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Enhanced gear fault diagnosis via heterodyne downconversion: Theoretical verification and optimized ultrasonic signal acquisition

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Measurement 2025年 256卷

作者： Jingchao Zhang Shaoqun Zhang Yixue Dong Chen Li Guoqian Jiang Yingwei Li Xiaoli Li School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao 066004 China Intelligent Control System R&D Department Computer Application Technology Research Institute China Ordnance Industry Beijing 100089 China School of Electrical Engineering Yanshan University Qinhuangdao 066004 China School of Automation Science and Engineering South China University of Technology Guangzhou 510641 China Pazhou Lab Guangzhou 510330 China

Ultrasonic fault diagnosis has emerged as a promising technique for gear fault detection, owing to its capability to capture modulated high-frequency transients induced by incipient or localized defects. However, its practical application is constrained by the requirement for extremely high sampling rates. Heterodyne downconversion offers a potential solution by translating ultrasonic spectral components to lower frequencies, though its effectiveness in preserving diagnostic features remains insufficiently validated. This study conducts a theoretical analysis of the influence of heterodyne downconversion on ultrasonic signal characteristics and proposes an optimized heterodyne-based ultrasonic acquisition system with enhanced charge amplification and frequency conversion circuits. Experimental evaluations using a gear fault test platform demonstrate that the downconverted signals preserve the envelope spectral features of the original ultrasonic signals. Furthermore, comparative analyses indicate that the proposed method achieves superior fault detection sensitivity compared to conventional vibration-based techniques, particularly under high rotational speeds. These findings validate the feasibility and diagnostic advantages of the proposed heterodyne-based approach for efficient and accurate ultrasonic condition monitoring.

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A novel Skin lesion prediction and classification technique: ViT-GradCAM

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Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) 2024年第9期30卷 e70040页

作者： Muhammad Shafiq Kapil Aggarwal Jagannathan Jayachandran Gayathri Srinivasan Rajasekhar Boddu Adugna Alemayehu School of Information Engineering Qujing Normal University Qujing China. Key Laboratory of Intelligent Sensor and System Design College of Information Engineering Qujing Normal University Qujing China. Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India. Department of AIML Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Hyderabad India. Lecturer in Software Engineering Wachemo University Hosaina Ethiopia.

BACKGROUND:Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinical experts in detecting and localizing skin lesions. Vision transformers (ViT) based on image segmentation classification using multiple classes provide fairly accurate detection and are gaining more popularity due to legitimate multiclass prediction capabilities. MATERIALS AND METHODS:In this research, we propose a new ViT Gradient-Weighted Class Activation Mapping (GradCAM) based architecture named ViT-GradCAM for detecting and classifying skin lesions by spreading ratio on the lesion's surface area. The proposed system is trained and validated using a HAM 10000 dataset by studying seven skin lesions. The database comprises 10 015 dermatoscopic images of varied sizes. The data preprocessing and data augmentation techniques are applied to overcome the class imbalance issues and improve the model's performance. RESULT:The proposed algorithm is based on ViT models that classify the dermatoscopic images into seven classes with an accuracy of 97.28%, precision of 98.51, recall of 95.2%, and an F1 score of 94.6, respectively. The proposed ViT-GradCAM obtains better and more accurate detection and classification than other state-of-the-art deep learning-based skin lesion detection models. The architecture of ViT-GradCAM is extensively visualized to highlight the actual pixels in essential regions associated with skin-specific pathologies. CONCLUSION:This research proposes an alternate solution to overcome the challenges of detecting and classifying skin lesions using ViTs and GradCAM, which play a significant role in detecting and classifying skin lesions accurately rather than relying solely on deep learning models.

关键词： Grad‐CAM Multi‐Headed Self attention (MSA) linear patch projection multilayer perceptron (MLP) skin lesion transformer encoder vision transformer (ViT)

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PerFedSAC: Energy-time-aware personalized federated learning via soft actor-critic in resource-constrained IoT

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Expert systems with Applications 2025年 292卷

作者： Jingwen Nie Xianhao Shen Shaohua Niu College of Computer Science and Engineering Guilin University of Technology Guilin 541006 China Guangxi Laboratory of Embedded Technology and Intelligent System Guilin University of Technology Guilin 541006 China College of Physics and Electronic Information Engineering Guilin University of Technology Guilin 541006 China School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China

