The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties ...The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties of organic coatings.This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over time.Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in real-time.Throughout the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating.The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis.This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings.Compared with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.展开更多
With the widespread adoption of encrypted Domain Name System(DNS)technologies such as DNS over Hyper Text Transfer Protocol Secure(HTTPS),traditional port and protocol-based traffic analysis methods have become ineffe...With the widespread adoption of encrypted Domain Name System(DNS)technologies such as DNS over Hyper Text Transfer Protocol Secure(HTTPS),traditional port and protocol-based traffic analysis methods have become ineffective.Although encrypted DNS enhances user privacy protection,it also provides concealed communication channels for malicious software,compelling detection technologies to shift towards statistical featurebased and machine learning approaches.However,these methods still face challenges in real-time performance and privacy protection.This paper proposes a real-time identification technology for encrypted DNS traffic with privacy protection.Firstly,a hierarchical architecture of cloud-edge-end collaboration is designed,incorporating task offloading strategies to balance privacy protection and identification efficiency.Secondly,a privacy-preserving federated learning mechanismbased on Federated Robust Aggregation(FedRA)is proposed,utilizingMedoid aggregation and differential privacy techniques to ensure data privacy and enhance identification accuracy.Finally,an edge offloading strategy based on a dynamic priority scheduling algorithm(DPSA)is designed to alleviate terminal burden and reduce latency.Simulation results demonstrate that the proposed technology significantly improves the accuracy and realtime performance of encrypted DNS traffic identification while protecting privacy,making it suitable for various network environments.展开更多
Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dua...Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dual-frequency ultrasound array.The broadband nature of electroacoustic signals requires ultrasound detector to cover both the high-frequency range(around 6MHz)signals generated by small targets and the low-frequency range(around 1MHz)signals generated by large targets.In our EAT system,we use the 6 MHz array to detect high-frequency signals from the electrodes,and the 1 MHz array for the electrical field.To test this,we conducted simulations using COMSOL Multiphysics^(®) and MATLAB's k-Wave toolbox,followed by experiments using a custom-built setup with a dual-frequency transducer and real-time data acquisition.The results demonstrated that the dual-frequency EAT system could accurately and simultaneously monitor the electroporation process,effectively showing both the treatment area and electrode placement with the application of 1 kV electric pulses with 100 ns duration.The axial resolution of the 6MHz array for EAT was 0.45 mm,significantly better than the 2mm resolution achieved with the 1MHz array.These findings validate the potential of dual-frequency EAT as a superior method for real-time electroporation monitoring.展开更多
Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements ...Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.展开更多
Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a prom...Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.展开更多
To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens...To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens using the SG4500 drilling rig.Results showed that the mechanical behavior(i.e.peak strength and rockburst intensity)of the rock was weakened under high-stress real-time drilling and exhibited a downward trend as the drilling diameter increased.The real-time drilling energy dissipation index(ERD)was proposed to characterize the energy relief during high-stress real-time drilling.The ERD exhibited a linear increase with the real-time drilling diameter.Furthermore,the elastic strain energy of post-drilling rock showed a linear relationship with the square of stress across different stress levels,which also applied to the peak elastic strain energy and the square of peak stress.This findingreveals the intrinsic link between the weakening effect of peak elastic strain energy and peak strength due to high-stress real-time drilling,confirmingthe consistency between energy relief and pressure relief effects.By establishing relationships among rockburst proneness,peak elastic strain energy,and peak strength,it was demonstrated that high-stress real-time drilling reduces rockburst proneness through energy dissipation.Specifically,both peak elastic strain energy and rockburst proneness decreased with larger drill bit diameters,consistent with reductions in peak strength,rockburst intensity,and fractal dimensions of high-stress real-time drilled rock.These results validate the energy relief mechanism of real-time drilling in mitigating rockburst risks.展开更多
