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检索条件"机构=Science and Technology Laboratory on Reliability Physics and Application of Electronic Component"

共 496 条记录，以下是41-50 订阅

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Comparative Study of Proton and Heavy Ion-induced Damages for GaN-based HEMTs 24

Comparative Study of Proton and Heavy Ion-induced Damages fo...

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8th International Conference on electronic Information technology and Computer Engineering, EITCE 2024

作者： Wu, Zhipeng Huang, Huixiang Yang, Jianqun Lei, Zhifeng Cui, Xiuhai Ma, Teng Peng, Chao School of Opto-electronic and Communication Engineering Xiamen University of Technology Fujian Xiamen China National Key Laboratory of Material Behavior and Evaluation Technology in Space Environment Harbin Institute of Technology Heilongjiang Harbin China Science and Technology on Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangdong Guangzhou China

ISBN: (纸本)9798400710094

The variations of the radiation damage induced by radiation from protons and heavy ions on Cascode GaN HEMTs are comparatively studied. 300 MeV proton and 500 MeV heavy ion irradiation are carried out for AlGaN/GaN HEMTs. Findings from the study indicate that exposure to a proton flux of 300 MeV, reaching a cumulative level of 1×1011 cm-2, leads to a reduction in the output current. Concurrently, there is a downward adjustment of 0.27 volts in the turn-on voltage, along with a 5.59% decline in the peak transconductance. Following irradiation, the creation of traps within the device’s channel layer results in a decline in its electrical efficiency. Under 500 MeV heavy ion irradiation with a total fluence of 3.167×105cm-2, a significant leakage current increase is observed when a drain bias of 100 volts is applied. An enhancement in the output current is observed, accompanied by a 0.11V downward adjustment in the voltage at which the channel forms and a significant 70.17% diminution in peak transconductance. Additionally, instances of single event burnout (SEB) are detectable when the drain bias exceeds 150 V. © 2024 Copyright held by the owner/author(s).

关键词： Gallium nitride

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Enhanced Inverter Hybrid Fault Diagnosis through RAM and CNN Integration 14

Enhanced Inverter Hybrid Fault Diagnosis through RAM and CNN...

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

作者： Meng, Linghui Li, Lin Jiang, Yuanyuan Science and Technology on Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangdong Guangzhou China Anhui University of Science and Technology School Institute of Artificial Intelligence Anhui Huainan China

ISBN: (纸本)9798350329988

Deep learning has been widely used in inverter open-circuit fault diagnosis;however, traditional neural networks only extract signal features of inverter faults without distinguishing between significant and minor features. To address this limitation, this paper proposes a diagnostic method for inverter hybrid faults that combine reverse attention mechanism (RAM) and convolutional neural networks. The proposed method highlights important features by utilizing RAM to reverse the attention and prune the minor features. In addition, long short-term memory is used to learn temporal information between the features. Finally, fault classification is performed using fully connected layers. Simulation experiments indicate that the proposed diagnostic method significantly improves fault diagnosis accuracy. Compared to traditional neural network fault diagnosis methods, our proposed method achieves up to 8.07% higher diagnosis accuracy, thereby validating its effectiveness. © 2023 IEEE.

关键词： Convolutional neural networks

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Analytical and Measurement-Based Method for Diagnosing the Fault of Channels in TSV-Based 3D ICs 1

Analytical and Measurement-Based Method for Diagnosing the F...

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2022 1st International Conference on Advances in Modern physics sciences and Engineering technology, ICPSET 2022

作者： Qu, Chenbing Zheng, Linting Wang, Liwei Sun, Chen Science and Technology on Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China

Three-dimensional integrated circuits (3D ICs) based on through silicon via (TSV) technology can effectively solve many bottlenecks in the development of ICs. It has rapidly developed into a key cutting-edge technology representing the medium and long-term sustainable development of microelectronics industry. Process fluctuation causes TSV process defects, resulting in the change of structural parameters of RDL and TSV interconnection structure. Finally, it leads to the degradation of performance parameters and functional failure of 3D interconnection and devices. Aiming at the high-resistance and open-circuited faults of 3D ICs, this paper develops an analysis method based on micro nano machining and detection technology. The electrical characteristics and images of typical chain TSV interconnections are analyzed by scanning electron microscope high-resolution imaging. The mechanism of fault diagnosis is based on potential difference and electron transfer. © Published under licence by IOP Publishing Ltd.

