Journal of Industrial Information Integration最新文献_第9页

Vision language model-enhanced embodied intelligence for digital twin-assisted human-robot collaborative assembly 基于视觉语言模型的数字化双辅助人机协同装配体智能研究

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-09-02 DOI: 10.1016/j.jii.2025.100943

Changchun Liu , Dunbing Tang , Haihua Zhu , Zequn Zhang , Liping Wang , Yi Zhang

Recently, embodied intelligence has emerged as a viable approach to achieving human-like perception, reasoning, decision-making, and execution capacities within human-robot collaborative (HRC) assembly contexts. Due to the lack of generalized enabling technologies and disconnections from physical control systems, embodied intelligence requires repetitive training of various functional models to operate in dynamic HRC scenarios, thereby struggling to adapt effectively to complex and evolving HRC environments. Hence, this study proposes a vision-language model (VLM)-enhanced embodied intelligence framework for digital twin (DT)-assisted human-robot collaborative assembly. Initially, the mapping between embodied agents and physical robots is established to achieve the encapsulation of embodied agents. Building upon the agent-based architecture, a VLM driven by both domain knowledge and real-time scenario data is constructed with sensory capabilities. Based on this, rapid recognition and response to dynamic HRC environments can be realized. Leveraging the strong generalization of VLMs, repetitive training of multiple perception models is circumvented. Furthermore, by utilizing the cognitive learning and intelligent reasoning capabilities of VLMs, an expert knowledge system for assembly processes is developed to provide task-oriented assistance and solution generation. To enhance the adaptability and generalization of complex HRC decision-making, VLMs support reinforcement learning through flexible configuration of HRC assembly state information processing, decision-action generation and guidance, and reward function design. In addition, a DT model of the HRC scenario is constructed to provide a simulation and deduction engine (i.e., embodied brain) for mitigating collision accidents. The decision results are then fed into the VLM as invocation parameters for corresponding sub-function code modules, generating complete collaborative robot action code to form the embodied neuron. Finally, compared with traditional decision methods (e.g., MA-A2C, DQN and GA) and VLM-enhanced MA-A2C, a series of comparative experiments conducted in a real-world HRC assembly scenario demonstrate that the proposed framework exhibits competitive advantages.

最近，具身智能已经成为在人机协作（HRC）装配环境中实现类人感知、推理、决策和执行能力的可行方法。由于缺乏广泛的使能技术和与物理控制系统的脱节，具身智能需要对各种功能模型进行重复训练，以在动态HRC场景中运行，从而难以有效地适应复杂和不断变化的HRC环境。因此，本研究提出了一个视觉语言模型（VLM）增强的具身智能框架，用于数字孪生（DT）辅助的人机协同装配。首先建立具身智能体与物理机器人之间的映射关系，实现对具身智能体的封装。在基于智能体的体系结构基础上，构建了具有感知能力的由领域知识和实时场景数据驱动的VLM。基于此，可以实现对动态HRC环境的快速识别和响应。利用vlm的强泛化，避免了多个感知模型的重复训练。利用vlm的认知学习和智能推理能力，开发了面向装配过程的专家知识系统，提供面向任务的辅助和解决方案生成。为了提高复杂HRC决策的适应性和泛化能力，VLMs通过HRC装配状态信息处理、决策行为生成与指导、奖励函数设计等柔性配置支持强化学习。此外，构建了HRC场景的DT模型，为减轻碰撞事故提供了仿真和推理引擎（即具身脑）。然后将决策结果作为相应子功能码模块的调用参数馈送到VLM中，生成完整的协作机器人动作码，形成嵌入神经元。最后，与传统的决策方法（如MA-A2C、DQN和GA）和vlm增强的MA-A2C相比，在现实HRC装配场景中进行的一系列对比实验表明，所提出的框架具有竞争优势。

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引用次数: 0

Enhancing precision in window to the brain modeling: Methodology and implementation of hybrid digital twins 提高窗口对大脑建模的精度：混合数字孪生的方法和实现

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-16 DOI: 10.1016/j.jii.2025.100973

Marcos Llamazares López , Macarena Trujillo Guillén , Juan-Carlos Cortés , Rafael-J. Villanueva

