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24th IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2024

作者： Xu, Fanjiang Sun, Zeyu Institute of Software Chinese Academy of Sciences National Key Laboratory of Space Integrated Information System China State Key Laboratory of Intelligent Game China

ISBN: (纸本)9798350365658

Machine learning (ML) innovations have significantly advanced the field of defect prediction in software development, offering the potential for automated error detection across vast codebases. These advancements promise to elevate software quality assurance by improving reliability and security. However, despite their benefits, existing defect prediction models are not without limitations, often failing to identify vulnerabilities or inaccurately flagging non-defective code segments as problematic. To overcome these shortcomings, this study introduces DPTester, a novel approach that diverges from traditional label-preserving transformations, aiming to more accurately mimic the complexities of real-world software development. Unlike previous methods, DPTester intentionally injects defects into source code to transform its semantics fundamentally. This methodology tests a defect prediction model's ability to identify and anticipate defects amidst semantic alterations. DPTester employs a two-step framework, consisting of automated test input and oracle generation. The initial phase generates test inputs by modifying conditional statements to induce potential defects. The subsequent phase evaluates the defect prediction models' performance using these inputs. A failure by a model to detect DPTester-introduced defects is considered an issue. Our evaluation of DPTester on two prominent defect prediction models, CodeT5+ and CodeBERT, involved the generation of 222,112 test inputs. This process demonstrated a 99% success rate in creating valid test scenarios. However, it exposed significant weaknesses in both models: CodeT5+ and CodeBERT's accuracy plummeted to 43% and 30%, respectively, when assessed against DPTester's complex test scenarios. Moreover, our analysis uncovered 144,104 and 98,574 prediction inconsistencies in CodeBERT and CodeT5+, respectively, underscoring the urgent need for model improvements to adeptly handle sophisticated testing landscapes. Furthermore

关键词： Prediction models

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Rapid prediction of flow and concentration fields in solid-liquid suspensions of slurry electrolysis tanks

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International Journal of Minerals,Metallurgy and Materials 2024年第9期31卷 2006-2016页

作者： Tingting Lu Kang Li Hongliang Zhao Wei Wang Zhenhao Zhou Xiaoyi Cai Fengqin Liu State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China State Key Laboratory of Intelligent Optimized Manufacturing in Mining&Metallurgy Process Beijing 102628China School of Materials Science and Engineering Lanzhou University of TechnologyLanzhou 730050China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing 100083China

Slurry electrolysis(SE),as a hydrometallurgical process,has the characteristic of a multitank series connection,which leads to various stirring conditions and a complex solid suspension *** computational fluid dynamics(CFD),which requires high computing resources,and a combination with machine learning was proposed to construct a rapid prediction model for the liquid flow and solid concentration fields in a SE *** scientific selection of calculation samples via orthogonal experiments,a comprehensive dataset covering a wide range of conditions was established while effectively reducing the number of simulations and providing reasonable weights for each ***,a prediction model of the SE tank was constructed using the K-nearest neighbor *** results show that with the increase in levels of orthogonal experiments,the prediction accuracy of the model improved *** model established with four factors and nine levels can accurately predict the flow and concentration fields,and the regression coefficients of average velocity and solid concentration were 0.926 and 0.937,*** with traditional CFD,the response time of field information prediction in this model was reduced from 75 h to 20 s,which solves the problem of serious lag in CFD applied alone to actual production and meets real-time production control requirements.

关键词： slurry electrolysis solid-liquid suspension computational fluid dynamics K-nearest neighbor algorithm rapid prediction

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Design and Experimental Evaluation of WLR-III

Design and Experimental Evaluation of WLR-III

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Li, Xu Fu, Yili Zhejiang University State Key Laboratory of Robotics and System Harbin Institute of Technology State Key Laboratory of Fluid Power and Mechatronic Systems China Harbin Institute of Technology Intelligent Robot Research Center Zhejiang Laboratory State Key Laboratory of Robotics and System Heilongjiang Province Harbin150001 China