An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of...Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.展开更多
Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning appr...Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning approach that combines visual detection and temporal behaviour classification.The methodology utilises object detection models—You Only Look Once(YOLOv12),Faster Region-based Convolutional Neural Network(RCNN),and Single Shot Detector(SSD)MobileNet—integrated with classification models such as Convolutional Neural Networks(CNN),Bidirectional Gated Recurrent Unit(Bi-GRU),and CNN-LSTM(Long Short-Term Memory).Two distinct datasets were used:the Online Exam Proctoring(EOP)dataset from Michigan State University and the School of Computer Science,Duy Tan Unievrsity(SCS-DTU)dataset collected in a controlled classroom setting.A diverse set of cheating behaviours,including book usage,unauthorised interaction,internet access,and mobile phone use,was categorised.Comprehensive experiments evaluated the models based on accuracy,precision,recall,training time,inference speed,and memory usage.We evaluate nine detector-classifier pairings under a unified budget and score them via a calibrated harmonic mean of detection and classification accuracies,enabling deployment-oriented selection under latency and memory constraints.Macro-Precision/Recall/F1 and Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)are reported for the top configurations,revealing consistent advantages of object-centric pipelines for fine-grained cheating cues.The highest overall score is achieved by YOLOv12+CNN(97.15%accuracy),while SSD-MobileNet+CNN provides the best speed-efficiency trade-off for edge devices.This research provides valuable insights into selecting and deploying appropriate deep learning models for maintaining exam integrity under varying resource constraints.展开更多
BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking rec...BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
Hypervelocity rocket sled systems are critical for testing advanced military technologies,yet track damage at speeds exceeding Mach 5 remains a significant challenge for system reliability and performance.In this stud...Hypervelocity rocket sled systems are critical for testing advanced military technologies,yet track damage at speeds exceeding Mach 5 remains a significant challenge for system reliability and performance.In this study,we investigated the hypervelocity impact response and protection for highstrength U71 Mn or bainitic steel used in rocket sled tracks.Flyer plate impact experiments using a two-stage light-gas gun were conducted to study the hypervelocity collision response,followed by the microstructural characterization via optical microscope,scanning electron microscopy equipped with electron backscatter diffraction to reveal underlying damage mechanisms.Then,the calibrated thermalmechanical coupled finite element simulations using the Johnson-Cook constitutive model and MieGrüneisen equation of state were carried out.Results indicated that bainitic steel exhibits superior impact resistance with predominantly smooth scratch-dominated damage due to its higher ductility.In contrast,U71 Mn suffered significant material spallation and crack propagation arising from brittle fracture mechanisms.Zinc-rich epoxy primer coatings effectively mitigated stress concentration and temperature rise in the substrate at impacting velocities below 2.4 km/s,so as to suppress the microstructural damage such as adiabatic shear bands and dynamic recrystallization.However,coating protection diminished at ultra-high-speed impacts due to the coating failure.Dimensional analysis established quantitative relationships of the gouge damage size to projectile mass,impact velocity,and material yield strength.This study provides in-depth insights into damage mechanisms in hypervelocity rail systems,demonstrating that bainitic steel combined with protective coatings can significantly enhance impact resistance and system reliability,offering valuable guidance for the design and optimization of hypervelocity testing platforms.展开更多
Waterborne acrylic coatings are widely utilized due to their cost-effectiveness,high transparency,strong resistance to weather and chemicals,impressive mechanical properties,and excellent adhesion to various substrate...Waterborne acrylic coatings are widely utilized due to their cost-effectiveness,high transparency,strong resistance to weather and chemicals,impressive mechanical properties,and excellent adhesion to various substrates.In these coatings,a reactive emulsifier containing phosphate groups can be integrated into the molecular chain during polymerization,which enhances the coating's compactness and corrosion resistance.This work focuses on the synthesis of styrene-butyl acrylate(St-BA)latex and methyl methacrylate-butyl acrylate(MMA-BA)latex using the reactive phosphate emulsifier ANPEO_(10)-P_(1) through seed emulsion polymerization,achieving a conversion rate of approximately 99%and a solid content close to 50%.The resulting coatings from St-BA and MMA-BA latexes demonstrated long-term corrosion protection for carbon steel and aluminum alloy due to in-situ phosphatization,effectively preventing flash rust.Notably,the MMA-BA coating exhibited remarkable durability,enduring immersion for up to 1224 h(51 d)on Q 235 carbon steel before reaching the failure threshold(|Z|0.01 Hz£106Ω·cm^(2))on Q 235 carbon steel.On 5052 aluminum alloy,the St-BA coating maintained|Z|0.01 Hz>10^(8)Ω·cm^(2) for 480 h(20 d).Furthermore,the corrosion resistance of St-BA and MMA BA coatings on Q 235 steel sheet and 5052 aluminum alloy surpassed that of commercially available MMA-BA and St BA coatings after immersion in a 3.5 wt%NaCl aqueous solution.This work also delves into the anticorrosion mechanism of MMA-BA and St-BA coatings.展开更多