The Window to the Brain (WttB) is a novel cranial implant designed to enhance therapeutic procedures involving brain tissue. Previous computational models studying the effectiveness of the WttB exhibited some discrepancies with experimental results and inconsistencies in certain parameter values. To overcome these drawbacks, the following steps are followed. We first perform a domain reduction where the model is solved via the finite element method. Then, model parameters are calibrated using asynchronous random Particle Swarm Optimization (arPSO) algorithm. A statistical identifiability analysis is performed to evaluate how accurately model parameters are estimated based on the quantity and quality of experimental data. Afterward, we implement Hybrid Digital Twins (HDT) using Grammatical Evolution and Lexicase Selection to improve the model fitting keeping the model complexity. The outcomes demonstrate a complete alignment between experimental and computational results, as well as reasonable values for all model parameters. The final optimized model achieved a mean absolute error of 0.1871, with a standard deviation of 0.0013 and a 95% confidence interval (CI) of [0.1866, 0.1876], indicating a very low residual error and high stability across simulations. Our computational approach enhances the results from previous studies, which can be more useful for improving clinical practice.

脑窗（WttB）是一种新型颅骨植入物，旨在加强涉及脑组织的治疗程序。以往研究WttB有效性的计算模型与实验结果存在一定的差异，在某些参数值上也存在不一致性。要克服这些缺点，需要遵循以下步骤。我们首先执行一个域约简，其中模型通过有限元方法求解。然后，采用异步随机粒子群优化（arPSO）算法对模型参数进行标定。进行统计可识别性分析，以评估基于实验数据的数量和质量估计模型参数的准确性。然后，我们使用语法进化和词法选择来实现混合数字双胞胎（HDT），以提高模型拟合，保持模型的复杂性。结果表明，实验结果与计算结果完全一致，所有模型参数的值都是合理的。最终优化模型的平均绝对误差为0.1871，标准差为0.0013,95%置信区间（CI）为[0.1866,0.1876]，表明残差非常低，跨模拟的稳定性很高。我们的计算方法增强了先前研究的结果，这对改善临床实践更有用。

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引用次数: 0

Enabling human–CPS cognitive interoperability: Cognitive architectures as technologies for human-like cognitive digital twins 实现人类- cps认知互操作性：作为类人认知数字孪生技术的认知架构

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-13 DOI: 10.1016/j.jii.2025.100969

Al Haj Ali Jana , Ben Gaffinet , Mario Lezoche , Hervé Panetto , Yannick Naudet

Cognition, the set of mental processes that enable humans to perceive, reason, learn and decide, plays an essential role in effective collaboration between humans and Cyber–Physical Systems (CPSs). To achieve seamless cognitive interoperability between humans and CPSs, it is necessary to integrate a Cognitive Digital Twin (CDT) and a Human Digital Twin (HDT) to provide digital representations of both physical assets and human cognitive states. In this article, we first analyse the three essential functions of CDT and HDT: emulation, cognition and simulation, and review the state-of-the-art technologies for each of them, from supervised learning and knowledge graphs to deep reinforcement learning. Focusing on the cognitive layer, we review the state of the art in cognitive architectures, describing their symbolic, sub-symbolic and hybrid types and reporting on their real-world implementations in different domains. We then assess the relevance of these architectures for the integration of human-like reasoning in CDTs. Finally, we identify the main technological challenges and gaps that need to be addressed in order to implement fully operational CDTs.

认知是一组使人类能够感知、推理、学习和决策的心理过程，在人类和信息物理系统（cps）之间的有效协作中起着至关重要的作用。为了实现人类和cps之间无缝的认知互操作性，有必要集成认知数字双胞胎（CDT）和人类数字双胞胎（HDT），以提供物理资产和人类认知状态的数字表示。在本文中，我们首先分析了CDT和HDT的三个基本功能：仿真、认知和仿真，并回顾了它们各自的最新技术，从监督学习和知识图到深度强化学习。关注认知层，我们回顾了认知架构的最新进展，描述了它们的符号、子符号和混合类型，并报告了它们在不同领域的实际实现。然后，我们评估了这些架构在cdt中集成类人推理的相关性。最后，我们确定了需要解决的主要技术挑战和差距，以便全面实施可操作的cdt。

