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Research on Rolling Bearing Fault Diagnosis Method of Fuzzy Broad Learning System Based on Genetic Algorithm Optimization 1

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Wu, Le Zhang, Chao Fei, Hongbo Qin, Feifan Liu, Guiyi Xu, Shuai Ouyang, Bing Wu, Yangbiao Zhang, Jing School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems in Inner Mongolia Autonomous Region Baotou014010 China

ISBN: (数字)9783031694837

ISBN: (纸本)9783031694820

The most common motor fault is the failure of bearing, and the traditional fault diagnosis method requires manual extraction of features, which has high uncertainty and complexity. In this paper, a motor bearing fault diagnosis method based on Gramian angular field image coding and CNN-SVM is proposed, which has three stages, firstly, the original bearing vibration signal is converted into a two-dimensional scale diagram by using Gramian angular field image coding. Second, next, an enhanced CNN model is employed to quickly and accurately identify the elements of the converted image. Finally, SVM are used as final classifiers to further improve the accuracy and speed of fault classification. In the experimental design, the model was verified and analyzed several times by using the bearing fault dataset of Case Western Reserve University, which verified the feasibility and superiority of the method and provided a theoretical basis for guiding bearing maintenance decisions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Image coding

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Sensitivity analysis and probability modelling of the structural response of a single-layer reticulated dome subjected to an external blast loading

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Defence technology（防务技术） 2023年第5期23卷 152-163页

作者： Shao-bo Qi Guang-yan Huang Xu-dong Zhi Feng Fan State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing100081PR China Key Lab of Structure Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of TechnologyHarbin150090China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin150090China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120China

The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic *** deterministic methods for predicting the consequences of specific explosions do not account for these ***,the impact of the uncertainties associated with these input variables on the structures’response needs to be studied and *** this study,a parametric uncertainty analysis was conducted ***,local and global sensitivity analyses were carried out to identify the drivers of the structural dynamic response.A probabilistic structural response model was established based on sensitive variables and a reasonable sample ***,some deterministic empirical methods for explosion-resistance design,including the plane blast load model of CONWEP,the curved blast load model under the 50%assurance level,and the 20%mass-increased method,were used for evaluating their *** results of the analyses revealed that the structural response of a single-layer reticulated dome to an external blast loading is lognormally ***,the MB0.5 method based on the curved reflector load model yielded results with a relatively stable assurance rate and reliability,but CONWEP did not;thus,the 1.2MB0.5 method can be used for making high-confidence simple *** addition,the results indicated that the structural response is very sensitive to the explosion *** on these results,it is suggested that for explosion proofing,setting up a defensive barrier is more effective than structural strengthening.

关键词： Dome structure Blast load uncertainty Sensitivity analysis Probabilistic investigation Reliability evaluation

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External blast flow field evolution and response mechanism of single-layer reticulated dome structure

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Defence technology（防务技术） 2023年第6期24卷 241-253页

Single-layer reticulated dome structure are commonly high-profile building in the public and can be attractive targets for terrorist bombings,so the public can benefit from enhanced safety with a stronger understanding of the behavior of single-layer reticulated dome structure under *** paper investigates the fluid-structure interaction process and the dynamic response performance of the singlelayer reticulated dome under external blast *** experimental and numerical results shown that structural deformation is remarkably delayed compared with the velocity of blast wave,which advises the dynamic response of large-span reticulated dome structure has a negligible effect on the blast wave propagation under *** failure modes are identified by comparing the plastic development of each ring and the residual spatial geometric of the structure,i.e.,minor vibration,local depression,severe damage,and overall *** plastic deformation energy and the displacement potential energy of the structure are the main consumers of the blast *** addition,the stress performance of the vertex member and the deep plastic ratio of the whole structure can serve as qualitative indicators to distinguish different failure modes.

关键词： External blast loading Reticulated dome structure Fluid-structure interaction dynamic response mode Response mechanism

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Deep Learning Based Signal Detector for OFDM Systems

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China Communications 2023年第12期20卷 66-77页

作者： Guangliang Pan Wei Wang Minglei Li Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China College of Control Science and Engineering China University of Petroleum(East China)Qingdao 266580China

In this paper,we propose a novel deep learning(DL)-based receiver design for orthogonal frequency division multiplexing(OFDM)*** entire process of channel estimation,equalization,and signal detection is replaced by a neural network(NN),and hence,the detector is called a NN detector(N^(2)D).First,an OFDM signal model is *** analyze both temporal and spectral characteristics of OFDM signals,which are the motivation for ***,the generated data based on the simulation of channel statistics is used for offline training of bi-directional long short-term memory(Bi-LSTM)***,a discriminator(F)is added to the input of Bi-LSTM NN to look for subcarrier transmission data with optimal channel gain(OCG),which can greatly improve the performance of the ***,the trained N^(2)D is used for online recovery of OFDM *** performance of the proposed N^(2)D is analyzed theoretically in terms of bit error rate(BER)by Monte Carlo simulation under different parameter *** simulation results demonstrate that the BER of N^(2)D is obviously lower than other algorithms,especially at high signal-to-noise ratios(SNRs).Meanwhile,the proposed N^(2)D is robust to the fluctuation of parameter values.

