The integration of water and fertilizer is a comprehensive technology combined irrigation and fertilizer, which has outstanding advantages of saving fertilizer, saving water, saving labor, protecting environment, high...The integration of water and fertilizer is a comprehensive technology combined irrigation and fertilizer, which has outstanding advantages of saving fertilizer, saving water, saving labor, protecting environment, high yield and high efficiency. Currently, most of the water and fertilizer integrated irrigation and fertilization and irrigation operation in the production-based greenhouse is achieved relying on artificial experience, which is hard to achieve timely, scientific and intelligent irrigation. In this study, the application of STM32 embedded system realized the real-time collection of the data from the humidity sensors buried in top, middle and low depth of soil, and water and fertilizer integrated irrigation work was completed in the greenhouse through automatic control according to the predetermined fertilization and irrigation strategies for different crops. Moreover, the system had remote monitoring function, which used the global system for mobile （GSM） module to provide users with remote short message services, and therefore, the users could not only achieve the remote intelligent monitoring on the irrigation, light, ventilation of the greenhouse through short messages, but also could start and stop the remote control system operation, so as to realize the automatic management of the greenhouse environment, achieving the purpose of remote fertilization and water-saving irrigation.展开更多
Through the analysis for the process of Walsh modulation and demodula tion,the adaptive error-limiting method suitable for the Walsh code shutting multiplex ing in the mine monitor system is advanced in this article. ...Through the analysis for the process of Walsh modulation and demodula tion,the adaptive error-limiting method suitable for the Walsh code shutting multiplex ing in the mine monitor system is advanced in this article. It is proved by theoretical analysis and circuit experiments that this method is easy to carry out and can not only improve the quality of information transmission but also meet the requirement of the system patrol test time without the increasement of system investment.展开更多
The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test rea...The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test reactor,and HL-2 A.Neutron fluxes can provide real-time parameters for nuclear fusion,including neutron source intensity and fusion power.Corresponding to different nuclear reaction periods,neutron fluxes span over seven decades,thereby requiring electronic devices to operate in counting and Campbelling modes simultaneously.Therefore,it is crucial to design a real-time NFM system to encompass such a wide dynamic range.In this study,a high-precision NFM system with a wide measurement range of neutron flux is implemented using realtime multipoint linear calibration.It can automatically switch between counting and Campbelling modes with variations in the neutron flux.We established a testing platform to verify the feasibility of the NFM system,which can output the simulated neutron signal using an arbitrary waveform generator.Meanwhile,the accurate calibration interval of the Campbelling mode is defined well.Based on the above-mentioned design,the system satisfies the requirements,offering a dynamic range of 10~8 cps,temporal resolution of 1 ms,and maximal relative error of 4%measured at the signal-to-noise ratio of 15.8 dB.Additionally,the NFM system is verified in a field experiment involving HL-2 A,and the measured neutron flux is consistent with the results.展开更多
A bunch arrival-time monitor(BAM) system,based on electro-optical intensity modulation scheme, is under study at Shanghai Soft X-ray Free Electron Laser.The aim of the study is to achieve high-precision time measureme...A bunch arrival-time monitor(BAM) system,based on electro-optical intensity modulation scheme, is under study at Shanghai Soft X-ray Free Electron Laser.The aim of the study is to achieve high-precision time measurement for minimizing bunch fluctuations. A readout electronics is developed to fulfill the requirements of the BAM system. The readout electronics is mainly composed of a signal conditioning circuit, field-programmable gate array(FPGA), mezzanine card(FMC150), and powerful FPGA carrier board. The signal conditioning circuit converts the laser pulses into electrical pulse signals using a photodiode. Thereafter, it performs splitting and low-noise amplification to achieve the best voltage sampling performance of the dual-channel analog-to-digital converter(ADC) in FMC150. The FMC150 ADC daughter card includes a 14-bit 250 Msps dual-channel high-speed ADC,a clock configuration, and a management module. The powerful FPGA carrier board is a commercial high-performance Xilinx Kintex-7 FPGA evaluation board. To achieve clock and data alignment for ADC data capture at a high sampling rate, we used ISERDES, IDELAY, and dedicated carry-in resources in the Kintex-7 FPGA. This paper presents a detailed development of the readout electronics in the BAM system and its performance.展开更多