ISBN: (纸本)9798350325706

This paper introduces the design and experimental evaluation of WLR-III, which stands for the third-generation hydraulic wheel-legged robot. WLR-III is expected to be applied to disaster scenarios where the mobility, adaptability and manipulation capability are required. Based on the development of the previous two generations of wheel-legged robots, this work continuously optimizes the design to achieve higher mobility and stronger adaptability by reducing weight & inertia. The hydraulic power transmission system adopts a hose-less design method to ensure the robustness of the system. What's more prominent is that the successful development of hydraulic power unit (HPU) enables WLR-III to realize hydraulic power autonomy. In addition, to accomplish all kinds of operational tasks in the rescue scene, the electro-hydraulic hybrid drives anthropomorphic arms with heavy load grippers were developed. Finally, the effectiveness and reliability of design optimization have been evaluated through a series of experiments, including grassland movement, load bearing, obstacle-stepping and tool-operating. To the authors' best knowledge, this is the first time that a hydraulic powered autonomous wheel-legged humanoid robot with the ability to operate simple tools has been developed. © 2023 IEEE.

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A Method for Abnormality Detection of Lithium-Ion Battery Packs Based on Kullback-Leibler Test and Greenwald-Khanna Clustering 11th

A Method for Abnormality Detection of Lithium-Ion Battery Pa...

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11th Frontier Academic Forum of Electrical Engineering, FAFEE 2024

作者： Wang, Chong Liu, Yajie Song, Yuanming Wang, Yu College of System Engineering National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha410073 China

ISBN: (纸本)9789819788231

During the operation of lithium-ion battery packs, there often exhibit certain abnormalities due to cell faults such as internal short circuit or unavoidable inconsistencies among cells, which affects the operation safety of the battery packs. Therefore, it is of great significance to carry out abnormality detection for the battery packs. Accordingly, this paper proposes a feature selection method based on Kullback-Leibler (K-L) test and an improved Greenwald-Khanna (GK) clustering algorithm. Initially, faults are introduced into the battery pack using the Simulink simulation platform to obtain simulation data. Subsequently, parameter identification is identified based on the Rint equivalent circuit model and the Recursive Least Squares (RLS) algorithm. Finally, better consistency features are selected using the K-L test as inputs to the GK clustering algorithm, and the K-Means++ method is used to optimize the GK algorithm for clustering features. The results demonstrate that this method can effectively distinguish between normal and abnormal batteries, achieving abnormality detection in battery packs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Clustering algorithms

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A Novel PLL Structure for Dynamic Stability Improvement of DFIG-based Wind Energy Generation systems During Asymmetric LVRT

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Journal of Modern Power systems and Clean Energy 2023年第4期11卷 1149-1164页

作者： Lei Guan Jun Yao State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqing 400044China

The dynamic coupling effect,which is introduced by the dual-sequence phase-locked loops(PLLs)used in doublyfed induction generator(DFIG)based wind energy generation systems(WEGSs)during asymmetric low voltage ride-through(LVRT)in weak grid,needs *** order to study this new dynamic coupling effect,an equivalent two-degree-of-freedom(2-DOF)spring damper particle model is used in this paper to develop a small-signal model for the dual-sequence *** dynamic interaction between the positive-sequence(PS)and negative-sequence(NS)PLLs is ***,the impact of the dynamic coupling between the dual-sequence PLLs on the dynamic stability during the steady-state stage of an asymmetric fault is *** analysis results show that the dynamic coupling between the dual-sequence PLLs will cause drift in the frequency and damping for the PS and NS PLL *** will change the instability modal of the system and introduce the risk of dynamic ***,the effectiveness of existing control strategies for enhancing the dynamic stability will be ***,a novel PLL structure is designed to improve the dynamic stability of the system during the steady-state stage of an asymmetric *** effectiveness of the proposed strategy is verified by simulations and experiments.

