Search

Your search keyword '"Yan, Gaowei"' showing total 192 results
Start Over Author "Yan, Gaowei" Search Limiters Academic (Peer-Reviewed) Journals
192 results on '"Yan, Gaowei"'

12. An Improved A* Algorithm Based on Localizability Estimation for Mobile Robots

Author

Yang, Rui, Dai, Kun, Yan, Gaowei, Cheng, Lan, 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, Li, Yong, 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, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, and Deng, Zhidong, editor

Published
2022
Full Text
View/download PDF

16. Coal flow detection method for conveyor belt based on TOF depth image restoration

Author

WANG Xinyue, QIAO Tiezhu, PANG Yusong, and YAN Gaowei

Subjects
belt conveyor, coal flow detection, tof camera, depth image restoration, edge correction, Mining engineering. Metallurgy, TN1-997
Abstract

In the traditional belt conveyor coal flow detection device, the nuclear belt scale has certain safety and environmental protection hidden dangers, and the detection precision of electronic belt scale is easily affected by the factors such as belt tension and stiffness. Moreover, non-contact detection methods based on technologies such as ultrasound, linear laser stripes and binocular vision have problems such as poor real-time performance and large measurement errors. A coal flow detection method for conveyor belt based on time-of-flight(TOF) depth image restoration is proposed. The TOF camera is used to obtain the coal conveying image of the conveyor belt. The TOF image is equalized, and the frame difference method and the boundary following algorithm are used to remove the background noise and obtain the coal region of interest. In order to solve the problem of inaccurate edge information caused by flying pixel noise and multi-path error noise at the edge of TOF depth image, the intensity image-guided depth image restoration algorithm is proposed. The Canny edge detection algorithm is used to find similar edges between the depth image and the intensity image. Based on the effective edge information of the intensity image, the unreliable data of the edge of the depth image is corrected. Furthermore, the high-precision depth images are obtained based on Navier-Stokes equation and median filter. The coal area is divided at the pixel level, the coal volume calculation model is established to obtain coal flow of conveyor belt by combining the conveyor belt speed. The experimental results show that the detection error is less than 3.78%, the standard deviation is less than 0.491 and the average processing time is 83 ms, which meets the actual production requirements.

Published
2022
Full Text
View/download PDF

23. Unsupervised Regression Model of Geodesic Flow Kernel Based on Dynamic Independent Component Analysis and Dynamic Principal Component Analysis

Author

LAI Yanbo, YAN Gaowei, CHENG Lan, and CHEN Zehua

Subjects
soft sensor, geodesic flow kernel, dynamic characteristics, dynamic independent component analysis, dynamic principal component analysis, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

It is difficult to accurately measure parameters by using the traditional soft sensor algorithm when the working condition of industrial process is changed. Therefore, a transfer learning strategy is introduced based on geodesic flow kernel to solve this problem. At the same time, the method is optimized to solve the problems of dynamic characteristic extraction and incomplete Gaussian distribution in industrial process. The augmented matrix is first constructed to deal with the dynamic characteristics of the process. Independent component analysis and principal component analysis are performed on the processed data to extract the non-Gaussian and Gaussian information of the source domain and the target domain. Then, the non-Gaussian and Gaussian information of the source domain is adapted to the target domain respectively on the Grassmann manifold. Finally, the maximum mean discrepancy is used to measure the distribution between the source domain and the target domain after domain adaptation, and the calculated results are applied to construct the weight of the model based on the source domain after domain adaptation. The results show that the method not only reduces the difference of distribution between the source domain and the target domain, but also solves the problems of dynamic characteristic extraction and incomplete Gaussian distribution in industrial process. The validity and the practicability of the model are proved by experiments on Tennessee Eastman data.

Published
2020
Full Text
View/download PDF

28. Speed regulation energy saving method of belt conveyor based on preview control

Author

HAN Dongsheng, DU Yonggui, PANG Yusong, QIAO Tiezhu, and YAN Gaowei

Subjects
belt conveyor, preview control, kalman filter, speed regulation, energy saving, Mining engineering. Metallurgy, TN1-997
Abstract

Current speed regulation energy saving methods all regulate speed of belt conveyor in short time, and speed mutation is easy to cause tear and slipping of belt conveyor. In view of above problem, a speed regulation energy saving method of belt conveyor based on preview control was proposed. According to material carrying capacity of preceding belt conveyor, speed which makes succeeding belt conveyor run at rated carrying capacity is calculated, and running speed of the succeeding belt conveyor is adjusted through preview control. Aiming at negative influence of noise on speed regulation effect, Kalman filter is used to estimate state of the controlled belt conveyor in the process of preview control, which can weaken noise interference and smooth speed regulation process. The simulation results show that the method can fully utilize carrying capacity of belt conveyor, reduce power consumption of belt conveyor, and achieve purpose of speed regulation and energy saving on the basis of ensuring safe operation of belt conveyor.

