Computers in Industry最新文献_第3页

Maximum subspace transferability discriminant analysis: A new cross-domain similarity measure for wind-turbine fault transfer diagnosis 最大子空间转移性判别分析：用于风力涡轮机故障转移诊断的新型跨域相似性测量方法

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-27 DOI: 10.1016/j.compind.2024.104194

Quan Qian , Fei Wu , Yi Wang , Yi Qin

{"title":"Maximum subspace transferability discriminant analysis: A new cross-domain similarity measure for wind-turbine fault transfer diagnosis","authors":"Quan Qian , Fei Wu , Yi Wang , Yi Qin","doi":"10.1016/j.compind.2024.104194","DOIUrl":"10.1016/j.compind.2024.104194","url":null,"abstract":"<div><div>In the field of fault transfer diagnosis, many approaches only focus on the distribution alignment and knowledge transfer between the source domain and target domain. However, most of these approaches ignore the precondition of whether this transfer task is transferable. Current mainstream transferability discrimination methods heavily depend on expert knowledge and are extremely vulnerable to the noise interference and variations in feature scale. This limits their applicability due to the intelligent requirements and complex industrial environment. To address the challenges mentioned previously, this paper introduces a novel cross-domain similarity measure called maximum subspace transferability discriminant analysis (MSTDA) with zero-label prior knowledge. MSTDA is comprised of a maximum subspace representation and a similarity measurement criterion. During the phase of maximum subspace representation, a new kernel-induced Hilbert space is designed to map the low-dimensional original samples into the high-dimensional space to maximize the separability of different faults and then solve the separable intrinsic fault features. Following that, a novel similarity measurement criterion that is resistant to variations in feature scale is developed. This criterion is based on the orthogonal bases of intrinsic feature subspaces. The mini-batch sampling strategy is used to ensure the timeliness of MSTDA. Finally, the experimental results on three cases, particularly in the actual wind turbine dataset, confirm that the proposed MSTDA outperforms other well-known similarity measure methods in terms of transferability evaluation. The related code can be downloaded from https://qinyi-team.github.io/2024/09/Maximum-subspace-transferability-discriminant-analysis.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104194"},"PeriodicalIF":8.2,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual channel visible graph convolutional neural network for microleakage monitoring of pipeline weld homalographic cracks 用于监测管道焊缝同色裂纹微渗漏的双通道可见图卷积神经网络

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-26 DOI: 10.1016/j.compind.2024.104193

Jing Huang , Zhifen Zhang , Rui Qin , Yanlong Yu , Yongjie Li , Quanning Xu , Ji Xing , Guangrui Wen , Wei Cheng , Xuefeng Chen

{"title":"Dual channel visible graph convolutional neural network for microleakage monitoring of pipeline weld homalographic cracks","authors":"Jing Huang , Zhifen Zhang , Rui Qin , Yanlong Yu , Yongjie Li , Quanning Xu , Ji Xing , Guangrui Wen , Wei Cheng , Xuefeng Chen","doi":"10.1016/j.compind.2024.104193","DOIUrl":"10.1016/j.compind.2024.104193","url":null,"abstract":"<div><div>When using a single sensor to monitor early microleakage of nuclear power pressure pipeline leakage, there are problems such as low monitoring accuracy and poor early warning reliability due to the limitations of the monitoring range and weak difference between the leakage signals. To address these challenges, this paper proposes a dual channel visible graph convolutional neural network (DCV-GCN). Firstly, the acoustic emission time-series data of each channel are truncated and divided, and the significant frequency bands are selected based on the envelope spectrum. On this basis, the sequence group is averaged to obtain the graph structure sequence. Then, the limited penetrable visibility (LPV) graph construction algorithm is used to calculate the adjacency matrix, and the important nodes is reserved according to the eigenvector centrality. Furthermore, the inverse ratio of the distance from the sensor in each single channel to the center of the crack is used as the fusion weight, and the adjacency matrices are merged after normalization to transform the construction of the graph structure dataset. Finally, the dataset is input into the graph convolutional neural network, and the effectiveness of the method is verified by carefully designing three homalographic cracks. The results show that the proposed method can effectively extract the distinguishing features with similar frequency components and similar leakage rates, and the recognition accuracy of different leakage states can reach 98.56 %. In addition, through ablation experiments and different parameter strategy settings, the operating mechanism is explained, which can provide a reference for monitoring and analysis by industrial technicians.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104193"},"PeriodicalIF":8.2,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Video-based automatic people counting for public transport: On-bus versus off-bus deployment 基于视频的公共交通人员自动计数：公交车上与公交车外的部署

