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distributed monitoring of Sheet Piles in a Cofferdam Using Optical Frequency Domain Reflectometry Technology

INDIAN GEOTECHNICAL JOURNAL 2025年第3期55卷 1908-1915页

作者： Jiang, Xin Bi, Gang Yang, Shaohua Li, Fan Geoengn Invest Inst Jiangsu Prov Nanjing 211102 Jiangsu Peoples R China Nanjing Tech Univ Coll Transportat Engn Nanjing 211816 Jiangsu Peoples R China

Sheet piles play a crucial role in cofferdams, significantly influencing safety during excavation. The integration of optical frequency domain reflectometry (OFDR) technology enables sheet piles to autonomously monitor stress and deformation throughout the construction process. The feasibility of this method was demonstrated in an engineering case study. Furthermore, a layout approach was proposed for glass-carbon fiber composite-based optical cables, demonstrating its suitability for the distributed monitoring of sheet piles within cofferdams. The wavelet theory and optical smooth spline algorithm were used for data analysis. The findings indicated that the OFDR technology successfully captured the strain, bending moment, and deflection distribution on sheet piles during various excavation stages. These findings support the promotion of OFDR-based monitoring of sheet piles as an innovative cofferdam monitoring technology.

关键词： OFDR Sheet pile Cofferdam distributed monitoring

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distributed monitoring of Power System Oscillations Using Multiblock Principal Component Analysis and Higher-order Singular Value Decomposition

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Journal of Modern Power Systems and Clean Energy 2022年第4期10卷 818-828页

作者： Arturo Román-Messina Alejandro Castillo-Tapia David A.Román-García Marcos A.Hernández-Ortega Carlos A.Morales-Rergis Claudia M.Castro-Arvizu Center for Research and Advanced Studies(CINVESTAV)of the National Polytechnic Institute of Mexico GuadalajaraJal.45017Mexico Instituto Tecnológico y de Estudios Superiores de Monterrey GuadalajaraJal.45070Mexico Autonomous University of Guadalajara GuadalajaraJal.45129Mexico Centro de Enseñanza Técnica Industrial and he is also with UAGGuadalajaraJal.44638Mexico

The primary goal in the analysis of hierarchical distributed monitoring and control architectures is to study the spatiotemporal patterns of the interactions between areas or *** this paper,a novel conceptual framework for distributed monitoring of power system oscillations using multiblock principal component analysis(MB-PCA)and higher-order singular value decomposition(HOSVD)is proposed to understand,characterize,and visualize the global behavior of the power *** proposed framework can be used to evaluate the influence of a given area or utility on the oscillatory behavior,uncover low-dimensional structures from high-dimensional data,and analyze the effects of heterogeneous data on the modal characteristics and interpretation of power *** metrics are then investigated to examine the relationships between the dynamic patterns and participation of individual data blocks in the global behavior of the *** application of these techniques is demonstrated by case studies of two systems:a 14-machine test system and a 5449-bus 635-generator equivalent model of a large power system.

关键词： distributed monitoring multiblock principal component analysis(MB-PCA) higher-order singular value decomposition(HOSVD) Tucker decomposition

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Research on distributed monitoring system of intelligent highway based on weak fiber Bragg grating

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MEASUREMENT 2025年 242卷

作者： Yue, Lina Li, Sheng Liu, Fang Nan, Qiuming Fan, Dian Jiang, Jinpeng Wang, Juntao Wang, Qing Wuhan Univ Technol Natl Engn Res Ctr Fiber Opt Sensing Technol & Netw 122 Luoshi Rd Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Civil Engn & Architecture Civil Engn 122 Luoshi Rd Wuhan 430070 Peoples R China

The intelligent highway distributed monitoring system employing wFBG sensing technology is promising in the transport engineering. This research proposes a system architecture consisting of weak fiber Bragg grating (wFBG), data link, edge computing region and client interface. The structure and demodulation of the strained optical fiber cable and vibrating optical fiber cable based on wFBG were developed and applied. Further, taking Chen-Bridge and the nearby roadway as the research object, the performance of two types of sensing optical cables was verified according to dynamic and static loading experiments as well as finite element analysis. Moreover, the implementation solutions for intelligent highway functions such as bridge safety status, roadway safety status, lane identification, traffic volume statistics with speed calculation are proposed. Finally, the improvement directions of wFBG applications are analyzed.

