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Bearing Remaining Life Prediction Method Based on Wavelet Transform Denoising and Feature Preservation CycleGAN under Unbalanced Samples 3

Bearing Remaining Life Prediction Method Based on Wavelet Tr...

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3rd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Wang, Songyang Yu, Jun Zhao, Kun Guo, Zhenyu School of Automation Harbin University of Science and Technology Harbin China School of Automation State Key Laboratory of Process Automation in Mining & Metallurgy Harbin University of Science and Technology Harbin China Cixing Group Co Ltd Beijing China State Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

ISBN: (纸本)9781665492812

With the rapid development of industrialization today, mechanical equipment has undergone significant development and progress in terms of type and quality. Rolling bearings are the key components of mechanical transmission and the most vulnerable mechanical components. Only 10% of rolling bearings can operate as designed. Exploring more scientific and reasonable test methods to predict the remaining service life of rolling bearings can not only reduce operating costs, but also prevent accidents. Life prediction models can be divided into three categories: statistical models, dynamic models, and data-driven prediction models. The existing life prediction models based on statistics, dynamics, etc. continue to increase the workload and difficulty of life prediction in the case of increasingly complex, time-consuming and labor-intensive mechanical equipment. With the rapid development of information technology, industrial process data collection has become efficient and convenient, providing sufficient data resources for data-driven intelligent life prediction technology, and gradually showing great development potential. The remaining life prediction mainly includes two key parts: the feature extraction of bearing vibration data and the construction of life prediction model. Therefore, this paper takes the rolling bearing as the research object, and carries out the remaining life prediction research from the two directions of feature extraction and prediction model construction. In the bearing operation monitoring data, the proportion of the fault data relative to the normal operation data is very small, forming a typical data imbalance phenomenon, and the traditional life prediction is not ideal when dealing with such data. In this paper, a secondary filtering method combining wavelet transform and parameter adaptive variational modal decomposition is used to preprocess the data and enhance the features;and fully consider the influence of unbalanced cluster data, a l

关键词： deep neural network remaining useful life prediction rolling bearing

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Intelligent expert control method and application in SABC grinding circuit based on hybrid model

Intelligent expert control method and application in SABC gr...

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第35届中国控制与决策会议

作者： Guobin Zou Junwu Zhou Daoxi Liu Tao Song Kang Li College of Information Science and Engineering Northeastern University State Key Laboratory of Process Automation in Mining and Metallurgy BGRIMM Technology Group State Key Laboratory of Process Automation in Mining and Metallurgy

SABC grinding circuit(Semi Autogenous+Ball mill+Crushing circuit) is an important typical configuration in comminution production,which has control problems such as uncertainty and strong *** this paper,an intelligent expert control method for grinding process based on hybrid model is ***,a hybrid model driven by mechanism and data is proposed to realize online perception of production indicators such as particle size in cyclone overflow;then,the application scope of expert rules is improved by intelligent correction of uncertainties;finally,the process mechanism knowledge and the online perception data of the hybrid model are integrated to realize the coordinated production of each sub process in the target SABC *** method proposed in this paper has been applied in an intelligent expert control system of SABC circuit in a concentrator to meet the production target.

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Analysis of Operational Data and Self-learning control Rules for mining Mill Equipment

Analysis of Operational Data and Self-learning Control Rules...

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Asian control Conference

作者： Guicheng Wang Liang Yuan Zhicheng Bai Guoliang Cai Ning Hua Xiaobin Li School of Electrical and Electronics Engineering Shanghai Institute of Technology Shanghai China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China Zijin Intelligent Control (Xiamen) Technology Co. Ltd. Xiamen China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The engineering application under industrial big-data analysis is of great significance for improving the optimization effect of enterprise production process control processes. By analyzing the operating principle of the semi-automatic mill and studying its control optimization strategy, based on the operational data of the SAG mill, industrial big-data analysis is adopted to self-learning its control optimization rules. Firstly, SPSS is used to preprocess the high-dimensional process data generated during the operation of the semi-automatic mill. Four parameters, namely power, axial pressure, grinding sound, and grinding concentration, are preliminarily selected. Then, PCA is used to screen and reduce the dimensionality of multidimensional data, and K-Means clustering algorithm is used to classify and identify the reduced dataset. After simulation research, the results show that PCA can reduce the redundancy of SAG mill operation data, and the control optimization rules formed by self-learning can serve as operational guidance for improving the efficiency and energy-saving of SAG mill operation. The effectiveness can be further verified in practical engineering applications in the later stage.

