检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Meng, Zhongwei Hu, Yizhang Bao, Zhongqiang Ou, Juan Deng, Meng Zeng, Bosong Zhang, Jingtong Deng, Huan Key Laboratory of Fluid and Power Machinery Ministry of Education School of Energy and Power Engineering Xihua University Chengdu610039 China Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province School of Automobile and Transportation Xihua University Chengdu610039 China Power Machinery and Vehicular Engineering Institute Zhejiang University Hangzhou310027 China

Compared with normal operating condition, internal combustion engines equipped with particulate filter (DPF/GPF) produce a large number of particulate emissions when start-up, which seriously restricts the engine to meet the requirements of Euro 7 regulation or near zero emissions. The research on the transient filtration characteristics of particulate filter can not only enrich the understanding of its transient filtration efficiency (TFE), but also provide theoretical support and experimental reference for further reducing its outlet particulate emissions. In this paper, based on a diesel engine test bench, the filter characteristics during cold and warm start are investigated, and the particulate emission performance at the inlet and outlet of the filter during cold and warm start is presented. Furthermore, a small simulative bench for testing the transient filtration characteristics of the filter is built under laboratory condition, and the influence of the inlet flow rate and particle number concentration on the TFE is experimentally studied. It is found that the inlet peak particle number flow rate (PPNFR) is an important parameter affecting the TFE. The influence of filter substrate temperature and particle loading on the TFE is also investigated. The results show that the TFE could be effectively improved by increasing the substrate temperature. The following research can furtherly discuss the influence of substrate pore structure parameter, particle characteristics, particle size and other factors on the TFE, which is target to find an optimization window to reduce the particulate emissions of the filter under engine start-up conditions. © 2023, The Authors. All rights reserved.

关键词： Particulate emissions

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TEMPORAL-SPATIAL REPRESENTATION LEARNING TRANSFORMER FOR EEG-BASED EMOTION RECOGNITION

arXiv

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arXiv 2022年

作者： Wang, Zhe Wang, Yongxiong Hu, Chuanfei Yin, Zhong Song, Yu School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology China Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin University of Technology China

Both the temporal dynamics and spatial correlations of Electroencephalogram (EEG), which contain discriminative emotion information, are essential for the emotion recognition. However, some redundant information within the EEG signals would degrade the performance. Specifically, the subjects reach prospective intense emotions for only a fraction of the stimulus duration. Besides, it is a challenge to extract discriminative features from the complex spatial correlations among a number of electrodes. To deal with the problems, we propose a transformer-based model to robustly capture temporal dynamics and spatial correlations of EEG. Especially, temporal feature extractors which share the weight among all the EEG channels are designed to adaptively extract dynamic context information from raw signals. Furthermore, multi-head self-attention mechanism within the transformers could adaptively localize the vital EEG fragments and emphasize the essential brain regions which contribute to the performance. To verify the effectiveness of the proposed method, we conduct the experiments on two public datasets, DEAP and MAHNOB-HCI. The results demonstrate that the proposed method achieves outstanding performance on arousal and valence classification. Copyright © 2022, The Authors. All rights reserved.

关键词： Emotion Recognition

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Temperature Compensation Method of Fluxgate Sensor Based on Polynomial Fitting

arXiv

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arXiv 2024年

作者： Yang, Ruiping Liu, Huan Ge, Jian Chugo, Daisuke Dong, Haobin 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 Faculty of Engineering Kwansai Gakuin University Osaka669-1330 Japan

Fluxgate sensors are widely used in the field of low frequency and weak vector magnetic field measurement because of their good performance, such as high resolution and low power consumption. However, during the long-term continuous observation, the drift errors of the fluxgate sensor will occur due to the variable ambient temperature. This paper proposes a temperature compensation method for fluxgate sensors based on polynomial fitting. First, a physical model of the temperature & fluxgate sensor was established on the COMSOL Multiphysics simulation platform, and the influence of temperature on the measurement performance of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature compensation model of the fluxgate sensor was constructed. And compared it with other temperature compensation method, the result shows that the proposed temperature compensation method is relatively simple and can better achieve real-time compensation for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were *** temperature drift is reduced from more than 500 nT before compensation to about 1 nT. The results show that the proposed method has a good temperature compensation effect on the data measured by the fluxgate sensor within a variable temperature background. Copyright © 2024, The Authors. All rights reserved.