Federated learning (FL) is an emerging distributed training framework that allows multiple edge devices to collaboratively build a global model without uploading raw data, effectively reducing the risk of data leakage. It is particularly suitable for privacy-sensitive Internet of Things (IoT) scenarios. Despite its significant advantages in protecting the data privacy of edge devices, FL still faces several challenges in real-world IoT applications. Factors such as device computational heterogeneity, data distribution diversity, and unstable communication environments make traditional strategies relying on random client selection insufficient to meet the dual requirements of system efficiency and model performance, often leading to unnecessary energy consumption and communication overhead. Moreover, most current methods focus on extracting common features from all clients, neglecting the personalized needs arising from data non independent and identically distributed(IID) and task heterogeneity, which limits the model’s convergence speed and generalization performance. To address these issues, we restructured the entire FL system framework and propose a personalized FL soft actor-critic (Per-FL-SAC) algorithm based on the soft actor-critic deep reinforcement learning algorithm. This method introduces a novel evaluation metric, global average local user precision (LUP), to measure the overall performance of FL, and selects appropriate clients in each round to accelerate convergence while controlling time and energy costs. Additionally, to enhance the model’s adaptability to data heterogeneity, we integrate a personalized layer structure into the local model to better preserve user-specific features and meet personalized modeling requirements. Extensive experiments were conducted on multiple datasets. Experimental results verify the significant advantages of the proposed Per-FL-SAC algorithm. In various comparative experiments, Per-FL-SAC achieves high convergence spe

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Research on obstacle detection and path planning based on visual navigation for mobile robot

Research on obstacle detection and path planning based on vi...

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作者： Yixiao Zheng Bixi Yan Chao Ma Xinyu Wang Haoyang Xue School of Instrument Science and Optoelectronic Engineering Beijing Information Science and Technology University Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering

Both obstacle and path planning are of significance for autonomous visual navigation of a mobile robot which is able to realize free movement and obstacle *** this paper,a scheme of obstacle detection which is based on binocular vision to identify obstacles is constructed and it is combined with improved A* algorithm for obstacle avoidance motion for mobile robot ***,a binocular vision system to detect the robot's perception of the environment is used and the visual information is *** a Gaussian filter is used to reduce the noise in the image,and the grayscale image is obtained through the binocular vision *** gray scale map is matched with SAD(Sum of Absolute Differences) in order to obtain the disparity image with ***,the location information of the obstacle is extracted through the environmental depth information contained in the disparity image,and the improved A* algorithm is used as the path planning algorithm in this paper,which can modify the path of the planning ***,the detection experiment of the robot visual obstacle avoidance system was established and the optimal path was *** examples show that,the obstacle avoidance system can complete the task of obstacle detection and give a better path for the mobile robot.

关键词： image filter Research on obstacle detection and path planning based on visual navigation for mobile robot

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Uplink Precoding Design for Cell-Free Massive MIMO with Iteratively Weighted MMSE

arXiv

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arXiv 2023年

作者： Wang, Zhe Zhang, Jiayi Ngo, Hien Quoc Ai, Bo Debbah, Mérouane The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China The Institute of Electronics Communications and Information Technology Queen’s University BelfastBT3 9DT United Kingdom The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Frontiers Science Center for Smart High-Speed Railway System The Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China The Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518066 China The Technology Innovation Institute Abu Dhabi United Arab Emirates CentraleSupélec University Paris-Saclay Gif-sur-Yvette91192 France

In this paper, we investigate a cell-free massive multiple-input multiple-output system with both access points and user equipments equipped with multiple antennas over the Weichselberger Rayleigh fading channel. We study the uplink spectral efficiency (SE) for the fully centralized processing scheme and large-scale fading decoding (LSFD) scheme. To further improve the SE performance, we design the uplink precoding schemes based on the weighted sum SE maximization. Since the weighted sum SE maximization problem is not jointly over all optimization variables, two efficient uplink precoding schemes based on Iteratively Weighted sum-Minimum Mean Square Error (I-WMMSE) algorithms, which rely on the iterative minimization of weighted MSE, are proposed for two processing schemes investigated. Furthermore, with maximum ratio combining applied in the LSFD scheme, we derive novel closed-form achievable SE expressions and optimal precoding schemes. Numerical results validate the proposed results and show that the I-WMMSE precoding schemes can achieve excellent sum SE performance with a large number of UE antennas. Copyright © 2023, The Authors. All rights reserved.

关键词： MIMO systems

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Multilayer SOH Equalization Scheme for MMC Battery Energy Storage system

Multilayer SOH Equalization Scheme for MMC Battery Energy St...