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引用次数: 0

From issues to routes: A cooperative costmap with lifelong learning for Multi-AMR navigation 从问题到路线：Multi-AMR导航终身学习的合作成本图

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-09-10 DOI: 10.1016/j.jii.2025.100941

Jiyeong Chae , Sanghoon Lee , Hyunkyo Seo, Kyung-Joon Park

In large-scale industrial environments where multi-AMR (Autonomous Mobile Robot) systems are deployed, the unpredictable occurrence of obstacles can significantly disrupt AMR navigation, hindering task execution. To overcome such disruptions, AMRs must frequently replan their routes in real time, often resulting in suboptimal trajectories. This paper proposes a multi-AMR path planning framework based on a Cooperative Costmap with Lifelong Learning, designed to enable efficient navigation even in environments where obstacle patterns are not known a priori. Inspired by issue-propagation models in social-network theory — which describe how public attention rises and fades over time within a network — the proposed approach models the temporal influence of encountered obstacles, allowing predictive path planning that adapts to changing obstacle patterns. The framework incorporates a lifelong learning mechanism to incrementally refine the influence parameter over time, thus ensuring adaptability in dynamic industrial settings. Simulation experiments demonstrate that the proposed approach increases task throughput by up to 18.0% and reduces average travel time by up to 30.1% compared to the standard ROS 2 navigation stack.

在部署多自主移动机器人（AMR）系统的大规模工业环境中，不可预测的障碍物会严重破坏自主移动机器人的导航，阻碍任务的执行。为了克服这种中断，amr必须经常实时重新规划路线，这通常会导致次优轨迹。本文提出了一种基于终身学习的合作成本图的多amr路径规划框架，旨在实现即使在障碍物模式先验未知的环境下也能高效导航。受社会网络理论中的问题传播模型的启发，该模型描述了公众注意力在网络中如何随着时间的推移而上升和消退，提出的方法模拟了遇到障碍的时间影响，允许预测路径规划，以适应不断变化的障碍模式。该框架包含终身学习机制，以随着时间的推移逐步完善影响参数，从而确保在动态工业环境中的适应性。仿真实验表明，与标准ROS 2导航堆栈相比，该方法将任务吞吐量提高了18.0%，平均行程时间减少了30.1%。

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引用次数: 0

Surfing twin transition in agri-food supply chains: The role of iot and data analytics in sustainable decision-making 农业食品供应链的双重转型：物联网和数据分析在可持续决策中的作用

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-18 DOI: 10.1016/j.jii.2025.100983

Maria Elena Latino, Marta Menegoli, Angelo Corallo, Maria Grazia Gnoni

The agri-food industry faces complex challenges that impact operational efficiency, profitability, and the ability to meet evolving consumer expectations for transparency and sustainability. Industry 4.0 technologies, particularly the Internet of Things and data analytics, offer substantial potential to enhance performance and support sustainability goals across the supply chain. This study investigates the application of Internet of Things and analytics through a multiple case study approach, illustrating how agri-food companies can transform operational and product data into actionable insights to inform decision-making and implement effective sustainability practices. The research adopts a four-phase methodology - Digitalization & Sustainability Case stud* Guideline- identifying market needs, mapping product information, elaborating data analysis, and collecting stakeholder feedback, thus providing a replicable guideline for conducting case studies in the intersection of digitalization and sustainability. A practical roadmap is presented for leveraging technological assets to generate meaningful sustainability indicators and rankings, supporting both operational managers and end consumers in accessing transparent, data-driven information. The study contributes to theory by advancing methodological rigor in multiple case studies and highlighting how data integration facilitates sustainable decision-making in agri-food supply chains. Practically, it offers actionable insights for managers aiming to enhance operational efficiency, improve communication of sustainability performance, and build consumer trust. The findings underscore the value of Internet of Things and analytics in enabling data-driven innovation and supporting future research on generalizing these approaches across diverse agri-food contexts.

