Advanced Engineering Informatics最新文献_第3页

Informative As-Built Modeling as a Foundation for Digital Twins Based on Fine-Grained Object Recognition and Object-Aware Scan-vs-BIM for MEP Scenes 基于细粒度对象识别和MEP场景中对象感知扫描- bim的信息建成建模作为数字孪生的基础

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-26 DOI: 10.1016/j.aei.2025.103382

Boyu Wang , Fangzhou Lin , Mingkai Li , Zhenyu Liang , Zhengyi Chen , Mingzhu Wang , Jack C.P. Cheng

{"title":"Informative As-Built Modeling as a Foundation for Digital Twins Based on Fine-Grained Object Recognition and Object-Aware Scan-vs-BIM for MEP Scenes","authors":"Boyu Wang , Fangzhou Lin , Mingkai Li , Zhenyu Liang , Zhengyi Chen , Mingzhu Wang , Jack C.P. Cheng","doi":"10.1016/j.aei.2025.103382","DOIUrl":"10.1016/j.aei.2025.103382","url":null,"abstract":"<div><div>Mechanical, electrical, and plumbing (MEP) systems are critical for delivering essential services and ensuring comfortable environments. To improve the management efficiency of these complex systems, digital twins (DTs) that reflect the as-is conditions of facilities are increasingly being adopted. To generate DT models, laser scanners are widely used to capture as-built environments in the form of high-resolution images and dense 3D measurements. However, existing scan-to-BIM methods primarily produce basic geometric models, lacking detailed descriptive attributes of the components. To address this limitation, this paper proposes an informative DT model generation method for MEP systems based on fine-grained object recognition and object-aware scan-vs-BIM. The proposed method adopts a few-shot learning strategy to detect target objects in complex 3D environments and identify their family types based on vision foundation models. Following this, the association between as-designed components and as-built installations is formulated as a bipartite graph matching problem, which is solved using the Hungarian algorithm. This enables the automated updating of as-designed models into as-built DT models. Notably, the proposed association method is robust and applicable to components with significant installation deviations, a common challenge in MEP systems. The feasibility of the proposed approach was validated through experiments conducted on two construction sites in Hong Kong. Results demonstrated that the proposed approach significantly enhanced the accuracy of the scan-vs-BIM of MEP systems, thereby enabling informative DT model generation.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103382"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

More attention for computer-aided conceptual design: A multimodal data-driven interactive design method 对计算机辅助概念设计的更多关注：一种多模式数据驱动的交互设计方法

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-26 DOI: 10.1016/j.aei.2025.103392

Zhixin Liu , Shanhe Lou , Yixiong Feng , Wenhui Huang , Bingtao Hu , Chengyu Lu , Jianrong Tan

{"title":"More attention for computer-aided conceptual design: A multimodal data-driven interactive design method","authors":"Zhixin Liu , Shanhe Lou , Yixiong Feng , Wenhui Huang , Bingtao Hu , Chengyu Lu , Jianrong Tan","doi":"10.1016/j.aei.2025.103392","DOIUrl":"10.1016/j.aei.2025.103392","url":null,"abstract":"<div><div>Computer-aided conceptual design (CACD) is a core means for the development of new products, as it can materialize designers’ inherent thinking. However, when designers encounter stagnation during CACD, they need to consult third-party design knowledge to seek inspiration, which frequently disrupts their design thinking process. Deep learning-empowered design methods and design knowledge management can be a potential solution to address these issues. This study proposes a multimodal design data-driven interactive design method. Multimodal data are utilized to identify the designer’s implicit intentions while design attention is abstracted to match relevant knowledge as computer feedback. It achieves the “designer-computer-designer” closed-loop interactive design through the mediation of design attention. The multimodal design data (design images and design descriptions) is obtained through sketch modeling and verbal protocol analysis experiments. A multimodal Transformer based on T2T-ViT and Bert (TB-Multiformer) is constructed to capture multimodal features to identify conceptual design intentions by utilizing cross-modal design attention modules and self-design attention modules. Since the identified attention can be used to match the knowledge that designers are more concerned about, an attention-based design knowledge recommendation method (AbDKR) is proposed to provide proactive knowledge feedback. It can prevent designers from spending time searching for design knowledge and helps them maintain sufficient inspiration. A case study on the conceptual design of two types of mechanical structure is conducted to illustrate the feasibility and practicability of the proposed approach.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103392"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reconstruction method of aircraft wing stress field under limited measurement points via multi-source heterogeneous information fusion 基于多源异构信息融合的有限测点下飞机机翼应力场重建方法

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-24 DOI: 10.1016/j.aei.2025.103387

