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检索条件"机构=School of Reliability Engineering and Systems Engineering"

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Prognostic-information-driven Policy for Joint Spare Parts Ordering and Postponed Replacement Optimization

Prognostic-information-driven Policy for Joint Spare Parts O...

引用

2023 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2023

作者： Han, Ruoran Ma, Xiaobing Yang, Li School of Reliability and Systems Engineering Beihang University China

ISBN: (纸本)9798350323153

This paper proposes a joint replacement and spare ordering policy, which utilizes prognostic information to update the adaptive decision of when to order spare parts and how long the repair is postponed after triggering the maintenance decision. A nonlinear Wiener process with randomness is established to characterize the degradation trend, along with updating online parameters under Bayesian framework at each inspection point. Unlike traditional discrete models, this strategy optimizes both ordering and maintenance, relying on a comprehensive cost rate indicator. Furthermore, based on residual useful life (RUL), this model adopts predictive maintenance to avoid resource waste of scheduled maintenance. Additionally, due to the timely maintenance accompanying monitoring reduces the availability of logistics resources, this model adopts a delay interval determined by RUL's expectation and a delay coefficient, and then which is optimized through order time and delay coefficient. Ultimately, the applicability of the proposed policy is verified by the actual case study of high-speed train bearings. © 2023 IEEE.

关键词： Bayesian update ordering time predictive maintenance residual useful life

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Fault Diagnosis of Unmanned Aerial Vehicle Based on the Slime Mold Algorithm under Imbalanced Data Conditions 14

Fault Diagnosis of Unmanned Aerial Vehicle Based on the Slim...

引用

14th International Conference on reliability, Maintainability and Safety, ICRMS 2023

作者： Wu, Xinman Zhang, Wenjin Li, Yu Suo, Mingliang Institute of Reliability Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350329988

With the rapid progress of technology, the application of unmanned aerial vehicles (UAVs) has become widespread in various civilian and military activities. The research on fault diagnosis during a flight is a critical step towards enhancing the safety of UAV systems. Swarm-inspired heuristic algorithms have attracted significant attention owing to their fast iteration speed and strong optimization capabilities. This paper proposes a UAV fault diagnosis method based on the slime mold algorithm (SMA) under the condition of imbalanced data, thus addressing the issue of low diagnostic accuracy caused by a significantly longer normal flight time compared to the fault flight time in UAV operations. Using a real-world dataset of UAV flight faults with multiple fault patterns, the proposed approach optimizes the parameters of the support vector machine through SMA, thereby improving the fault diagnosis performance during actual UAV flights. © 2023 IEEE.

关键词： Micro air vehicle (MAV)

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Fault Feature Recognition Of Satellite Power System Based On Incremental Learning 15

Fault Feature Recognition Of Satellite Power System Based On...

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15th IEEE Global reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Li, Zhipeng Yang, Yang Dong, Yanchen Zhu, Baolong Suo, Mingliang School of Reliability and Systems Engineering Beihang University Beijing100191 China No.31850 Unit People's Liberation Army of China Beijing102200 China Jinan250353 China Institute of Reliability Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering School of Reliability and Systems Engineering Beihang University Beijing100191 China

ISBN: (纸本)9798350354010

In modern communications and technology, satellite power systems play a central role, and their reliability and fault diagnosis technology are increasingly important. Traditional fault diagnosis methods mainly include signal processing and model-based methods, but they are often inefficient and have limited accuracy when processing complex data sets. This paper proposes a feature selection algorithm based on incremental learning to improve the efficiency and accuracy of fault diagnosis. Its advantage is that it can only evaluate the newly added feature set without the need to reprocess the entire data set, thus optimizing the feature selection process and significantly improving the efficiency and response speed of the algorithm. In order to verify its effectiveness, this article selected 8 public data sets and 4 satellite power system simulation data sets for testing. Then, widely used algorithms are introduced to compare with the algorithm proposed in this article for a more comprehensive comparative analysis. By comparing the differences in running time and classification accuracy of the algorithms, it is concluded that the algorithm proposed in this article can significantly reduce the running time while maintaining or improving the classification effect, verifying the feasibility of the algorithm. © 2024 IEEE.

关键词： Satellite communication systems

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Research on reliability Management and Control Method of Aeronautical Product Development Based on systems engineering Management Plan 31st

Research on Reliability Management and Control Method of Aer...