关键词： Dimensionality reduction Energy consumption Technological innovation Redundancy Force process control Clustering algorithms

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Pore structure characterization and seepage analysis of ionic rare earth orebodies based on computed tomography images

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International Journal of mining Science and technology 2022年第2期32卷 411-421页

作者： Xianping Luo Yongbing Zhang Hepeng Zhou Kunzhong He Boyuan Zhang Dongming Zhang Weijing Xiao National Innovation Center for Rare Earth Functional Material Jiangxi University of Science and TechnologyGanzhou 341000China Key Laboratory of Ionic Rare Earth Resources Development and Application Ministry of EducationJiangxi University of Science and TechnologyGanzhou 341000China Jiangxi Key Laboratory of Mining&Metallurgy Environmental Pollution Control Jiangxi University of Science and TechnologyGanzhou 341000China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400044China

Pore network structure of ore body is a diffusion channel of leaching agent solution that exerts a significant influence on *** ore body structure,pore distribution,pore and throat size,and pore network characteristics of topsoil,weathered,and semiweathered layers of ionic rare earth ore in southern Jiangxi Province were explored in this *** effect of leaching operation on the pore structure was investigated,and main factors affecting the seepage were *** showed that the semiweathered layer presents a dense structure and a small number of unconnected *** of topsoil and weathered layers are mainly long and narrow column openings with some planar *** pore distribution and large size span were *** with the weathered layer,the topsoil layer demonstrates larger voids,smaller average pore volume and equivalent radius,and fewer coordination throats;however,the average equivalent radius of the throat in the topsoil layer is larger and largescale channels exist through ore body ***,permeability of the topsoil layer is significantly higher than that of the weathered *** clay minerals migrate easily and the occurrence of silting in the small porosity blocks the throat and significantly decreases the permeability of the ore body in the leaching *** equivalent radius of the throat is the key to the *** the migration of fine particles is an effective measure to protect the throat and shorten the leaching period.

关键词： Ionic rare earth ore CT scanning 3D visualization Pore characteristics Permeability

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Intelligent expert control method and application in SABC grinding circuit based on hybrid model

Intelligent expert control method and application in SABC gr...

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Chinese control and Decision Conference, CCDC

作者： Guobin Zou Junwu Zhou Daoxi Liu Tao Song Kang Li College of Information Science and Engineering Northeastern University State Key Laboratory of Process Automation in Mining and Metallurgy Beijing China BGRIMM Technology Group State Key Laboratory of Process Automation in Mining and Metallurgy Beijing China

SABC grinding circuit (Semi Autogenous + Ball mill + Crushing circuit) is an important typical configuration in comminution production, which has control problems such as uncertainty and strong coupling. In this paper, an intelligent expert control method for grinding process based on hybrid model is proposed. First, a hybrid model driven by mechanism and data is proposed to realize online perception of production indicators such as particle size in cyclone overflow; then, the application scope of expert rules is improved by intelligent correction of uncertainties; finally, the process mechanism knowledge and the online perception data of the hybrid model are integrated to realize the coordinated production of each sub process in the target SABC circuit. The method proposed in this paper has been applied in an intelligent expert control system of SABC circuit in a concentrator to meet the production target.

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key technologies for intelligent mining of underground metal mines

MetaResource

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MetaResource 2024年第1期1卷 13-22页

作者： Kai Zhan Yuansheng Zhang Zhaoyang Ma Xu Liu Xiao Lv Guanzhou Liu Huxin Wang Xincheng Liang BGRIMM Technology Group BeijingChina BGRIMM Intelligent Technology Co.Ltd BeijingChina State Key Laboratory of Intelligent Optimized Manufacturing in Mining&Metallurgy Process BeijingChina

Currently,global mining development has entered a new historical *** the gradual depletion of shallow mineral resources and the increasing proven reserves of deep resources,deep resource exploitation has become a global mining ***,deep resource development faces numerous challenges,including product pricing,production costs,operational safety,and workforce *** development of intelligent and even autonomous mining technologies,along with the establishment of smart mines,has become an inevitable choice for deep resource exploitation.A key technology and complete technical system for underground metal mine intelligent mining is constructed around the mining production process,with"ore flow"as the main ***"equipment intelligence","precise positioning","real-time dispatching","high-speed communication",and"continuous mining"as the main themes,remote,tele-controlled,and intelligent mine production management is being *** achievements are demonstrated in engineering applications at multiple mining enterprises,providing theoretical foundations and technical support for the intelligent,efficient,and green development of deep mineral resources.

关键词： intelligent mining metal mines intelligent equipment real time dispatching cluster control

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Semantic Segmentation Research of Motion Blurred Images by Event Camera

Semantic Segmentation Research of Motion Blurred Images by E...

