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46 results on '"Huang, Shize"'

6. Urban Rail Transit Power Monitoring System Techniques Based on Synchronous Phasor Measurement Unit

Author

Huang, Shize, Yang, Lingyu, Xue, Ji, Yu, Kai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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7. Bionic Vision-Based Pantograph–Catenary Contact Point Detection Study in China High-Speed Railway

Author

Wu, Zaixin, Huang, Shize, Yu, Liangliang, Chen, Wei, Yang, Lingyu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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8. Recognition of Signal Fault Curves Based on Dynamic Time Warping for Rail Transportation

Author

Huang, Shize, Wu, Zaixin, Zhang, Fan, Yu, Kai, Yang, Lingyu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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11. The Simulation of the Longitudinal Force of Heavy Haul Trains

Author

Huang, Shize, Guo, Qiyi, Yu, Liangliang, Liu, Yue, Zhang, Fan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Samad, Tariq, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Jia, Limin, editor, Qin, Yong, editor, Suo, Jianguo, editor, Feng, Jianghua, editor, Diao, Lijun, editor, and An, Min, editor

Published
2018
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15. A Decentralized ETC Architecture Based on Blockchain Technology

Author

Huang, Shize, Yang, Lingyu, Yang, Xiaolu, Li, Xinghua, and Gao, Fei

Subjects
Transportation industry
Abstract

Electronic toll collection (ETC) has been widely spread in China, providing efficient, comfortable, and convenient toll services. However, the nature of centralization of those ETC systems has incurred serious security threatens. Given blockchain's features of self-trust, decentralized architecture, and traceability, we propose a decentralized ETC architecture based on blockchain technology. After implementing our architecture in a test network, we verify its feasibility. A thorough discussion indicates that our architecture can effectively operate normal ETC services while avoiding most attacks that threaten traditional ETC systems. The proposed architecture provides a brand new way of conventional ETC system optimization., Author(s): Shize Huang [1]; Lingyu Yang [2]; Xiaolu Yang (corresponding author) [3]; Xinghua Li [2]; Fei Gao [4] 1. Introduction Electronic toll collection (ETC) has been widely used for its [...]

Published
2021
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22. Predicting Pedestrian Counts for Crossing Scenario Based on Fused Infrared-Visual Videos

Author

Huang, Shize, Chen, Wei, Yu, Rongjie, Yang, Xiaolu, and Dong, Decun

Subjects
Intelligence gathering, Retirement benefits, Transportation industry, Institute of Electrical and Electronics Engineers Computer Society
Abstract

Estimating the number of pedestrians based upon surveillance videos and images has been a critical task while implementing intelligent signal controls at intersections. However, this has been a difficult task considering the pedestrian waiting area is an outdoor scenario with complex and time-varying surrounding environment. In this study, a method for estimating pedestrian counts based on multisource video data has been proposed. First, the partial least squares regression (PLSR) model is developed to estimate the number of pedestrians from single-source video (either visible light video or infrared video). Meanwhile, the temporal feature of the scenario (daytime or nighttime) is identified based on visible light video. According to the recognized time periods, pedestrian count detection results from the visible light and infrared video data can be obtained with preset corresponding confidence levels. The empirical experiments showed that this fusion method based on environment perception holds the benefits of 24-hour monitoring for outdoor scenarios at the pedestrian waiting area and substantially improved accuracy of pedestrian counting., 1. Introduction Estimating the number of pedestrians is critical within the intelligent transportation system. The pedestrian counts have been a vital input for intersection signal control [1], the guidance of [...]

Published
2018
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23. Cluster Analysis Based Arc Detection in Pantograph-Catenary System

Author

Huang, Shize, Yu, Liangliang, Zhang, Fan, Zhu, Wei, and Guo, Qiyi

Subjects
Algorithms -- Analysis, Railroads, Electric power transmission, Algorithm, Transportation industry
Abstract

The pantograph-catenary system, which ensures the transmission of electrical energy, is a critical component of a high- speed electric multiple unit (EMU) train. The pantograph-catenary arc directly affects the power supply quality. The Chinese Railway High-speed (CRH) is equipped with a 6C system to obtain pantograph videos. However, it is difficult to automatically identify the arc image information from the vast amount of videos. This paper proposes an effective approach with which pantograph video can be separated into continuous frame-by-frame images. Because of the interference from the complex operating environment, it is unreasonable to directly use the arc parameters to detect the arc. An environmental segmentation algorithm is developed to eliminate the interference. Time series in the same environment is analyzed via cluster analysis technique (CAT) to find the abnormal points and simplified arc model to find arc events accurately. The proposed approach is tested with real pantograph video and performs well., 1. Introduction In high-speed electric multiple unit trains, the pantograph-catenary system is one of the critical components in the transmission of electric energy to the train. Any problem that occurs [...]

