Detecting Coal Pulverizing System Anomaly Using a Gated Recurrent Unit and Clustering

Chen, Zian; Yan, Zhiyu; Jiang, Haojun; Que, Zijun; Gao, Guozhen; Xu, Zhengguo

doi:10.3390/s20113271

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…In addition, the ACCNN melting error is 2.11% lower than the negative of DCA melting, and the DCA melting error is 6.16%. Therefore, the method mentioned in this document gets the SOTA accuracy in the AC-AID database [24].…”

Section: Comparison Of Error Rate Of Attribute Cooperativementioning

confidence: 98%

Automatic Detection of Small- and Medium-Sized Targets in High-Resolution Images Based on Computer Vision and Deep Learning Energy

Yin

2022

Wireless Communications and Mobile Computing

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In order to solve the problem that it is difficult for traditional manual feature algorithms to deal with complex image features quickly and automatically in high-resolution images, an automatic detection method for small objects in high-resolution images based on computer vision and deep learning energy is proposed. Starting from the deep learning target detection system, this paper studies many problems in the system according to the characteristics of target spatial deformation, more small targets, easy confusion, and rough regional proposal in high-score remote sensing images. The results showed that a combination of spatial deformation strength with spatial deformation resistance and multiphase coupling were all proposed to be comparable with spatial deformation. The process of tracking international products in the system has been extended to study local channels. Pay attention to the operation of the machine, make full use of rich semantic data of local characteristics and the world of spatial points, which will help to improve the accuracy of the purpose of the chaw, and identify ways to create a shared database. The proposed method is evaluated on three attribute, classification joint datasets; ACCNN on the AC-AID dataset, the performance of ACCNN is suboptimal on AC-AID and is very close to the best method for DCA fusion. The average error rate of DCA fusion is 5.67%; on the AC-UCM dataset, the error rate of ACCNN is 2.11% lower than the suboptimal method DCA fusion, and the error rate of DCA fusion is 6.16%. On the AC-Sydney dataset, the error rate of ACCNN is 1.86% lower than the suboptimal method DCA fusion, and the error rate of DCA fusion is 5.99%, which obtains quite competitive results, experimenting with high-resolution images.

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Section: Comparison Of Error Rate Of Attribute Cooperativementioning

confidence: 98%

Automatic Detection of Small- and Medium-Sized Targets in High-Resolution Images Based on Computer Vision and Deep Learning Energy

Yin

2022

Wireless Communications and Mobile Computing

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“…The most striking recent work in this area is found in article [56] by the authors D. Das and S. Das. See also [57] by Wang, Zhao, Zhang, and Hu [58] as well as by Yi and Zhou. Features of transport are found, first of all, in the variety in properties of bulk materials, which in turn have a decisive influence on the properties and characteristics of slurry and the parameters of pressure pipeline transportation.…”

Section: Mathematical Models Of Transportation Of Coal-water Suspensionsmentioning

confidence: 99%

A Review of Methods, and Analytical and Experimental Studies on the Use of Coal–Water Suspensions

2022

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Research in the field of building mathematical models for combustion processes has been ongoing ever since the chemical reactions of combustion were first discovered. The authors of this review have systematized mathematical models of coal–water suspension (CWS) combustion processes, the sequence of analytical and experimental studies, and have also shown the global genesis of the CWS use. In addition, this review touches upon a topic that is inextricably linked with the combustion of CWS, namely their transportation from the place of coal mining to their place of thermal utilization. For developing countries, their own energy independence is in the foreground, as it is the basis for their economic independence and also a means for other sectors of their economy to be protected from the impact of market changes in fuel prices in the future spot world market. The authors of this review explored the possibility of using Kyrgyz brown coal and transporting it through a coal pipeline from a mountainous area to an industrial site for thermal utilization in specialized steam boiler units. As the economic analysis showed, for the conditions of the Republic of Kyrgyzstan, the use of CWS and coal pipelines with rising prices for natural gas is economically justified. The recommendations of the authors are used in scientific reports and methodological recommendations for the energy and mining sectors of the Republic of Kyrgyzstan, how the recommendations can also be applied to similar conditions in the highlands of Russia, China, and India.

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Remaining Useful Life Prediction for Bearings Based on a Gated Recurrent Unit

Que

Jin

2021

IEEE Trans. Instrum. Meas.

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Detecting Coal Pulverizing System Anomaly Using a Gated Recurrent Unit and Clustering

Cited by 4 publications

References 29 publications

Automatic Detection of Small- and Medium-Sized Targets in High-Resolution Images Based on Computer Vision and Deep Learning Energy

Automatic Detection of Small- and Medium-Sized Targets in High-Resolution Images Based on Computer Vision and Deep Learning Energy

A Review of Methods, and Analytical and Experimental Studies on the Use of Coal–Water Suspensions

Remaining Useful Life Prediction for Bearings Based on a Gated Recurrent Unit

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