For the purpose of the monitor system in digital protection, the embedded real-time operating system (RTOS) and the embedded GUI (Graphical User Interface) is introduced to design the monitor system. Combining the nec...For the purpose of the monitor system in digital protection, the embedded real-time operating system (RTOS) and the embedded GUI (Graphical User Interface) is introduced to design the monitor system. Combining the necessity and the application value of the operation system, the choice of embedded Linux and Qt/Embedded is completely viable for the monitor system in digital protection for generator-transformer sets. The design with embedded Linux and embedded GUI enriches system information, increases developing efficiency and improve the generality.展开更多
Αcloud-based home electricity data-monitoring system,which is based on an Arduino Mega controller,is proposed for monitoring the electricity consumption(electrical power)and power quality(PQ)in home.This system is al...Αcloud-based home electricity data-monitoring system,which is based on an Arduino Mega controller,is proposed for monitoring the electricity consumption(electrical power)and power quality(PQ)in home.This system is also capable of monitoring the fundamental frequency and supply-voltage transients to ensure that the appliances operate in a safe operation range.The measured data(voltage and current)are transmitted through a Wi Fi device between the Arduino controller and server.The transmission control protocol(TCP)server is set up to acquire the high-data transmission rate.The server system immediately displays the calculated parameters and the waveform of the acquired signal.A comparison with a standard measurement device shows that the proposed system,which can be built at a low cost,exhibits the same functions as a factory product.展开更多
The thesis describes an advanced digital solution to mining digital image monitor system, which makes up the shortage of the traditional mining analog image monitor. It illustrates the system components and how to cho...The thesis describes an advanced digital solution to mining digital image monitor system, which makes up the shortage of the traditional mining analog image monitor. It illustrates the system components and how to choose the encoder bandwidth of the system. The problem of image multicast and its solution in LAN are also discussed.展开更多
A test system is developed for the BESIII ETOF/MRPC beam tests of data acquisition, environment monitoring and automatic control. The software framework is based on the CAMAC bus, VME bus and Serial Port,which are res...A test system is developed for the BESIII ETOF/MRPC beam tests of data acquisition, environment monitoring and automatic control. The software framework is based on the CAMAC bus, VME bus and Serial Port,which are responsible for communications with the detectors. The monitor system works well in the beam test.展开更多
Based on the control requirements of artificial grass tufting machine,an overall plan is proposed on control of CANopen bus.In the control system,on the basis of CoDeSys soft PLC technology of fieldbus control system,...Based on the control requirements of artificial grass tufting machine,an overall plan is proposed on control of CANopen bus.In the control system,on the basis of CoDeSys soft PLC technology of fieldbus control system,LMC20 realizes the communication by making CANopen bus connect with ATV71,OTB module and these underlying slave stations.The humanized operation interface is realized by touch screens and user-friendly application which is developed through CoDeSys,and detailed analysis of the monitor system and the principle and method of monitor system are also provided in the paper.展开更多
Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings...Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.展开更多
The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which ...The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.展开更多
The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process ...The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process conditions can lead to degradation in layer quality and non-uniformity,highlighting the need for real-time monitoring to improve overall quality and efficiency.In this study,an AI-based monitoring system was developed to evaluate layer width and assess quality in real time.Three deep learning models Faster Region-based Convolutional Neural Network(R-CNN),You Only Look Once version 8(YOLOv8),and Single Shot MultiBox Detector(SSD)were compared,and YOLOv8 was ultimately selected for its superior speed,flexibility,and scalability.The selected model was integrated into a user-friendly interface.To verify the reliability of the system,bead width control experiments were conducted,which identified feed speed and extrusion speed as the key process parameters.Accordingly,a Central Composite Design(CCD)experimental plan with 13 conditions was applied to evaluate layer width and validate the system’s reliability.Finally,the proposed system was applied to the additive manufacturing of an aerospace component,where it successfully detected bead width deviations during printing and enabled stable fabrication with a maximum geometric deviation of approximately 6 mm.These findings demonstrate the critical role of real-time monitoring of layer width and quality in improving process stability and final product quality in composite material additive manufacturing.展开更多