Lin Lin, Lingyu Yue, Dan Liu, Jinlei Wu, Sihao Zhang, Yikun Liu, Shiwei Suo

{"title":"Reconstruction method of aircraft wing stress field under limited measurement points via multi-source heterogeneous information fusion","authors":"Lin Lin, Lingyu Yue, Dan Liu, Jinlei Wu, Sihao Zhang, Yikun Liu, Shiwei Suo","doi":"10.1016/j.aei.2025.103387","DOIUrl":"10.1016/j.aei.2025.103387","url":null,"abstract":"<div><div>Due to the aircraft wing’s topological structure and lightweight design requirements, strain sensors installed on the wing are very limited. Traditional methods, relying on limited sensor data as a single information source, are insufficient for full-stress field monitoring, leading to a high prediction error. To address this issue, a novel wing stress field reconstruction method with limited measurement points is developed via multi-source heterogeneous information fusion. To be specific, two information fusion modules are designed to jointly overcome the challenges of limited measurement data and high non-linearity during full-stress field reconstruction. On one hand, the finite element mechanism-based information fusion module (FEMIFM) is proposed to derive and establish a mechanical model that relates the wing stress to positional parameter, in order to introduce physical information and reduce the non-linearity of the reconstruction mapping. On the other hand, the simulation stress expectation-based information fusion module (SSEIFM) leverages stress expectations derived from simulated stress fields under various operating conditions to incorporate statistical information, thereby enhancing the robustness and reasonableness of reconstruction results. Moreover, a soft-threshold loss function is proposed, which ignores zero-drift errors of strain sensors, improving the reconstruction accuracy of critical stress points. Finally, the developed method can be seamlessly integrated with popular neural networks (i.e., Transformer, convolutional neural networks, multilayer perceptron, etc.). Extensive experiments are conducted to validate the effectiveness of the developed method on an actual aircraft wing stress dataset.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103387"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep stacked state-observer based neural network (DSSO-NN): A new network for system dynamics modeling and application in bearing 基于深度堆叠状态观测器的神经网络（DSSO-NN）：一种新的系统动力学建模网络及其在轴承中的应用

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-24 DOI: 10.1016/j.aei.2025.103357

Diwang Ruan , Yan Wang , Yiliang Qian , Jianping Yan , Zhaorong Li

{"title":"Deep stacked state-observer based neural network (DSSO-NN): A new network for system dynamics modeling and application in bearing","authors":"Diwang Ruan , Yan Wang , Yiliang Qian , Jianping Yan , Zhaorong Li","doi":"10.1016/j.aei.2025.103357","DOIUrl":"10.1016/j.aei.2025.103357","url":null,"abstract":"<div><div>System dynamics modeling holds significant importance in engineering, especially for high-dimensional, non-linear, and time-varying systems. Traditional methods often encounter challenges such as poor interpretability, low computational efficiency, and limited generalization capabilities. To address these issues, this paper proposes a novel framework for dynamics modeling, Deep Stacked State-observer based Neural Network (DSSO-NN). This framework integrates the Extended State Observer (ESO) with state–space equations, leveraging the efficient state estimation of ESO and the powerful fitting capabilities of neural networks. Firstly, based on the system’s state–space equations, an ESO is constructed and then discretized to obtain neurons tailored for system modeling. Subsequently, serial and parallel structures are explored and compared to determine the optimal structure for validation, culminating in the construction of the DSSO network. Furthermore, critical factors influencing DSSO-NN performance, including ESO hyperparameter (<span><math><mi>δ</mi></math></span>), system order, and the number of layers, are optimized. Experimental results on Case Western Reserve University and FEMTO datasets demonstrate that DSSO-NN effectively captures system dynamics and achieves superior performance. This study showcases the robust performance and broad application potential of DSSO-NN in bearing dynamics modeling, providing a novel approach for complex dynamics modeling.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103357"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prognostics of complex machinery with sparse multilabel multimodal run-to-failure data: A graph neural network approach 基于稀疏多标签多模态运行到故障数据的复杂机械预测：一种图神经网络方法

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-24 DOI: 10.1016/j.aei.2025.103361

Sagar Jose , Ryad Zemouri , Khanh T.P Nguyen , Kamal Medjaher , Mélanie Lévesque , Antoine Tahan

