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Research on flame classification and recognition based on object detection and similarity fusion

The Journal of China Universities of Posts and Telecommunications 2021年第5期28卷 59-67页

作者： He Xin Zhou Junhua Liao Zhonghua Zhai Xiang Sun Siyuan School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network(Faster R-CNN), whose mean average-precision(mAP) is 93.6%. Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue(RGB) color histograms of the three flames.

关键词： flame classification object detection similarity fusion

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Ontology Modelling of Smart Product-Service system Components towards Mass Personalization

Ontology Modelling of Smart Product-Service System Component...

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2024 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2024

作者： Chen, Lucheng Sheng, Guojun Qin, Chenggang Wang, Chao Wu, Alexander T.Y. Nuertai, Ayala Zhou, Tongtong Ming, Xinguo SJTUSME-COSMOPlat Joint Research Center for New Generation Industrial Intelligent Technology School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Co. Ltd Shandong Qingdao266100 China State Key Laboratory of Massive Personalized Customization System and Technology Shandong266100 China School of Design Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798350386097

Customer products have become increasingly driven by mass personalization as industries are shifting to knowledge-driven user-centric design approaches such as Smart Product-Service systems (Smart PSS) to better meet expectations and remain competitive. However current user-centric design methods lack a semantic framework that properly models the components of a Smart PSS, leading to a lack in the usefulness of the knowledge generated from user research. This paper aims to create an ontological model that defines the components of a Smart PSS and their relationships to help enterprises better support dynamic personalization requirements. A case-study of electric vehicles is then presented to explore the usage of the ontology-based knowledge model on a Smart PSS. © 2024 IEEE.

关键词： Smart manufacturing

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Analyzing Influence Factors of Blockchain Technology in Prognostics and Health Management Based on Spherical Fuzzy DEMATEL Method and Technology Adoption Theory

Analyzing Influence Factors of Blockchain Technology in Prog...

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2024 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2024

作者： Hai, Zhengwei Meng, Xiangxiu Hui, Guo Lu, XiaoPing Zhou, Tongtong Ming, Xinguo SJTUSME-COSMOPlat Joint Research Center for New Generation Industrial Intelligent Technology School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Co. Ltd Shandong Qingdao266100 China State Key Laboratory of Massive Personalized Customization System and Technology Shandong 266100 China School of Design Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798350386097

Prognostics and health management (PHM) aims to reduce sudden failures during system operation, thereby improving system performance and protecting personal safety from harmful condition. Nonetheless, implementation of PHM still faces many difficulties related to security, privacy, and trustiness issues. Blockchain, an emerging technology, has great potential to resolve these problems. Adopting blockchain in PHM is a challenging task and a comprehensive analysis is required before jumping into innovation. However, scientific surveys pertaining to the topic are still scarce. In this article, a systematical exploration of the potential and influence factor of blockchain adoption in PHM is presented. combined technology adoption theory (TAT) is proposed as theoretical foundation for identifying influence factors of blockchain adoption in PHM. Twenty-one factors at both individual-level and firm-level are captured. Thirdly, a dual-ideal distance based spherical fuzzy DEMATEL is introduced to evaluate the interrelationships and importance of the influence factors with considering vagueness and hesitancy of experts’ judgements. Aiming to demonstrate the feasibility and effectiveness, a case study and several comparative analyses are performed finally. © 2024 IEEE.

关键词： Blockchain adoption DEMATEL Influence factor Prognostics and health management (PHM) Spherical fuzzy sets

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Sector Patch Embedding: An Embedding Module Conforming to The Distortion Pattern of Fisheye Image

arXiv

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arXiv 2023年

作者： Yang, Dianyi Tang, Jiadong Gao, Yu Yang, Yi Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Fisheye cameras suffer from image distortion while having a large field of view(LFOV). And this fact leads to poor performance on some fisheye vision tasks. One of the solutions is to optimize the current vision algorithm for fisheye images. However, most of the CNN-based methods and the Transformer-based methods lack the capability of leveraging distortion information efficiently. In this work, we propose a novel patch embedding method called Sector Patch Embedding(SPE), conforming to the distortion pattern of the fisheye image. Furthermore, we put forward a synthetic fisheye dataset based on the ImageNet-1K and explore the performance of several Transformer models on the dataset. The classification top-1 accuracy of ViT and PVT is improved by 0.75% and 2.8% with SPE respectively. The experiments show that the proposed sector patch embedding method can better perceive distortion and extract features on the fisheye images. Our method can be easily adopted to other Transformer-based models. Source code is at https://***/IN2-ViAUn/Sector-Patch-Embedding. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition systems