The study of long-term pavement performance is a fundamental topic in the field of highway engineering.Through comprehensive and in-depth research on the pavement system,the previous scattered,one-sided,superficial,an...The study of long-term pavement performance is a fundamental topic in the field of highway engineering.Through comprehensive and in-depth research on the pavement system,the previous scattered,one-sided,superficial,and perceptual knowledge and experience are summarized and sublimated into a systematic and complete engineering theory,thereby providing powerful guidance and assistance for the practice of pavement design,construction,maintenance,operation,and management.In this research,the mentoring system deployment technology for automatic monitoring is carried out for long-term pavement performance.By burying a variety of sensors in different parts of the road surface,base,roadbed,slope,etc.,a sensor monitoring network based on the Internet of Things technology is formed to achieve accurate,reliable,and continuous observation of environmental meteorology,physical state,mechanical response,structural deformation,and other indicators.The large amount of data and high real-time requirements mean that the perception data collected from sensors,including temperature,humidity,pressure,asphalt strain,and displacement,can be used to train a deep learning model based on a Convolutional Neural Network(CNN)algorithm.This model predicts multi-point pavement displacement to detect damage such as asphalt cracks and potholes.The response of the proposed CNN achieved a high accuracy rate,regression rate,and F-score equal to 87.24%,84.12%,and 85.96%,respectively.This work highlights the potential of using a variety of sensors to aid deep learning algorithms for monitoring long-term pavement performance.展开更多
Pulmonary rehabilitation(PR)aims to improve lung function in patients with chronic respiratory disease(CRD).In recent years,significant advancements have been made in pulmonary rehabilitation technologies,demonstratin...Pulmonary rehabilitation(PR)aims to improve lung function in patients with chronic respiratory disease(CRD).In recent years,significant advancements have been made in pulmonary rehabilitation technologies,demonstrating their potential for enhancing lung function in patients with respiratory diseases.The purpose of this study is to outline recent developments in the field of pulmonary rehabilitation guided by pulmonary rehabilitation robots,which has not been previously addressed in earlier reviews.To fill this gap,this paper first provides a systematic summary of the monitoring and actuation technologies of pulmonary rehabilitation robot systems and evaluates these technologies from multiple dimensions,including portability,wearability potential,invasiveness,and clinical applications,analyzing the potential for integrating various technologies into pulmonary rehabilitation robot systems.Furthermore,three technical directions are proposed:real-time precise monitoring,suitable structure and actuation strategies,and the intelligence of pulmonary rehabilitation robot systems.On the basis of these directions,this paper presents a comprehensive technical outlook for a soft wearable pulmonary rehabilitation robot system,providing reference and guidance for future research.To our knowledge,this is the first review of pulmonary rehabilitation robot systems and their key technologies.Additionally,the review section on respiratory assistive technologies simultaneously covers key technologies such as mechanical ventilation(MV),exoskeleton robots,and functional electrical stimulation(FES)for the first time.It also summarizes the respiratory assistive technology paradigm from the innovative perspectives of respiratory assistive modalities,targeted body sites,and types of ventilation for the first time.This study offers a broader perspective and a deeper understanding of pulmonary re-habilitation robots,with a technical outlook encompassing multimodal data fusion perception,respiratory event detection and intention recognition,full-phase assistance strategies,modeling,decoupling,and quantification of multipleinput multiple-output(MIMO)systems,as well as model-based interactive control strategies.展开更多
Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecastin...Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control.Hanging yellow sticky boards is a common way to monitor and trap those pests which are attracted to the yellow color.To achieve real-time,low-cost,intelligent monitoring of these vegetable pests on the boards,we established an intelligent monitoring system consisting of a smart camera,a web platform and a pest detection algorithm deployed on a server.After the operator sets the monitoring preset points and shooting time of the camera on the system platform,the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day.The pests trapped on the yellow sticky boards in vegetable fields,Plutella xylostella,Phyllotreta striolata and flies,are very small and susceptible to deterioration and breakage,which increases the difficulty of model detection.To solve the problem of poor recognition due to the small size and breaking of the pest bodies,we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests.The algorithm uses an overlapping sliding window method,an improved Res2Net network as the backbone network,and a recursive feature pyramid network as the neck network.The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images,with precision levels of 96.5,92.2 and 75.0%,and recall levels of 96.6,93.1 and 74.7%,respectively,and an F_(1) value of 0.880.Compared with other algorithms,our algorithm has a significant advantage in its ability to detect small target pests.To accurately obtain the data for the newly added pests each day,a two-stage pest matching algorithm was proposed.The algorithm performed well and achieved results that were highly consistent with manual counting,with a mean error of only 2.2%.This intelligent monitoring system realizes precision,good visualization,and intelligent vegetable pest monitoring,which is of great significance as it provides an effective pest prevention and control option for farmers.展开更多
Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These...Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.展开更多
Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reas...Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.展开更多
Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for...Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for personalized guidance,and enhance training effectiveness while reducing the risk of injury.However,conventional rotational speed sensors often exhibit signal loss and limited responsiveness at low speeds,leading to inaccurate feedback and constraining the development of intelligent fitness devices.Therefore,this paper proposes a triboelectric rotational speed sensor(TRSS),which employs a coaxial reverse magnetic modulation transmission mechanism to enhance low-speed monitoring,thereby overcoming low-speed signal loss.The sensor enables real-time detection of rotational speed in fitness equipment,and features a compact structure,doubled resolution,and high detection accuracy of 0.21 rad s−1.Performance test indicates a sensitivity of 3.15 Hz(rad s−1)−1,a linear correlation coefficient of 0.99892,and an average error of 1.19%in simulated tests,which demonstrates the capability of the sensor for accurate motion monitoring at low speeds.Furthermore,a triboelectric magnetic-modulated rotational monitoring system(TMRMS)is developed and validated through cycling experiments,demonstrating excellent performance across a wide speed range.These findings highlight the strong potential of the system for advancing next-generation smart fitness applications.展开更多
This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The ...This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The IHLOA algorithm introduces three key innovations:(1)chaotic initialization to enhance population diversity and global search capability,(2)adaptive random walk strategies to escape local optima,and(3)a cross-strategy mechanism to accelerate convergence and enhance fault detection accuracy and robustness.The system comprises both hardware and software components.The hardware includes sensors such as the BH1750 light intensity sensor,DS18B20 temperature sensor,and INA226 current and voltage sensor,all interfaced with the STM32F103C8T6 microcontroller and the ESP8266 module for wireless data transmission.The software,developed using QT Creator,incorporates an IHLOA-MLP model for fault diagnosis.The user-friendly interface facilitates intuitive monitoring and scalability for multiple systems.Experimental validation on a PV array demonstrates that the IHLOA-MLP model achieves a fault detection accuracy of 94.55%,which is 2.4%higher than the standard MLP,while reducing variance by 63.64%compared to the standard MLP.This highlights its accuracy and robustness.When compared to other optimization algorithms such as BKA-MLP(94.10%accuracy)and HLOA-MLP(94.00%accuracy),the IHLOA-MLP further reduces variance to 0.08,showcasing its superior performance.The system selects voltage as a feature vector to maintain circuit stability,avoiding efficiency impacts from series current sensors.This combined hardware and software approach further reduces false alarms to 0.1%through a consecutive-judgment mechanism,significantly enhancing practical reliability.This work provides a cost-effective and scalable solution for improving the stability and safety of PV systems in real-world applications.展开更多
In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this stu...In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.展开更多
基金Supported by the Scientific Research Plan of the Education Department of Jilin Province(2014322)~~
文摘The integration of water and fertilizer is a comprehensive technology combined irrigation and fertilizer, which has outstanding advantages of saving fertilizer, saving water, saving labor, protecting environment, high yield and high efficiency. Currently, most of the water and fertilizer integrated irrigation and fertilization and irrigation operation in the production-based greenhouse is achieved relying on artificial experience, which is hard to achieve timely, scientific and intelligent irrigation. In this study, the application of STM32 embedded system realized the real-time collection of the data from the humidity sensors buried in top, middle and low depth of soil, and water and fertilizer integrated irrigation work was completed in the greenhouse through automatic control according to the predetermined fertilization and irrigation strategies for different crops. Moreover, the system had remote monitoring function, which used the global system for mobile （GSM） module to provide users with remote short message services, and therefore, the users could not only achieve the remote intelligent monitoring on the irrigation, light, ventilation of the greenhouse through short messages, but also could start and stop the remote control system operation, so as to realize the automatic management of the greenhouse environment, achieving the purpose of remote fertilization and water-saving irrigation.