In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawate...In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawater,and NS4 using electrochemical impedance spectroscopy(EIS)to monitor the evolution of the substrate surface,which affects the current required to reach the protection potential(Eprot).Experimental data were collected as training datasets and analyzed using statistical methods,including box plots and correlation matrices.Subsequently,ANNs were applied to predict the current demand at different exposure times,enabling the estimation of electrochemical parameters(limiting voltage values)that can be used to optimize a self-regulating ICCP system.The obtained electrochemical parameters were then used,through Particle Swarm Optimization(PSO),to fine-tune an ANN-based proportional-integral-derivative(PID)controller for the ICCP system.展开更多
Deep sea,with rich oil,gas,and mineral resources,plays an increasingly crucial role in scientific and industrial realms.However,the highly corrosive feature of deep sea hinders further exploration and development,whic...Deep sea,with rich oil,gas,and mineral resources,plays an increasingly crucial role in scientific and industrial realms.However,the highly corrosive feature of deep sea hinders further exploration and development,which requires metal materials with robust corrosion resistance.This review covers an in-depth and all-around overview of the up-to-date advances in corrosion and protection of metals in deep-sea environment.Firstly,the unique characteristics of deep-sea environment are summarized in detail.Subsequently,the corrosion performances of metals in both in situ and simulated deep-sea environments are illustrated systematically.Furthermore,corrosion prevent strategies of metals,including sacrificial anode protection,organic coatings,as well as coatings achieved by physical vapor deposition(PVD coatings),are highlighted.Finally,we outline current challenges and development trends of corrosion and protection of metals in deep-sea environment in the future.The purpose of this review is not only to summarize the recent progress on metal corrosion and protection in deep sea,but also to aid us in understanding them more comprehensively and deeply in a short time,so as to boost their fast development.展开更多
The regenerative braking energy utilization system(RBEUS)stands as a promising technique for improving the efficiency and power quality of electrified railways.Beyond the vital aspects of energy management and control...The regenerative braking energy utilization system(RBEUS)stands as a promising technique for improving the efficiency and power quality of electrified railways.Beyond the vital aspects of energy management and control strategies,ensuring fault protection is paramount for the secure and steady operation of the traction power supply system(TPSS)integrated with RBEUS.This paper introduces an innovative protection scheme tailored to diverse RBEUS application scenarios.Firstly,fault categories are streamlined into three levels:system,equipment,and warning.Subsequently,a novel multi-port active power differential protection method,aligned with RBEUS operational principles,is crafted to serve as a comprehensive and sensitive main protection.Building upon this foundation,a hierarchical protection structure for RBEUS is established,addressing the intricacies and variations in fault types while boosting anti-disturbance capabilities under faulty conditions.Embracing the principle of railway-oriented safety,a collaborative RBEUS-TPSS protection scheme is put forth.Finally,through simulated scenarios encompassing various fault conditions,the proposed scheme’s feasibility and effectiveness are convincingly validated.展开更多
Neurons are notoriously vulnerable cell types.Even the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological cond...Neurons are notoriously vulnerable cell types.Even the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological conditions,including stroke,head trauma,and neurodegenerative disease,can generate stress in neurons,affecting their survival and proper function.In most neural pathologies,mitochondria become dysfunctional and this plays a pivotal role in the process of cell death.The challenge over the last few decades has been to develop effective interventions that improve neuronal homeostasis under pathological conditions.Such interventions,often referred to as disease-modifying or neuroprotective,have,however,proved frustratingly elusive,at both preclinical and,in particular,clinical levels.In this perspective,we highlight two factors that we feel are key to the development of effective neuroprotective treatments.These are:firstly,the choice of dose of intervention and method of application,and secondly,the selection of subjects,whether they be patients or the animal model.展开更多