arXiv

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arXiv 2023年

作者： Gao, Yu Su, Lutong Liang, Hao Yue, Yufeng Yang, Yi Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods assume a unique camera and rarely consider multi-camera scenarios. Besides, some NeRF methods that can optimize intrinsic and extrinsic parameters still remain susceptible to suboptimal solutions when these parameters are poor initialized. In this paper, we propose MC-NeRF, a method that enables joint optimization of both intrinsic and extrinsic parameters alongside NeRF. The method also supports each image corresponding to independent camera parameters. First, we tackle coupling issue and the degenerate case that arise from the joint optimization between intrinsic and extrinsic parameters. Second, based on the proposed solutions, we introduce an efficient calibration image acquisition scheme for multi-camera systems, including the design of calibration object. Finally, we present an end-to-end network with training sequence that enables the estimation of intrinsic and extrinsic parameters, along with the rendering network. Furthermore, recognizing that most existing datasets are designed for a unique camera, we construct a real multi-camera image acquisition system and create a corresponding new dataset, which includes both simulated data and real-world captured images. Experiments confirm the effectiveness of our method when each image corresponds to different camera parameters. Specifically, we use multi-cameras, each with different intrinsic and extrinsic parameters in real-world system, to achieve 3D scene representation without providing initial poses. The Code and supplementary materials are available at https://***/MC-NeRF Copyright © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

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CRRS: Concentric Rectangles Regression Strategy for Multi-point Representation on Fisheye Images

arXiv

引用

arXiv 2023年

作者： Wang, Xihan Xu, Xi Gao, Yu Yang, Yi Yue, Yufeng Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Modern object detectors take advantage of rectangular bounding boxes as a conventional way to represent objects. When it comes to fisheye images, rectangular boxes involve more background noise rather than semantic information. Although multi-point representation has been proposed, both the regression accuracy and convergence still perform inferior to the widely used rectangular boxes. In order to further exploit the advantages of multi-point representation for distorted images, Concentric Rectangles Regression Strategy(CRRS) is proposed in this work. We adopt smoother mean loss to allocate weights and discuss the effect of hyper-parameter to prediction results. Moreover, an accurate pixel-level method is designed to obtain irregular IoU for estimating detector performance. Compared with the previous work for muti-point representation, the experiments show that CRRS can improve the training performance both in accurate and stability. We also prove that multi-task weighting strategy facilitates regression process in this design. Source code is at https://***/IN2-ViAUn/Concentric-Rectangles-Loss. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Multi-Robot Collaborative Identification and Trajectory Optimization for Fine Operation of Uncertain Objects

SSRN

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SSRN 2024年

作者： Cheng, Tianhong Xu, Wenfu Yan, Lei The School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robots Shenzhen518055 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Multi-robot systems offer many advantages over single robots such as flexible operation, high efficiency, and large payload, making it highly promising for applications in large equipment assembly, complex part manufacturing, and maintenance. However, uncertainties in the shape, size, mass, and inertia of manipulated objects, coupled with spatial constraints in multi-robot collaborative operations, pose significant challenges. To address the above issues, this paper proposes a multi-robot collaborative identification and trajectory optimization framework for fine operation of uncertain object. First, the compound multi-robot and object system is modelled. Then a power identification method is presented by introducing the motor model. Regarding the uncertainties related to manipulated objects, a novel momentum observer is designed, which enables the identification of physical properties of the object manipulated by the multi-robot system such as its mass, inertia, and the position of center of mass. Subsequently, for multi-robot collaborative operations, the paper explores collaborative trajectory optimization methods across various levels, including initial scene design, path allocation, and energy-efficient trajectory optimization. Several typical simulations and collaborative polishing experiment validate the effectiveness of the proposed method. © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

Multi-Destination Cooperative Task Offloading in Blockchain-...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Ping Lang Daxin Tian Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization.