关键词： Simulation platform

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Optimal consensus control for partially unknown multi-agent systems with switching communication topology*

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IFAC-PapersOnLine 2023年第2期56卷 1210-1216页

作者： Wenpeng He Xin Chen Menglin Zhang Yipu Sun Akinori Sekiguchi Jinhua She 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 School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

Since the local neighborhood tracking error system for switching multi-agent systems (MASs) is time-varying, the existing optimal consensus method for fixed MASs cannot be used in switching MASs. This paper proposes a new approach to solve the optimal consensus problems of linear switching MASs. Firstly, a new augment local neighborhood tracking error (ALNTE) system, which is based on the joint communication topology, is developed to construct the control object, and the open-loop estimation method is used to estimate the ALNTE for individuals. Secondly, based on the ALNTE system, the performance index is designed, and the value iteration method is used to solve the coupled Hamilton-Jacobi-Bellman equations and obtain the optimal control. Finally, theoretical analysis is given to prove the learning stability and control stability of the value iteration method, and a numerical simulation is used to verify the effectiveness of the proposed method.

关键词： Switching topology multi-agent systems (MASs) optimal control value iteration augment local neighborhood tracking error (ALNTE)

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Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Anomaly Detection Based on Principle of Justifiable Granular...

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2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold 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 University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

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Signal conditioning and quality estimation method of Overhauser magnetometer 4

Signal conditioning and quality estimation method of Overhau...

引用

4th International Symposium on Power Electronics and control engineering, ISPECE 2021

作者： Zheng, Lidong Dong, Haobin Luo, Wang Ge, Jian Liu, Huan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (数字)9781510650374

ISBN: (纸本)9781510650367

Overhauser magnetometer reaches an ultra-high accuracy benefit from the outputted frequency of free induction decay transversal signal is proportional to the magnetization on measuring the real scalar geomagnetic field. Nevertheless, the magnitude of the accuracy is an important factor that severely affects the validity of geomagnetic field data. Since the real value of the geomagnetic field is unknown, we propose a measurement quality estimation method through analyzing the envelope of the free induction decay transversal signal from the Overhauser magnetometer. The estimation model includes the SNR and the decay slope characteristics of the signal is indicated in an two-digit number changes from 00∼99. The results demonstrated that the proposed estimation method can effective performance the reliability of magnetometer measurement data in our experiments. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Magnetometers

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Semi-supervised Anomaly Detection and Location Based on Generative Adversarial Network 6

Semi-supervised Anomaly Detection and Location Based on Gene...

引用

6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Liu, Wei Gao, Mingqiang Duan, Shuaidong Wei, Longsheng China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation For Complex Systems Wuhan China Engineering Research Center of Intelligent Technology For Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9780738133737

With the development of artificial intelligence, the anomaly detection plays more and more important role in security monitoring field. Because it is difficult to label abnormal data, most of the supervised methods consumed a lot of manpower and obtained low performance and generality. Inspired by this motivation, this paper proposes a semi-supervised method for anomaly detection in video frames based on GAN (Generative Adversarial Network), in which only normal data was used as the training sample. The quality gap between the predicted frame and the ground truth is used as the basis to determine whether it is abnormal. Moreover, the mathematical morphology approach was adopted to locate the anomaly area in the frames. Experiments show that our method can successfully detect abnormal frames in video and can also locate the area where abnormal behavior occurs in frames. © 2021 IEEE.