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作者： Ma, Zhan Gao, Feng Gu, Xin Li, Nan Wu, Qiang Wang, Xiaohui Wang, Xiaolong Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jinan Power Supply Company Jinan China Electric Power Research Institute State Grid Tianjin Electric Power Company Tianjin China School of Information Science and Engineering Shandong University Jinan China

It is preferable for the retired batteries to balance their states-of-health (SOH) in the battery energy storage system (BESS) since it can prolong the system lifetime and reduce the maintenance burden. So far, the corresponding balancing techniques mainly focus on either the SOH balancing among packs or the SOH balancing of cells inside a pack. This article further proposes the multilayer SOH equalization scheme to equalize all cells' SOHs of large-scale BESS by comprehensively combining the pack SOH balancing strategy and the commercial cell equalization techniques. It is noted that the balancing schemes for pack and cell cannot be simply superimposed since packs and cells have totally different connection modes and are equipped with different types of balancing circuits. In specific, the modular multilevel converter (MMC) is assumed to coordinate the pack and cell SOH equalization schemes, where the charging/discharging power per submodule is properly adjusted according to the extent of cell SOH deviation and the extent of pack SOH deviation together. MATLAB simulation and experimental results of a 10-kWh MMC-BESS prototype verified the performance of the proposed method. © 1986-2012 IEEE.

关键词： Power converters

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An Automated Feature engineering Method for Online Payment Fraud Detection

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Jisuanji Xuebao/Chinese Journal of Computers 2020年第10期43卷 1983-2001页

作者： Wang, Cheng Wang, Chang-Qi Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

Internet finance fraud is an increasingly serious social and economic problem. Online payment services (OPSs) are the typical models of Internet finance, and the fraudulent transaction in OPSs is also a typical fraud pattern. The method of identifying fraudulent transactions by constructing a fraud detection model based on machine learning has become a promising idea for online payment anti-fraud. In the process of constructing fraud detection models, the feature engineering is the most critical step. It is also one of the most time-consuming and specialized steps in the relevant area. In the study of feature engineering, the existing online payment fraud detection models are mainly carried out by experts in the form of manual construction based on business knowledge. However, there are many fraud scenarios in OPSs where the process of feature construction is so different. Artificial feature construction methods can no longer meet the increasing demand of anti-fraud. An important way to solve this problem is to automate feature engineering. In the field of Internet financial anti-fraud, the expressibility and interpretability of features play a pivotal role. It is helpful to understand the original source fields and their construction process of important features. This is useful for mining and analyzing the characteristics of fraud methods and follow-up improvement rules engines. These are of great significance for fraud detection models. Therefore, the interpretability of the model method is particularly important. Usually, the optimization of detection accuracy is carried out under the premise of ensuring interpretability. This paper proposed a lightweight, tree-structure, high efficiency and scalable automatic feature engineering method for fraud detection of online payment. The method is as follows: (1) The method has low requirements on the calculation conditions and little dependence on the dataset samples. To realize this advantage, it used the tree structur

关键词： Feature extraction

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Pinning boundary sampled-data synchronization of coupled reaction–diffusion neural networks

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Neurocomputing 2025年 648卷

作者： Zi-Peng Wang Bo-Ming Chen Junfei Qiao Biao Luo Huai-Ning Wu Tingwen Huang Guangwei Chen School of Information Science and Technology Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System and Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing 100124 China School of Automation Central South University Changsha 410083 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen 518107 China

In this paper, the pinning boundary sampled-data (SD) synchronization problem of coupled reaction–diffusion neural networks (CRDNNs) with SD-based couplings is investigated under boundary and distributed SD measurements. First, a pinning boundary SD controller is designed to effectively address the synchronization problem of CRDNNs, utilizing boundary and distributed SD measurements and requiring only a small number of sensors and actuators. Then, linear matrix inequalities provide adequate conditions that ensure exponential stability of the synchronization error system by using the designed pinning boundary SD controller, derived through inequality techniques and Lyapunov functionals. Finally, we present a numerical example to showcase the practical applicability and effectiveness of the proposed pinning boundary SD synchronization method.

