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optimal sensor configuration and Feature Selection for AHU Fault Detection and Diagnosis

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2017年第3期13卷 1369-1380页

作者： Li, Dan Zhou, Yuxun Hu, Guoqiang Spanos, Costas J. Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

Experiments show that operation efficiency and reliability of buildings can greatly benefit from rich and relevant datasets. More specifically, data can be analyzed to detect and diagnose system and component failures that undermine energy efficiency. Among the huge quantity of information, some features are more correlated with the failures than others. However, there has been little research to date focusing on determining the types of data that can optimally support fault detection and diagnosis (FDD). This paper presents a novel optimal feature selection method, named information greedy feature filter (IGFF), to select essential features that benefit building FDD. On one hand, the selection results can serve as reference for configuring sensors in the data collection stage, especially when the measurement resource is limited. On the other hand, with the most informative features selected by the IGFF, the performance of building FDD could be improved and theoretically justified. A case study on air-handling unit (AHU) is conducted based on the dataset of the ASHRAE Research Project 1312. Numerical results show that, compared with several baselines, the FDD performances of conventional classification methods are greatly enhanced by the IGFF.

关键词： Air-handling unit (AHU) data-driven method fault detection and diagnosis (FDD) feature selection optimal sensor configuration

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optimal sensor configuration for ultrasonic guided-wave inspection based on value of information

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2020年 135卷 106377-000页

作者： Cantero-Chinchilla, Sergio Chiachio, Juan Chiachio, Manuel Chronopoulos, Dimitrios Jones, Arthur Univ Nottingham Inst Aerosp Technol Nottingham NG7 2RD England Univ Nottingham Composites Grp Nottingham NG7 2RD England Univ Granada Dept Struct Mech & Hydraul Engn E-18001 Granada Spain Aernnova Engn Div SA Madrid 28034 Spain

Condition-based maintenance critically relies on efficient and reliable structural health monitoring systems, where the number, position and type of sensors are determined according to rational and principled criteria. This paper proposes the use of the value of information and the relative expected information gain as optimality criteria to determine the best number and positions of sensors, respectively. The proposed methodology is general, but in this paper it is specialized for ultrasonic guided-wave optimal system configuration. Two case studies are used to illustrate the suitability of the proposed methodology in providing the optimal sensor configuration of an ultrasonic guided-wave based structural health monitoring system. The results confirm the value of information as an efficient and rational index to compare among different sensor positioning strategies, while accounting for the underlying modeling and measurement uncertainties. As key contribution, a novel framework that trades-off between amount and cost of information is provided. The results show that geometrically unconstrained sensor configurations are preferred, since they provide a healthier balance between the amount of information and the benefit of such information. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： optimal sensor configuration Value of information Bayesian inverse problem Ultrasound Time of flight SHM

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optimal sensor configuration for structural response prediction by a modified Nelder-Mead simplex method

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STRUCTURAL CONTROL & HEALTH MONITORING 2021年第5期28卷 e2712-e2712页

作者： Yin, Tao Wuhan Univ Sch Civil Engn Wuhan 430072 Peoples R China

The optimal configuration of the sensor system is extremely critical to effectively control the test cost and ensure the quality of the collected data for structural health monitoring (SHM) system. Different from the traditional sensor configuration criterion, the information entropy measure aims to minimize the uncertainty of structural model parameters to be identified, which can ensure that the collected data provides the maximum amount of information for the model identification. However, most of the current researches within the framework of entropy measure are aimed at the model identification, while studies that consider response prediction are still rare. In this paper, by constructing the posterior predictive distribution function of the frequency response functions (FRFs) at the unmeasured positions of structures and also the corresponding information entropy representation, the optimal sensor configuration problem for the purpose of structural response prediction at the unmeasured position is studied. A modified bound-constrained Nelder-Mead simplex method to handle the binary encoded optimization variables is also proposed, which can effectively solve the combinatorial optimization problem in the optimal sensor configuration. The methodology proposed is validated by a forced vibration study conducted for a laboratory rectangular cantilever plate. The obtained results show that the prediction error and uncertainty of the higher-order modes of the FRFs at the unmeasured positions is generally larger than that of the lower ones. Also, by comparing the performance of worst and optimal sensor layouts, the importance of the optimal configuration for response prediction at unmeasured locations is clearly revealed especially for a small number of sensors.