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Conference on Vehicle control and Intelligence (CVCI)

作者： Xiangyong Liu Fengfeng Yin Wei Jiang Siwen Fan College of Automotive Studies Tongji University Shanghai China State Key Laboratory of Process Automation in Mining & Metallurgy and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Bgrimm Technology Group Shanghai China Department of Electromechanical Engineering University of Macau Shanghai China State Key Laboratory of Process Automation in Mining & Metallurgy and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Bgrimm Technology Group Beijing China Linyi Engineering Branch China Railway Jinan Group Co Ltd Linyi China School of Mechatronical Engineering: Name of Organization Shanghai China

The semantic segmentation of road objects is a prerequisite for autonomous driving. Rapid or bumpy movement of vehicles can lead to the images to be blurred, which reduces the safety of autonomous driving. This study combines the dynamic visual sensor (DVS) and RGB camera to improve the detection accuracy of road semantic segmentation. Firstly, based on DVS and RGB images, we develop two datasets of blurred images, including the stone and run datasets. Then, a double channels’ detection network is designed with several Swin-transformer modules, and the two channels are designed to extract features from DVS and RGB images, respectively. In addition, a feature fusion module is designed to extract attention from DVS images. Finally, experiments demonstrate that our proposed double-channels’ fusion method achieves the state-of-the-art segmentation performance for blurred images.

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Inspection trolley based on the distance detection obstacle

Inspection trolley based on the distance detection obstacle

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Chinese control and Decision Conference, CCDC

作者： Guicheng Wang Ao Sheng Xiaobin Li Min Zhang Changliang Guan Fengfeng Yin School of Electrical and Electronics Engineering Shanghai Institute of Technology Shanghai China Library Shanghai Institute of Technology Shanghai China Zijin Intelligent Control (Xiamen) Technology Co. Ltd. Xiamen China State Key Laboratory of Process Automation in Mining & Metallurgy and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

In Industry 4.0 background, unmanned full-process automated production has gradually become a hot topic, and the realization of intelligent and information factory requires the joint cooperation of multiple industries, in which the inspection device that replaces traditional manual work is an inescapable topic. At present, domestic and foreign research on intelligent inspection trolley is focused on obstacle avoidance function based on various sensors. In this context, it is introduced an algorithm based on monocular camera as a sensor, using Python language to access OpenCV library, and utilizing Gaussian filter function and Canny operator-based image contour extraction to complete the distance measurement. The algorithm can achieve the distance measurement and obstacle avoidance function at a lower cost. The test results show that the system can automatically identify the distance of obstacles in the inspection process, and according to the visual information captured by the camera in real time, it can independently generate steering action and collision reminder, and can complete the preliminary requirement of intelligent inspection.

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An online rock lithological detecting method using color and texture analysis

An online rock lithological detecting method using color and...

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Chinese control and Decision Conference, CCDC

作者： Bo Lu Junwu Zhou Qingkai Wang Gang Yu Kang Li School of Information Science and Engineering Northeastern University BGRIMM Technology Group Beijing China BGRIMM Technology Group State Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In the crushing and comminution process, different lithological rocks strongly affect the performance of crushing equipment. However, traditional lithological identification cannot be analyzed in a timely manner for processing control. Many rock lithological classification methods using color images have been proposed in the past, but few have successfully connected their results with online equipment monitoring. In this paper, we have developed an automatic vision system to evaluate rock lithology in real-time using color and texture features. The results show that the proposed method based on color and texture is robust and outperforms previous methods that rely on any single feature alone. This will help achieve reliable and precise control of the Semi-autogenous mill (SAG) feeding process.

关键词： Image color analysis Machine vision process control Color Rocks Real-time systems Minerals

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PHM of Roller Tyre in Nonferrous Metal Crushing process Based on DUAE

PHM of Roller Tyre in Nonferrous Metal Crushing Process Base...

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Chinese control and Decision Conference, CCDC

作者： Zhenyu Guo Yu Fu Kang Li Guobin Zou Qingkai Wang BGRIMM Technology Group State Key Laboratory of Process Automation in Mining and Metallurgy Beijing China College of Information Science and Engineering Northeastem University Shenyang China

The roller mill is a crucial production equipment for the nonferrous metal beneficiation process, responsible for crushing ores. Over time, the roller tyre of the roller mill gradually wears down, ultimately impacting the crushing efficiency. Therefore, Prognostics and Health Management (PHM) of the roller tyre is crucial to enhancing the production efficiency of the roller mill. In this study, a PHM method based on Dual Autoencoder (DUAE) is proposed to predict the grinding roller tyre’s service life. The effectiveness of the proposed PHM method is validated using actual data from a domestic concentrator. This research demonstrates that the PHM of roller tyres can be effectively conducted.

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