Traditional impact protection structures(IPSs)dissipate impact energy according to the plastic dissipation mechanism,which is only effective for single impacts due to the irreversible deformation of structures.To achi...Traditional impact protection structures(IPSs)dissipate impact energy according to the plastic dissipation mechanism,which is only effective for single impacts due to the irreversible deformation of structures.To achieve multi-impact protection,this paper proposes a novel chiral periodic structure with the deformation self-recovery function and the high energy conversion efficiency based on the flexoelectric mechanism.A theoretical model is formulated on the electromechanical responses of a flexoelectric beam under rotational boundaries.The equivalent stiffness and damping characteristics are subsequently derived to construct the electromechanical responses of the structure under constant velocity and mass impacts.Discussions are addressed for the influence of the structural scale effect and resistance on the electromechanical responses.The results show that the energy conversion efficiency increases by 2 to 3 orders of magnitude,reaching as high as 85.3%,which can match well with those of structures reported in the literature based on the plastic energy dissipating mechanism.展开更多
Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter...Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter.Therefore,the need to monitor disc cutter wear in real-time has emerged as a technical challenge for TBMs.In this study,real-time disc cutter wear monitoring is developed based on sound and vibration sensors.For this purpose,the microphone and accelerometer were used to record the sound and vibration signals of cutting three different types of rocks with varying abrasions on a laboratory scale.The relationship between disc cutter wear and the sound and vibration signal was determined by comparing the measurements of disc cutter wear with the signal plots for each sample.The features extracted from the signals showed that the sound and vibration signals are impacted by the progression of disc wear during the rock-cutting process.The signal features obtained from the rock-cutting operation were utilized to verify the machine learning techniques.The results showed that the multilayer perceptron(MLP),random subspace-based decision tree(RS-DT),DT,and random forest(RF)methods could predict the wear level of the disc cutter with an accuracy of 0.89,0.951,0.951,and 0.927,respectively.Based on the accuracy of the models and the confusion matrix,it was found that the RS-DT model has the best estimate for predicting the level of disc wear.This research has developed a method that can potentially determine when to replace a tool and assess disc wear in real-time.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52371049)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(YESS,No.2020QNRC001)the National Science and Technology Resources Investigation Program of China(Nos.2021FY100603 and 2019FY101404)。
文摘The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties of organic coatings.This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over time.Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in real-time.Throughout the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating.The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis.This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings.Compared with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.
文摘With the widespread adoption of encrypted Domain Name System(DNS)technologies such as DNS over Hyper Text Transfer Protocol Secure(HTTPS),traditional port and protocol-based traffic analysis methods have become ineffective.Although encrypted DNS enhances user privacy protection,it also provides concealed communication channels for malicious software,compelling detection technologies to shift towards statistical featurebased and machine learning approaches.However,these methods still face challenges in real-time performance and privacy protection.This paper proposes a real-time identification technology for encrypted DNS traffic with privacy protection.Firstly,a hierarchical architecture of cloud-edge-end collaboration is designed,incorporating task offloading strategies to balance privacy protection and identification efficiency.Secondly,a privacy-preserving federated learning mechanismbased on Federated Robust Aggregation(FedRA)is proposed,utilizingMedoid aggregation and differential privacy techniques to ensure data privacy and enhance identification accuracy.Finally,an edge offloading strategy based on a dynamic priority scheduling algorithm(DPSA)is designed to alleviate terminal burden and reduce latency.Simulation results demonstrate that the proposed technology significantly improves the accuracy and realtime performance of encrypted DNS traffic identification while protecting privacy,making it suitable for various network environments.
基金supported by the National Institute of Health(R37CA240806,U01CA288351,and R50CA283816)support from UCI Chao Family Comprehensive Cancer Center(P30CA062203).
