Considering its structural features,geometric shapes,service mode,environmental media,mechanical behavior,etc,the special nature and complexity of tailings dam were summarized.The technical approach to safety manageme...Considering its structural features,geometric shapes,service mode,environmental media,mechanical behavior,etc,the special nature and complexity of tailings dam were summarized.The technical approach to safety management for tailings dam was proposed,which is the on-line automated monitoring and early warning information.The results show that a strong theoretical basis can be provided for security monitoring and security management of tailings dam.Online automated monitoring system for tailings dam has full implementation of the information.It is applied widely in Lingnan gold mine,Xiadian gold mine and Hedong gold mine in Zhaoyuan,Shandong Province,and achieves good effect.展开更多
The online-monitoring methods for insulation performance of current transformers of 330-750 kV substation are analyzed and compared.The effectiveness and availability of each method are discussed.Main features,advanta...The online-monitoring methods for insulation performance of current transformers of 330-750 kV substation are analyzed and compared.The effectiveness and availability of each method are discussed.Main features,advantages and disadvantages of each method and its corresponding standard are also described.展开更多
The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining...The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.展开更多
To promote the accuracy and application of arcing time measurement for SF_6 circuit breaker in substation,five measurement methods are investigated by two cases experimentally. First,the test results of the five metho...To promote the accuracy and application of arcing time measurement for SF_6 circuit breaker in substation,five measurement methods are investigated by two cases experimentally. First,the test results of the five methods for a circuit breaker in different stages of wear and a circuit breaker with a component failure were presented. Then,the time error is analyzed by simulation.Finally,the advantage and disadvantage of these methods are discussed.展开更多
Comparing and analyzing some volume deformation measuring means for cement-based materials at home and abroad, a continuous online monitor of cement-based material volume deformation in multiple environments is develo...Comparing and analyzing some volume deformation measuring means for cement-based materials at home and abroad, a continuous online monitor of cement-based material volume deformation in multiple environments is developed. The device is designed based on the environmental simulation technology, micro-distance measuring technology of laser and eddy current, and transmission agent online monitoring the deformation of multi-group samples. This device can be used widely, such as glass, ceramics, walling material, and so on, with high precision, low testing cost, and intellectualization.展开更多
Injection molding is a complicated production technique for the manufacturing of polymer products.During injection molding,it's hard to predict molding quality;the injection molding parameters,such as mold tempera...Injection molding is a complicated production technique for the manufacturing of polymer products.During injection molding,it's hard to predict molding quality;the injection molding parameters,such as mold temperature,melt temperature,packing pressure and packing time,affect the final properties of product.The cavity pressure is a significant key factor.Residual stress and injection molding weight are significantly affected by the cavity pressure.This study created an approach to predict weight of injection-molded by real-time online cavity pressure monitoring.This study uses a 6-inch with thickness lmm light guide panel and the largest area beneath the pressure curve of time as well as the maximum pressure as its characteristic.The upper and lower limits of the control are set to+2 standard deviations,and GUI(Graphical User Interface)-based LabVIEW software is used to perform calculation and analysis of the pressure curve.The results of the experiment show that the online internal cavity pressure monitoring system can effectively monitor the quality of the molded products.In 500 injection molding cycle tests,its error rate was less than 8%,whereas the deviation in mass of the molded products selected through the system's filtering process was successfully controlled to be within±4%.展开更多
Power cable is one of the important components of power system infrastructure and plays an important role infrastructure and plays an important role in power supply process. If power cable runs under high voltage and ...Power cable is one of the important components of power system infrastructure and plays an important role infrastructure and plays an important role in power supply process. If power cable runs under high voltage and large current for a long time, it may exceed the temperature limit due to overload, insulation aging and joint failure. If the abnormality cannot be found in time, it will directly affect the service life of the cable. The insulation performance of power cable is the main factor that determines the normal operation of power cable. And the temperature of cable joint and conductor is the key index that affects the insulation performance of power cable. Monitoring the temperature of power cable is one of the key technologies in power system research and development.展开更多