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31st European Safety and reliability Conference, ESREL 2021

作者： Li, Jiake Wang, Wei Li, Jingfen School of Reliability and Systems Engineering Beihang University China

ISBN: (纸本)9789811820168

The SEMP (systems engineering management plan) is a management program that controls the entire product development process by managing the entire manufacturing process. The development risk of existing aerospace products is highly related to its complexity and maturity, which are mainly reflected in requirements demonstration, design analysis and test verification. Therefore, based on the theory of SEMP, this paper puts forward a quality control scheme from three aspects of requirement demonstration, design analysis and test verification, and establishes a management and control method for quality characteristics of aerospace product development, such as reliability. It can help product development enterprises to manage and control their product development process more comprehensively, so as to reduce the risk of product development, which is of great significance to improve the overall quality of aviation products and reduce the risk of development. This method can also provide a new idea for the development and control of aviation products in the future, which is helpful to avoid risks and improve the quality of aviation products. © ESREL 2021. Published by Research Publishing, Singapore.

关键词： Product development

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Distributionally Robust Inventory Optimization Method for Spare Parts Fill Rate 28

Distributionally Robust Inventory Optimization Method for Sp...

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28th International Conference on Automation and Computing, ICAC 2023

作者： Li, Ruowen Chang, Wenbing Yang, Linchao Xiao, Yiyong Zhou, Shenghan School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350335859

This paper attempts to address the uncertain demand decision problem for spare parts in complex industrial equipment. The classic approach to inventory optimization assumes that the demand distribution is known in advance. However, this is not always the case. In recent years, more and more researchers have used data-driven approaches offers another choice, but that requires a large amount of dataset to generate high-quality decisions, which are not available in many real-world settings. On the other hand, most studies focus on cost minimization with no limits on spare parts fill rate. In order to overcome this problem, the proposed method uses chance constraint to characterize the spare parts fill rate, introduces it into the random inventory model under the cost minimization framework, and finally models and solves it through distribution robust optimization. The proposed method is evaluated through numerical research, and it is proved that the proposed method can achieve a higher spare parts fill rate with a small sample size and have the robustness to overcome the uncertainty of demand. © 2023 IEEE.

关键词： Optimization

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Infrared Thermal Imaging-Based Power MOSFET Thermal Resistance Test Method Research 14

Infrared Thermal Imaging-Based Power MOSFET Thermal Resistan...

引用

14th IEEE Global reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Shao, Hongming Zhang, Sujuan Wan, Bo Wang, Ye Long, Mengxiang School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350301359

Based on the high-precision infrared thermal imaging camera, the calibration effect of black paint coating on the emissivity and temperature measurement results was investigated. We developed a set of device junction temperature test schemes with reduced error, utilizing the Infrascope TM-HST hot spot detection system. Experimental tests were conducted to verify the repeatability of the thermal resistance measurement results obtained from the devised scheme. Based on the structure-function theory, the junction temperature drop curve is obtained by using the determined test scheme, and the integral structure function curve of the device is analyzed to determine the thermal resistance parameters of each structural layer of the device under test. The results demonstrate the practicality and effectiveness of using the structure function method to analyze the thermal resistance parameters of power MOSFETs. © 2023 IEEE.

关键词： infrared thermal imaging power devices structure-function thermal resistance

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Quantitative Safety Analysis Method for Complex Equipment System Based on FRAM 14

Quantitative Safety Analysis Method for Complex Equipment Sy...

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14th International Conference on reliability, Maintainability and Safety, ICRMS 2023

作者： Luo, Ximing Jing, Yongfeng Jiao, Jian School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350329988

As complex equipment systems evolve to higher levels of sophistication, conventional risk and safety assessment techniques may find it challenging to offer a comprehensive risk analysis, especially in discerning the interactions and linkages among diverse functional elements. The functional resonance analysis method (FRAM) provides a functional viewpoint for system understanding and the analysis of potential hazards emerging from these functional couplings. This study devised a quantitative approach to assess the safety level of intricate equipment systems, with a focus on functional couplings as framed by FRAM. Quantitative scrutiny was applied to the interrelationships among functions within the system, culminating in an evaluation of the system's overall safety level. The viability of the proposed methodology was corroborated through a case study. © 2023 IEEE.