文摘Electroacoustic Tomography(EAT)is an imaging technique that detects ultrasound waves induced by electrical pulses,offering a solution for real-time electroporation monitoring.This study presents EAT system using a dual-frequency ultrasound array.The broadband nature of electroacoustic signals requires ultrasound detector to cover both the high-frequency range(around 6MHz)signals generated by small targets and the low-frequency range(around 1MHz)signals generated by large targets.In our EAT system,we use the 6 MHz array to detect high-frequency signals from the electrodes,and the 1 MHz array for the electrical field.To test this,we conducted simulations using COMSOL Multiphysics^(®) and MATLAB's k-Wave toolbox,followed by experiments using a custom-built setup with a dual-frequency transducer and real-time data acquisition.The results demonstrated that the dual-frequency EAT system could accurately and simultaneously monitor the electroporation process,effectively showing both the treatment area and electrode placement with the application of 1 kV electric pulses with 100 ns duration.The axial resolution of the 6MHz array for EAT was 0.45 mm,significantly better than the 2mm resolution achieved with the 1MHz array.These findings validate the potential of dual-frequency EAT as a superior method for real-time electroporation monitoring.
基金the support of the Major Science and Technology Project of Yunnan Province,China(Grant No.202502AD080007)the National Natural Science Foundation of China(Grant No.52378288)。
文摘Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.
基金supported by National Natural Science Foundation of China(No.62301008)China Postdoctoral Science Foundation(No.2022M720272)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.
基金supported by the National Natural Science Foundation of China(Grant No.42077244)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_0434).
文摘To investigate the energy relief effect of real-time drilling in preventing rockburst in high-stress rock,a series of high-stress real-time drilling uniaxial compression tests were conducted on red sandstone specimens using the SG4500 drilling rig.Results showed that the mechanical behavior(i.e.peak strength and rockburst intensity)of the rock was weakened under high-stress real-time drilling and exhibited a downward trend as the drilling diameter increased.The real-time drilling energy dissipation index(ERD)was proposed to characterize the energy relief during high-stress real-time drilling.The ERD exhibited a linear increase with the real-time drilling diameter.Furthermore,the elastic strain energy of post-drilling rock showed a linear relationship with the square of stress across different stress levels,which also applied to the peak elastic strain energy and the square of peak stress.This findingreveals the intrinsic link between the weakening effect of peak elastic strain energy and peak strength due to high-stress real-time drilling,confirmingthe consistency between energy relief and pressure relief effects.By establishing relationships among rockburst proneness,peak elastic strain energy,and peak strength,it was demonstrated that high-stress real-time drilling reduces rockburst proneness through energy dissipation.Specifically,both peak elastic strain energy and rockburst proneness decreased with larger drill bit diameters,consistent with reductions in peak strength,rockburst intensity,and fractal dimensions of high-stress real-time drilled rock.These results validate the energy relief mechanism of real-time drilling in mitigating rockburst risks.
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金Natural Science Foundation of Beijing Municipality under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.
文摘Online examinations have become a dominant assessment mode,increasing concerns over academic integrity.To address the critical challenge of detecting cheating behaviours,this study proposes a hybrid deep learning approach that combines visual detection and temporal behaviour classification.The methodology utilises object detection models—You Only Look Once(YOLOv12),Faster Region-based Convolutional Neural Network(RCNN),and Single Shot Detector(SSD)MobileNet—integrated with classification models such as Convolutional Neural Networks(CNN),Bidirectional Gated Recurrent Unit(Bi-GRU),and CNN-LSTM(Long Short-Term Memory).Two distinct datasets were used:the Online Exam Proctoring(EOP)dataset from Michigan State University and the School of Computer Science,Duy Tan Unievrsity(SCS-DTU)dataset collected in a controlled classroom setting.A diverse set of cheating behaviours,including book usage,unauthorised interaction,internet access,and mobile phone use,was categorised.Comprehensive experiments evaluated the models based on accuracy,precision,recall,training time,inference speed,and memory usage.We evaluate nine detector-classifier pairings under a unified budget and score them via a calibrated harmonic mean of detection and classification accuracies,enabling deployment-oriented selection under latency and memory constraints.Macro-Precision/Recall/F1 and Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)are reported for the top configurations,revealing consistent advantages of object-centric pipelines for fine-grained cheating cues.The highest overall score is achieved by YOLOv12+CNN(97.15%accuracy),while SSD-MobileNet+CNN provides the best speed-efficiency trade-off for edge devices.This research provides valuable insights into selecting and deploying appropriate deep learning models for maintaining exam integrity under varying resource constraints.