Published
2018
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25. Turnout Fault Diagnosis through Dynamic Time Warping and Signal Normalization

Author

Huang, Shize, Zhang, Fan, Yu, Rongjie, Chen, Wei, Hu, Fei, and Dong, Decun

Subjects
Railroads -- Safety and security measures, Fault location (Engineering) -- Methods, Transportation industry
Abstract

Turnout is one key fundamental infrastructure in the railway signal system, which has great influence on the safety of railway systems. Currently, turnout fault diagnoses are conducted manually in China; engineers are obliged to observe the signals and make problem solving decisions. Thus, the accuracies of fault diagnoses totally depend on the engineers' experience although massive data are produced in real time by the turnout microcomputer-based monitoring systems. This paper aims to develop an intelligent diagnosis method for railway turnout through Dynamic Time Warping (DTW). We firstly extract the features of normal turnout operation current curve and normalize the collected turnout current curves. Then, five typical fault reference curves are ascertained through the microcomputer-based monitoring system, and DTW is used to identify the turnout current curve fault through test data. The analysis results based on the similarity data indicate that the analyzed five turnout fault types can be diagnosed automatically with 100% accuracy. Finally, the benefits of the proposed method and future research directions were discussed., 1. Introduction Recently, the railway system has experienced rapid development all over the world [1] with both the freight and passenger traffic demands increasing. According to a report from the [...]

Published
2017
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34. Nighttime agglomerate fog event detection considering car light glare based on video

Author

Huang, Shize, Tan, Qunyao, Fan, Qianhui, Zhang, Zhaoxin, Zhang, Yi, and Li, Xingying

Abstract

Agglomerate fog event poses more serious threat than normal foggy weather to expressway traffic safety, due to its localized nature and suddenly uneven formation. However, vision-based fog detection methods typically estimate visibility for individual images and ignore the difference in the characteristics of even and uneven fog, lacking use of temporal information to differentiate between normal foggy weather and agglomerate fog events. Meanwhile, detection of fog at night faces strong interference from car lights that is always overlooked. This study proposes a nighttime agglomerate fog event detection method for videos, taking into account car light interference. Depth disparity feature is constructed based on the information entropy of depth estimation result, and in order to build a metric for uneven characteristics in the field of view, we creatively introduce the Moran’s index to establish uneven feature, generating two-dimensional feature time series for each video. By extracting interpretable features from the two-dimensional feature time series after removing car light interference frames, a classification model based on XGBoost is built to differentiate agglomerate fog, normal fog, and no fog videos. Experiments are carried out utilizing real monitoring data from roadside surveillance cameras to validate the effectiveness of features and model. Furthermore, a fog event detection dataset containing over 1500 videos is established, making up data scarcity for vision-based agglomerate fog event detection and providing support for future research.

Published
2024
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35. Trusted Perception Method for Traffic Signs That Are Physically Attacked

Author

Huang, Shize, Tan, Qunyao, Zhang, Zhaoxin, Fan, Qianhui, Zhang, Yi, and Li, Xingying

Abstract

Traffic sign recognition is a crucial method by which autonomous driving systems acquire road information, and is predominantly based on deep neural networks (DNNs). However, the recognition results of DNNs are not always trustworthy for traffic signs subject to abnormal disturbance. Recently, the phenomenon of adversarial examples successfully deceiving DNNs has garnered considerable attention. Because DNN-based computer vision techniques are becoming increasingly prevalent in traffic scenarios, the misclassification of attacked traffic signs by DNN classifiers poses serious safety hazards. Although numerous methods have been proposed for crafting physical adversarial examples that are robust in the real world, most existing defense approaches focus on digital attacks, which necessitate the adversary infiltrating the embedded system; thus, it becomes challenging to obtain results. A reliable approach for defending against physical adversarial traffic signs enables autonomous vehicles to achieve trusted perception of traffic signs. In this paper, we present a deep image prior-based pipeline to defend against robust adversarial traffic signs in the real world, an approach that circumvents the need for prior data sets during training. Our approach protects the safety of autonomous vehicles by performing image reconstruction of captured traffic sign images. The genuine traffic sign class can be inferred by leveraging the consistency of the victim classifier’s decision results for reconstructed images at different stages. Additionally, we evaluate the efficacy of our defense pipeline for detecting other potential types of physical adversarial traffic signs that may exist in the real world, thus demonstrating the generalizability of our approach.