关键词： distributed monitoring Weak fiber Bragg grating (wFBG) Intelligent highway Optical fiber cable

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Subspace-Aided distributed monitoring and Control Performance Optimization Approach for Interconnected Industrial Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第5期21卷 3839-3848页

作者： Huo, Mingyi Luo, Hao Xiao, Bing Jiang, Yuchen Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai 200093 Peoples R China Harbin Inst Technol Dept Control & Simulat Ctr Harbin 150001 Peoples R China Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China

This article proposes a subspace-aided distributed monitoring and control performance optimization integrated framework and the corresponding distributed monitoring and optimization approaches equivalent to centralized designs. It effectively realizes the online global control performance optimization and solves the predesigned controller parameter adjustment limitation. The main contributions of this article are as follows. First, the proposed distributed monitoring and optimization modules can cooperate to establish a subspace-aided distributed integrated framework. The framework effectively addresses the issue of separate design in monitoring and optimization, achieving modularization that facilitates the expansion and maintenance of interconnected systems. Second, the proposed subspace-aided control performance optimization approach breaks the limitations of existing methods that require predesigned controller parameter adjustments, which can achieve distributed control performance optimization while ensuring closed-loop stability of interconnected systems. Third, the proposed optimization approach can automatically adjust the iterative step size, avoiding the disadvantage of manually setting the step size in the traditional optimization algorithm. It shortens the optimization time and reduces the design difficulty. The new methodologies have been evaluated against the current techniques and validated using an interconnected dc motor system, which holds significant engineering importance.

关键词： monitoring Interconnected systems Adaptive control Accuracy Informatics Electronic mail Vectors Noise Neural networks Maintenance distributed control performance optimization distributed integrated framework distributed monitoring subspace-aided

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Data-Driven Design of distributed monitoring and Optimization System for Manufacturing Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第7期20卷 9455-9464页

作者： Wang, Hao Luo, Hao Ren, Lei Huo, Mingyi Jiang, Yuchen Kaynak, Okyay Harbin Inst Technol Control & Simulat Ctr Harbin 150001 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Bogazici Univ TR-34342 Istanbul Turkiye Ningbo Univ Sci & Technol Ningbo Peoples R China

The intelligent manufacturing system is a complex, large-scale, interconnected system composed of many intelligent agents, and there may be physical or information space couplings between the agents. A distributed monitoring system and optimization control method are proposed to ensure the system completes its tasks safely and efficiently. The distributed monitoring system based on the average consensus algorithm is equivalent to the centralized design method, in which the submonitoring system only requires local and neighbor subsystem information. The advantage of this design is that it uses local and interactive information to achieve global diagnosis. In addition, sending data from all subsystems to a central computing node is challenging to implement in large-scale manufacturing systems. Based on the centralized plug-and-play (PnP) optimization control method, an average consensus algorithm distributed manufacturing system PnP optimization control method is proposed. Its advantage is that it uses local information and interactive information to achieve global control optimization. On this basis, an integrated architecture for distributed fault detection and optimization control is developed. The simulation results verify the feasibility and effectiveness of proposed method.

关键词： Data-driven distributed monitoring distributed optimization manufacturing system

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From Local to Global Consistency in distributed monitoring of Petri Net Models

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第1期68卷 494-501页

作者： Jiroveanu, George Boel, Rene K. K. Romanian Natl Power Grid Co CNTEE Bucharest 030786 Romania Univ Ghent ELIA Syst Res Grp B-9042 Ghent Belgium

In this technical article we consider a distributed analysis of a plant given by local petri net models (components) that interact via shared transitions. For each component, there is a local agent that performs local calculations and exchanges information with its neighbours for monitoring the plant. We relax the standard requirement that the interaction graph between components is a tree and, for the general case, we investigate under which conditions the local consistency of the local estimates imply their global consistency. Moreover, we show that if the information exchanged between agents incorporates additional information related to the execution time intervals of the shared transitions, the globally consistent estimates become equal to the results derived in a CR.

关键词： distributed monitoring global consistency (GC) local consistency (LC) petri nets (PN)

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A local-global transformer for distributed monitoring of multi-unit nonlinear processes

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JOURNAL OF PROCESS CONTROL 2023年第1期122卷 13-26页

作者： Yi, Yongshuai Zhao, Haitao Hu, Zhengwei Peng, Jingchao East China Univ Sci & Technol Sch Informat Sci & Engn Automat Dept Shanghai 200237 Peoples R China

