate computation speed. Experimental results demonstrate that the proposed method exhibits certain advantages over the traditional PSO algorithm in terms of optimizing the neural network intrusion detection training method, as evaluated comprehensively in terms of efficiency and accuracy. These findings highlight the potential of the proposed method for improving the efficiency and accuracy of neural network intrusion detection training when compared to the traditional PSO algorithm. © 2023 IEEE.

关键词： Intrusion detection

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Magneto-Optical Imaging and Defect Detection Under Pulsed Magnetic Field Excitation

Magneto-Optical Imaging and Defect Detection Under Pulsed Ma...

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2024 Academic Conference of China Instrument and Control Society, ACCIS 2024

作者： Liang, Yiling Tian, Lulu University of Electronic Science and Technology of China dept. The School of Automation Engineering Chengdu Sichuan China

ISBN: (纸本)9798350350326

Eddy current magneto-optical detection technology has been widely applied in various fields, including non-destructive testing, aerospace industry, archaeological artifacts, and art inspection. It enables the acquisition of internal defect and stress information without damaging the surface of the object. This study aims to investigate the fundamental principles of defect detection using a magneto-optical imaging system under different laser frequencies. An experimental setup was designed to expand the laser spot to a 5cmx 5cm magnetic field region using a beam expander, and tests were conducted within the range of 0.25mT-1mT. The feasibility of defect detection at different laser frequencies was experimentally verified. The results demonstrate that the system maintains high stability in dynamic measurements at various laser frequencies and possesses a wide range of defect detection capabilities. Optical image signals were extracted using a CCD camera, and defect information was oriented and rapidly acquired through image processing methods. The research indicates that this method can effectively detect and extract defect information within the maximum brightness of the laser source and the peak excitation of the signal generator, showing significant application prospects. © 2024 IEEE.

关键词： Defect Detect Magneto-Optical Imaging

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First-Principles Calculations of Phase Transition, Phonon Spectra, Thermodynamic Properties and Elasticity for Puo2 Polymorphs

SSRN

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SSRN 2024年

作者： Ai, Junjie Ma, Tengfei You, Hang Xie, Minghong Tian, Xiaofeng The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

The first principles are utilized to calculate the phase transition, phonon spectra, thermodynamic properties, and elasticity of PuO2 under varying pressures. Under the compression condition, the anticipated pressure of phase transition from Fm-3m to Pnma is 26.0 GPa, from Pnma to Cmcm is 112.9 GPa, and from Cmcm to I4/mmm phase is 588.0 GPa. And under tensile conditions, the phase transition pressure of anticipating from Fm-3m phase to P42/mnm and Pnnm phase occur at -8.6 GPa and -8.5 GPa. The phonon spectra of these six structures show that all phases are dynamically stable under the selected pressure. Meanwhile, the verification results of the mechanical stability criterion show that Fm-3m, Pnma, Cmcm and I4/mmm of PuO2 are mechanically stable, nevertheless P42/mnm and Pnnm are unstable in high pressure. The thermodynamic properties were then calculated to further research the patterns of variation in the coefficient of thermal expansion, bulk modulus, Gibbs free energy, and heat capacity with temperature, and these were compared with experimental data. © 2024, The Authors. All rights reserved.

关键词： Elasticity

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Optimized Interleaved PWM of Internal-Parallel Multilevel Converter-Fed Dual-Three-Phase PMSM Drives With Reduced Torque Ripples 49

Optimized Interleaved PWM of Internal-Parallel Multilevel Co...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Yang, Xiaofan Zhou, Dehong Shen, Zewei Zou, Jianxiao Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350331820

The Internal-Parallel Multilevel Converter (IPMC) with reduced device count is implemented to drive the dual three-phase permanent magnet synchronous motor (DTP-PMSM) forming multilevel multiphase motor drives. However, due to the restriction of the low switching frequency (LSF) module sharing, only the parallel high switching frequency (HSF) switching states can keep interleaving operation, whereas the proportional-integral (PI) control, the resulting voltage reference, and the LSF switching state remain simultaneous, which leads to asymmetric pulse width modulation (PWM) waveform and significant harmonics. In this paper, the effect of asymmetric PWM waveform on current and torque harmonics is investigated. Meanwhile, a decoupled modulation strategy with optimized interleaved PWM is proposed to solve the problem, thus achieving the reduction of the corresponding order and switching frequency torque harmonics with a certain improvement in the current ripple. The experimental results with the IPMC-fed DTP-PMSM drive prototype are provided to verify the validity and superiority of the proposed modulation strategy compared to the traditional interleaving scheme and the non-interleaving technique. © 2023 IEEE.

关键词： Pulse width modulation

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