{"title":"Prognostics of complex machinery with sparse multilabel multimodal run-to-failure data: A graph neural network approach","authors":"Sagar Jose , Ryad Zemouri , Khanh T.P Nguyen , Kamal Medjaher , Mélanie Lévesque , Antoine Tahan","doi":"10.1016/j.aei.2025.103361","DOIUrl":"10.1016/j.aei.2025.103361","url":null,"abstract":"<div><div>The practical requirements for maintaining machine operability often conflict with the data needs for training prognostics models due to the limited availability of run-to-failure (RTF) data in industry settings. This scarcity is exacerbated by irregular and infrequent inspections, resulting in sparse datasets. The literature tends to address this challenge by trajectory data augmentation methods which creates more RTF data by transformations on available trajectories, but these methods still require some trajectories to begin with. To address the challenge faced by industries where running any machine to failure without intervention is impractical, we propose a diagnostics feature similarity-based method to construct full RTF trajectories from partial data, which is then used in a graph neural network for prognostics. Unlike conventional graph-based prognostics that primarily model sensor interactions through static graph structures, this research explores fault propagation as an evolving graph, a novel approach in the application of GNNs. It posits that condition monitoring data from various machines across diverse health states can effectively generate prognostic insights and model degradation evolution as a dynamic graph with physically meaningful node-edge embeddings. The efficacy of this method is demonstrated through its application in a hydrogenerator prognostics case study involving multiple fault states.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103361"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid sensor fault detection and diagnosis method for air-handling unit based on multivariate analysis merged with deep learning 一种基于多元分析和深度学习的空气处理机组混合传感器故障检测与诊断方法

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-24 DOI: 10.1016/j.aei.2025.103360

Long Gao , Donghui Li , Ningyi Liang

{"title":"A hybrid sensor fault detection and diagnosis method for air-handling unit based on multivariate analysis merged with deep learning","authors":"Long Gao , Donghui Li , Ningyi Liang","doi":"10.1016/j.aei.2025.103360","DOIUrl":"10.1016/j.aei.2025.103360","url":null,"abstract":"<div><div>This paper proposes a novel air-handling unit (AHU) sensor fault detection and diagnosis (FDD) method by utilizing multivariate analysis merged with deep learning. In reality, sensor measurements in AHU systems are affected by outdoor air temperature, which results in poor detection performance of existing data-driven methods. To overcome this difficulty, a robust canonical correlation analysis (RCCA) is firstly proposed by removing the effect of outdoor air temperature, which is realized by performing an orthogonal decomposition of process variables. The better detection performance is delivered by using data from an orthogonal subspace of outdoor air temperature. Then, with the aid of the proposed detection method, a RCCA-based fault bank is constructed based on the principle of parity space. A neural network-based diagnosis method is proposed by means of the RCCA-based fault bank, which reduces the influence of noises and thus faults are easily diagnosed compared with traditional neural network-based methods. The proposed method is purely data-driven, and thus it is easily used for FDD in real systems. Finally, the effectiveness of the hybrid method is verified using experimental data from ASHRAE RP-1312. Results show that the proposed method is superior to the state-of-the-art methods, and the diagnosis performance is significantly improved by using the deep learning method with the aid of multivariate analysis.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103360"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Alternating interaction fusion of Image-Point cloud for Multi-Modal 3D object detection 交替交互融合图像-点云，实现多模态三维物体检测

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-24 DOI: 10.1016/j.aei.2025.103370

Guofa Li , Haifeng Lu , Jie Li , Zhenning Li , Qingkun Li , Xiangyun Ren , Ling Zheng

{"title":"Alternating interaction fusion of Image-Point cloud for Multi-Modal 3D object detection","authors":"Guofa Li , Haifeng Lu , Jie Li , Zhenning Li , Qingkun Li , Xiangyun Ren , Ling Zheng","doi":"10.1016/j.aei.2025.103370","DOIUrl":"10.1016/j.aei.2025.103370","url":null,"abstract":"<div><div>A mainstream feature fusion method involves enhancing Lidar point cloud information by incorporating camera, but it fails to fully utilize the rich information in images. Another method uses a dual-channel parallel approach to fuse image and point cloud information, but it also faces issues such as excessive module stacking and high computational demands. Therefore, we propose a powerful alternating interaction fusion approach. Firstly, it resolves the problem of unilateral fusion schemes that overly rely on point cloud information and fail to fully utilize image data. Secondly, it tackles the problem of excessive module stacking and high computational demands in dual-channel parallel fusion schemes of point cloud and image data. Specifically, our alternate interactive fusion module implements a method where image and point cloud BEV features mutually enhance each other. Local attention interactions are engaged between image features containing point cloud information and regular image features. This enhances the expressiveness of image features. Subsequently, internal BEV attention interactions occur between point cloud BEV features with enriched image information and regular point cloud BEV features. This step improves the expressiveness of the point cloud BEV features. Experiments on the large-scale nuScenes dataset demonstrate that our proposed method outperforms both the unilateral point cloud-centric fusion and the parallel interactive fusion approaches.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103370"},"PeriodicalIF":8.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing gaze interaction performance: Design and optimization of perspective-driven fisheye view 增强凝视交互性能：视角驱动鱼眼视图的设计与优化

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-23 DOI: 10.1016/j.aei.2025.103365