This paper proposed an online monitoring and early-warning system of dynamic stress of crane metal structure,and designed this system’s hardware,including sensor unit,data gathering unit,and controlling&processin...This paper proposed an online monitoring and early-warning system of dynamic stress of crane metal structure,and designed this system’s hardware,including sensor unit,data gathering unit,and controlling&processing unit of this sys-tem,and discussed the waterproof protection for resistance strain wafer and scheme of data gathering and transmission of dynamic strain gauge,moreover developed system software of real-time and online monitoring dynamic stress,including data gathering by DLL and data display&processing based on Visual C++.The system applies the dynamic strain gauge to gather the data of the stress,and communicates between PLC control system of crane and upper industrial computer,so that realize the real-time online monitoring and early-warning for crane’s metal structure stress.The test results show this system carry on real time and online monitoring to dynamic stress of loud-bearing metal structure longly and stability,and can give an alarm and overload protection on time.So the system has good practice value.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
The operation furnace profile for the high heat load zone was one of the important factors affecting the stable and high-quality production of the blast furnace,but it was difficult to monitor directly.To address this...The operation furnace profile for the high heat load zone was one of the important factors affecting the stable and high-quality production of the blast furnace,but it was difficult to monitor directly.To address this issue,an online calculation model for the operation furnace profile was proposed based on a dual-driven approach combining data and mechanisms,by integrating mechanism experiment,numerical simulation,and machine learning.The experimentally determined slag layer hanging temperature was 1130℃,and the thermal conductivity ranged from 1.32 to 1.96 m^(2)℃^(-1).Based on the 3D slag-hanging numerical simulation model,a database was constructed,containing 2294 sets of mechanism cases for the slag layer.The fusion of data modeling,heat transfer theory,and expert experience enabled the online calculation of key input variables for the operation furnace profile,particularly the quantification of the“black-box”variable of gas temperature.Simulated data were used as inputs,and light gradient boosting machine was applied to construct the online calculation model for the operation furnace profile.This model facilitated the online calculation of the slag layer thickness and other key indices.The coefficient of determination of the model exceeded 0.98,indicating high accuracy.A slag layer state judgment model was constructed,categorizing states as shedding,too thin,normal,and too thick.Real-time data were applied,and the average slag thickness in the high heat load area of the test data ranged from 40 to 80 mm,which was consistent with field experience.The absolute value of the Pearson correlation coefficient between slag layer thickness,thermocouple temperature,and heat load data was above 0.85,indicating that the calculated results closely aligned with the actual trends.A 3D visual online monitoring system for the operation furnace profile was created,and it has been successfully implemented at the blast furnace site.展开更多
Non-point source(NPS)pollution has been the major cause of water quality degradation.However,there are still shortcomings in the current monitoring methods for NPS pollution,such as small monitoring range,error of mon...Non-point source(NPS)pollution has been the major cause of water quality degradation.However,there are still shortcomings in the current monitoring methods for NPS pollution,such as small monitoring range,error of monitoring data,time-consuming and laborious monitoring process.Although the established method,field experiment plots,was used effectively in the first and second national pollution source census in China.However,when the results obtained by monitoring experimental plots are extrapolated to a field or larger scale,there are considerable uncertainties because of the characteristics of large spatial and temporal variation of farmland.To optimize the farmland surface runoff monitoring methods,an online monitoring system for continuous cropping based on a serial pipeline was developed,which takes diversion trench,online flowmeter and dynamic acquisition device as the main body.Compared with the current farmland monitoring methods,this system can realize more precise automatic monitoring of water quantity and quality,and lower costs.This innovative method will provide greater confidence in the actual monitoring of NPS pollution from farmland and wider practical application.This new method could prove particularly valuable for the next national pollution source census in China.展开更多
Aiming at the problems in the traditional peanut sowing operation process, such as single monitoring mode, lack of online monitoring function, inability to deeply utilize data, and difficulty in tracing the sowing qua...Aiming at the problems in the traditional peanut sowing operation process, such as single monitoring mode, lack of online monitoring function, inability to deeply utilize data, and difficulty in tracing the sowing quality, an online monitoring system for peanut sowing parameters based on the Internet of Things (IoT) was designed. The online monitoring system for peanut sowing parameters consists of a peanut seed-metering monitoring device, an on-board monitoring terminal, and an online monitoring cloud platform. The system can monitor parameters such as seed spacing, seeding rate, missed seeding, vehicle speed, temperature, and humidity. It transmits data through RS485 and IoT communication, and supports local interaction and cloud data storage and analysis. The seed-metering monitoring device uses laser opposite reflection and window fiber optic sensors to monitor the missed seeding and seed-metering status in real time. The on-board terminal uses an optoelectronic rotary encoder to collect the rotational speed