关键词： Doubly-fed induction generator(DFIG) phaselocked loop(PLL) dynamic stability dynamic coupling weak grid asymmetric low-voltage ride through(LVRT)

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Electrohydrodynamic printing for high resolution patterning of flexible electronics toward industrial applications

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InfoMat 2024年第2期6卷 28-56页

作者： Zhouping Yin Dazhi Wang Yunlong Guo Zhiyuan Zhao Liqiang Li Wei Chen Yongqing Duan State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanthe People's Republic of China Optics Valley Laboratory Wuhanthe People's Republic of China Key Laboratory for Micro/Nano Technology and System of Liaoning Province Dalian University of TechnologyDalianthe People's Republic of China Beijing National Laboratory for Molecular Sciences Key Laboratory of Organic SolidsInstitute of ChemistryChinese Academy of SciencesBeijingthe People's Republic of China Institute of Molecular Aggregation Sciences Tianjin UniversityTianjinthe People's Republic of China

Electrohydrodynamic(EHD)printing technique,which deposits micro/nanostructures through high electric force,has recently attracted significant research interest owing to their fascinating characteristics in high resolution(<1μm),wide material applicability(ink viscosity 1–10000 cps),tunable printing modes(electrospray,electrospinning,and EHD jet printing),and compatibility with flexible/wearable *** the laboratory level of the EHD printed electronics'resolution and efficiency is gradually approaching the commercial application level,an urgent need for developing EHD technique from laboratory into industrialization have been put ***,we first discuss the EHD printing technique,including the ink design,droplet formation,and key technologies for promoting printing efficiency/*** we summarize the recent progress of EHD printing in fabrication of displays,organic field-effect transistors(OFETs),transparent electrodes,and sensors and ***,a brief summary and the outlook for future research effort are presented.

关键词： display electrohydrodynamic printing flexible electronics organic field-effect transistor printhead

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Multi-Agent Reinforcement Learning with Region Division and Leader-Follower Communication

Multi-Agent Reinforcement Learning with Region Division and ...

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2024 China Automation Congress, CAC 2024

作者： Wang, Chao Xu, Xiang Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798350368604

The integration of multi-agent reinforcement learning (MARL) into complex systems has paved new ways for collaborative problem-solving. However, traditional approaches to MARL frequently encounter the challenge of achieving efficient communication among agents, essential for coordinated action. This paper introduces a region division and leader-follower(RDLF) communication algrithm with the MARL framework. RDLF divides the environment into several regions, each managed by a leader agent that coordinates the actions of follower agents and handling inter-region communication. This hierarchical structure reduces unnecessary communication, enhancing learning efficiency. Experimental results in multi-particle environments demonstrate RDLF’s superiority over existing MARL algorithms, especially with increasing agent numbers. RDLF effectively addresses scalability and communication challenges in large-scale multi-agent systems, providing a robust foundation for its application in complex and dynamic environment. © 2024 IEEE.

关键词： Adversarial machine learning

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Multi-Level Feature Alignment Method for Advancing Remaining Useful Life Prediction of Rolling Bearing

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IEEE Internet of Things Journal 2025年第12期12卷 22023-22035页

作者： Pei, Xuewu Gao, Yiping Li, Xinyu Gao, Liang Zhao, Xingxin Huazhong University of Science and Technology State Key Laboratory of Intelligent Manufacturing Equipment and Technology Wuhan430074 China Chongqing Changjiang Bearing Co. Ltd Chongqing401336 China

Rolling bearings are the key components of various equipment and easily subject to failure, remaining useful life (RUL) prediction technology can grasp their health statuses to make a reasonable maintenance plan. Transfer learning methods for rolling bearing cross-domain RUL prediction focus on the direct alignment of the degradation process between the target domain and source domain. However, the working condition and degradation process of rolling bearing to be predicted are unknown, which are different from the target domain or source domain. The caused data distribution discrepancy has seriously affected the RUL prediction acceptance. To solve this problem, a multi-level feature alignment (MLFA) method for advancing RUL prediction without target domain data for training is proposed. Specifically, a proposed weighted TOPSIS is implemented for supervised label making to train a robust RUL prediction prior model. The three level feature alignment (TLFA) strategy, which involves feature alignment by the proposed adaptive nonlinear state estimation, envelope spectrum, envelope spectrum-combined deep convolutional autoencoder, is developed to mitigate the data distribution discrepancy between the predicted and prior entities. TLFA transforms prediction tasks from cross-domain to different failure behaviors. Extensive experiments conducted on both public and industrial scene run-to-failure bearing datasets validated the superiority of the MLFA. These results from comparison experimental show that MLFA improves MAE and RMSE about 0.061 and 0.054 individually than some state-of-the-art methods. © 2014 IEEE.