农业食品行业面临着复杂的挑战，这些挑战影响着运营效率、盈利能力以及满足消费者对透明度和可持续性不断变化的期望的能力。工业4.0技术，特别是物联网和数据分析，为提高整个供应链的绩效和支持可持续发展目标提供了巨大的潜力。本研究通过多案例研究的方法研究了物联网和分析的应用，说明了农业食品公司如何将运营和产品数据转化为可操作的见解，为决策提供信息并实施有效的可持续性实践。本研究采用四阶段方法——数字化与可持续发展案例研究指南——确定市场需求，绘制产品信息，详细分析数据，收集利益相关者反馈，从而为在数字化与可持续发展的交叉领域进行案例研究提供可复制的指南。本文提出了一个实用的路线图，用于利用技术资产生成有意义的可持续性指标和排名，支持运营经理和最终消费者访问透明的、数据驱动的信息。该研究通过在多个案例研究中推进方法的严谨性，并强调数据集成如何促进农业食品供应链中的可持续决策，从而为理论做出贡献。实际上，它为管理者提供了可操作的见解，旨在提高运营效率，改善可持续发展绩效的沟通，并建立消费者信任。研究结果强调了物联网和分析在实现数据驱动创新方面的价值，并支持未来在不同农业食品环境中推广这些方法的研究。

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引用次数: 0

Manufacturing process scheduling method based on multi-level and cross-chain collaboration under industrial internet environment 工业互联网环境下基于多级跨链协同的制造过程调度方法

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-11 DOI: 10.1016/j.jii.2025.100972

Wenjun Xu , Jinshan Zhong , Jiayi Liu , Shuang Zheng , Xianglong Zou , Feng Liu

Under the industrial internet environment, achieving effective manufacturing process scheduling requires collaboration across the workshop level, production line level, industrial chain, and value chain. This collaboration enables the integration of manufacturing process information, aligning scheduling more closely with practical operations. However, the existing scheduling approaches mainly focus on a single level or a single chain, lacking the ability to address multi-level and cross-chain collaborative optimization. To overcome this limitation, this paper proposes a scheduling method for manufacturing process based on multi-level and cross-chain collaboration (MPMLCC) under the industrial internet environment. Firstly, the mathematical model is established to represent the four key stages of the manufacturing process: parts procurement, transportation, sub-assembly, and final assembly. The optimization model aims to minimize both the makespan and the total cost, reflecting time and cost efficiency across all stages. Then, an improved multi-objective grey wolf optimizer (IMOGWO) is designed to solve the MPMLCC scheduling problem. The algorithm integrates the opposition-based learning (OBL), the multi-neighborhood local search strategy to balance global exploration and local exploitation. Case studies based on the small satellites Oresat0 and Oresat1B are conducted to verify the effectiveness of the proposed method. Experimental results demonstrate that the proposed approach significantly improves solution quality and stability compared to the other multi-objective optimization algorithms. Furthermore, the scheduling outcomes confirm the effectiveness of manufacturing process information integration and collaborative optimization across multiple levels and chains.

在工业互联网环境下，实现有效的制造过程调度需要车间层面、生产线层面、产业链、价值链层面的协同。这种协作能够集成制造过程信息，使调度与实际操作更紧密地结合起来。然而，现有的调度方法主要集中在单一层次或单链上，缺乏解决多层次和跨链协同优化的能力。为了克服这一局限性，本文提出了一种工业互联网环境下基于多级跨链协同的制造过程调度方法。首先，建立了零件采购、运输、分装和总装四个关键制造阶段的数学模型；优化模型的目标是最小化完工时间和总成本，反映所有阶段的时间和成本效率。然后，设计了一种改进的多目标灰狼优化器（IMOGWO）来解决MPMLCC调度问题。该算法结合了基于对立的学习（OBL）和多邻域局部搜索策略，平衡了全局探索和局部开发。以小卫星Oresat0和Oresat1B为例，验证了该方法的有效性。实验结果表明，与其他多目标优化算法相比，该方法显著提高了解的质量和稳定性。此外，调度结果验证了制造过程信息集成和跨层次、跨链协同优化的有效性。

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引用次数: 0

An ontology-based digital thread framework to support early concurrent engineering in the aerospace industry 一种支持航空航天工业早期并发工程的基于本体的数字线程框架

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-18 DOI: 10.1016/j.jii.2025.100984