关键词： channel estimation deep learning OFDM optimal channel gain signal detection

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Numerical simulation of the forming characteristics of the circumferential MEFP with integrated shell and liner 5

Numerical simulation of the forming characteristics of the c...

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2021 5th International Conference on Fluid Mechanics and Industrial Applications, FMIA 2021

作者： Ma, Guangsong He, Guanglin Zhang, Yulong Qiao, Zenghui Science and Technology on Electromechanical Dynamic Control Laboratory Beijing Institute of Technology Beijing China PLA Strategic Support Force Beijing10081 China

To study the forming characteristics of the multiple explosively formed projectile (MEFP) warhead of the small-caliber grenade with the integrated design of the liner and shell, the liner thickness is less than the shell thickness as the research object, and LS-DYNA is used for numerical simulation. On this basis, the influence of the curvature radius and the center thickness of the liner on the forming results of the projectile is further studied, and the integrated design of the MEFP forming result and the separate design were compared and analyzed. The simulation results show that, when the liner thickness structure is smaller than the shell thickness, the projectile shape is better. The shape of MEFP with the integral design is better than the separate design, and the forming velocity of the integral design is slightly lower than the separate design with the curvature radius increase of the outer and inner wall. When the liner curvature radius is fixed, the shape of MEFP with the integral design is better than the separate design, and the forming velocity of MEFP with the integral design is slightly less than the separate design with the liner center thickness increase. The results show that the forming characteristics of circumferential MEFP of integrated design and separate design have a certain similarity. The shape of MEFP with the integrated design is better than that with separate design, however, the forming velocity of MEFP with the integrated design is slightly lower than that with separate design. © Published under licence by IOP Publishing Ltd.

关键词： Projectiles

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Rolling Bearing Fault Diagnosis Method Based on Wavelet Time–Frequency Map and Improved ConvNext 1

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and Performance Engineering Network, TEPEN 2023

作者： Qin, Feifan Zhang, Chao Wang, Jianguo Zhao, Wentao Li, Jianjun Liu, Tongtong College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014010 China

ISBN: (数字)9783031494215

ISBN: (纸本)9783031494208

The purpose of this article is to address the issue of traditional fault diagnosis methods for rolling bearings, which are unable to accurately diagnose the fault signals of non-linear and non-stationary rolling bearings. To achieve this goal, this article proposes a rolling bearing fault diagnosis method based on wavelet time–frequency maps and an improved ConvNext model. This method first leverages the advantages of wavelet time–frequency analysis to transform the original signal into a two-dimensional wavelet time–frequency map. Subsequently, a new generation of convolutional neural networks, ConvNext, is utilized as the foundational network for rolling bearing fault diagnosis models. The network is enhanced by introducing lightweight attention modules, such as the Convolutional Block Attention Module (CBAM) and the Efficient Channel Attention Network (ECA), to improve the Block modules in the basic network. The wavelet time–frequency map is then used as a feature map input to the improved ConvNext network for training, aiming to achieve rolling bearing fault diagnosis recognition. Finally, experimental results demonstrate that the proposed method exhibits a high level of fault recognition accuracy and stability in laboratory data. It also demonstrates a certain degree of robustness, offering a new solution for rolling bearing fault diagnosis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Failure analysis

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A Lightweight Network for the Hot-Rolled Steel Strip Surface Defect Detection

A Lightweight Network for the Hot-Rolled Steel Strip Surface...

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作者： Liu, Jiaxue Zhang, Chao Li, Jianjun College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014000 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014000 China

ISBN: (纸本)9783031494123

With the amazing development of deep learning, more and more research apply it to the field of computer vision in recent years. However, most object detection networks are difficult to apply in our real life because of the complex structures and numerous parameters. So, it is meaningful to focus our attention on designing some lightweight network architecture in the future. In this paper, we will propose a new convolutional neural network that named M2I3-SSD (MobileNetV2-InceptionV3 Single Shot MultiBox Detector) and its variant named M2I3R-SSD (MobileNetV2-InceptionV3-NoRelu6 Single Shot MultiBox Detector) to detect the surface defection of the hot-rolled steel strip. Then fine-tune as a transfer learning method was used in our paper to reduce the overfitting problem caused by small database. And we do a lot of experiments to verify the performance about the proposed model in the end. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Object detection

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Bearing Remaining Life Prediction Based on Temporal Convolutional Networks with Hybrid Dilated Convolutions

Bearing Remaining Life Prediction Based on Temporal Convolut...