and calculate the parameters. The operation status is displayed through the human-machine interaction module, and the data is packaged and sent to the cloud server via a wireless network. The online monitoring cloud platform selects the Alibaba Cloud IoT platform, connects with it through the MQTT protocol, and conducts visual development using IoT-studio to achieve data display, analysis, and statistics. Through the test on the simulated test bench, the accuracy rates of the seed spacing, seeding rate, and missed seeding monitoring of the seed-metering monitoring module of the system exceed 98.02%, 98.03%, and 99%, respectively. The field test based on the actual seeder shows that the monitoring effect of the seed spacing of 16 cm and 20 cm is good. The accuracy rate of the 27 cm seed spacing decreases slightly with the increase of the speed but still exceeds 97%. The accuracy rates of the missed seeding and seeding rate monitoring exceed 98%, and the online monitoring module transmits data normally. After testing, each part of the system has good performance, meeting the functional and accuracy requirements of the online monitoring of peanut sowing operation parameters.展开更多
The core objectives of intelligent manufacturing are to enhance product quality,reduce production costs,and improve manufacturing efficiency.One of the key technologies to achieve this goal is the monitoring and contr...The core objectives of intelligent manufacturing are to enhance product quality,reduce production costs,and improve manufacturing efficiency.One of the key technologies to achieve this goal is the monitoring and control of the machining process.Traditional offline tool condition monitoring(TCM)methods are prone to human error and require additional downtime.By contrast,tool condition online monitoring technology enables real-time monitoring throughout the machining process.This study reviews the progress of research on online monitoring of tool conditions and process parameter control based on tool status.It provides a detailed analysis from three perspectives:tool condition perception,algorithms for monitoring and control,and applications of monitoring and control.In terms of tool condition perception,the advantages and drawbacks of various sensing methods are explored.In terms of monitoring and control algorithms,developments from traditional monitoring algorithms to intelligent monitoring and parameter control algorithms are progressively reviewed.With regard to applications,the review focuses on how to adjust process parameters online on the basis of TCM by building on abnormal detection,tool wear monitoring,and life prediction to protect tools and improve machining efficiency.Then,the main development trends in tool condition online monitoring and control are introduced.Unlike previous reviews,this work extends the discussion beyond TCM to include recent progress in process parameter control on the basis of tool condition.The integration of tool online monitoring and process parameter control is recognized as one of the essential technologies for realizing intelligent manufacturing.展开更多
Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on ed...Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on edge computing and DL(deep learning).In order to solve the high amount of computation brought by the deep neural network and meet the limited computing resources at the edge,a lightweight SSD(Single Shot MultiBox Detector)target recognition network is designed at the edge,which adopts the MobileNets network to replace VGG16 network in the original model to reduce redundant computing.In the cloud,three detection algorithms(Faster-RCNN,Retinanet,YOLOv3)with obvious differences in detection performance are selected to obtain the coordinates and confidence of the insulator self-explosion area,and then the self-explosion fault detection of the overhead transmission line is realized by a novel multimodel fusion algorithm.The experimental results show that the proposed scheme can effectively reduce the amount of uploaded data,and the average recognition accuracy of the cloud is 95.75%.In addition,it only increases the power consumption of edge devices by about 25.6W/h in their working state.Compared with the existing online monitoring technology of insulator selfexplosion at home and abroad,the proposed scheme has the advantages of low transmission delay,low communication cost and high diagnostic accuracy,which provides a new idea for online monitoring research of power internet of things equipment.展开更多
Laser-induced breakdown spectroscopy(LIBS)is widely used for elemental analysis.However,its application for monitoring and analyzing a laser machining process by examining the changes in spectral information warrants ...Laser-induced breakdown spectroscopy(LIBS)is widely used for elemental analysis.However,its application for monitoring and analyzing a laser machining process by examining the changes in spectral information warrants further investigation.In this study,we investigate the effect of laser parameters on the spectra,variations in the time-resolved plasma emission spectra,and the relationship between the morphology of craters and plasma plume evolution during the femtosecond(fs)laser ablation of sapphire.The Boltzmann plot method and Stark’s broadening model are employed to estimate the temporal temperature and electron density of the plasma plume,revealing the process of plasma evolution.This study aims to demonstrate the feasibility of LIBS for online monitoring of laser processing through experimental data and theoretical explanations.展开更多