Eliott Duverger , Alexis Aubry , Rebeca Arista , Eric Levrat

The increasing complexity of the aerospace industry has highlighted the need to anticipate issues from the entire lifecycle of aircrafts. Identified too late, issues originating from the manufacturing or the maintenance phases can have considerable consequences on the overall development costs, time and quality of aircraft development. Concurrent Engineering (CE) is an approach that aims to improve the design process of a system by considering all lifecycle phases from the initial conceptualization. However, this way of working demands a high degree of collaboration and extensive knowledge sharing among the involved stakeholders. The digitization of the industry has provided new opportunities addressing such challenges. Approaches based on Model-Based Systems Engineering (MBSE), Knowledge-Based Engineering (KBE) and Artificial Intelligence (AI) are providing compelling ways to foster cross-domain collaboration while incorporating knowledge supporting design decisions. This paper leverages an ontology-based digital thread framework as a bridge between aircraft and manufacturing engineering activities. With enriched insights and global perspectives, this framework aims to enable early cross-domain trade-offs analysis to support knowledge-driven concurrent and collaborative engineering during the conceptual design phase.

航空航天业日益复杂，这凸显了从飞机的整个生命周期预测问题的必要性。由于发现得太晚，制造或维护阶段产生的问题可能会对飞机开发的总体成本、时间和质量产生相当大的影响。并行工程（CE）是一种旨在通过考虑从初始概念化开始的所有生命周期阶段来改进系统设计过程的方法。然而，这种工作方式需要参与的利益相关者之间的高度协作和广泛的知识共享。行业的数字化为应对这些挑战提供了新的机遇。基于模型的系统工程（MBSE）、基于知识的工程（KBE）和人工智能（AI）的方法提供了令人信服的方法来促进跨领域协作，同时结合支持设计决策的知识。本文利用基于本体的数字线程框架作为飞机和制造工程活动之间的桥梁。通过丰富的洞察力和全局视角，该框架旨在支持早期的跨领域权衡分析，从而在概念设计阶段支持知识驱动的并发和协作工程。

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引用次数: 0

A Certificateless Aggregate G+G Signature Scheme with Intersection Method for Efficiency Improvement in Smart Grids 一种面向智能电网效率提升的无证书聚合G+G签名方案

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-27 DOI: 10.1016/j.jii.2025.100991

Songshou Dong , Yanqing Yao , Huaxiong Wang

Smart grids (SGs) can greatly improve the efficiency, reliability, and sustainability of traditional grids. In an industrial SG, real-time user-side metering data may be frequently collected for monitoring and controlling electricity consumption. To reduce the burden on SGs, most existing privacy-preserving schemes use aggregated signatures to ensure the integrity of the message and improve communication efficiency. In CRYPTO ’24, Marius et al. proposed an aggregating Falcon signature scheme LaBRADOR, which is a trapdoor-based lattice signature scheme. Currently, there are two types of lattice-based signature schemes: one is a trapdoor-based signature scheme, and the other is a Fiat-Shamir-based signature scheme. There is currently no particularly efficient Fiat-Shamir-based lattice-based aggregate signature scheme. Therefore, we construct an aggregate signature scheme with constant signature size without rejection sampling under the Fiat-Shamir style based on the G+G lattice signature (ASIACRYPT ’23) and the intersection method (EUROCRYPT ’11). In addition, we make our scheme certificateless to resist malicious key generation centers and the key escrow problem, and apply our scheme to SGs. Compared with other schemes, our signature scheme has a smaller aggregated signature size (any number of signatures), less signature time, and is more secure. Finally, we demonstrate that our scheme is existentially unforgeable in the context of adaptive chosen message attacks against type I and type II adversaries in the random oracle model.

