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Deep Multimodal Learning and Fusion Based intelligent Fault Diagnosis Approach

Journal of Beijing Institute of Technology 2021年第2期30卷 172-185页

作者： Huifang Li Jianghang Huang Jingwei Huang Senchun Chai Leilei Zhao Yuanqing Xia Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of TechnologyBeijing 100081China

Industrial Internet of Things(IoT)connecting society and industrial systems represents a tremendous and promising paradigm *** IoT,multimodal and heterogeneous data from industrial devices can be easily collected,and further analyzed to discover device maintenance and health related potential knowledge *** data-based fault diagnosis for industrial devices is very helpful to the sustainability and applicability of an IoT *** how to efficiently use and fuse this multimodal heterogeneous data to realize intelligent fault diagnosis is still a *** this paper,a novel Deep Multimodal Learning and Fusion(DMLF)based fault diagnosis method is proposed for addressing heterogeneous data from IoT environments where industrial devices ***,a DMLF model is designed by combining a Convolution Neural Network(CNN)and Stacked Denoising Autoencoder(SDAE)together to capture more comprehensive fault knowledge and extract features from different modal ***,these multimodal features are seamlessly integrated at a fusion layer and the resulting fused features are further used to train a classifier for recognizing potential ***,a two-stage training algorithm is proposed by combining supervised pre-training and fine-tuning to simplify the training process for deep structure models.A series of experiments are conducted over multimodal heterogeneous data from a gear device to verify our proposed fault diagnosis *** experimental results show that our method outperforms the benchmarking ones in fault diagnosis accuracy.

关键词： fault diagnosis deep learning multimodal heterogeneous data multimodal fused features

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Collaborative SLAM system Based on Shared Priori Maps

Collaborative SLAM System Based on Shared Priori Maps

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Wu, Chunxu Shou, Yicheng Li, Zhen Liu, Xiangdong School of Automation and Key Laboratory for Intelligent Control and Decision on Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789811966125

Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mapping

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Distributed Group Coordination of Random Communication Constrained Cyber-Physical systems Using Cloud Edge Computing

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2024年 2卷 196-205页

作者： Ren, Hongru Long, Yinren Ma, Hui Li, Hongyi Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Guangdong University of Technology School of Mathematics and Statistics Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing Key Laboratory of Generic Technology and System of Service Robots Chongqing400715 China

This paper studied the distributed group coordinated control problem of cyber-physical systems (CPSs) with multi-agent architecture. We build the distributed networked multi-group agent systems (NMGASs) with nonlinear and unknown dynamics via cloud edge computing. The common and challenging situations of random communication constraints in CPSs are considered, including network-induced delay, packet dropout, and packet disorder, which are treated as round-trip time (RTT) delay. To actively compensate for RTT delay and achieve coordination among all agents, a data-driven cloud edge predicted control strategy is designed. This strategy only needs to obtain the I/O measurement data of the systems, and can automatically carry out adaptive learning, which has more extensive application scenarios compared to model-based control methods. Theoretical analysis yields the conditions of simultaneous stability and consensus of the closed-loop systems with the proposed strategy. Finally, the practical examples are provided to illustrate the effectiveness of the proposed strategy. © 2023 IEEE.

关键词： Edge computing

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Optimized Gaussian kernel regression for X-ray pulsar signal profile construction 3

Optimized Gaussian kernel regression for X-ray pulsar signal...

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3rd International Conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2024

作者： Dong, Yan Zhuang, Yutao Wang, Ruoning National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100071 China

ISBN: (纸本)9781510690219

With the continuous advancement of pulsar-based navigation technology, signal processing issues in X-ray pulsar navigation applications have received increasing attention. One of the key factors limiting the improvement of navigation accuracy is the low signal-to-noise ratio (SNR) of epoch-folded profiles. Pulsar profiles contain many important characteristic features, such as pulse shape symmetry and multi-pulse structures. To facilitate further study, it is necessary to reduce noise and obtain high-SNR pulsar profiles. This study addresses this issue by proposing a method for high-precision pulsar profile construction based on optimized Gaussian kernel regression. The constructed profiles are evaluated and analyzed in terms of profile quality and phase information estimation based on the profile. The results show that the SNR of the epoch-folded profiles after denoising is significantly better than that of the original profiles, providing an important reference for signal processing in X-ray pulsar navigation applications. © 2025 SPIE.

关键词： Image denoising

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Spatially Dense Multi-Target Track Segment Association Algorithm 42

Spatially Dense Multi-Target Track Segment Association Algor...