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-26 DOI: 10.1016/j.compind.2024.104195

Chris McCarthy, Hadi Ghaderi, Felip Martí, Prem Jayaraman, Hussein Dia

{"title":"Video-based automatic people counting for public transport: On-bus versus off-bus deployment","authors":"Chris McCarthy, Hadi Ghaderi, Felip Martí, Prem Jayaraman, Hussein Dia","doi":"10.1016/j.compind.2024.104195","DOIUrl":"10.1016/j.compind.2024.104195","url":null,"abstract":"<div><div>Interest in Automatic People Counting (APC) for crowd detection and management is rapidly growing. While a range of Internet of Things (IoT) sensors and systems exist, video analytics is emerging as a particularly attractive option — especially for applications where more traditional methods of people counting are not available, unreliable or expensive. In this paper we focus on automatic people counting in the public transport context – specifically, rail replacement bus services – in which bus companies are typically contracted to provide bus services to replace train services during periods of planned and unplanned line disruption. This presents a particularly compelling use-case for video-based people counting, while also presenting unique challenges. Field trials are thus vital to the proper assessment of video-based APC solutions, however remain relatively scarce in the literature. While datasets to support research and benchmarking exist, these do not capture the intrinsic complexities of real-world deployment and the implications of selected configurations — in particular, on-vehicle versus off-vehicle use cases. In this paper, we evaluate our own video-based APC solution, representative of state-of-the-art approaches in the literature, in two separate extensive (i.e, multi-day) metropolitan field trials covering both on and off-bus use-cases. Through real-world deployment of the system in both settings, we highlight key differences with respect to APC accuracy, as well as other practical considerations, and the validity of underlying assumptions in both on and off-bus scenarios.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104195"},"PeriodicalIF":8.2,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TDAD: Self-supervised industrial anomaly detection with a two-stage diffusion model TDAD：利用两阶段扩散模型进行自我监督式工业异常检测

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-26 DOI: 10.1016/j.compind.2024.104192

Changyun Wei , Hui Han , Yu Xia , Ze Ji

引用次数: 0

A novel anomaly detection method for magnetic flux leakage signals via a feature-based unsupervised detection network 通过基于特征的无监督检测网络对漏磁通信号进行异常检测的新方法

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-25 DOI: 10.1016/j.compind.2024.104190

He Zhao, Jinhai Liu, Qiannan Wang, Xiangkai Shen, Lin Jiang

{"title":"A novel anomaly detection method for magnetic flux leakage signals via a feature-based unsupervised detection network","authors":"He Zhao, Jinhai Liu, Qiannan Wang, Xiangkai Shen, Lin Jiang","doi":"10.1016/j.compind.2024.104190","DOIUrl":"10.1016/j.compind.2024.104190","url":null,"abstract":"<div><div>High-precision anomaly detection, as the key technology of magnetic flux leakage (MFL) signal detection, is a challenging task. It is difficult to detect anomalies in MFL signals due to the variety of anomalies and the characteristics of the anomalies are easily submerged in the variation of the natural signals. To address the above issues, a feature-based unsupervised detection network (FUDet) is designed, which accomplishes the unsupervised anomaly detection task through feature discrimination and feature reconstruction. Firstly, a bidirectional discrimination module is proposed, which can input normal and anomaly feature distributions to mine the characteristics of samples, so as to enhance the ability of the model to recognize anomaly signals. Secondly, a dynamic noise generation module is designed to generate different feature distributions for each input that are consistent with the characteristics of MFL signals. This module creates an adversarial effect with the discriminator, allowing it to identify more subtle feature differences through training. Finally, a reconstruction classification module is designed to naturally reconstruct the non-normal features and normal features into normal signals, which can be used to detect anomalies by comparing the difference between the input signals and the reconstructed signals. Experimentally, the method is proved to outperform the P-AUROC of the state-of-the-art method by 3.1% under MFL signals and achieves outstanding results in MFL signal anomaly detection.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104190"},"PeriodicalIF":8.2,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extended realities and discrete events simulations: A systematic review to define design trade-offs and directions 扩展现实与离散事件模拟：界定设计权衡和方向的系统审查