智能电网可以极大地提高传统电网的效率、可靠性和可持续性。在工业SG中，可能经常收集实时用户端计量数据以监测和控制用电量。为了减轻SGs的负担，现有的大多数隐私保护方案都使用聚合签名来保证消息的完整性，提高通信效率。在CRYPTO’24中，Marius等人提出了一种聚合猎鹰签名方案LaBRADOR，这是一种基于活门的格子签名方案。目前，基于格子的签名方案主要有两种：一种是基于trapdoor的签名方案，另一种是基于fiat - shamir的签名方案。目前还没有特别高效的基于fiat - shamir的格子聚合签名方案。因此，我们基于G+G格签名（ASIACRYPT’23）和交点方法（EUROCRYPT’11），构造了一个在菲亚特-沙米尔风格下无拒绝抽样且签名大小不变的聚合签名方案。此外，为了抵御恶意密钥生成中心和密钥托管问题，我们使我们的方案无证书化，并将我们的方案应用于SGs。与其他方案相比，我们的签名方案具有签名总大小（任意数量的签名）更小、签名时间更短、安全性更高的优点。最后，我们证明了我们的方案在随机oracle模型中针对类型I和类型II对手的自适应选择消息攻击的背景下是存在不可伪造的。

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引用次数: 0

An EMD-based forecasting framework integrating GMM and BiLSTM for helicopter engine anomaly detection 结合GMM和BiLSTM的直升机发动机异常检测emd预测框架

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-10-30 DOI: 10.1016/j.jii.2025.101003

Qi Shen , Jingwei Guo , Yihui Tian , Zhen-Song Chen

The safety of helicopter operations is paramount, yet early signs of potential failures often go undetected, highlighting the need for robust signal alert systems during flights. Detecting anomalies in helicopter engine behavior through vibration analysis is critically important due to the long-sequence nature and complexity of the data, which present significant challenges for real-time assessment and are not adequately addressed by traditional methods such as preset thresholds or basic statistical models, as these approaches struggle to capture intricate spatiotemporal dependencies and overlapping fault patterns in real-world scenarios. To address these challenges, we introduce a novel hybrid model that leverages Empirical Mode Decomposition (EMD) for signal decomposition and analysis, effectively overcoming the limitations of traditional approaches. EMD is particularly advantageous as it decomposes complex signals into Intrinsic Mode Functions (IMFs), enabling more accurate anomaly detection in long sequences. Following EMD, the Gaussian Mixture Model (GMM) is employed to precisely recognize various fault patterns, ensuring a robust foundation for anomaly detection. Bidirectional Long Short-Term Memory (BiLSTM) networks further enhance the model by capturing temporal dependencies in both directions, integrating critical spatiotemporal information and improving predictive accuracy. Experimental results demonstrate that this integrated EMD-GMM-BiLSTM approach is not only highly sensitive and accurate in detecting anomalies but also significantly simpler and more efficient than more complex frameworks such as encoder-decoder models or Transformers. This method ensures the operational safety of helicopters and supports the broader adoption of low-altitude economic activities by providing essential safety guarantees.

直升机操作的安全是至关重要的，然而潜在故障的早期迹象往往未被发现，这突出了在飞行过程中对强大的信号警报系统的需求。由于数据的长序列性质和复杂性，通过振动分析检测直升机发动机异常行为至关重要，这对实时评估提出了重大挑战，并且无法通过预设阈值或基本统计模型等传统方法充分解决，因为这些方法难以捕捉复杂的时空依赖性和重叠故障模式。为了应对这些挑战，我们引入了一种新的混合模型，该模型利用经验模态分解（EMD）进行信号分解和分析，有效地克服了传统方法的局限性。EMD尤其具有优势，因为它将复杂信号分解为内禀模态函数（IMFs），从而能够在长序列中更准确地检测异常。在EMD的基础上，采用高斯混合模型（GMM）精确识别各种故障模式，为异常检测奠定了坚实的基础。双向长短期记忆（BiLSTM）网络通过捕获两个方向的时间依赖性、整合关键时空信息和提高预测精度进一步增强了模型。实验结果表明，这种集成EMD-GMM-BiLSTM方法不仅在异常检测方面具有很高的灵敏度和准确性，而且比编码器-解码器模型或变压器等更复杂的框架更简单、更高效。该方法通过提供必要的安全保障，确保了直升机的运行安全，支持低空经济活动的广泛采用。

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引用次数: 0

Special issue on “Industrial information integration in space informatics” 《空间信息学中的产业信息集成》特刊

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration

Pub Date : 2025-11-01 Epub Date: 2025-09-14 DOI: 10.1016/j.jii.2025.100957

Yuk Ming Tang , Andrew W.H. Ip , Kai Leung Yung , Zhuming Bi , Zhili Sun

引用次数: 0