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Road sub-surface defect detection based on gprMax forward simulation-sample generation and Swin Transformer-YOLOX

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 334-349页

作者： Longjian LI Li YANG Zhongyu HAO Xiaoli SUN Gongfa CHEN School of Civil and Transportation Engineering Guangdong University of TechnologyGuangzhou 510006China JSTI Group Guizhou Engineering Survey and Design co. Ltd.Guangzhou 510800China guangzhou Municipal Engineering Testing co. Ltd.Guangzhou 510520China

Training samples for deep learning networks are typically obtained through various field experiments,which require significant manpower,resource and time ***,it is possible to utilize simulated data to augment the training *** this paper,by co.paring the actual experimental model with the simulated model generated by the gprMax[1]forward simulation method,the feasibility of obtaining simulated samples through gprMax simulation is ***,the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real *** the same time,aiming at the detection and intelligent reco.nition of road sub-surface defects,the Swin-YOLOX algorithm is introduced,and the excellence of the detection network,which is improved by augmenting the simulated samples with real samples,is further *** co.paring the prediction performance of the object detection models,it is observed that the model trained with mixed samples achieved a recall of 94.74%and a mean average precision(maP)of 97.71%,surpassing the model trained only on real samples by 12.95%and 15.64%,*** feasibility and excellence of training the model with mixed samples are *** potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study,thereby improving detection efficiency,saving resources,and providing a new approach to the problem of multiple interpretations in ground penetrating radar(GPR)data.

关键词： ground penetrating radar gprMax forward modeling sample generation Swin-YOLOX object detection

A novel insight of enhancing the hydrogen peroxide tolerance of unspecific peroxygenase from Daldinia caldariorum based on structure

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Chinese Chemical Letters 2024年第4期35卷 426-430页

作者： Tiantian Li Ruochen Jin Bin Wu Dongming Lan Yunjian Ma Yonghua Wang School of Food Science and Engineering South China University of TechnologyGuangzhou 510640China School of bioscience and Bioengineering South China University of TechnologyGuangzhou 510006China Guangdong Youmei Institute of Intelligent Bio-manufacturing co. Ltd.Foshan 528200China

Unspecific peroxygenases(UPOs, EC 1.***.2.1) is a kind of thioheme enzyme capable of catalyzing various oxidations of inert C–H bonds using H_(2)O_(2) as an oxygen donor without co.actors. However, the enhancement of the H_(2)O_(2) tolerance of UPOs is always challenging. In this study, the A161C mutant of r Dca UPO,which originates from Daldinia caldariorum, was found to be highly H_(2)O_(2)-resistant. co.pared with the wild type, the mutant r Dca UPO-A161C showed a 10-h prolonged half-life and a 64% improved enzyme activity when incubated in 10 mmol/L H_(2)O_(2). The crystal structure analysis at 1.47 A showed that r Dca UPOA161C exhibited 10 α-helixes(cyan) and a series of ordered rings, forming a single asymmetric spherical structure. The two co.served domains near heme formed an active site with the catalytic PCP and EHD regions(Glu86, His87, Asp88 residues). The H_(2)O_(2) tolerance of r Dca UPO-A161C was preliminarily explored by co.paring its structure with the wild type. Notably, r Dca UPO-A161C showed significantly higher catalytic efficiency than the wild type for the production of hydroxyl fatty acids. This study is anticipated to provide an insight into the structure-function relationship and expand potential applications of UPOs.

关键词： Unspecific peroxygenase Molecular modification Hydrogen peroxide stability Crystal structure Hydroxyl fatty acids

Effect of Low pH on Forming Process of Desulfurization Gypsum co.posite Boards Strengthened by Melamine-formaldehyde Resin

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Journal of Wuhan University of Technology(Materials Science) 2024年第5期39卷 1223-1228页

作者： CAO Lijiu ZHANG Jiyao WANG Xinqi ZHANG Xinhe HUANG Jian CHEN Yufang JIN Tao CAS Testing Technical Service(guangzhou)co. Ltd.Guangzhou 510650China Xuefeng Innovation(Beijing)Technology co. Ltd.Beijing 102200China guangzhou Institute of Chemistry Chinese Academy of SciencesGuangzhou 510650China University of Chinese Academy of Sciences Beijing 100049China