关键词： Roller bearings

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An anomaly detection method for spacecraft solar arrays based on the ILS-SVM model

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Journal of systems Engineering and Electronics 2023年第2期34卷 515-529页

作者： WANG Yu ZHANG Tao HUI Jianjiang LIU Yajie College of Systems Engineering National University of Defense TechnologyChangsha 410073China Hunan Key Laboratory of Multi-energy System Intelligent Interconnection Technology Changsha 410073China Beijing Institute of Tracking and Telecommunication Technology Beijing 100094China

Solar arrays are important and indispensable parts of spacecraft and provide energy support for spacecraft to operate in orbit and complete on-orbit *** a spacecraft is in orbit,because the solar array is exposed to the harsh space environment,with increasing working time,the performance of its internal electronic components gradually degrade until abnormal damage *** damage makes solar array power generation unable to fully meet the energy demand of a ***,timely and accurate detection of solar array anomalies is of great significance for the on-orbit operation and maintenance management of *** this paper,we propose an anomaly detection method for spacecraft solar arrays based on the integrated least squares support vector machine(ILS-SVM)model:it selects correlated telemetry data from spacecraft solar arrays to form a training set and extracts n groups of training subsets from this set,then gets n corresponding least squares support vector machine(LS-SVM)submodels by training on these training subsets,respectively;after that,the ILS-SVM model is obtained by integrating these submodels through a weighting operation to increase the prediction accuracy and so on;finally,based on the obtained ILS-SVM model,a parameterfree and unsupervised anomaly determination method is proposed to detect the health status of solar *** use the telemetry data set from a satellite in orbit to carry out experimental verification and find that the proposed method can diagnose solar array anomalies in time and can capture the signs before a solar array anomaly occurs,which reflects the applicability of the method.

关键词： spacecraft solar array anomaly detection integrated least squares support vector machine(ILS-SVM) induced ordered weighted average(IOWA)operator integrated model

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Coupling effects of SiC and TiB_(2) particles on crack inhibition in Al-Zn-Mg-Cu alloy produced by laser powder bed fusion

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Journal of Materials Science & technology 2023年第33期164卷 37-51页

作者： Ning Li Ting Wang Lixia Zhang Liang Zhang State Key Laboratory of Advanced Welding and Joining Harbin Institute of Technology at WeihaiWeihai 264209China Shandong Provincial Key Laboratory of Special Welding Technology Harbin Institute of Technology at WeihaiWeihai 264209China Institute of Intelligent Manufacturing Technology Shenzhen PolytechnicShenzhen 518055China

A novel Al-Zn-Mg-Cu alloy free of cracks was produced utilizing laser powder bed fusion(LPBF)and modified with SiC and TiB_(2) *** interdependent effects of SiC and TiB_(2) particles on morphology,microstructure,and crystallographic texture were *** mechanisms behind phase evolution and crack inhibition were *** results show that a nearly dense Al-Zn-Mg-Cu alloy could be obtained when the mass fraction of SiC and TiB2 particles was 4%.TiB_(2) particles remained stable and acted as nucleation agents in the molten *** SiC particles reacted with the Al matrix to form rod-like Al_(4)C_(3),lamellate Al_(4)SiC_(4),and flocculent Si phases,which provided nucleation agents and liquid replenishment for matrix *** columnar grains of the matrix were refined into equiaxed grains,and the average size decreased from 37.15μm to 7.54μ*** preferential growth of grains along the(001)〈001〉direction was suppressed and transformed into a disordered random *** innovative Al-Zn-Mg-Cu alloy demonstrated an ultimate tensile strength of 492±12 MPa and an elongation of 7.2%±0.7%.The microhardness was enhanced,and the microhardness heterogeneity was *** solidification properties were regulated,the temperature interval between solidus and liquidus was narrowed,and the liquidity of the molten pool was *** hot cracking of Al-Zn-Mg-Cu alloy was inhibited due to the interdependent effects of grain refinement by TiB2 particles and sufficient liquid metal replenishment by SiC particles.

关键词： Laser powder bed fusion Solidification cracks Al-Zn-Mg-Cu alloys In-situ reaction Microstructure evolution

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