文摘Through the analysis for the process of Walsh modulation and demodula tion,the adaptive error-limiting method suitable for the Walsh code shutting multiplex ing in the mine monitor system is advanced in this article. It is proved by theoretical analysis and circuit experiments that this method is easy to carry out and can not only improve the quality of information transmission but also meet the requirement of the system patrol test time without the increasement of system investment.
基金supported by the National Natural Science Foundation of China(Nos.11475131,11975307,and 11575184)the National Magnetic Confinement Fusion Energy Development Research(No.2013GB104003)。
文摘The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test reactor,and HL-2 A.Neutron fluxes can provide real-time parameters for nuclear fusion,including neutron source intensity and fusion power.Corresponding to different nuclear reaction periods,neutron fluxes span over seven decades,thereby requiring electronic devices to operate in counting and Campbelling modes simultaneously.Therefore,it is crucial to design a real-time NFM system to encompass such a wide dynamic range.In this study,a high-precision NFM system with a wide measurement range of neutron flux is implemented using realtime multipoint linear calibration.It can automatically switch between counting and Campbelling modes with variations in the neutron flux.We established a testing platform to verify the feasibility of the NFM system,which can output the simulated neutron signal using an arbitrary waveform generator.Meanwhile,the accurate calibration interval of the Campbelling mode is defined well.Based on the above-mentioned design,the system satisfies the requirements,offering a dynamic range of 10~8 cps,temporal resolution of 1 ms,and maximal relative error of 4%measured at the signal-to-noise ratio of 15.8 dB.Additionally,the NFM system is verified in a field experiment involving HL-2 A,and the measured neutron flux is consistent with the results.
基金supported by the National Key R&D Plan(No.2016YFA0401900)
文摘A bunch arrival-time monitor(BAM) system,based on electro-optical intensity modulation scheme, is under study at Shanghai Soft X-ray Free Electron Laser.The aim of the study is to achieve high-precision time measurement for minimizing bunch fluctuations. A readout electronics is developed to fulfill the requirements of the BAM system. The readout electronics is mainly composed of a signal conditioning circuit, field-programmable gate array(FPGA), mezzanine card(FMC150), and powerful FPGA carrier board. The signal conditioning circuit converts the laser pulses into electrical pulse signals using a photodiode. Thereafter, it performs splitting and low-noise amplification to achieve the best voltage sampling performance of the dual-channel analog-to-digital converter(ADC) in FMC150. The FMC150 ADC daughter card includes a 14-bit 250 Msps dual-channel high-speed ADC,a clock configuration, and a management module. The powerful FPGA carrier board is a commercial high-performance Xilinx Kintex-7 FPGA evaluation board. To achieve clock and data alignment for ADC data capture at a high sampling rate, we used ISERDES, IDELAY, and dedicated carry-in resources in the Kintex-7 FPGA. This paper presents a detailed development of the readout electronics in the BAM system and its performance.
文摘For the purpose of the monitor system in digital protection, the embedded real-time operating system (RTOS) and the embedded GUI (Graphical User Interface) is introduced to design the monitor system. Combining the necessity and the application value of the operation system, the choice of embedded Linux and Qt/Embedded is completely viable for the monitor system in digital protection for generator-transformer sets. The design with embedded Linux and embedded GUI enriches system information, increases developing efficiency and improve the generality.