Published
2018
Full Text
View/download PDF

40. Knowledge-Based Genetic Algorithms

Author

Yan, Gaowei, Xie, Gang, Chen, Zehua, Xie, Keming, Carbonell, Jaime G., editor, Siekmann, J\'org, editor, Wang, Guoyin, editor, Li, Tianrui, editor, Grzymala-Busse, Jerzy W., editor, Miao, Duoqian, editor, Skowron, Andrzej, editor, and Yao, Yiyu, editor

Published
2008
Full Text
View/download PDF

41. Application of BP Network-Based Multi-sensor Fusion Techniques in Measurement of the Unburned Carbon in Fly Ash

Author

Yan, Gaowei, Xie, Gang, Xie, Keming, Chen, Zehua, Wang, Hongbing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Jun, editor, Liao, Xiao-Feng, editor, and Yi, Zhang, editor

Published
2005
Full Text
View/download PDF

42. The Application of IMEA in Nonlinearity Correction of VCO Frequency Modulation

Author

Yan, Gaowei, Xie, Jun, Xie, Keming, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Lipo, editor, Chen, Ke, editor, and Ong, Yew Soon, editor

Published
2005
Full Text
View/download PDF

43. MEA Based Nonlinearity Correction Algorithm for the VCO of LFMCW Radar Level Gauge

Author

Yan, Gaowei, Xie, Gang, Qiu, Yuxia, Chen, Zehua, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Ślęzak, Dominik, editor, Wang, Guoyin, editor, Szczuka, Marcin, editor, Düntsch, Ivo, editor, and Yao, Yiyu, editor

Published
2005
Full Text
View/download PDF

45. Multi-source unsupervised soft sensor based on joint distribution alignment and mapping structure preservation

Author

Zhang, Z. (author), Yan, Gaowei (author), Qiao, Tiezhu (author), Fang, Yaling (author), Pang, Y. (author), Zhang, Z. (author), Yan, Gaowei (author), Qiao, Tiezhu (author), Fang, Yaling (author), and Pang, Y. (author)

Abstract

Aiming at the problem of mismatch between real-time data distribution and modeling data distribution caused by the change of working conditions in industrial process, which leads to the performance deterioration of the soft sensor model, a multi-source unsupervised soft sensor method based on joint distribution alignment and mapping structure preservation is proposed. Firstly, the method uses the hypergraph to establish the complex structure of feature and label, and clusters the hypergraph matrix in multiple views to completely construct the class pseudo label; then dynamic distribution alignment is used to adapt marginal distribution and conditional distribution between the data of historical working conditions and the current working conditions, and the hypergraph Laplacian operator is introduced for manifold regularization to prevent the mapping relationship between feature and label from being destroyed; finally, similar working conditions are introduced to further enhance the robustness of the model. The experimental results show that compared with the traditional unsupervised soft sensor methods, the method used in this paper can effectively improve the prediction accuracy of the model., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

Published
2022
Full Text
View/download PDF

46. Dynamic transfer partial least squares for domain adaptive regression

Author

Zhao, Zhijun (author), Yan, Gaowei (author), Ren, Mifeng (author), Cheng, Lan (author), Zhu, Zhujun (author), Pang, Y. (author), Zhao, Zhijun (author), Yan, Gaowei (author), Ren, Mifeng (author), Cheng, Lan (author), Zhu, Zhujun (author), and Pang, Y. (author)

Abstract

The traditional soft sensor models are based on the independent and identical distribution assumption, which are difficult to adapt to changes in data distribution under multiple operating conditions, resulting in model performance deterioration. The domain adaptive transfer learning methods learn knowledge in different domains by means of distribution alignment, which can reduce the impact of data distribution differences, and effectively improve the generalization ability of the model. However, most of the existing models established by domain adaptation methods are static models, which cannot reflect the dynamic characteristics of the system, and have limited prediction accuracy when applied to dynamic system modeling under multiple operating conditions. The dynamic system modeling methods can effectively extract the dynamic characteristics of the data, but they cannot deal with the concept drift problem caused by the change of data distribution. This paper proposes a new dynamic transfer partial least squares method, which maps the high-dimensional process data into the low-dimensional latent variable subspace, establishes the dynamic regression relationship between the latent variables and the labels, and realizes the systematic dynamic modeling, at the same time, the model adds regular terms for distribution alignment and structure preservation, which realizes dynamic alignment of data distribution difference. The effectiveness of the proposed method is validated on three publicly available industrial process datasets., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results