关键词： Three dimensional integrated circuits

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New Diagnostics for Inferring Multiple Fault Scenarios and Accurate Fault Localization

New Diagnostics for Inferring Multiple Fault Scenarios and A...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhou, Huisi Hu, Wei Zhu, Dan Wang, Liwei Northwestern Polytechnical University School of Cybersecurity Xi'an710072 China Research & Development Institute Northwestern Polytechnical University Shenzhen China Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory Guangzhou430070 China

ISBN: (纸本)9798350351255

For many high-tech fields such as mobile communication systems, network management, and satellite and space applications, it is vital to discover faulty components of manufactured devices in a timely manner to ensure safety. Model-based diagnosis is a crucial element in fault diagnosis. It aims to find the possible causes of the observed unexpected behaviors of a system when assuming all of its components work correctly. In this paper, we propose two diagnostics, namely, the Improved Model-Based Diagnosis (IMBD) and the Localization-Based Diagnosis (LBD), to address the research challenge that massive candidate diagnoses are needed in the traditional model-based diagnosis approach for repairing the faulty system. Our diagnostics realizes a simulator to simulate the single-fault scenarios, through which we can reason about the scenarios where multiple faults occur and find which components are more likely to fail in the multiple-fault system. Experiments using the ISCAS-85 benchmarks indicate that LBD is superior to IMBD and SAT-based approaches for accurate fault localization. © 2024 IEEE.

关键词： Satellite communication systems

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Fracture Analysis of QBe2.0 Beryllium Bronze Conductive Spring 14

Fracture Analysis of QBe2.0 Beryllium Bronze Conductive Spri...

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

作者： Li, Ziyang Zhang, Kun Zhu, Gang Zhao, Hao Zhang, Yingjie Sun, Lixian Reliability Research and Analysis Center China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China Science and Technology on Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China Guangxi Key Laboratory of Information Materials Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9798350329988

Beryllium bronze conductive elastic materials are widely used in aerospace electronics, and the reliability of this material is critical for aircraft equipment A batch of conductive springs suffered from fracture failure during assembly. The fractography, chemical composition, microstructure, and microhardness of the spring were investigated, and the causes of fracture and improvement measures were discussed. The fractographs of the spring show an intergranular fracture accompanied with a dimple fracture. The chemical composition of the raw material conforms to the technical requirements. The sizes of the precipitates in the failed spring were primarily 1-2 um, while the size of the precipitates in the un-failed spring were less than 0.5 um. The grain boundary of the failed spring was wider, with larger particle phases distributed at the grain boundaries. Additionally, the average hardness of the fracture spring was 394.4 HV, which exceeds the technical requirements. The hardness of the un-failed spring met the requirements. According to the results of microstructure and hardness, improper aging treatment led to material embrittlement, and the spring suffered an intergranular fracture during assembly. © 2023 IEEE.

关键词： Brinell Hardness

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Study on total dose radiation effect of γ rays on β-Ga2O3SBD

Study on total dose radiation effect of γ rays on β-Ga2O3S...

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2023 Advanced Fiber Laser Conference, AFL 2023

作者： Fu, Weili Ma, Teng Zhong, Xiangli Lei, Zhifeng Wang, Jinbin Song, Hongjia Xiao, Tao Zhang, Hong Peng, Chao Zhang, Zhangang National-Provincial Laboratory of Special Function Thin Film Materials School of Materials Science and Engineering Xiangtan University Xiangtan Hunan411105 China Reliability Physics and Application Technology of Electronic Component Key Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China

ISBN: (纸本)9781510677661

Gallium oxide Ga2O3 has recently gained attention as a new power electronics semiconductor for aerospace applications. β-Ga2O3 has an extremely high bandgap energy of 4.8-4.9 eV and an expected high breakdown field of 8 MV/cm, which exceed those of traditional wide-bandgap semiconductor materials such as silicon carbide (SiC) and gallium nitride (GaN). These qualities make β-Ga2O3 a favorable choice for micro high-power and high-frequency devices. It is important to consider device application in a radiation environment. Due to its wide bandgap and high breakdown field, β- Ga2O3 has significant potential for use in Schottky barrier diodes (SBDs) in environments with extremely high radiation. In the radiation environment of space, it is crucial to contemplate the dependability of semiconductor devices in radiation, as alpha particles, gamma rays, heavy ions, X-rays, and other factors could induce single event effects, total ionizing dose effects, and displacement damage effects on semiconductor devices in spacecraft. Therefore, the impact of gamma-ray radiation with a total dose was analyzed on a new SBD device which can tolerate 650 V. The results indicate that radiation has a minor impact on the diode's forward performance. Conversely, the device's reverse electrical properties are significantly impacted by radiation. In addition, we examined the internal physical mechanism of diode performance deterioration triggered by gamma-ray radiation utilizing the outcomes of β-Ga2O3 Schottky diode radiation testing and analysis. To characterize the radiation tolerance of this material, studies on irradiation damage are required. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Schottky barrier diodes

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Avionics fault classification based on improved Word2Vec word embedding 3

Avionics fault classification based on improved Word2Vec wor...

引用

3rd International Symposium on Computer applications and Information Systems, ISCAIS 2024

作者： Li, He Li, Xiangning Yang, Peiliang Zhou, Zhenwei Cheng, Liye Hong, Danni Guangzhou Institute of Technology Xidian University Guangzhou511363 China School of Mechano-Electronic Engineering Xidian University Xi’an710065 China Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Institute Guangzhou511370 China

ISBN: (纸本)9781510681316

In this paper, we present a fault classification approach that utilizes aeronautical text data by using improved Word2Vec and Convolutional Neural Network (CNN) models for fault diagnosis. The Word2Vec model is used for vectorization, and the fusion of word vector, character vector and N-gram method is used for text representation. In addition, the vector constructed based on the method are used as inputs to the CNN model, which is capable of extracting fault feature from the text data. The experimental results demonstrate that in comparison with other approaches, the method presented in this article has a better classification effect, the model has a certain degree of improvement in various indexes. In practice, it effectively decreases the manual reliance on fault text classification, and achieves the optimal performance indexes in accuracy, recall and f1-score, indicating the effectiveness of the method proposed in this paper. © 2024 SPIE.