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Line Drawing Guided Progressive Inpainting of Mural Damage

arXiv

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arXiv 2022年

作者： Li, Luxi Zou, Qin Zhang, Fan Yu, Hongkai Chen, Long Song, Chengfang Huang, Xianfeng Wang, Xiaoguang Li, Qingquan Department of Computer Science Technology United International College of Beijing Normal University HongKong Baptist University Zhuhai China Machine Vision and Robotics Laboratory School of Computer Science Wuhan University Wuhan China State Key Laboratory of Surveying Mapping and Remote Sensing Information Engineering Wuhan University Wuhan China Department of Electrical Engineering and Computer Science Cleveland State University OH United States Institute of Automation Chinese Academy of Sciences Beijing China Cultural Heritage Intelligent Computing Laboratory Wuhan University Wuhan China Guangming Laboratory Shenzhen University Shenzhen China

Mural image inpainting is far less explored compared to its natural image counterpart and remains largely unsolved. Most existing image-inpainting methods tend to take the target image as the only input and directly repair the damage to generate a visually plausible result. These methods obtain high performance in restoration or completion of some pre-defined objects, e.g., human face, fabric texture, and printed texts, etc., however, are not suitable for repairing murals with varying subjects and large damaged areas. Moreover, due to discrete colors in paints, mural inpainting may suffer from apparent color bias. To this end, in this paper, we propose a line drawing guided progressive mural inpainting method. It divides the inpainting process into two steps: structure reconstruction and color correction, implemented by a structure reconstruction network (SRN) and a color correction network (CCN), respectively. In structure reconstruction, SRN utilizes the line drawing as an assistant to achieve large-scale content authenticity and structural stability. In color correction, CCN operates a local color adjustment for missing pixels which reduces the negative effects of color bias and edge jumping. The proposed approach is evaluated against the current state-of-the-art image inpainting methods. Qualitative and quantitative results demonstrate the superiority of the proposed method in mural image inpainting. The codes and data are available at https://***/qinnzou/mural-image-inpainting . © 2022, CC BY-NC-ND.

关键词： Restoration

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GSH-triggered sequential catalysis for tumor imaging and eradication based on star-like Au/Pt enzyme carrier system

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Nano Research 2020年第1期13卷 160-172页

作者： Amin Zhang Qian Zhang Gabriel Alfranca Shaojun Pan Zhicheng Huang Jin Cheng Qiang Ma Jie Song Yunxiang Pan Jian Ni Lijun Ma Daxiang Cui Institute of Nano Biomedicine and Engineering Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment InstrumentDepartment of Instrument Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong University800 Dongchuan RDShanghai200240China National Center for Translational Medicine Collaborative Innovational Center for System BiologyShanghai Jiao Tong University800 Dongchuan RoadShanghai200240China School of Biomedical Engineering Shanghai Jiao Tong UniversityShanghai200240China Instituto de Ciencia de Materiales de Aragón(ICMA) CSIC/Universidad de ZaragozaC/Pedro Cerbuna 1250009ZaragozaSpain Department of Tumor Xintai People’s HospitalXintai271200China Department of Tumor in Tongren Hospital Shanghai Jiao Tong University School of Medicine1111 XianXia RoadShanghai200336China

Distinctively different metabolism between tumor cells and normal cells endows tumor tissues unique *** this regard,we have successfully prepared a sequential catalytic platform based on Au/Pt star for tumor *** multifunctional probes consisted of a gold/platinum star-shaped core(Au/Pt star)conjugated with a GSH-sensitive disulfide bond(S–S),a targeting ligand(rHSA-FA),a near-infrared fluorophore(IR780)and glucose oxidase(GOx).When systemically administered in a xenografted murine model,the probes specifically targeted the tumor *** the disulfide linker was cleaved by intracellular GSH,the IR780 molecules could be released for photo-thermal therapy&photodynamic therapy(PTT&PDT)and ***,the Pt nanolayer of the Au/Pt star and the GOx formed a sequential catalytic system:GOx effectively catalyzed intracellular glucose by consuming oxygen to generate H2O2 and enhance the local acidity,and the Pt layer exhibited peroxidase-like property to catalyze H2O2 producing toxic·OH for tumor oxidative *** we demonstrated that our probes simultaneously possessed a GSH-sensitive release,real-time imaging ability,and synergetic cancer starving-like therapy/enzyme oxidative therapy/PTT/PDT features,which provides a potential strategy for effective tumor theragnostic.

关键词： Au/Pt star GSH-responsive GOx peroxidase sequential nanocatalyst cancer starving-like therapy enzyme oxidative therapy photo-thermal therapy&photodynamic therapy(PTT&PDT)

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