Published
2024
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37. Using Petri Net to diagnose the fault location of Motor

Author

Qiyi Guo, Zhang Minjuan, Huang Shize, and Hu Jingtai

Subjects
Engineering, business.industry, media_common.quotation_subject, Control (management), Petri net, Fault (power engineering), Maintenance engineering, Reliability engineering, Power (physics), Software, business, Function (engineering), Circuit breaker, media_common
Abstract

Generally, small motors are protected by circuit breakers. When the motor fails, it take a long time to restore power, and diagnostic work is done by experienced workers rather than auto diagnostic software. After a detailed study on Control and Protective Switching device, an approach is proposed to realize such a function that can locate the fault by Petri net and expert knowledge. The diagnosis study cases verified the approach is effective and high-speed.

Published
2011

38. Study on magnetizing model of TA core based on Jiles-Atherton theory

Author

Hu Jingtai, Huang Shize, Guo Qi-yi, and Peng Yu

Subjects
Core (optical fiber), Engineering, Magnetization, business.industry, Magnetic modeling, Solid core, Electronic engineering, Mechanics, Numerical models, business, Magnetic hysteresis, Air gap (plumbing), Current transformer
Abstract

The research status of magnetizing model of TA core is analyzed and summarized. Five kinds of magnetizing models are illustrated briefly. Magnetizing model of solid core based on Jiles-Atherton theory is deeply analyzed. And the simulation of dynamic hysteresis loop is realized. Combined with the related theoretical derivation of air gapped core, the magnetizing model based on Jiles-Atherton theory is successfully used in magnetic modeling of air gapped core. Then the simulation of dynamic hysteresis loop is realized. After analysis of the simulation results, some important features of air gapped core's magnetic properties are found.

Published
2011

39. Research on the forecast of the limited temperature rise of motor based on artificial neural network

Author

Hu Jingtai, Huang Shize, Guo Qi-yi, and Guo Yuping

Subjects
Neutral network, Artificial neural network, Computer science, business.industry, Rise time, Intelligent decision support system, Control engineering, Limit (mathematics), business, Automation, Induction motor, Electronic mail, Simulation
Abstract

This article introduce a system based on neutral nekwork. It can estimate the limit temperature rise time of the asynchronous motor. The system avoids the defects of existing motor thermal overload protection methods. Use amount of data to verify the intelligent system can estimate the time from start status to limit temperature status.

Published
2010

40. Reliability Analysis on Dual Power Supply Controller Based on FMEA and FTA

Author

Zhang Minjuan, Guo Qi-yi, Hu Jingtai, and Huang Shize

Subjects
Reliability theory, Fault tree analysis, Engineering, Control theory, business.industry, Stability (learning theory), Hardware_PERFORMANCEANDRELIABILITY, Fault (power engineering), business, Decision tree model, Reliability (statistics), Power (physics), Reliability engineering
Abstract

This paper uses FTA (Fault Tree Analysis) with FMEA (Fault Mode Effect and Analysis) to do the study on reliability of low voltage apparatus. Establishing the fault tree is the most important step in using fault tree analysis. The validity of the tree model will have a great impact on the study result. The combination of the two analysis method can give a full-scale and detailed analysis of the product. Let FMEA get the product's fault mode and fault effect, and use Fault Tree Analysis method to build the fault tree and carry out qualitative analysis and quantitative analysis. The study result gives both theoretical and practical advices on improving the product's stability.

Published
2010

41. DFTSNA: A distributed fault-tolerant shipboard system

Author

Huang Shize, Li Qingnan, Xu Jiangfeng, and Xu Jie

Subjects
Computational Theory and Mathematics, Hardware and Architecture, Computer science, High availability, Reliability (computer networking), Fault tolerance, Software, Computer Science Applications, Theoretical Computer Science, Reliability engineering
Abstract

This paper describes the architecture, fundamental principle and implementation of a distributed fault-tolerant system—DFTSNA. Its objective is to combine extreme reliability with high availability in a shipboard environment. Multi-level fault tolerance is considered and several special-purpose hardware subsystems (F-T clusters) are developed. The physical and functional distribution of the system is emphasized to meet the stringent shipboard requirements. A number of algorithms are produced to support fault-tolerant operation.

Published
1990

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