Nonlinear modeling of modern industrial processes with multi-unit, large-scale characteristics is very challenging. Centralized modeling involving all process variables at a time may neglect local behaviors. And most local-global modeling methods tend to ignore the correlation between units. To preserve the intra-unit information and inter-unit correlation, this paper proposes a local-global transformer (LGT) for distributed process monitoring. First, the local representation of each unit is extracted based on feedforward neural networks (FNN). Considering that the units have a fixed order in the process, the designed orthogonal positional encoding (OPE) is added to the local representation to obtain the token of each unit, which also enhances the local behaviors. Then the attention mechanism in the transformer can adaptively adjust the attention to different units and learn the inter-unit correlation from the tokens to extract global features. Finally, the distributed monitoring framework and the variable contribution rate are combined to achieve fault detection and location. The proposed LGT demonstrates the feasibility through a numerical simulation. Extensive experimental results on Tennessee Eastman (TE) process and three-phase flow (TPF) process show the superiority of LGT. The source code of LGT can be found in https://***/YiQian-137/Local--global-transformer.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Fault detection Fault location distributed monitoring Attention mechanism Transformer encoder

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Case study for Data Center distributed monitoring 12

Case study for Data Center Distributed Monitoring

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IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Benetti, Elisa Fracassetti, Matteo Mazzini, Gianluca Lepida ScpA Via Liberaz 15 I-40128 Bologna Italy

ISBN: (纸本)9781665483032

In just a few years, following a merger and new regional assignments, the same company has seen an exponential increase in hardware and software under management. Although a monitoring system was obviously already in place, a re-evaluation of it was necessary. In addition to the increase in the amount of objects to be monitored, their type has also changed: by managing healthcare infrastructures, which are critical by their nature, constant, reliable and fast monitoring has become essential. Starting from the first decision to keep the monitoring tool already in operation, its distributed architecture was then revised, optimizing it in the monitoring management subdivisions and providing for multi-level redundancies, also with a view to the continuous growth of the objects to be monitored.

关键词： data center distributed monitoring high availability scalability resilience

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Double-Layer distributed monitoring Based on Sequential Correlation Information for Large-Scale Industrial Processes in Dynamic and Static States

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第9期17卷 6419-6428页

作者： Huang, Jian Yang, Xu Peng, Kaixiang Univ Sci & Technol Beijing Key Lab Knowledge Automat Ind Proc Minist Educ Sch Automat & Elect Engn Beijing 100083 Peoples R China

Due to the complex static, dynamic, and large-scale characteristics for modern industrial processes, in this article, we propose a double-layer distributed monitoring approach based on multiblock slow feature analysis and multiblock independent component analysis. To this end, the processed dataset is divided into the static and dynamic blocks on the basis of the sequential information of each variable in the first layer. Considering the correlations between the variables in the large-scale processes, the sequential correlation matrices in two blocks are calculated, which serves as the second-layer block division rule. Then, the static and dynamic blocks are further divided into several static and dynamic subblocks in which the variables in each subblock are strongly correlated and in the same state. The slow feature analysis and independent component analysis monitoring models are, respectively, generated for the dynamic and static subblocks. Finally, the monitoring results in each subblock are integrated by Bayesian inference to get the final statistics. The average fault detection rate of the proposed method for the Tennessee Eastman process is 0.842, while those of the other traditional methods are lower than 0.75, which shows the advantages of the proposed method.

关键词： monitoring Correlation Feature extraction Integrated circuits Covariance matrices Independent component analysis Principal component analysis distributed monitoring dynamic and static characteristics independent component analysis (ICA) sequential mutual information (SMI) slow feature analysis (SFA)

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Data-Driven distributed Robust monitoring and Control Optimization for Interconnected Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第2期21卷 1399-1408页

作者： Wang, Hao Luo, Hao Qiao, Xinyu Huo, Mingyi Xu, Xiaoyi Harbin Inst Technol Dept Control & Simulat Ctr Harbin 150001 Peoples R China Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai 200093 Peoples R China

This article proposes a projection-aided robust distributed monitoring and control optimization approach for interconnected systems with disturbances. The disturbances and state coupling between subsystems are a challenge in achieving accurate distributed process monitoring using data-driven techniques. To address the problems, a distributed adaptive residual generator uses the average consensus algorithm to perform data fusion on the subsystem residual generator to implement disturbance decoupling process monitoring. The key to implementing this process is to use input and output data disturbance in the perturbed orthogonal complementary space to drive the adaptive residual generator. Then, using the projection technique, the residual signal in the disturbance space drives the distributed learning of plug-and-play (PnP) controller parameters. The average consensus algorithm ensures that the subsystem PnP controller parameter gradient consistency converges to the centralized design. The feasibility and effectiveness of the proposed approach are verified and demonstrated through a simulation.

关键词： monitoring Interconnected systems Generators Optimization Observers Aerospace electronics Accuracy distributed databases Computational modeling Principal component analysis Data-driven (DD) distributed monitoring disturbance rejection control interconnected systems

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