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作者： Zhang, Jing Li, Haiguang Zhang, Chao Wu, Yangbiao Liu, Guiyi College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China College of Energy and Environment Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China

ISBN: (纸本)9783031494208

Rolling bearings play a crucial role in mechanical equipment, impacting both running time and costs significantly. Accurate prediction of remaining life allows timely maintenance actions to be taken, thereby reducing downtime and maintenance costs, and is essential for effective equipment maintenance and operation. In this paper, we propose a new bearing life prediction model based on hybrid dilated time convolutional network structure. We address the issue of convolutional kernel discontinuity caused by empty convolutions in the Temporal Convolutional Network by introducing the Hybrid Dilated Convolution technique. This alleviates the problem of local feature loss to some extent and enables more global features to be captured. Finally, the effectiveness of the model was validated on the publicly available FEMTO-ST dataset. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Convolution

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Dual Functional Diblock Amino Acid Copolymer Displaying Synergistic Effect with Curcumin against MRSA and Encapsulation of Curcumin

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Chinese Journal of Chemistry 2023年第23期41卷 3333-3338页

作者： Yueming Wu Yuan Chen Haowen Yu Alideertu Dong Runhui Liu State Key Laboratory of Bioreactor Engineering East China University of Science and TechnologyShanghai200237 China Key Laboratory for Ultrafine Materials of Ministry of Education Frontiers Science Center for Materiobiology and Dynamic Chemistry Shanghai Frontiers Science Center of Optogenetic Techniques for Cell MetabolismResearch Center for Biomedical Materials of Ministry of EducationSchool of Materials Science and EngineeringEast China University of Science and TechnologyShanghai200237 China Engineering Research Center of Dairy Quality and Safety Control Technology Ministry of EducationInner Mongolia UniversityHohhotInner Mongolia010021 China

The intensive use of antibiotics intensifies the development of bacterial resistance,which has become a serious problem ***-resistant Staphylococcus aureus(MRSA)has resulted in significant morbidity and ***,it is an urgent need to develop new antimicrobial drugs and administration ***,we report a dual functional diblock copolymer PLL20-b-PBLG20,which was prepared by superfast and water-insensitive polymerization on N-carboxyanhydrides(NCA)initiated by tetraalkylammonium *** addition to direct antimicrobial activity,PLL20-b-PBLG20 also exerts a synergistic bactericidal effect against MRSA with curcumin,a plant extract with antibacterial ***,PLL20-b-PBLG20 successfully encapsulates curcumin to form nanoparticles via *** combination of dual functional PLL20-b-PBLG20 and curcumin holds promise in combating MRSA infections.

关键词： Amino acid polymer Antimicrobial Synergy Encapsulation MRSA

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Time-series Data Modeling Guided by Visual Information

Time-series Data Modeling Guided by Visual Information

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International Conference on Information, Communication and Networks (ICICN)

作者： Ke Zhang Junzheng Wang Xiang Zhang Yu Shi Ting Wang School of Automation Beijing Institute of Technology Beijing China Science and Technology on Electromechanical Dynamic Control Laboratory Xi’an Institute of Electron-mechanical Information Technology Xi’an China

Time-series data typically contain issues such as missing data and noise, which can impact the model's precision and stability. This paper proposes a Transformer structure-based visual information-guided temporal data modeling algorithm to address the issues as mentioned above. The algorithm effectively captures the time-series structure of the time-series data, thereby enhancing the model's precision and stability. To evaluate the performance of the proposed algorithm, a dataset containing visual information aligned with time-series data is compiled, and a comprehensive quantitative and qualitative analysis is performed. Conduct a comprehensive quantitative and qualitative analysis. The results indicate that visual information can assist time-series data in capturing the intricate dynamics of the time-series data, thereby enhancing the performance of the proposed algorithm and facilitating its comprehension. The results indicate that visual information can assist time-series data in capturing the complex dynamics of time-series data, and thus in comprehending and predicting their behavior and trends. The application of this algorithm will advance research in the field of modeling and predicting time series data. Applying this algorithm will advance research and practice in modeling and forecasting time series data.

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