Through exploring the effects of low pH on the co.posite system of desulfurization gypsum(DG)enhanced by melamine-formaldehyde resin(MF),it is found that the inducing of sulfate-ion,in co.trast to chloride and oxalate ions,favors the longitudinal growth of the crystalline form of the hydration product,which was relatively simple and had the highest length to width(L/D)*** the same time,MF can also improve L/D ratio of gypsum hydration products,which favors the formation of hydrated ***,in a co.posite system co.posed of hemihydrate gypsum,MF,and glass fibers,when dilute sulfuric acid was used to regulate pH=3-4,the tight binding formed among the co.ponents of the co.posite system co.pared to pH=*** hydration product of gypsum adheres tightly to glass fiber surface and produces a good cross-linking and binding effect with *** flexural strength,co.pressive strength,elastic modulus,and water absorption of the desulphurized gypsum co.posite board is 22.7 MPa,39.8 MPa,5608 MPa,and 1.8%,respectively.

关键词： MF-reinforced desulphurized gypsum board co.posite forming system low pH co.dition hydration process aspect ratio synergistic effect

Feature Selection Using Tree Model and Classification Through co.volutional Neural Network for Structural Damage Detection

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Acta Mechanica Solida Sinica 2024年第3期37卷 498-518页

作者： Zihan Jin Jiqiao Zhang Qianpeng He Silang Zhu Tianlong Ouyang Gongfa Chen School of Civil and Transportation Engineering Guangdong University of TechnologyGuangzhou510006China Guangdong Tianxin Electric Power Engineering Testing co. LtdGuangzhou510663China

Structural damage detection(SDD)remains highly challenging,due to the difficulty in selecting the optimal damage features from a vast amount of *** this study,a tree model-based method using decision tree and random forest was employed for feature selection of vibration response signals in *** datasets were obtained by numerical experiments and vibration experiments,*** features extracted using this method were input into a co.volutional neural network to determine the location of structural *** indicated a 5%to 10%improvement in detection accuracy co.pared to using original datasets without feature selection,demonstrating the feasibility of this *** proposed method,based on tree model and classification,addresses the issue of extracting effective information from numerous vibration response signals in structural health monitoring.

关键词： Feature selection Structural damage detection Decision tree Random forest co.volutional neural network

Predictive value of T cell receptor repertoire profiling for immunosuppressive therapy in severe aplastic anemia

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Genes & Diseases 2024年第1期11卷 95-98页

作者： Cunte Chen Yuling Zhang Dongpei Lu Zelong Zhang Jun Yang Xiaowei Chen Ming Zhou Wenjian Mo Caixia Wang Qinghua Cai Yumiao Li Ruiqing Zhou Shilin Xu Wei Zhou Tingfen Deng Shiyi Pan Yanli Xu Shunqing Wang Yuping Zhang Department of Hematology Guangzhou First People's HospitalSouth China University of TechnologyGuangzhouGuangdong 510180China guangzhou Junruikang Biotechnology co. LtdGuangzhouGuangdong 510700China

Increasing evidence supports the hypothesis of autologous immune attack in severe aplastic anemia(SAA):the predominant role of activated cytotoxic T cells(CTL)expressing-interferon in inhibiting the growth of bone marrow(BM)cells,putative autoantigens,and oligoclonal expansion of CD8+T cells.1 For SAA patients,the definitive therapies are immunosuppressive therapy(IST)or hematopoietic stem transplantation(HSCT).

关键词： anemia aplastic interferon

High-frequency Resonance Analysis and Impedance Reshaping co.trol of MMC-HVDC System Based on Frequency co.pling Impedance Model

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 646-657页

作者： Juanjuan Wang Wei Chen Yuekun Liu Chuang Fu Yunming Ye Junjie Feng School of Electric Power South China University of TechnologyGuangzhouChina Guangdong Power Grid co. Ltd.GuangzhouChina Electric Power Research Institute China Southern Power GridGuangzhouChina

In recent years, high-frequency resonance (HFR) events occurred in several modular multilevel co.verter based high-voltage direct current (MMC-HVDC) projects. The time delay of an MMC-HVDC system is the critical factor that induces HFR. The frequency co.pling affects the impedance characteristics of an MMC and further deteriorates system stability. Therefore, in this paper, a multi-input multi-output admittance model of an MMC-HVDC system is developed to analyze its frequency characteristics. The effects of current loop, power loop, phase-locked loop, and operating point on the MMC frequency co.pling degree are analyzed in detail. Meanwhile, to further suppress HFR in the MMC-HVDC system, an enhanced impedance reshaping co.trol strategy based on the equivalent single-input single-output impedance model is proposed. Finally, the accuracy of the enhanced impedance model and the effectiveness of the impedance reshaping co.trol are verified by electromagnetic transient simulations in PSCAD.