基金supported by MOST under Grant No.106-2221-E-468-011-MY2。
文摘Αcloud-based home electricity data-monitoring system,which is based on an Arduino Mega controller,is proposed for monitoring the electricity consumption(electrical power)and power quality(PQ)in home.This system is also capable of monitoring the fundamental frequency and supply-voltage transients to ensure that the appliances operate in a safe operation range.The measured data(voltage and current)are transmitted through a Wi Fi device between the Arduino controller and server.The transmission control protocol(TCP)server is set up to acquire the high-data transmission rate.The server system immediately displays the calculated parameters and the waveform of the acquired signal.A comparison with a standard measurement device shows that the proposed system,which can be built at a low cost,exhibits the same functions as a factory product.
文摘The thesis describes an advanced digital solution to mining digital image monitor system, which makes up the shortage of the traditional mining analog image monitor. It illustrates the system components and how to choose the encoder bandwidth of the system. The problem of image multicast and its solution in LAN are also discussed.
基金Supported by the State Key program of National Natural Science of China(No.10979003)National Natural Science Foundation of China(No.10775181)China Postdoctoral Science Foundation(No.20090460521)
文摘A test system is developed for the BESIII ETOF/MRPC beam tests of data acquisition, environment monitoring and automatic control. The software framework is based on the CAMAC bus, VME bus and Serial Port,which are responsible for communications with the detectors. The monitor system works well in the beam test.
文摘Based on the control requirements of artificial grass tufting machine,an overall plan is proposed on control of CANopen bus.In the control system,on the basis of CoDeSys soft PLC technology of fieldbus control system,LMC20 realizes the communication by making CANopen bus connect with ATV71,OTB module and these underlying slave stations.The humanized operation interface is realized by touch screens and user-friendly application which is developed through CoDeSys,and detailed analysis of the monitor system and the principle and method of monitor system are also provided in the paper.
基金supported by the Research Funding Project for Graduate Education and Teaching Reform of Beijing University of Posts and Telecommunications(No.2024Y036)the Postgraduate Education and Teaching Reform Research Fund Project of Beijing University of Posts and Telecommunications(No.2024Z007)the Postgraduate Education and Teaching Reform Project of Beijing University of Posts and Telecommunications(2025).
文摘Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.
基金supported by Jiangxi Polytechnic Institute Key Research Topics in Educational Reform 2025-JGJG-07.
文摘The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.
基金support of the Korea Institute of Industrial Technol-ogy as“Development of a remote manufacturing system for high-risk,high-difficulty pipe production processes”(kitech EH-25-0004)supported by the Technology Innovation Program(or Industrial Strategic Technology Development Program)(RS-2023–00237714+2 种基金Development of Dynamic Metrology Tool for CMP Process StabilizationRS-2025–02634755Development of Real-Time Electrical Fire Prevention System Technology Reflecting the Characteristics of Traditional Markets)funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea).
文摘The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process conditions can lead to degradation in layer quality and non-uniformity,highlighting the need for real-time monitoring to improve overall quality and efficiency.In this study,an AI-based monitoring system was developed to evaluate layer width and assess quality in real time.Three deep learning models Faster Region-based Convolutional Neural Network(R-CNN),You Only Look Once version 8(YOLOv8),and Single Shot MultiBox Detector(SSD)were compared,and YOLOv8 was ultimately selected for its superior speed,flexibility,and scalability.The selected model was integrated into a user-friendly interface.To verify the reliability of the system,bead width control experiments were conducted,which identified feed speed and extrusion speed as the key process parameters.Accordingly,a Central Composite Design(CCD)experimental plan with 13 conditions was applied to evaluate layer width and validate the system’s reliability.Finally,the proposed system was applied to the additive manufacturing of an aerospace component,where it successfully detected bead width deviations during printing and enabled stable fabrication with a maximum geometric deviation of approximately 6 mm.These findings demonstrate the critical role of real-time monitoring of layer width and quality in improving process stability and final product quality in composite material additive manufacturing.