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42nd Chinese control Conference, CCC 2023

作者： Yao, Yan Yan, Liping Xia, Yuanqing School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other tasks. The existing track segment association algorithms have low correlation accuracy in dense distributed or long-time interruption situations. To this purpose, a dense multi-target track segment association (DMTTSA) algorithm is proposed. Firstly, two identical networks based on the multi-head probability sparse (ProbSparse) self-attention are used to capture the long-term dependencies of the tracks. Then, the bidirectional quadruplet hard sample loss (BiQuaHard loss) is constructed to make the tracks belonging to the same targets closer and the tracks belonging to the different targets farther. Finally, DMTTSA takes the closest track pairs in the feature space as the associated tracks and divides the unassociated tracks into the birth and dead tracks in chronological order. Some comparative experiments are carried out to show the anti-noise performance of the DMTTSA, as well as the effectiveness of solving the problem of dense multi-target track interruption. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Target tracking

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An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2621-2640页

作者： Jing Xin Kenan Du Jiale Feng Mao Shan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Australian Centre for Field Robotics The University of SydneySydney2006Australia

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D *** current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time *** address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space ***,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud ***,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud *** also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor *** results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic ***,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

关键词： 3D semantic map online reconstruction RGB-D images semantic segmentation indoor mobile robot

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Multi-Time-Scale Variational Mode Decomposition-Based Robust Fault Diagnosis of Railway Point Machines Under Multiple Noises

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Chinese Journal of Electronics 2024年第3期33卷 814-822页

作者： Junqi LIU Tao WEN Guo XIE Yuan CAO Clive Roberts Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology The School of Electronic and Information Engineering Beijing Jiaotong University Birmingham Centre for Railway Research and Education University of Birmingham

The fault diagnosis of railway point machines(RPMs) has attracted the attention of engineers and *** have studies considered diverse noises along the *** fulfill this aspect,a multi-time-scale variational mode decomposition(MTSVMD) is proposed in this paper to realize the accurate and robust fault diagnosis of RPMs under multiple *** decomposes condition monitoring signals after coarse-grained processing in varying *** this manner,the information contained in the signal components at multiple time scales can construct a more abundant feature space than at a single *** the experimental validation,a random position,random type,random number,and random length(4R) noise-adding algorithm helps to verify the robustness of the *** adequate experimental results demoristrate the superiority of the proposed MTSVMD-based fault diagnosis.

关键词： Railway point machines Fault diagnosis Multi-time-scale Variational mode decomposition

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Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm 42

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Tianyi Ma, Liling Wang, Junzheng School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789887581543

With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit distance. Second, Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift schedule. Finally, AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an NEDC. The results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance, and the economy is optimized by 3%. The feasibility of the comprehensive shift schedule is verified. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Electric vehicles

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Electric Dual Variable Pump controlled Hydraulic Motor 42

Electric Dual Variable Pump Controlled Hydraulic Motor

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42nd Chinese control Conference, CCC 2023

作者： Yang, Jianmin Wang, Junzheng Niu, Shanshuai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain difficulties to the control. The electric double-variable pump[1] is a dual-input single-output system, and it is a nonlinear system[2]. It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the system. In this paper, an intelligent control rule is proposed for the nonlinear problem of double input and single output. Through backstepping design[3], the nonlinear system is transformed into multiple linear subsystems. Then the original system is turned into two independent subsystems with single input and single output, which are controlled separately. The co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the system. The results show that the response speed of the system has been greatly improved. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Backstepping

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Robust Model Predictive control for PMSM Drives Against Parameter Mismatch 41

Robust Model Predictive Control for PMSM Drives Against Para...

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第41届中国控制会议

作者： Luwei Shao Wei Shen Fan Li Chuanyu Ge State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

As an advanced control method of permanent magnet synchronous motor(PMSM),finite control set model predictive control(FCS-MPC) has earned widespread attention for its advantages of intuitive concept,splendid dynamic performance and capability of handling the constraints and ***,the dependence on the model parameter accuracy is the main barrier for FCS-MPC to be applied to the industry *** order to solve this issue,this paper presents a robust FCS-MPC against parameter *** proposed strategy utilizes the prediction error in the d-and q-axis currents during the past instant to calculate the compensation which should be added to the predicted currents in the next ***,the cost function in the proportional-integral form is designed as ***,the simulation results and experimental results prove the proposed method's effectiveness in suppressing the influence of model parameter mismatch on the control performance of PMSM.

关键词： permanent magnet synchronous motor finite control set model predictive control parameter mismatch

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