关键词： frequency response function information entropy Nelder– Mead simplex method optimal sensor configuration response prediction structural health monitoring

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INFORMATION ENTROPY-BASED optimal sensor configuration FOR CONTINUOUS-COORDINATE STRUCTURES

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12th International Symposium on Structural Engineering (ISSE-12)

作者： Yin, Tao Li, Dianqing Zhu, Hongping Wuhan Univ Sch Civil & Architectural Engn Wuhan 430072 Peoples R China Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China Huazhong Univ Sci & Technol Sch Civil Engn & Mech Wuhan 430074 Peoples R China

ISBN: (纸本)9787030357878

For works related to the sensor placement problem in the literature, the generally used discrete-coordinate systems modeled by the finite element (FE) can only approximate their actual dynamic behavior, and the sensors are confined to be put only on discrete nodes corresponding to the coarse mesh scheme usually employed. An optimal sensor placement methodology for the continuous-coordinate structures with typical distributed-parameter properties has been proposed by the authors to minimize the uncertainties associated with the identified structural modeling parameters, where the information entropy is employed as a measure to quantify the uncertainty. The optimal sensor configuration is obtained by minimizing the information entropy through a continuous optimization procedure. However, in the obtained optimal configuration results for the continuous-coordinate structures, some sensors tend to be infinitely close to each other, and the main purpose of this paper to introduce an effective approach to overcome this drawback.

关键词： optimal sensor configuration structural model updating bayesian statistical identification framework information entropy genetic algorithm

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Identification of Supersonic Inlet Unstarted State and optimal sensor configuration Based on EI-SPEA2

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JOURNAL OF AEROSPACE ENGINEERING 2023年第2期36卷 04022131-04022131页

作者： Zhao, Yong-Ping Yang, Tian-Lin Tan, Hui-Jun Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn 29 Yudao St Nanjing 210016 Peoples R China

As the key starting component of supersonic flight, identification of the unstarted state of the supersonic inlet is the premise of restarting the inlet and an important link of engine protection control. In order to explore the characteristics of the dynamic pressure inside the inlet, the selection of a pressure sensor configuration scheme, that is, how to obtain more abundant pressure information with fewer sensors, is also an urgent problem to be solved. This paper combines time-frequency analysis and deep learning for flow pattern recognition of a supersonic inlet and proposes a strength-based Pareto evolutionary algorithm combined with improved extinction and migration strategies (EI-SPEA2). The signals of all sensors were preliminarily processed using continuous wavelet transform, and the dynamic signals of all sensors were transformed into two-dimensional (2D) time-frequency spectrograms, which were then used as inputs by convolutional neural network to determine the inlet flow patterns from the dynamic sensor signals. A multiobjective optimization algorithm, EI-SPEA2, was adopted, which takes the minimum classification error, minimum number of selected sensors, and optimal sensor distribution as the optimization objectives. Through the continuous iteration of the population, identification of the unstarted state and optimal configuration of sensors was carried out simultaneously. By introducing the improved EI strategy at the end of iteration, SPEA2 can get rid of the local optimum and achieve convergence faster. A distance index for measuring sensor distribution and two indexes for measuring sensor information differentiation are proposed to improve sensor configuration scheme. The experimental results demonstrated that compared with competitive methods, EI-SPEA2 has better performance on both dual-objective optimization problems and three-objective optimization problems. Moreover, three indexes proposed to measure the distribution of the sensor are benefic

关键词： Identification of unstarted state Time-frequency analysis Convolutional neural network Multiobjective evolutionary algorithm optimal sensor configuration

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Robust optimal sensor configuration using the value of information

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STRUCTURAL CONTROL & HEALTH MONITORING 2022年第12期29卷 e3143-e3143页

作者： Cantero-Chinchilla, Sergio Papadimitriou, Costas Chiachio, Juan Chiachio, Manuel Koumoutsakos, Petros Fabro, Adriano T. Chronopoulos, Dimitrios Univ Bristol Dept Mech Engn Bristol BS8 1TR Avon England Univ Thessaly Dept Mech Engn Volos Greece Univ Granada Andalusian Res Inst Data Sci & Computat Intellige Dept Struct Mech & Hydraul Engn Granada 18001 Spain Harvard Univ Sch Engn & Appl Sci 29 Oxford St Cambridge MA 02138 USA Swiss Fed Inst Technol Computat Sci & Engn Lab Clausiusstr 33 CH-8092 Zurich Switzerland Univ Brasilia Dept Mech Engn Brasilia DF Brazil Katholieke Univ Leuven Dept Mech Engn & Mechatron Syst Dynam LMSD B-9000 Ghent Belgium

Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for (1) uncertainties from updatable and nonupdatable parameters, (2) variability of the objective function with respect to nonupdatable parameters, and (3) the spatial correlation between sensors. The optimal sensor configuration is obtained by maximizing the expected value of information, which leads to a cost-benefit analysis that entails model parameter uncertainties. The proposed methodology is demonstrated on an application of structural health monitoring in plate-like structures using ultrasonic guided waves. We show that accounting for uncertainties is critical for an accurate diagnosis of damage. Furthermore, we provide critical assessment of the role of both the effect of modeling and measurement uncertainties and the optimization algorithm on the resulting sensor placement. The results on the health monitoring of an aluminum plate indicate the effectiveness and efficiency of the proposed methodology in discovering optimal sensor configurations.