文摘The study of long-term pavement performance is a fundamental topic in the field of highway engineering.Through comprehensive and in-depth research on the pavement system,the previous scattered,one-sided,superficial,and perceptual knowledge and experience are summarized and sublimated into a systematic and complete engineering theory,thereby providing powerful guidance and assistance for the practice of pavement design,construction,maintenance,operation,and management.In this research,the mentoring system deployment technology for automatic monitoring is carried out for long-term pavement performance.By burying a variety of sensors in different parts of the road surface,base,roadbed,slope,etc.,a sensor monitoring network based on the Internet of Things technology is formed to achieve accurate,reliable,and continuous observation of environmental meteorology,physical state,mechanical response,structural deformation,and other indicators.The large amount of data and high real-time requirements mean that the perception data collected from sensors,including temperature,humidity,pressure,asphalt strain,and displacement,can be used to train a deep learning model based on a Convolutional Neural Network(CNN)algorithm.This model predicts multi-point pavement displacement to detect damage such as asphalt cracks and potholes.The response of the proposed CNN achieved a high accuracy rate,regression rate,and F-score equal to 87.24%,84.12%,and 85.96%,respectively.This work highlights the potential of using a variety of sensors to aid deep learning algorithms for monitoring long-term pavement performance.
基金supported by the National Key Research and Development Project(2022YFB4703200)。
文摘Pulmonary rehabilitation(PR)aims to improve lung function in patients with chronic respiratory disease(CRD).In recent years,significant advancements have been made in pulmonary rehabilitation technologies,demonstrating their potential for enhancing lung function in patients with respiratory diseases.The purpose of this study is to outline recent developments in the field of pulmonary rehabilitation guided by pulmonary rehabilitation robots,which has not been previously addressed in earlier reviews.To fill this gap,this paper first provides a systematic summary of the monitoring and actuation technologies of pulmonary rehabilitation robot systems and evaluates these technologies from multiple dimensions,including portability,wearability potential,invasiveness,and clinical applications,analyzing the potential for integrating various technologies into pulmonary rehabilitation robot systems.Furthermore,three technical directions are proposed:real-time precise monitoring,suitable structure and actuation strategies,and the intelligence of pulmonary rehabilitation robot systems.On the basis of these directions,this paper presents a comprehensive technical outlook for a soft wearable pulmonary rehabilitation robot system,providing reference and guidance for future research.To our knowledge,this is the first review of pulmonary rehabilitation robot systems and their key technologies.Additionally,the review section on respiratory assistive technologies simultaneously covers key technologies such as mechanical ventilation(MV),exoskeleton robots,and functional electrical stimulation(FES)for the first time.It also summarizes the respiratory assistive technology paradigm from the innovative perspectives of respiratory assistive modalities,targeted body sites,and types of ventilation for the first time.This study offers a broader perspective and a deeper understanding of pulmonary re-habilitation robots,with a technical outlook encompassing multimodal data fusion perception,respiratory event detection and intention recognition,full-phase assistance strategies,modeling,decoupling,and quantification of multipleinput multiple-output(MIMO)systems,as well as model-based interactive control strategies.
基金supported by the Collaborative Innovation Center Project of Guangdong Academy of Agricultural Sciences,China(XTXM202202).
文摘Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control.Hanging yellow sticky boards is a common way to monitor and trap those pests which are attracted to the yellow color.To achieve real-time,low-cost,intelligent monitoring of these vegetable pests on the boards,we established an intelligent monitoring system consisting of a smart camera,a web platform and a pest detection algorithm deployed on a server.After the operator sets the monitoring preset points and shooting time of the camera on the system platform,the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day.The pests trapped on the yellow sticky boards in vegetable fields,Plutella xylostella,Phyllotreta striolata and flies,are very small and susceptible to deterioration and breakage,which increases the difficulty of model detection.To solve the problem of poor recognition due to the small size and breaking of the pest bodies,we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests.The algorithm uses an overlapping sliding window method,an improved Res2Net network as the backbone network,and a recursive feature pyramid network as the neck network.The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images,with precision levels of 96.5,92.2 and 75.0%,and recall levels of 96.6,93.1 and 74.7%,respectively,and an F_(1) value of 0.880.Compared with other algorithms,our algorithm has a significant advantage in its ability to detect small target pests.To accurately obtain the data for the newly added pests each day,a two-stage pest matching algorithm was proposed.The algorithm performed well and achieved results that were highly consistent with manual counting,with a mean error of only 2.2%.This intelligent monitoring system realizes precision,good visualization,and intelligent vegetable pest monitoring,which is of great significance as it provides an effective pest prevention and control option for farmers.