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Extrusion/Inkjet Printing of Verteporfin-Loaded Bilayer Skin Substitutes for Wound Healing and Structure Reconstruction

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Journal of Bionic Engineering 2024年第6期21卷 2969-2984页

作者： Tian Jiao Ruilu Zhou Junrong Jiao Junna Jiao Qin Lian School of Intelligent Manufacturing and Electrical Engineering Nanyang Normal University1638 Nanyang RoadNanyang473061Henan ProvincePeople’s Republic of China Nanyang Normal University Library Nanyang Normal University1638 Nanyang RoadNanyang473061Henan ProvincePeople’s Republic of China Key Lab for Special Functional Materials of Ministry of Education School of Materials Science and EngineeringHenan UniversityKaifeng475004People’s Republic of China School of Basic Medical Sciences Xinxiang Medical University601 Jinsui AvenueXinxiang453000Henan ProvincePeople’s Republic of China State Key Laboratory for Manufacturing System Engineering Xi’an Jiaotong University28 Xianning West RoadXi’an710049Shaanxi ProvincePeople’s Republic of China

The shortage of transplantable skin is the leading cause of death in patients with extensive skin *** this challenge urgently requires the development of skin substitutes capable of wound repair and facilitating skin *** this study,a biomimetic bilayer skin tissue model consisting of collagen,gelatin/sodium alginate,fibroblasts,human umbilical vein endothelial cells,keratinocytes,melanocytes,and verteporfin was ***,the skin model was fabricated using precise extrusion/inkjet bioprinters,and it reconstruction capabilities were evaluated through skin defect repair *** printed skin tissue reduced the inflammatory response of the wound by 38%and inhibited the expression of TGF-βand YAP,and promoted the transformation of macrophages from M1 phenotype to M2 phenotype,thus promoting the reasonable reconstruction of fibronectin and collagen on the wound,finally promoting the wound healing,and reducing the wound contraction and scar *** addition,the proliferation and differentiation of human umbilical vein endothelial cells,keratinocytes,and melanocytes in printed skin increased the number of regenerated blood vessels by 123%,while promoting the reconstruction of multilayer epidermal structure and skin *** outcomes of this investigation present a promising skin model and therapeutic strategy for skin injury,offering a potential avenue for the reconstruction of skin structure and function.

关键词： Bioprinting Multicellular printing Biomimetic Skin substitutes Wound healing

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A Forecast Error Correction Method Based on Seq2Seq and Auto Encoder for Short-term Wind Power Forecast Enhancement

A Forecast Error Correction Method Based on Seq2Seq and Auto...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Haoyu Ma Ming Yang Zifen Han Bo Wang Jianfeng Che Menglin Li Key Laboratory of Power System Intelligent Dispatch Control Shandong University Jinan China State Grid Gansu Power Grid Corporation Lanzhou China National Key Laboratory of Renewable Energy Grid-Integration China Electric Power Research Institute Beijing China

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

Accurate wind power forecast (WPF) is highly significant for the safe and economic operation of power systems, and implementing error correction is a common and effective manner to further enhance the forecasting performance. Nonetheless, existing error correction methods fail to consider temporal relationship and may inadvertently increase the error under certain circumstances, thereby compromising the local precision of forecast. In order to address these issues, this paper proposes an error correction model based on Seq2Seq and auto encoder (AE) to improve forecasting accuracy. Firstly, the seq2seq with attention mechanism is introduced to infer the probable error sequence through learning the temporal relationship between the numerical weather prediction sequence and the actual error sequence. Secondly, the samples that the seq2seq providing a positive error inference are collected and the AE model is employed to extract the meteorological features at these moments. Finally, on the basis of the above two models, the error correction method is constructed consisting of preliminary error inference and posterior correction determination. Using operational data from Ningxia province, the proposed method is validated for its remarkable superiority based on the evaluation metrics.

关键词： Accuracy Wind energy Heuristic algorithms Wind power generation Predictive models Feature extraction Error correction Numerical models Wind forecasting Forecasting

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