关键词： Neural network models

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Using Load Transient Waveform to Analyze Fault Propagation Mechanism in DC-DC Switching Power Supply

Using Load Transient Waveform to Analyze Fault Propagation M...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Wan, Junliang Yu, Pengfei Cai, Qiang-Ming Cao, Xin Zhou, Longjian Li, Haoran Zhu, Yuyu Fan, Jun Laboratory of Science and Technology on Reliability Physics and Application of Electronic Component Guangzhou China Southwest University of Science and Technology School of Information Engineering Mianyang China Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mianyang China Tianfu Institute of Research and Innovation China

ISBN: (纸本)9798350375909

The degradation of certain components within DC-DC power supplies can lead to abnormal performance, resulting in the occurrence of faults. The degradation of components can cause changes in output voltage and current, and the different degradation characteristics of components have different impacts on the characteristics of output parameters. Therefore, it is necessary to master this impact relationship, that is, the fault propagation mechanism can be used to effectively diagnose faults and manage health. Studying the fault propagated mechanism is an important prerequisite for fault diagnosis. Output terminals of DC-DC power supply are usually connected in parallel with electrolytic capacitors. The function of electrolytic capacitors is to filter, filtering out most of the AC part of the output voltage, and reducing the ripple of the output voltage. Electrolytic capacitors are the most vulnerable components to failure in switching power supplies, with approximate 60% of failed components being electrolytic capacitors. Therefore, the fault propagation mechanism of electrolytic capacitors is a key research topic. Most research focuses on the fault propagation mechanism based on steady-state output signals. This article studies the fault propagation mechanism based on transient output signals. Through experimental testing, the impact of parameter degradation of electrolytic capacitors on the transient waveform of output voltage and the mapping relationship between capacitor degraded parameters and transient waveform are studied. The method is to analyze the voltage waveform when the current step changes using equivalent degradated experiments of capacitors. Its advantage lies in the fact that transient waveforms are more sensitive than steady-state waveforms and require lower sampling rates, making it easier to analyze the degradated characteristics of electrolytic capacitors. For power supplies with simple structures, data is collected through simulation. For commerc

关键词： Capacitor bank

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Fault Diagnosis of Avionics System Based on Improved CNN and BiLSTM 6

Fault Diagnosis of Avionics System Based on Improved CNN and...

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6th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2023

作者： Li, He Hong, Danni Zhou, Zhenwei Li, Xiangning Liu, Junbin Guangzhou Institute of Technology Xidian University China Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Institute China School of Mechano-Electronic Engineering Xidian University China

ISBN: (纸本)9798400709203

This paper presents a novel approach for diagnosing faults in aerospace systems by leveraging the power of Word2vec to transform text data into word vectors. Using improved Convolutional Neural Network(CNN) and bi-directional LSTM models to extract fault feature information from the input data, introducing an attention mechanism to focus more on key feature information in the data, and employing a dropout regularization method to prevent the model from being overfitted. Our model considers local features, as well as contextual information, which fully extracts the feature information of the text to classify the fault data. Compared with other methods, the proposed method outperforms other techniques and significantly reduces the manual dependence of fault classification, saves the troubleshooting time of maintenance personnel, and achieves the optimum in accuracy, recall and f1-score performance indicators, which demonstrates the effectiveness of our approach. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Failure analysis

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Fault Information Mining in Avionics components Based on Unstructured Data 14

Fault Information Mining in Avionics Components Based on Uns...

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

作者： Zhou, Zhenwei Liu, Junbin He, Shilie Li, He Reliability Physics and Application of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Institute Guangzhou511370 China Guangzhou Institute of Technology XD University Huangpu District Guangzhou510555 China

ISBN: (纸本)9798350329988

To address the requirements of unstructured fault data mining and statistical analysis of avionics systems, this study excavates implicit knowledge, investigates potential knowledge associations, and realizes a deep understanding of knowledge to better interpret data. Combined with recent progress of text data extraction technology, this paper studies the entity relationship extraction and failure time statistical method based on attention-based bidirectional long short-term memory to realize the statistical analysis of failure time law of components. In this study, 413 cases of unstructured fault data of avionics system components were collected, and the entity relationship extraction and failure statistical methods proposed in this paper were verified and analyzed. The results showed that the components would have a high probability of failure within 10,000 hours of each flight, and the number and time of multi-function control display failures were high. This paper proposes an unstructured data analysis method for avionics systems, which can provide a reference for a maintenance engineer, provide a basis for the management decision-making of avionics maintenance institutions, and improve the maintenance quality of avionics systems. © 2023 IEEE.

关键词： Decision making

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