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RISS 인기검색어
- 검색키워드
- 저자 : Chunliang Zhang (검색결과 6 건)
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Research on bolt contour extraction and counting of locomotive running gear based on deep learning
Yong Zhang,Bo Long,Huajun Wang,Chunliang Gao 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5
The detection of abnormal running gear is essential to a locomotive’s daily maintenance, with the posture and quantity of various small bolts being important indicators to judge whether the locomotive is running safely. Traditional detection algorithms are easily affected by light changes, stain coverage, and image distortion, which is difficult to meet the detection requirements. Thus this paper proposes a deep learning based on bolt detection method that is appropriate for locomotive running gears. First, a bolt segmentation network was developed based on an improved U-netthat compensates the image information loss after multiple cross fusions involving the fusion of front and back convolution layer feature images. Furthermore, the proposed network utilizes the PReLU activation function and employs the concept structure to optimize the convolution method. This strategy aims to improve further the model’s segmentation accuracy and convergence speed. On this basis, we exploited several morphological transformations to improve the contour detection accuracy and ensure the bolt counting accuracy. The experimental results on the mainline running train data highlight that, compared with U-net, the proposed network’s recall rate and the mean intersection over union value are increased by 5.38 and 14.3, respectively. Furthermore, the bolt counting method’s loss function and mean absolute errors are significantly reduced compared with the contour extraction algorithm.
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Xiaolong Li,Shubao Geng,Hanjie Chen,정철의,Chunliang Wang,Hongtao Tu,Jinyong Zhang 한국응용곤충학회 2017 Journal of Asia-Pacific Entomology Vol.20 No.1
The apple leafminer, Phyllonorycter ringoniella Matsumura (Lepidoptera: Gracillariidae), is an important insect pest of apple, with four to six generations a year in Korea, Japan, and China. The effect of mass trapping with sex pheromone traps on P. ringoniellawas investigated in apple orchards in 2015 in Yinchuan, China. Trap density treatments were 0, 75, 150, and 225/ha in the Control, T1, T2, and T3 orchard blocks, respectively. Average numbers of male catches permonitoring trapwere significantly lower in T2 and T3 treatments and highest in the control. Control efficiencies estimated fromthe leaf damage were 86.67±4.71, 97.23±3.93, and 100% in T1, T2, and T3, respectively. Significant within-tree migration of the moths from the lower part to the upper part was indicated by the shift of trap catches from lower (1–2 m high) to upper portions (3 m high) of the tree from early August. Mass trapping with sex pheromone traps can be one effective and environmentally friendly method to reduce the P. ringoniella populations in apple orchards. Trap density of 150/ha and hanging at 2 m height was recommended for growers to control and monitor its population, respectively
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Improved RFID Middleware Architecture and Optimal Algorithm based on Internet of Things
Weiqing Qu,Yuedou Qi,Qi Zhang,Chunliang Zhou 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.11
Internet of things is a wireless data communications technology, while radio frequency identification (RFID) is an emerging technology in the automatic identification of the Internet of things. In fact, it means the use of RFID system identification technology through the Internet to achieve the application of information interconnection and sharing. In this paper, the author analyzes an improved RFID middleware architecture and optimal algorithm based on internet of things. Through the analysis of RFID middleware technology, we put forward an optimized load balancing algorithm. The results show that the optimization algorithm is superior to the existing algorithms in the average time of load balancing and label processing.
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Experimental study of the association between sandstone size effect and strain rate effect
Siming Kao,Guang-Ming Zhao,Wensong Xu,Xiang Cheng,Chunliang Dong,Ruofei Zhang 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.9
The association between sandstone size effect and strain rate effect were investigated experimentally with a split Hopkinson pressure bar (SHPB) system. The sandstone samples with Φ50 mm and different lengths were loaded under the constant ratio of punch velocity to sample length to study their size effects. Sandstone samples with constant length of 25 mm were taken as the reference to study their strain rate effects. Results indicate that, under the same velocity of the punch, strain rate of each sandstone sample is inversely proportional sample length; dynamic strength of sandstone increases with the strain rate and the length to diameter ratio (L/D), and presents a quadratic curvilinear relation with strain rate while presenting a cubic curvilinear relation with sample L/D; the reasonable L/D of Φ50 mm sandstone samples ranges from 0.5 to 0.8; that dissipated energy can present a fixed proportional relation with punch kinetic energy is unrelated to sample length.
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Dynamic model-based back-stepping control design for-trajectory tracking of seabed tracked vehicles
Hong Xiong,Yuxiang Chen,Yuxiao Li,Hong Zhu,Chunliang Yu,Jingguo Zhang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.8
Tracked vehicles are widely used as seabed production tools to ensure a stable motion on soft sediments. However, the slippage resulted from the complex nonlinear trackterrain interaction while trajectory tracking causes problems for precisely predicting the motion. Accordingly, a “proper” motion control method is necessitated. This work proposes a novel dynamic modeling approach and motion control method for seabed tracked vehicles under nonholonomic constraints, with the inclusion of the effects of the bulldozing resistance, compaction resistance, water resistance, and the direction and velocity of the current. The backstepping control based on a model-based proportional-integral-derivative three degrees-offreedom method is applied in the controller, and its stability is proven by Lyapunov theory. The effectiveness and accuracy of the method in controlling seabed tracked vehicles are validated by simulation examples.
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An Adaptive Neural Sliding Mode Control with ESO for Uncertain Nonlinear Systems
Jianhui Wang,Peisen Zhu,Biaotao He,Guiyang Deng,Chunliang Zhang,Xing Huang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
An adaptive neural sliding mode control with ESO for uncertain nonlinear systems is proposed to improve the stability of the control system. Any control system inevitably exists uncertain disturbances and nonlinearities which severely affect the control performance and stability. Neural network can be utilized to approximate the uncertain nonlinearities. Nevertheless, it produces approximate errors, which will become more difficult to deal with as the order of the system increases. Moreover, these errors and uncertain disturbances will result in a consequence that the control system can be unable to converge quickly, and has to deal with a lot of calculations. Therefore, in order to perfect the performance and stability of the control system, this paper combines sliding mode control and ESO, and designs an adaptive neural control method. The simulation results illustrate that the improved system has superior tracking performance and anti-interference ability.
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