Wei-Chi Huang, Yi-Yan Wang, Lin-Han Fan, Sha-Tong Yang, Ya-Feng Niu

{"title":"Enhancing gaze interaction performance: Design and optimization of perspective-driven fisheye view","authors":"Wei-Chi Huang, Yi-Yan Wang, Lin-Han Fan, Sha-Tong Yang, Ya-Feng Niu","doi":"10.1016/j.aei.2025.103365","DOIUrl":"10.1016/j.aei.2025.103365","url":null,"abstract":"<div><div>Gaze interaction has been receiving increasing attention. However, it faces the critical challenge of low spatial accuracy. To enhance the performance of gaze interaction in high-information-density interfaces, this study explores the effects of fisheye views and their key parameters (max scale and effective range) on gaze interaction. To maintain consistency in motor space, the study proposes a perspective-driven fisheye view algorithm. Based on this algorithm, a gaze interaction experiment involving single-character visual search was conducted. The results indicate that fisheye views significantly improve both temporal and spatial performance in gaze interaction without altering the size of the motor space. Furthermore, the max scale and effective range of the fisheye view have varying impacts on different performance metrics. Overall, a max scale of 175 % and an effective range of 3 times the element center distance are identified as optimal parameter settings. These findings provides important theoretical and practical guidance for the application of fisheye view, and underscore the critical role of visual attention guidance in gaze interaction.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103365"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Knowledge graph exploitation to enhance the usability of risk assessment in construction safety planning 利用知识图谱提高建筑安全规划风险评估的可用性

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-23 DOI: 10.1016/j.aei.2025.103305

K.W. Johansen , C. Schultz , J. Teizer

{"title":"Knowledge graph exploitation to enhance the usability of risk assessment in construction safety planning","authors":"K.W. Johansen , C. Schultz , J. Teizer","doi":"10.1016/j.aei.2025.103305","DOIUrl":"10.1016/j.aei.2025.103305","url":null,"abstract":"<div><div>Construction projects and their dynamic and yet hazardous work environments face significant challenges. Despite advancements, many proposed solutions for information extraction and utilization remain impractical due to complexity and lack of interoperability. Information is often siloed in proprietary formats, making it difficult to integrate. This issue is evident in the construction safety domain, where advanced risk analysis tools provide detailed insights to hazards but can be overwhelming. Similar challenges exist in cost estimation, schedule evaluation, progress monitoring, and quality compliance checking. Decision-making in construction scheduling struggles to assess how changes impact site safety due to insufficient information and knowledge extraction capabilities, especially when it comes to cross-domain knowledge extraction. This study aims to make safety information accessible to safety and planning professionals. By leveraging Digital Twins, automated safety analysis, and knowledge representation, we enable decision-makers to gain deeper insights into their domain and understand the interplay between project planning and safety. We propose a framework for knowledge extraction, an ontology for capturing knowledge, and query building blocks to transform natural language questions into actionable queries. These methods are tested in a case study, revealing valuable insights into the cross-domain impact of decisions.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103305"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Meta-knowledge random attention update network for few-shot and anti-noise remaining useful life prediction 基于元知识随机关注更新网络的少弹抗噪剩余寿命预测

IF 8 1区工程技术

Advanced Engineering Informatics Pub Date : 2025-04-23 DOI: 10.1016/j.aei.2025.103358

Jing Yang , Xiaomin Wang , Minglan Zhang , Lin Liu , Jiuyong Li

{"title":"Meta-knowledge random attention update network for few-shot and anti-noise remaining useful life prediction","authors":"Jing Yang , Xiaomin Wang , Minglan Zhang , Lin Liu , Jiuyong Li","doi":"10.1016/j.aei.2025.103358","DOIUrl":"10.1016/j.aei.2025.103358","url":null,"abstract":"<div><div>In industrial systems, the remaining useful life (RUL) prediction of industrial equipment is crucial to ensure system’s safe operation. Current RUL prediction models have made notable advancements, predominantly through the utilization of extensive degradation data exhibiting analogous patterns or approximate distributions. However, when the labeled degraded data is limited and the data is affected by noise, the distribution discrepancies between RUL data will increase, preventing these methods from effectively capturing shared knowledge among the data and struggling to obtain satisfactory prediction performance. In this respect, a new meta-knowledge random attention update network model is proposed for few-shot and anti-noise RUL prediction. First, we treat the learned kernel features as random latent variables in a Monte Carlo sampling manner. Then, the attention mechanism is introduced in the random kernel to realize the control of local degradation information and enhance the learning of specific knowledge by the model. In addition, to reduce the impact of unnecessary or noisy information on meta-knowledge, the integration of shared knowledge and specific information is implemented within the knowledge update procedure. Comprehensive experiments are performed on datasets pertaining to engine and bearing degradation to assess the efficacy of the proposed model, with the results confirming its superiority.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103358"},"PeriodicalIF":8.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0