关键词： guided waves optimal sensor configuration prediction model error robust optimization structural health monitoring value of information

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INFORMATION ENTROPY-BASED optimal sensor configuration FOR CONTINUOUS-COORDINATE STRUCTURES

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The Twelfth International Symposium on Structural Engineering

作者： Tao Yin Dianqing Li Hongping Zhu School of Civil & Architectural Engineering Wuhan University State Key Laboratory of Water Resources & Hydropower Engineering Science Wuhan University School of Civil Engineering & Mechanics Huazhong University of Science and Technology

ISBN: (纸本)9787030357878

＜正＞For works related to the sensor placement problem in the literature,the generally used discrete-coordinate systems modeled by the finite element（FE） can only approximate their actual dynamic behavior,and the sensors are confined to be put only on discrete nodes corresponding to the coarse mesh scheme usually *** optimal sensor placement methodology for the continuous-coordinate structures with typical distributed-parameter properties has been proposed by the authors to minimize the uncertainties associated with the identified structural modeling parameters, where the information entropy is employed as a measure to quantify the *** optimal sensor configuration is obtained by minimizing the information entropy through a continuous optimization ***,in the obtained optimal configuration results for the continuous-coordinate structures,some sensors tend to be infinitely close to each other,and the main purpose of this paper to introduce an effective approach to overcome this drawback.

关键词： optimal sensor configuration structural model updating bayesian statistical identification framework information entropy genetic algorithm

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Robust optimal sensor configuration for modal sensing

Robust optimal sensor configuration for modal sensing

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Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

作者： Feng Wang Daokui Li Guojin Tang College of Aerospace and Matrial Engineering National University of Defense Technology Changsha Hunan China

ISBN: (纸本)0780393953

Extract modal displacements from sensor outputs, known as modal sensing, is a key issue in independent modal space control. Spillover in the sensed modal displacements is usually inevitable when finite number of discrete sensors are used. This paper investigate the influence of the sensor configuration on spillover level and robustness of the modal sensor. It's found that the condition number of the modal sensor is the key factor. Thus, an optimization problem is developed to determine the optimal sensor configuration. The modified simulated annealing algorithm is employed to solve the problem. An clamped beam with five piezoelectric sensors is modeled using the finite method. Numerical simulations verified the theoretical analysis.

关键词： modal analysis piezoelectric actuators sensors simulated annealing vibration control modal sensing optimal sensor configuration piezoelectric sensors simulated annealing

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optimal configuration of sensor Network for Structural Shape Reconstruction Based on Improved Jaya Algorithm 43

Optimal Configuration of Sensor Network for Structural Shape...

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43rd Chinese Control Conference (CCC)

作者： Yang, Hong Jiao, Peng Chen, Leran Gao, Zhiyuan Zhang, Hesheng Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200444 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

In the research background of aerospace structural health monitoring, The optimal configuration of the strain sensor network used for shape reconstruction of flexible plate structures is studied. Based on the characteristics of the 3D curved surface reconstruction algorithm, the co-row and co-column, row and column spacing, and strain distribution are employed as the optimization criteria of sensor network optimization configuration and the reconstruction error of structural shape is used as the evaluation metric of optimization effect. In order to solve the problem that the traditional Jaya algorithm is prone to local optimums in the optimal configuration solution, an improved algorithm is proposed to design a comprehensive optimization of the number and location of sensor deployment in the sensor network. In addition, the simulation results show that the shape reconstruction effect of the plate structure is improved effectively through the optimal design of the sensor network configuration. Finally, the optimally configured sensor network is used to conduct shape reconstruction experiments on aluminum alloy plate, which verifies the effectiveness of the optimal configuration method and provides some theoretical basis for the optimal configuration of the sensor network for structural shape reconstruction.

关键词： Structural Shape Reconstruction optimal sensor configuration Error of Reconstruction Improved Jaya Optimization Algorithm

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optimal configuration of sensor Network for Structural Shape Reconstruction Based on Improved Jaya Algorithm

Optimal Configuration of Sensor Network for Structural Shape...

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第43届中国控制会议

作者： Hong Yang Peng Jiao Leran Chen Zhiyuan Gao Hesheng Zhang School of Mechatronic Engineering and Automation Shanghai University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the research background of aerospace structural health monitoring,The optimal configuration of the strain sensor network used for shape reconstruction of flexible plate structures is *** on the characteristics of the 3D curved surface reconstruction algorithm,the co-row and co-column,row and column spacing,and strain distribution are employed as the optimization criteria of sensor network optimization configuration and the reconstruction error of structural shape is used as the evaluation metric of optimization *** order to solve the problem that the traditional Jaya algorithm is prone to local optimums in the optimal configuration solution,an improved algorithm is proposed to design a comprehensive optimization of the number and location of sensor deployment in the sensor *** addition,the simulation results show that the shape reconstruction effect of the plate structure is improved effectively through the optimal design of the sensor network ***,the optimally configured sensor network is used to conduct shape reconstruction experiments on aluminum alloy plate,which verifies the effectiveness of the optimal configuration method and provides some theoretical basis for the optimal configuration of the sensor network for structural shape reconstruction.

关键词： Structural Shape Reconstruction optimal sensor configuration Error of Reconstruction Improved Jaya Optimization Algorithm

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