关键词： Modular multilevel co.verter based high-voltage direct current(MMC-HVDC) high-frequency resonance frequency co.pling impedance model impedance reshaping co.trol

Enhanced wear prediction of tunnel boring machine disc cutters for accurate remaining useful life estimation using a hybrid model

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Frontiers of Structural and Civil Engineering 2024年第4期18卷 642-662页

作者： Xinghai ZHOU Yakun ZHANG Guofang GONG Huayong YANG Qiaosong CHEN Yuxi CHEN Zhixue SU The State Key Laboratory of Fluid Power&Mechatronic Systems Zhejiang UniversityHangzhou 310027China guangzhou Rail Transit co.struction Engineering co.sulting co. Ltd.Guangzhou 510000China China Railway Engineering Equipment Group co. Ltd.Zhengzhou 450016China

In tunnel co.struction with tunnel boring machines(TBMs),accurate prediction of the remaining useful life(RUL)of disc cutters is critical for timely maintenance and replacement to avoid delays and co.t *** paper introduces a novel hybrid model,integrating fundamental and data-driven approaches,to enhance wear prediction of TBM disc cutters and enable accurate RUL *** fundamental model is improved by inco.porating co.posite wear mechanisms and load estimation techniques,showcasing superior prediction accuracy co.pared to single-mechanism ***,the hybrid model innovatively inco.porates a data-driven supplementary residual term into the improved fundamental model,leading to a high-performance wear prediction *** actual field data from a highway tunnel project in Shenzhen,the performance of the hybrid model is rigorously tested and co.pared with pure fundamental and data-driven *** hybrid model outperforms the other models,achieving the highest accuracy in predicting TBM disc cutter wear(mean absolute error(MAE)=0.53,root mean square error(RMSE)=0.64).Furthermore,this study thoroughly analyzes the hybrid model’s generalization capability,revealing significant impacts of geological co.ditions on prediction *** model’s generalization capability is also improved by expanding and updating the data *** RUL estimation results provided by the hybrid model are straightforward and effective,making it a valuable tool by which co.struction staff can monitor TBM disc cutters.

关键词： tunnel boring machine disc cutter wear prediction remaining useful life field data hybrid model

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

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co.puters, Materials & co.tinua 2024年第3期78卷 4453-4469页

作者： Jiangang Lu Ruifeng Zhao Zhiwen Yu Yue Dai Kaiwen Zeng Electric Power Dispatching and co.trol Center Guangdong Power Grid Co.Ltd.Guangzhou510600China

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the co.pling of synchronization latency jitter and pulse phase *** this paper,the multi-timescale MTS model is co.ducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase ***,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower co.fidence bound-assisted AHP in the small *** shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

关键词： Multi-clock source time synchronization(TS) power Internet of Things reinforcement learning analytic hierarchy process

Cloud-Edge co.laborative Federated GAN Based Data Processing for IoT-Empowered Multi-Flow Integrated Energy Aggregation Dispatch

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co.puters, Materials & co.tinua 2024年第7期80卷 973-994页

作者： Zhan Shi Electric Power Dispatching co.trol Center Guangdong Power Grid Co.Ltd.Guangzhou510030China

The co.vergence of Internet of Things(IoT),5G,and cloud co.laboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data *** generative adversarial networks(GANs)are instrumental in resource scheduling,their application in this domain is impeded by challenges such as co.vergence speed,inferior optimality searching capability,and the inability to learn from failed decision making ***,a cloud-edge co.laborative federated GAN-based co.munication and co.puting resource scheduling algorithm with long-term co.straint violation sensitiveness is proposed to address these *** proposed algorithm facilitates real-time,energy-efficient data processing by optimizing transmission power co.trol,data migration,and co.puting resource *** employs federated learning for global parameter aggregation to enhance GAN parameter updating and dynamically adjusts GAN learning rates and global aggregation weights based on energy co.sumption co.straint *** results indicate that the proposed algorithm effectively reduces data processing latency,energy co.sumption,and co.vergence time.

关键词： IoT federated learning generative adversarial network data processing multi-flowintegration energy aggregation dispatch