文摘BACKGROUND:Hemiplegia,a prevalent stroke-related condition,is often studied for motor dysfunction;however,spasticity remains under-researched.Abnormal muscle tone significantly hinders hemiplegic patients’walking recovery.OBJECTIVE:To determine whether early suspension-protected training with a personal assistant machine for stroke patients enhances walking ability and prevents muscle spasms.METHODS:Thirty-two early-stage stroke patients from Shenzhen University General Hospital and the China Rehabilitation Research Center were randomly assigned to the experimental group(n=16)and the control group(n=16).Both groups underwent 4 weeks of gait training under the suspension protection system for 30 minutes daily,5 days a week.The experimental group used the personal assistant machine during training.Three-dimensional gait analysis(using the Cortex motion capture system),Brunnstrom staging,Fugl-Meyer Assessment for lower limb motor function,Fugl-Meyer balance function,and the modified Ashworth Scale were evaluated within 1 week before the intervention and after 4 weeks of intervention.RESULTS AND CONCLUSION:After the 4-week intervention,all outcome measures showed significant changes in each group.The experimental group had a small but significant increase in the modified Ashworth Scale score(P<0.05,d=|0.15|),while the control group had a large significant increase(P<0.05,d=|1.48|).The experimental group demonstrated greater improvements in walking speed(16.5 to 38.44 cm/s,P<0.05,d=|4.01|),step frequency(46.44 to 64.94 steps/min,P<0.05,d=|2.32|),stride length(15.50 to 29.81 cm,P<0.05,d=|3.44|),and peak hip and knee flexion(d=|1.82|to|2.17|).After treatment,the experimental group showed significantly greater improvements than the control group in walking speed(38.44 vs.26.63 cm/s,P<0.05,d=|2.75|),stride length,peak hip and knee flexion(d=|1.31|to|1.45|),step frequency(64.94 vs.59.38 steps/min,P<0.05,d=|0.85|),and a reduced support phase(bilateral:24.31%vs.28.38%,P<0.05,d=|0.88|;non-paretic:66.19%vs.70.13%,P<0.05,d=|0.94|).For early hemiplegia,personal assistant machine-assisted gait training under the suspension protection system helps establish a correct gait pattern,prevents muscle spasms,and improves motor function.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金financial support from the National Key Research and Development Program(Grant No.2024YFA1209801)the National Natural Science Foundation of China(Grant Nos.12302140,12325204)+4 种基金the China Postdoctoral Science Foundation(Grant No.2023M732794)the Fundamental Research Funds for the Central Universities of China(Grant No.sxzy012023213)the Scientific Research Program of Shaanxi Province(Grant No.2023JC-XJ-02)the Young Talent Support Program of Xi'an Science and Technology Association(Grant No.959202413069)Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(Grant No.GZB20230575)。
文摘Hypervelocity rocket sled systems are critical for testing advanced military technologies,yet track damage at speeds exceeding Mach 5 remains a significant challenge for system reliability and performance.In this study,we investigated the hypervelocity impact response and protection for highstrength U71 Mn or bainitic steel used in rocket sled tracks.Flyer plate impact experiments using a two-stage light-gas gun were conducted to study the hypervelocity collision response,followed by the microstructural characterization via optical microscope,scanning electron microscopy equipped with electron backscatter diffraction to reveal underlying damage mechanisms.Then,the calibrated thermalmechanical coupled finite element simulations using the Johnson-Cook constitutive model and MieGrüneisen equation of state were carried out.Results indicated that bainitic steel exhibits superior impact resistance with predominantly smooth scratch-dominated damage due to its higher ductility.In contrast,U71 Mn suffered significant material spallation and crack propagation arising from brittle fracture mechanisms.Zinc-rich epoxy primer coatings effectively mitigated stress concentration and temperature rise in the substrate at impacting velocities below 2.4 km/s,so as to suppress the microstructural damage such as adiabatic shear bands and dynamic recrystallization.However,coating protection diminished at ultra-high-speed impacts due to the coating failure.Dimensional analysis established quantitative relationships of the gouge damage size to projectile mass,impact velocity,and material yield strength.This study provides in-depth insights into damage mechanisms in hypervelocity rail systems,demonstrating that bainitic steel combined with protective coatings can significantly enhance impact resistance and system reliability,offering valuable guidance for the design and optimization of hypervelocity testing platforms.