关键词： Safety engineering

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A Short-term Demand of Bike-sharing Forecasting Model Based on Spatio-temporal Graph Data 28

A Short-term Demand of Bike-sharing Forecasting Model Based ...

引用

28th International Conference on Automation and Computing, ICAC 2023

作者： Song, Chaofei Zhou, Shenghan Chang, Wenbing Xiao, Yiyong Fu, Yu Yang, Linchao School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350335859

The research aims to use deep learning to develop a site-level bike-sharing demand prediction model to address the uneven distribution of free-flowing vehicles due to the growth of bike-sharing into the market. In recent years, cycling has become an important form of supportive public transportation, especially for 'last mile' commuting. However, with the increase of bike-sharing activities in the market, some free-flowing vehicles are facing different spatial and temporal distribution problems. To overcome these challenges, we use a Graph Convolutional Neural Networks (GCN) to capture the spatial relationships between bike-sharing sites, a Gate Recurrent Unit (GRU) to capture the temporal proximity and periodicity of each site's historical data, and an Attention mechanism to dynamically capture the temporal dependencies and improve the model's performance. It is shown that the proposed approach has better performance compared to other models, as demonstrated by MAE and RMSE measurements, which have signals of 1.09 and 2.21 on this dataset, respectively. the error is reduced by at least 21.4% compared to other comparative models, showing strong predictive performance. Thus, this paper implements a deep learning model that can accurately predict the demand of bike-sharing stations, which provides a decision basis for solving the scheduling of unbalanced spatial and temporal distribution of bike-sharing. © 2023 IEEE.

关键词： Forecasting

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RESEARCH ON UNMANNED CLUSTER RECONNECTION DECISION-MAKING METHOD CONSIDERING RESOURCE SUPPLEMENTATION 34th

RESEARCH ON UNMANNED CLUSTER RECONNECTION DECISION-MAKING ME...

引用

34th Congress of the International Council of the Aeronautical Sciences, ICAS 2024

作者： Yao, Mengfei Wang, Xiaohong Kong, Linghao Fu, Guicui Wang, Xiaohui Yao, Jun School of Reliability and Systems Engineering Beihang University China Chinese Aeronautical Establishment China

In recent years, with the widespread application, intelligence, and increasing complexity of task scenarios of unmanned cluster systems in various fields, the system capability of clusters has become increasingly dynamic and flexible. It is not only related to the state of individuals but also to the reconnection patterns of clusters. Consequently, the capability can be reversibly enhanced through structural adjustments or resource replenishment in the system. Therefore, addressing the issue of how to make decisions on resource replenishment methods to efficiently and reasonably utilize resources, and thereby ensuring the high reliability operation of unmanned clusters, this paper focuses on the unmanned aerial vehicle (UAV) cluster system in open environments. It analyzes the available states of unmanned clusters under conditions of no reconnection, reconnection, and resource replenishment, and proposes methods for decision optimization of cluster resource replenishment based on degree-preferred connections and particle swarm algorithm. This provides a systematic approach to solving the problems of replenishment, scale changes, and decision optimization of unmanned cluster resources. © 2024, International Council of the Aeronautical Sciences. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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reliability Assessment of Anti-SEU Computer System with Timed Refresh and Backup Fault Tolerance 14

Reliability Assessment of Anti-SEU Computer System with Time...

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14th IEEE Global reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Zhang, Zhongqing Fu, Guicui Wan, Bo Wang, Xiangfen School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (纸本)9798350301359

Spacecraft often fail due to single event upset (SEU) events. To enhance system reliability, a variety of anti-radiation reinforcement measures are used in combination. This paper proposes a reliability assessment method for a computer system that adopts timed refresh and backup fault tolerant measures. This method establishes a failure probability model for the SEU-prone RAM devices in computer systems by considering the state transition characteristics of the timed refresh task and the error correction rules of Hamming codes. Additionally, the Bootstrap small sample data processing method is utilized to obtain the confidence interval estimation of the failure probability. Furthermore, a dynamic fault tree is established according to various backup measures and logical architectures of the anti-SEU computer system. The reliability of the system during the mission is estimated using the Monte Carlo method. At the end of the paper, a case study is carried out. The reliability data of components or systems obtained by this method will provide a reference for designers to evaluate whether the spacecraft is operating safely in orbit. © 2023 IEEE.

关键词： anti-SEU computer system backup fault tolerance RAM reliability assessment timed refresh

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