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46 results on '"Suo, Mingliang"'

1. An Outline of Prognostics and Health Management Large Model: Concepts, Paradigms, and Challenges

Author

Tao, Laifa, Li, Shangyu, Liu, Haifei, Huang, Qixuan, Ma, Liang, Ning, Guoao, Chen, Yiling, Wu, Yunlong, Li, Bin, Zhang, Weiwei, Zhao, Zhengduo, Zhan, Wenchao, Cao, Wenyan, Wang, Chao, Liu, Hongmei, Ma, Jian, Suo, Mingliang, Cheng, Yujie, Ding, Yu, Song, Dengwei, and Lu, Chen

Subjects
Computer Science - Artificial Intelligence, Computer Science - Software Engineering, Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control
Abstract

Prognosis and Health Management (PHM), critical for ensuring task completion by complex systems and preventing unexpected failures, is widely adopted in aerospace, manufacturing, maritime, rail, energy, etc. However, PHM's development is constrained by bottlenecks like generalization, interpretation and verification abilities. Presently, generative artificial intelligence (AI), represented by Large Model, heralds a technological revolution with the potential to fundamentally reshape traditional technological fields and human production methods. Its capabilities, including strong generalization, reasoning, and generative attributes, present opportunities to address PHM's bottlenecks. To this end, based on a systematic analysis of the current challenges and bottlenecks in PHM, as well as the research status and advantages of Large Model, we propose a novel concept and three progressive paradigms of Prognosis and Health Management Large Model (PHM-LM) through the integration of the Large Model with PHM. Subsequently, we provide feasible technical approaches for PHM-LM to bolster PHM's core capabilities within the framework of the three paradigms. Moreover, to address core issues confronting PHM, we discuss a series of technical challenges of PHM-LM throughout the entire process of construction and application. This comprehensive effort offers a holistic PHM-LM technical framework, and provides avenues for new PHM technologies, methodologies, tools, platforms and applications, which also potentially innovates design, research & development, verification and application mode of PHM. And furthermore, a new generation of PHM with AI will also capably be realized, i.e., from custom to generalized, from discriminative to generative, and from theoretical conditions to practical applications.

Published
2024

3. Optimized Selection of Inertial Measurement Unit by Considering Calibration Information and Long-Term Stability

Author

Ma, Xiaofei, Huang, Hailian, Xing, Jingyi, Ma, Ke, Suo, Mingliang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Deng, Yimin, editor

Published
2023
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4. A Novel Method for Aircraft Actuator Fault Diagnosis Based on Causal Graph and T-S Fuzzy Model

Author

Chen, Yu, Tao, Laifa, Li, Yue, Wang, Qiang, Suo, Mingliang, Zhao, Zhengduo, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Deng, Yimin, editor

Published
2023
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40. Neighborhood grid clustering and its application in fault diagnosis of satellite power system.

Author

Suo, Mingliang, Zhu, Baolong, Zhou, Ding, An, Ruoming, and Li, Shunli

Subjects
FAULT diagnosis, ARTIFICIAL satellite attitude control systems, NEIGHBORHOODS, ARTIFICIAL satellites, DATA mining
Abstract

Data-driven fault diagnosis, known to be simple and convenient, is more suitable for diagnosing the complicated spacecraft systems, e.g. the satellite power system. Nevertheless, it is difficult to extract the rules for diagnosing from unlabeled data. In this paper, a clustering approach based on neighborhood relationship and spatial grid partition is proposed to compensate for the above deficiency. In order to deal with the data-driven fault diagnosis issue, a diagnostic strategy is designed, which is a combination of the proposed clustering method and the entropy weight. Finally, multiple experiments, consisting of the artificial data clustering, comparison experiments on satellite data mining, and a case of fault diagnosis on satellite power system, are carried out to illustrate the versatility and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Published
2019
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42. L2-L∞ filtering for a class of stochastic nonlinear systemswith aperiodic sampling.

Author

Zhu, Baolong, Suo, Mingliang, Zhang, Zhiping, Li, Min, and Li, Shunli

Subjects
INFORMATION filtering, NONLINEAR systems, STOCHASTIC analysis, FILTERS (Mathematics), APERIODICITY, CHUA'S circuit
Abstract

Thiswork investigates the problem of L2-L∞ filtering for a class of stochastic nonlinear systems with nonuniform sampling. The sampled-data filter developed in this paper is an impulsive differential system whose states change abruptly at every sampling instant. The resulting filtering error system is modeled as a stochastic nonlinear impulsive differential system. The goal is to propose a method for designing a target filter that ensures the stochastic asymptotic stability of the filtering error system and guarantees a prescribed L2-L∞ performance. Based on a time-varying Lyapunov functional, by virtue of a convex combination technique, a design method to achieve such a filter is formulated in the form of solving a set of linear matrix inequalities. The effectiveness of the proposed filtering strategy is shown via a numerical example of a stochastic Chua's circuit system. [ABSTRACT FROM AUTHOR]

Published
2018
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43. Notice of Retraction: A new idea of identification of road traffic conditions

Author

Sun Qi, Guo Dudu, Liang Yan-ping, and Suo Mingliang

Subjects
Traffic congestion reconstruction with Kerner's three-phase theory, Computer science, business.industry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Floating car data, Vehicle Information and Communication System, Traffic flow, Transport engineering, Traffic congestion, Traffic engineering, ComputerSystemsOrganization_MISCELLANEOUS, Traffic optimization, business, Traffic bottleneck
Abstract

Urban traffic congestion is one of the major problems faced by nearly every country in the world. Research on traffic congestion evaluation in country and abroad is summarized from both technology of traffic data collection and method of identification of road traffic conditions. Traditional detectors can never provide any data on traffic conditions beyond the detection point, nor the traffic data of the whole road network. But high resolution satellite imagery may provide a new method for collection of traffic data. And two methods for traffic congestion evaluation are put forward based on high resolution satellite imagery.

Published
2010

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