基金Project(52373065)supported by the National Natural Science Foundation of ChinaProject(2220004002898)supported by the Zhuhai Industry University Research Cooperation and Basic and Applied Research Projects,China。
文摘Waterborne acrylic coatings are widely utilized due to their cost-effectiveness,high transparency,strong resistance to weather and chemicals,impressive mechanical properties,and excellent adhesion to various substrates.In these coatings,a reactive emulsifier containing phosphate groups can be integrated into the molecular chain during polymerization,which enhances the coating's compactness and corrosion resistance.This work focuses on the synthesis of styrene-butyl acrylate(St-BA)latex and methyl methacrylate-butyl acrylate(MMA-BA)latex using the reactive phosphate emulsifier ANPEO_(10)-P_(1) through seed emulsion polymerization,achieving a conversion rate of approximately 99%and a solid content close to 50%.The resulting coatings from St-BA and MMA-BA latexes demonstrated long-term corrosion protection for carbon steel and aluminum alloy due to in-situ phosphatization,effectively preventing flash rust.Notably,the MMA-BA coating exhibited remarkable durability,enduring immersion for up to 1224 h(51 d)on Q 235 carbon steel before reaching the failure threshold(|Z|0.01 Hz£106Ω·cm^(2))on Q 235 carbon steel.On 5052 aluminum alloy,the St-BA coating maintained|Z|0.01 Hz>10^(8)Ω·cm^(2) for 480 h(20 d).Furthermore,the corrosion resistance of St-BA and MMA BA coatings on Q 235 steel sheet and 5052 aluminum alloy surpassed that of commercially available MMA-BA and St BA coatings after immersion in a 3.5 wt%NaCl aqueous solution.This work also delves into the anticorrosion mechanism of MMA-BA and St-BA coatings.
文摘In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawater,and NS4 using electrochemical impedance spectroscopy(EIS)to monitor the evolution of the substrate surface,which affects the current required to reach the protection potential(Eprot).Experimental data were collected as training datasets and analyzed using statistical methods,including box plots and correlation matrices.Subsequently,ANNs were applied to predict the current demand at different exposure times,enabling the estimation of electrochemical parameters(limiting voltage values)that can be used to optimize a self-regulating ICCP system.The obtained electrochemical parameters were then used,through Particle Swarm Optimization(PSO),to fine-tune an ANN-based proportional-integral-derivative(PID)controller for the ICCP system.
基金the National Key R&D Program of China(No.2022YFB3808800)the National Natural Science Foundation of China(Nos.52301406 and 52375219)+2 种基金the Natural Science Foundation of Zhejiang Province(No.LR21E050001)the China Postdoctoral Science Foundation(No.2023M733600)the Ningbo Natural Science Foundation(No.2023J329).
文摘Deep sea,with rich oil,gas,and mineral resources,plays an increasingly crucial role in scientific and industrial realms.However,the highly corrosive feature of deep sea hinders further exploration and development,which requires metal materials with robust corrosion resistance.This review covers an in-depth and all-around overview of the up-to-date advances in corrosion and protection of metals in deep-sea environment.Firstly,the unique characteristics of deep-sea environment are summarized in detail.Subsequently,the corrosion performances of metals in both in situ and simulated deep-sea environments are illustrated systematically.Furthermore,corrosion prevent strategies of metals,including sacrificial anode protection,organic coatings,as well as coatings achieved by physical vapor deposition(PVD coatings),are highlighted.Finally,we outline current challenges and development trends of corrosion and protection of metals in deep-sea environment in the future.The purpose of this review is not only to summarize the recent progress on metal corrosion and protection in deep sea,but also to aid us in understanding them more comprehensively and deeply in a short time,so as to boost their fast development.
