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An improved YOLOv7 for the state identification of sliding chairs in railway turnout

High-Speed Railway 2024年第2期2卷 71-76页

作者： Yuan Cao Zongbao Liu Feng Wang Shuai Su Yongkui Sun Wenkun Wang National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong UniversityBeijing 100044China School of Automation and Intelligence Beijing Jiaotong UniversityBeijing 100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing 100044China Zhuzhou CRRC Times Electric Co. LTD.Zhuzhou 412001China

The sliding chairs are important components that support the switch rail conversion in the railway *** to the harsh environmental erosion and the attack from the wheel vibration,the failure rate of the sliding chairs accounts for up to 10%of the total failure number in ***,there is little research carried out in the existing literature to diagnose the deterioration states of the sliding *** fill out this gap,by utilizing the images containing the sliding chairs,we propose an improved You Only Look Once version 7(YOLOv7)to identify the state of the sliding ***,to meet the challenge brought by the small inter-class differences among the sliding chair states,we first integrate the Convolutional Block Attention Module(CBAM)into the YOLOv7 backbone to screen the information conducive to state ***,an extra detector for a small object is customized into the YOLOv7 network in order to detect the small-scale sliding chairs in ***,we revise the localization loss in the objective function as the Efficient Intersection over Union(EIoU)to optimize the design of the aspect ratio,which helps the localization of the sliding ***,to address the issue caused by the varying scales of the sliding chairs,we employ K-means++to optimize the priori selection of the initial anchor ***,based on the images collected from real-world turnouts,the proposed method is verified and the results show that our method outperforms the basic YOLOv7 in the state identification of the sliding chairs with 4%improvements in terms of both mean Average Precision@0.5(mAP@0.5)and F1-score.

关键词： Railway turnout Sliding chairs state identification Object detection

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An on-line capacitor state identification method based on improved RLS

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Transportation Safety and Environment 2021年第3期3卷 231-243页

作者： Shu Cheng Chang Liu Shengxian Xue Maoyu Wang Xun Wu Yu Luo School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China CRRC Changchun Rail Car Co. LtdChangchun 130062China Shenyang Bullet Train Section of China Railway Shenyang Bureau Group Co.Ltd Shenyang 110021China

As an essential part of DC-Link in the power converter,capacitor plays a crucial role in absorbing ripple current and suppressing ripple *** health and residual service life of the DC-Link capacitor is one of the decisive factors for the safety,stability,and efficiency of the system in which it is *** at the shortcomings of existing methods,such as low dynamic sensitivity of data update and fluctuation of identification results,a capacitor state identification method based on improved RLS is proposed in this *** proposed method is optimized by introducing the forgetting factor algorithm and root means square algorithm to modify the iterative formula and final identification *** with existing methods,this method can identify the capacitor’s current state in real time and ***,we successfully verified the accuracy,robustness,and adaptability of the proposed method by a series of experimental tests on a dSPACE platform.

关键词： DC-Link capacitor state identification recursive least square algorithm

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state identification of Automatic Gauge Control Hydraulic Cylinder Using Acoustic Emission

State Identification of Automatic Gauge Control Hydraulic Cy...

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2013年中国智能自动化学术会议

作者： Hongzhi Chen Chao Wu Yanguang Sun Hua Zhao state Key Laboratory of Hybrid Process Industry Automation System and Equipment Technology Automation Research and Design Institute of Metallurgical Industry Drive Department Beijing Aritime Intelligent Control Co.Ltd

The growing requirements of steel products qualities bring even tricky restrictions to the hydraulic cylinder which acts as a screw down to maintain the rolling spaces ***,faults and disfunctions are unavoidable and bring underlying safety *** with un-expected loading is one of major impact that may cause catastrophic consequence happen to the cylinder,as the classical diagnostic process to-some-extent lack of cross-validating and timeconsuming, the paper proposes the potentials of using acoustic emission to fill the *** works include the data acquisition process to record the ultrasound acoustic signals from the hydraulic cylinder,application of modified image based acoustic emission approach to generate visual effects,as well as the application of principal component analysis to project the profiles onto the 3D plane for further *** the analysis of image based profiles,the subtle differences of various cylinder conditions can be examined using the pixel and intensity values. By assessing the projection of profiles in the principal component space,a clear trajectory can be observed with normal and overload conditions allocated upon the positive and negative sides of the *** result provided not only the potential of using acoustic emission for dynamic state identification of the subtle changes,but also opens up the possibility of preventive measures to the cylinder at risks.