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-24 DOI: 10.1016/j.compind.2024.104188

Giulia Wally Scurati , Francesco Ferrise , Marco Bertoni

引用次数: 0

Development of immersive bridge digital twin platform to facilitate bridge damage assessment and asset model updates 开发沉浸式桥梁数字孪生平台，促进桥梁损坏评估和资产模型更新

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-23 DOI: 10.1016/j.compind.2024.104189

Muhammad Fawad , Marek Salamak , Qian Chen , Mateusz Uscilowski , Kalman Koris , Marcin Jasinski , Piotr Lazinski , Dawid Piotrowski

{"title":"Development of immersive bridge digital twin platform to facilitate bridge damage assessment and asset model updates","authors":"Muhammad Fawad , Marek Salamak , Qian Chen , Mateusz Uscilowski , Kalman Koris , Marcin Jasinski , Piotr Lazinski , Dawid Piotrowski","doi":"10.1016/j.compind.2024.104189","DOIUrl":"10.1016/j.compind.2024.104189","url":null,"abstract":"<div><div>Conventional infrastructure asset management practices have heavily relied on static data collection and suffered from decision lags. Though advanced Structural Health Monitoring (SHM) systems were extensively explored based on multi-functional sensor deployment, asset model updating has not been achieved to facilitate timely and effective decision-making of infrastructure managers due to a lack of system integration. To address this challenge, this study develops the Immersive Bridge Digital Twin Platform (IBDTP) to allow infrastructure managers to automate the SHM processes of bridges and engage them in immersive decision-making processes based on Scan-to-BIM and Augmented Reality (AR) technologies. A novel 3D game engine is proposed as part of IBDTP and was tested using a single-span concrete arch bridge located in Poland. Results show that the measurement data collected and presented in IBDTP improves the infrastructure managers' accessibility to major damage data of the bridge to plan for future interventions. The functions of the IBDTP can be potentially scaled for different types of bridges and critical infrastructure, substantially improving the traditional SHM in terms of data management and 3D structural visualization.</div></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104189"},"PeriodicalIF":8.2,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166361524001179/pdfft?md5=a6ebf35ab4db5c14eeed0be759e6256a&pid=1-s2.0-S0166361524001179-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Product digital twins: An umbrella review and research agenda for understanding their value 产品数字孪生：了解其价值的总体回顾和研究议程

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-21 DOI: 10.1016/j.compind.2024.104181

Francisco Gomez Medina , Veronica Martinez Hernandez

{"title":"Product digital twins: An umbrella review and research agenda for understanding their value","authors":"Francisco Gomez Medina , Veronica Martinez Hernandez","doi":"10.1016/j.compind.2024.104181","DOIUrl":"10.1016/j.compind.2024.104181","url":null,"abstract":"<div><p>Product Digital Twins (DTs) are digital representations of a physical asset that update synchronously throughout its lifecycle. Over the past decade, a rich and varied literature on the development of new technologies and approaches to implementing product DTs has emerged. This literature has been reviewed multiple times, but the variety in focus and scope of DT reviews has become so extensive that it is challenging to assess our collective understanding and knowledge of DT theory. We address this issue by conducting a systematic umbrella review of product DT reviews, classifying and analysing review themes to understand strengths and shortcomings of product DT literature. Our analysis reveals a key shortcoming in the product DT literature: There is currently little evidence and understanding of DT value. Understanding how DTs provide value to an organisation is of paramount importance, as it will determine the elements of the DT that truly have an effect on value, as well as the mechanisms by which that value is created. We conclude this work by presenting a five-item research agenda to address these shortcomings and develop our understanding of DT value. Since DTs can be complex and expensive to implement, research and practice should focus on those elements of the DT that provide value to the organisation.</p></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104181"},"PeriodicalIF":8.2,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016636152400109X/pdfft?md5=9a355badb7559ca56d607a28d5927053&pid=1-s2.0-S016636152400109X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated corner grading of trading cards: Defect identification and confidence calibration through deep learning 交易卡的自动边角分级：通过深度学习进行缺陷识别和信心校准