基金supported by the National Natural Science Foundation of China(Nos.52107126 and52077179)the Key Regional Innovation and Development Joint Fund Project(No.2023YFB2303901)the funding of Chengdu Guojia Electrical Engineering Co.,Ltd.(No.NEEC-2022-B11).
文摘The regenerative braking energy utilization system(RBEUS)stands as a promising technique for improving the efficiency and power quality of electrified railways.Beyond the vital aspects of energy management and control strategies,ensuring fault protection is paramount for the secure and steady operation of the traction power supply system(TPSS)integrated with RBEUS.This paper introduces an innovative protection scheme tailored to diverse RBEUS application scenarios.Firstly,fault categories are streamlined into three levels:system,equipment,and warning.Subsequently,a novel multi-port active power differential protection method,aligned with RBEUS operational principles,is crafted to serve as a comprehensive and sensitive main protection.Building upon this foundation,a hierarchical protection structure for RBEUS is established,addressing the intricacies and variations in fault types while boosting anti-disturbance capabilities under faulty conditions.Embracing the principle of railway-oriented safety,a collaborative RBEUS-TPSS protection scheme is put forth.Finally,through simulated scenarios encompassing various fault conditions,the proposed scheme’s feasibility and effectiveness are convincingly validated.
基金supported by Fonds Clinatec and COVEA France(to JM).
文摘Neurons are notoriously vulnerable cell types.Even the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological conditions,including stroke,head trauma,and neurodegenerative disease,can generate stress in neurons,affecting their survival and proper function.In most neural pathologies,mitochondria become dysfunctional and this plays a pivotal role in the process of cell death.The challenge over the last few decades has been to develop effective interventions that improve neuronal homeostasis under pathological conditions.Such interventions,often referred to as disease-modifying or neuroprotective,have,however,proved frustratingly elusive,at both preclinical and,in particular,clinical levels.In this perspective,we highlight two factors that we feel are key to the development of effective neuroprotective treatments.These are:firstly,the choice of dose of intervention and method of application,and secondly,the selection of subjects,whether they be patients or the animal model.
基金Project supported by the National Natural Science Foundation of China(No.12272138)。
文摘Traditional impact protection structures(IPSs)dissipate impact energy according to the plastic dissipation mechanism,which is only effective for single impacts due to the irreversible deformation of structures.To achieve multi-impact protection,this paper proposes a novel chiral periodic structure with the deformation self-recovery function and the high energy conversion efficiency based on the flexoelectric mechanism.A theoretical model is formulated on the electromechanical responses of a flexoelectric beam under rotational boundaries.The equivalent stiffness and damping characteristics are subsequently derived to construct the electromechanical responses of the structure under constant velocity and mass impacts.Discussions are addressed for the influence of the structural scale effect and resistance on the electromechanical responses.The results show that the energy conversion efficiency increases by 2 to 3 orders of magnitude,reaching as high as 85.3%,which can match well with those of structures reported in the literature based on the plastic energy dissipating mechanism.
文摘Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter.Therefore,the need to monitor disc cutter wear in real-time has emerged as a technical challenge for TBMs.In this study,real-time disc cutter wear monitoring is developed based on sound and vibration sensors.For this purpose,the microphone and accelerometer were used to record the sound and vibration signals of cutting three different types of rocks with varying abrasions on a laboratory scale.The relationship between disc cutter wear and the sound and vibration signal was determined by comparing the measurements of disc cutter wear with the signal plots for each sample.The features extracted from the signals showed that the sound and vibration signals are impacted by the progression of disc wear during the rock-cutting process.The signal features obtained from the rock-cutting operation were utilized to verify the machine learning techniques.The results showed that the multilayer perceptron(MLP),random subspace-based decision tree(RS-DT),DT,and random forest(RF)methods could predict the wear level of the disc cutter with an accuracy of 0.89,0.951,0.951,and 0.927,respectively.Based on the accuracy of the models and the confusion matrix,it was found that the RS-DT model has the best estimate for predicting the level of disc wear.This research has developed a method that can potentially determine when to replace a tool and assess disc wear in real-time.