基金partially supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1A6A1A03025242)by the Korea government(MIST)(RS-2023-00302751,RS-2024-00343686)the Research Grant of Kwangwoon University in 2024。
文摘Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.
基金supported by the National Natural Science Foundation of China(Nos.12172248,12302022,12021002,and 12132010)the Tianjin Research Program of Application Foundation and Advanced Technology of China(No.23JCZDJC00950)。
文摘Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.
基金supported by the National Key R&D Project from Minister of Science and Technology(Grant No.2021YFA1201604)Beijing Natural Science Foundation(Grant No.3244038)+1 种基金GuangDong Basic and Applied Basic Research Foundation(Grant No.2024A1515140103)Jilin Province Development and Reform Commission(Grant No.2024C006-3).
文摘Real-time detection of low-speed motion and precise monitoring of low-intensity exercise are crucial for smart fitness systems.These capabilities enable continuous data acquisition,capture subtle motion variations for personalized guidance,and enhance training effectiveness while reducing the risk of injury.However,conventional rotational speed sensors often exhibit signal loss and limited responsiveness at low speeds,leading to inaccurate feedback and constraining the development of intelligent fitness devices.Therefore,this paper proposes a triboelectric rotational speed sensor(TRSS),which employs a coaxial reverse magnetic modulation transmission mechanism to enhance low-speed monitoring,thereby overcoming low-speed signal loss.The sensor enables real-time detection of rotational speed in fitness equipment,and features a compact structure,doubled resolution,and high detection accuracy of 0.21 rad s−1.Performance test indicates a sensitivity of 3.15 Hz(rad s−1)−1,a linear correlation coefficient of 0.99892,and an average error of 1.19%in simulated tests,which demonstrates the capability of the sensor for accurate motion monitoring at low speeds.Furthermore,a triboelectric magnetic-modulated rotational monitoring system(TMRMS)is developed and validated through cycling experiments,demonstrating excellent performance across a wide speed range.These findings highlight the strong potential of the system for advancing next-generation smart fitness applications.
基金supported by the National Natural Science Foundation of China(12064027,12464010)2022 Jiangxi Province High-level and Highskilled Leading Talent Training Project Selected(No.63)+1 种基金Jiujiang"Xuncheng Talents"(No.JJXC2023032)Jiujiang Natural Science Foundation Project(Key Technologies Research on Autonomous Cruise Solar-Powered UAV-2025-1).
文摘This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The IHLOA algorithm introduces three key innovations:(1)chaotic initialization to enhance population diversity and global search capability,(2)adaptive random walk strategies to escape local optima,and(3)a cross-strategy mechanism to accelerate convergence and enhance fault detection accuracy and robustness.The system comprises both hardware and software components.The hardware includes sensors such as the BH1750 light intensity sensor,DS18B20 temperature sensor,and INA226 current and voltage sensor,all interfaced with the STM32F103C8T6 microcontroller and the ESP8266 module for wireless data transmission.The software,developed using QT Creator,incorporates an IHLOA-MLP model for fault diagnosis.The user-friendly interface facilitates intuitive monitoring and scalability for multiple systems.Experimental validation on a PV array demonstrates that the IHLOA-MLP model achieves a fault detection accuracy of 94.55%,which is 2.4%higher than the standard MLP,while reducing variance by 63.64%compared to the standard MLP.This highlights its accuracy and robustness.When compared to other optimization algorithms such as BKA-MLP(94.10%accuracy)and HLOA-MLP(94.00%accuracy),the IHLOA-MLP further reduces variance to 0.08,showcasing its superior performance.The system selects voltage as a feature vector to maintain circuit stability,avoiding efficiency impacts from series current sensors.This combined hardware and software approach further reduces false alarms to 0.1%through a consecutive-judgment mechanism,significantly enhancing practical reliability.This work provides a cost-effective and scalable solution for improving the stability and safety of PV systems in real-world applications.
文摘In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.