关键词： Generative adversarial networks

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Experimental Study on the Pressure Drop and Thickness Variation of Carbon Black Particle Layer During Oxidation on Dpf Channels

SSRN

引用

SSRN 2023年

作者： Deng, Meng Meng, Zhongwei Ou, Juan Wu, Daigeng Bao, Zhongqiang Key Laboratory of Fluid and Power Machinery Ministry of Education School of Energy and Power Engineering Xihua University Chengdu610039 China Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province School of Automobile and Transportation Xihua University Chengdu610039 China Power Machinery and Vehicular Engineering Institute Zhejiang University Hangzhou310027 China

Studying the changes in pressure drop and thickness of particle layers during oxidation is crucial to understanding the regeneration performance of diesel particulate filters (DPFs) and optimizing the regeneration process. In this study, carbon black particle layers on the channels of a DPF were regenerated actively using a visualized single-channel test bench. Online measurements and analysis of pressure drop and particle layer thickness were performed to examine their dynamic behavior. The results showed that the regeneration process of the particle layer can be categorized into three stages. In the first stage, the pressure drop slowly decreased while the thickness continued to increase. In the second stage, the decrease rate of the pressure drop increased as the deposition thickness grew, which was most significant in the range of 112 μm to 147 μm. Simultaneously, the thickness of the particle layer is still increasing due to thermal expansion. When the thickness is no more than 193 μm, it peaked and then started to decrease. When the thickness exceeded 273 μm, the phenomenon of continuous thickening occurred. In the third stage, the pressure drop reached its lowest point, while the decreased rate of thickness was relatively high. Consequently, a time delay was observed between the rapid decline of thickness and the subsequent steep decrease in pressure drop, and this delay increased with the growth of the particle layer thickness. Once the deposition thickness reached 404 μm, the particle layer would suspend on the filter wall and form a gap during the heating process. © 2023, The Authors. All rights reserved.

关键词： Carbon black

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Loss-induced quantum nonreciprocity

arXiv

引用

arXiv 2024年

作者： Li, Baijun Zuo, Yunlan Kuang, Le-Man Jing, Hui Lee, Chaohong Institute of Quantum Precision Measurement State Key Laboratory of Radio Frequency Heterogeneous Integration College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Shenzhen518045 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China

Attribute to their robustness against loss and external noise, nonreciprocal photonic devices hold great promise for applications in quantum information processing. Recent advancements have demonstrated that nonreciprocal optical transmission in linear systems can be achieved through the strategic introduction of loss. However, a crucial question remains unanswered: can loss be harnessed as a resource for generating nonreciprocal quantum correlations? Here, we take a counterintuitive stance by engineering loss to generate a novel form of nonreciprocal quantum correlations, termed nonreciprocal photon blockade. We examine a dissipative three-cavity system comprising two nonlinear cavities and a linear cavity. The interplay of loss and nonlinearity leads to a robust nonreciprocal single- and two-photon blockade, facilitated by destructive quantum interference. Furthermore, we demonstrate the tunability of this nonreciprocal photon blockade by manipulating the relative phase between the two nonlinear cavities. Remarkably, this allows for the reversal of the direction of nonreciprocity. Our study not only sheds new light on the concept of loss-engineered quantum nonreciprocity but also opens up a unique pathway for the design of quantum nonreciprocal photonic devices. © 2024, CC BY-NC-SA.

关键词： Photons

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Human pose recognition based on multiple features and random forest algorithm 2

Human pose recognition based on multiple features and random...

引用

2nd International Conference on Computer Vision, Image, and Deep Learning

作者： Fang, Di Wang, Hong Meng, Fanglong 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

ISBN: (数字)9781510646827

ISBN: (纸本)9781510646810

Human pose recognition based on bone node data collected by depth camera is a key problem in the field of human-computer interaction. To improve the accuracy of human pose recognition, a new algorithm based on multiple features and random forest model is proposed. Firstly, a 93-dimensional vector is defined, which contains the coordinate feature of the joint and the distance feature, and the distance feature is selected according to the spatial position of the joint. Then, in the process of body pose recognition, the random forest model is combined with Bagging algorithm to ensure the balance of samples, so as to improve the classification performance of the classifier for different samples. Finally, the performance test of the constructed classifier is carried out on the UTKinect-action3D Dataset. The experimental result shows that the algorithm can effectively identify a variety of human posture, and the recognition rate reaches more than 90%. The fusion of multiple features is of great significance to improve the accuracy of human posture recognition. © 2021 SPIE.

关键词： Decision trees

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