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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

Regulating Blood Clot Fibrin Films to Manipulate Biomaterial-Mediated Foreign Body Responses

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Research 2024年第2期2023卷 565-581页

作者： Yang Zou Zhengjie Shan Zongpu Han Jieting Yang Yixiong Lin Zhuohong Gong Lv Xie Jieyun Xu Runlong Xie Zhuofan Chen Zetao Chen Hospital of Stomatology Guanghua School of StomatologySun Yat-sen University and Guangdong Research Center for Dental and Cranial Rehabilitation and Material EngineeringGuangzhou 510055China

The clinical efficacy of implanted biomaterials is often co.promised by host immune reco.nition and subsequent foreign body responses(FBRs).During the implantation,biomaterials inevitably co.e into direct co.tact with the blood,absorbing blood protein and forming blood *** studies have been carried out to regulate protein adsorption,thus manipulating ***,the role of clot surface fibrin films formed by clotting shrinkage in host reactions and FBR is often *** of the principle of fibrin film formation being relevant to fibrinogen or clotting factor absorption,it is feasible to manipulate the fibrin film formation via tuning the absorption of fibrinogen and clotting *** biological hydroxyapatite reserved bone architecture and microporous structure,the smaller particle size may expose more microporous structures and adsorb more fibrinogen or clotting ***,we set up 3 sizes(small,co.nition and FBR and demonstrates the feasibility of a strategy to regulate FBR by modulating fibrin films via tuning the absorption of blood proteins.

关键词： Blood subsequent biomaterials

Migration Behavior of Impurity Iron in Silico. Melt Under Pulsed Electric Current

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Acta Metallurgica Sinica(English Letters) 2024年第5期37卷 889-903页

作者： Mengcheng Zhou Yaxiong Dai Changhao Liu Shengli Ding Xinfang Zhang School of Metallurgical and Eco.ogical Engineering University of Science and Technology BeijingBeijing 100083China guangdong Zhongnan Iron&Steel co. Ltd.Guangdong 512123China

The impurity iron in silico. material will seriously affect the photoelectric co.version efficiency of silico. solar ***,the traditional silico. purification method has the disadvantages of long cycle,high energy co.sumption and serious *** this study,an efficient and green pulsed electric current purification technology is *** electromigration effect of iron elements,the current density gradient driving of iron phase,and the gravity of iron phase all affect the migration behavior of iron phase in silico. melt under pulsed electric *** of the depth of electrode insertion into the silico. melt,the solubility of iron in silico. decreases under the pulsed electric current,which helps to form the iron *** the same time,the iron phase tends to sink toward the bottom under the influence of *** the electrode is shallowly inserted,a non-uniform electric field is formed in the silico. melt,and the iron phase is mainly driven by the current density gradient to accelerate sink toward the *** the electrode is fully inserted,an approximately uniform electric field is formed in the silico. melt,and iron elements are preferentially migrated to the cathode by electromigration,forming iron phase sinking at the *** study of impurity iron migration behavior in silico. melt under pulsed electric current provides a new approach for the purification of polycrystalline silico..

关键词： Metallurgical silico. Pulsed electric current Iron-rich phase Current density gradient Electromigration

Anomaly Detection Algorithm of Power System Based on Graph Structure and Anomaly Attention

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co.puters, Materials & co.tinua 2024年第4期79卷 493-507页

作者： Yifan Gao Jieming Zhang Zhanchen Chen Xianchao Chen Zhaoqing Power Supply Bureau of guangdong Power Grid co. Ltd.Zhaoqing526060China

In this paper, we propose a novel anomaly detection method for data centers based on a co.bination of graphstructure and abnormal attention mechanism. The method leverages the sensor monitoring data from targetpower substations to co.struct multidimensional time series. These time series are subsequently transformed intograph structures, and co.responding adjacency matrices are obtained. By inco.porating the adjacency matricesand additional weights associated with the graph structure, an aggregation matrix is derived. The aggregationmatrix is then fed into a pre-trained graph co.volutional neural network (GCN) to extract graph structure ***, both themultidimensional time series segments and the graph structure features are inputted into a pretrainedanomaly detectionmodel, resulting in co.responding anomaly detection results that help identify abnormaldata. The anomaly detection model co.sists of a multi-level enco.er-deco.er module, wherein each level includesa transformer enco.er and deco.er based on co.relation differences. The attention module in the enco.ing layeradopts an abnormal attention module with a dual-branch structure. Experimental results demonstrate that ourproposed method significantly improves the accuracy and stability of anomaly detection.

关键词： Anomaly detection transformer graph structure

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

An optimization-oriented modeling approach using input co.vex neural networks and its application on optimal chiller loading

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Building Simulation 2024年第4期17卷 639-655页

作者： Shanshuo Xing Jili Zhang Song Mu Dalian University of technology Dalian116024China guangdong Airport Baiyun Information technology co. Ltd.Guangzhou510000China

Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller *** optima obtained by model-based optimization algorithms are dependent on precise and solvable objective *** classical neural networks cannot provide co.vex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based *** this paper,we leverage the input co.vex neural networks(ICNN)to identify the chiller model to co.struct a co.vex mapping between co.trol variables and the objective function,which enables the NN-based OCL as a co.vex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model co.parison based on an experimental data set,and the statistical results show that,on the premise of retaining prior co.vexities,the proposed model depicts excellent approximation power for the data set,especially the unseen ***,the ICNN model is applied to a typical OCL problem for a multi-chiller system and co.bined with three types of optimization *** with co.ventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing co.secutive co.ling load inputs and an impressive co.vergence speed.

关键词： chiller plant input co.vex neural network optimal load distribution co.vex optimization

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

Performance and Optimization of Air Source Heat Pump Water Heater with Cyclic Heating

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 179-187页

作者：李凡陆高锋丁云霄郑春元李斌翟晓强 co.lege of Mechanical and Power Engineering Shanghai Jiao Tong UniversityShanghai 200240China guangdong Midea HVAC Equipment co. Ltd.Foshan 528311GuangdongChina

A new type of microchannel co.denser applied in the air source heat pump water heater(ASHPWH)with cyclic heating was proposed in this *** operating performance of the ASHPWH was frst ***,the structure of the microchannel co.denser was optimized with the implement of vortex ***,a numerical model of the ASHPWH was established and the optimized microchannel co.denser was *** experimental results showed that the average co.fficient of performance(co.)of the 1HP(735 W)ASHPWH reached *** addition,the optimized microchannel co.denser co.ld be matched with a 3 HP(2430W)ASHPWH with an average heating capacity of 10.30 kW,and achieving an average co. of 4.24,14.6%higher than the limit value in the national standard.

关键词： air source heat pump water heater(ASHPWH) cyclic heating microchannel co.denser

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