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-19 DOI: 10.1016/j.compind.2024.104187

Lutfun Nahar , Md. Saiful Islam , Mohammad Awrangjeb , Rob Verhoeve

{"title":"Automated corner grading of trading cards: Defect identification and confidence calibration through deep learning","authors":"Lutfun Nahar , Md. Saiful Islam , Mohammad Awrangjeb , Rob Verhoeve","doi":"10.1016/j.compind.2024.104187","DOIUrl":"10.1016/j.compind.2024.104187","url":null,"abstract":"<div><p>This research focuses on trading card quality inspection, where defects have a significant effect on both the quality inspection and grading. The present inspection procedure is subjective which means the grading is sensitive to mistakes made by individuals. To address this, a deep neural network based on transfer learning for automated defect detection is proposed with a particular emphasis on corner grading which is a crucial factor in overall card grading. This paper presents an extension of our prior study, in which we achieved an accuracy of 78% by employing the VGG-net and InceptionV3 models. In this study, our emphasis is on the DenseNet model where convolutional layers are used to extract features and regularisation methods including batch normalisation and spatial dropout are incorporated for better defect classification. Our approach outperformed prior findings, as evidenced by experimental results based on a real dataset provided by our industry partner, achieving an 83% mean accuracy in defect classification. Additionally, this study investigates various calibration approaches to fine-tune the model confidence. To make the model more reliable, a rule-based approach is incorporated to classify defects based on confidence scores. Finally, a human-in-the-loop system is integrated to inspect the misclassified samples. Our results demonstrate that the model’s performance and confidence are expected to improve further when a large number of misclassified samples, along with human feedback, are used to retrain the network.</p></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104187"},"PeriodicalIF":8.2,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166361524001155/pdfft?md5=94620ae9f7ac6add13e46e3c2ecef436&pid=1-s2.0-S0166361524001155-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-granularity spatiotemporal object modelling of waterborne traffic elements 水上交通要素的多粒度时空对象建模

IF 8.2 1区计算机科学

Computers in Industry Pub Date : 2024-09-17 DOI: 10.1016/j.compind.2024.104185

Xiaodong Cheng , Yuanqiao Wen , Zhongyi Sui , Liang Huang , He Lin

{"title":"Multi-granularity spatiotemporal object modelling of waterborne traffic elements","authors":"Xiaodong Cheng , Yuanqiao Wen , Zhongyi Sui , Liang Huang , He Lin","doi":"10.1016/j.compind.2024.104185","DOIUrl":"10.1016/j.compind.2024.104185","url":null,"abstract":"<div><p>The electronic navigational charts are crucial carriers for representing the multi-source heterogeneous data of Waterborne Traffic Elements (WTEs). However, their layer-based modelling method has some shortcomings in expressing the multi-granularity features, complex relationships, and dynamic evolution of elements. This paper proposes an objectification modelling method for WTEs based on the concept of multi-granularity spatiotemporal object modelling. A classification system for waterborne traffic objects is developed based on the relevance of behavior to elements; combining characteristics of waterborne traffic, a data model for waterborne traffic objects is constructed from eight aspects: spatiotemporal reference, spatiotemporal position, spatial form, basic information, attributes, behavioral ability, structure, and associative relationships. An object extraction function is also established, extracting object attributes and relationships between objects according to different element classes. Taking the Jiashan section of the Hangzhou-Shanghai Line in Zhejiang Province as the experimental subject, the multi-granularity spatiotemporal characteristics, dynamic evolution, and relationship expression of channel class objects are tested. The experimental results show that the proposed method provides the theoretical basis and data organization mode for the multi-granularity expression of WTEs.</p></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"164 ","pages":"Article 104185"},"PeriodicalIF":8.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0