关键词： state identification Acoustic emission Automatic gauge control

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identification of Steady state and Transient state

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 261-270页

作者：于生李向舜 School of Automation Wuhan University of TechnologyWuhan 430070China

identification of steady state and transient state plays an important role in modeling,control,optimiza-tion,and fault detection of industrial *** existing methods for state identification are not satisfactory in practical applications due to problems of ideal hypothesis,too many parameters,and poor *** this paper,a novel state identification approach is *** problem of state identification is transformed into finding the noise band of differential *** practical application,automatic selection of noise band amplitude is proposed to make the method convenient to be *** of gross errors,low signal-to-noise ratio and online identification are *** comparison with other two methods shows that the proposed method has better identification *** and experiments also prove the effectiveness and practicability of the proposed method.

关键词： state identification steady state transient state noise band differential signal

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identification of navigation characteristics of single otter trawl vessel using four machine learning models

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Journal of Oceanology and Limnology 2023年第3期41卷 1206-1219页

作者： Qi LIU Yunxia CHEN Haihong MIAO Yingbin WANG School of Fishery Zhejiang Ocean UniversityZhoushan 316022China Zhoushan Ecological Environment Bureau Putuo Branch Zhoushan 316100China Marine Fisheries Bureau of Putuo District Zhoushan 316105China

Fishing logbook records the fishing behaviors and other information of fishing ***,the accuracy of the recorded information is often difficult to guarantee due to the misreport and *** fishing vessel monitoring system(VMS)can monitor and record the navigation information of fishing vessels in real time,and it may be used to improve the accuracy of identifying the state of fishing *** the VMS data and fishing logbook are combined to establish their relationships,then the navigation characteristics and fishing behavior of fishing vessels can be more accurately ***,first,a method for determining the state of VMS data points using fishing log data was ***,the relationship between VMS data and the different states of fishing vessels was further ***,the state of the fishing vessel was predicted using VMS data by building machine learning *** speed,heading,longitude,latitude,and time as features from the VMS data were extracted by matching the VMS and logbook data of three single otter trawl vessels from September 2012 to January 2013,and four machine learning models were established,i.e.,Random Forest(RF),Adaptive Boosting(AdaBoost),K-Nearest Neighbor(KNN),and Gradient Boosting Decision Tree(GBDT)to predict the behavior of fishing *** prediction performances of the models were evaluated by using normalized confusion matrix and receiver operator characteristic *** show that the importance rankings of spatial(longitude and latitude)and time features were higher than those of speed and *** prediction performances of the RF and AdaBoost models were higher than those of the KNN and GBDT *** model showed the highest prediction performance for fishing ***,AdaBoost model exhibited the highest prediction performance for non-fishing *** study offered a technical basis for judging the navigation characteristics of fishing vessels,which improved the alg

关键词： vessel monitoring system(VMS) fishing logbook single otter trawler state identification machine learning

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A Fault Detection and Isolation Method Based on R-Fast ICA and K-Fisher for Roller Bearings on the Urban Rail Vehicles

A Fault Detection and Isolation Method Based on R-Fast ICA a...

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2015年中国智能自动化学术会议

作者： Linlin Kou Yong Qin Xiaoqin Cheng Zhenyu Zhang state Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

Operating status of roller bearings directly affects the safety of the urban rail vehicle,so accurate identification of the state has considerably practical *** fault detection and isolation method of the roller bearing operational was performed by the comprehensive utilization of fast independent component analysis(Fast ICA),and kernel fisher *** ICA method was used to denoise and extract signal with fault *** fault characteristic signal separation used Fast ICA with the normal signal applied as a signal *** Pearson product-moment correlation coefficient had been used to determine which component was the extracted one we *** eight indicators were extracted as roller bearings’ state features after Fast *** on the features under different states,the states of roller bearings on the urban rail vehicles were identified by the K-Fisher *** experiment results indicated that the accuracies of the multiple states identification was more than 96 %,and verified the superiority of the proposed method.

关键词： Roller bearings state identification R-Fast ICA K-fisher

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