Online diagnosis methods for high-voltage(HV)cable faults have been extensively studied.Power cable fault monitoring is not accurate,and the degree of data fusion analysis of current methods is insufficient.To address...Online diagnosis methods for high-voltage(HV)cable faults have been extensively studied.Power cable fault monitoring is not accurate,and the degree of data fusion analysis of current methods is insufficient.To address these problems,an online monitoring method based on the locus-analysis for HV cable faults is developed.By simultaneously measuring two circulating currents in a coaxial cable,a two-dimensional locus diagram is drawn.The fault criteria and database are established to detect the fault by analyzing the changes of the locus characteristic parameters.A cross-connected grounding simulation model of a high-voltage cable is developed,and several faults at different locations are simulated.Fault identification is established based on the changes in the long axis,short axis,eccentricity,and tilt angle of the track.The simulation and field experiments show that this method can provide an increased amount of fault-monitoring reference information,which can improve the monitoring accuracy and provide a new approach to cable fault monitoring.展开更多
The condition of bolted connections significantly affects the structural safety.However,conventional bolt tension sensors fail to provide precise measurements due to their bulky size or inadequate stability.This study...The condition of bolted connections significantly affects the structural safety.However,conventional bolt tension sensors fail to provide precise measurements due to their bulky size or inadequate stability.This study employs the piezoresistive effect of crystalline silicon material to fabricate an ultrathin sensor.The sensor exhibits a linear relationship between pressure and voltage,an exceptional stability at varying temperatures,and a superior resistance to corrosion,making it adaptable and user-friendly for applications of high-strength bolt tension monitoring.A monitoring system,incorporating the proposed sensor,has also been developed.This system provides real-time display of bolt tension and enables the assessment of sensor and structural conditions,including bolt loosening or component failure.The efficacy of the proposed sensor and monitoring system was validated through a project carried out at the Xiluodu Hydropower Plant.According to the results,the sensor and online monitoring system effectively gauged and proficiently conveyed and stored bolt tension data.In addition,correlations were created between bolt tensions and essential unit parameters,such as water head,active power,and pressures at vital points,facilitating anomaly detection and early warning.展开更多
A method based on solution of the inverse heat conduction problem was presented for online stress monitoring and fatigue life analysis of boiler drums. The mathematical model of the drum temperature distribution is ba...A method based on solution of the inverse heat conduction problem was presented for online stress monitoring and fatigue life analysis of boiler drums. The mathematical model of the drum temperature distribution is based on the assumptions that the difference of temperature along the longitudinal axis of the boiler drum is negligible with changes only in the radial direction and the circumferential direction, and that the outer surface of drum is thermaUy insulated. Combining this model with the control-volume method provides temperatures at different points on a cross-section of the drum. With the temperature data, the stresses and the life expectancy of the boiler drum are derived according to the ASME code. Applying this method to the cold start-up process of a 300 MW boiler demonstrated the absence of errors caused by the boundary condition assumptions on the inner surface of the drum and testified that the method is an applicable technique for the online stress monitoring and fatigue life analysis of boiler drums.展开更多
A new on-line predictive monitoring and prediction model for periodic biological processes is proposed using the multiway non-Gaussian modeling. The basic idea of this approach is to use multiway non-Gaussian modeling...A new on-line predictive monitoring and prediction model for periodic biological processes is proposed using the multiway non-Gaussian modeling. The basic idea of this approach is to use multiway non-Gaussian modeling to extract some dominant key components from daily normal operation data in a periodic process, and subsequently combining these components with predictive statistical process monitoring techniques. The proposed predictive monitoring method has been applied to fault detection and diagnosis in the biological wastewater-treatment process, which is based on strong diurnal characteristics. The results show the power and advantages of the proposed predictive monitoring of a continuous process using the multiway predictive monitoring concept, which is thus able to give very useful conceptual results for a daily monitoring process and also enables a more rapid detection of the process fault than other traditional monitoring methods.展开更多
A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cell...A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cells)could become the anchor of linkage attacks to re-identify the users.Focusing on trajectory privacy in online health monitoring,we propose the User Trajectory Model(UTM),a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data(e.g.,number of individuals covered by each small cell),and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness(i.e.,the expectation and the variance).Eventually,exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation,confirm our theoretical deductions and present counter-intuitive insights.展开更多
基金Projects(50874064,50804026,50904039)supported by the National Natural Science Foundation of ChinaProject(200804290002)supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(G2010F10)supported by S&T Plan Project from Shandong Provincial Education Department
文摘Considering its structural features,geometric shapes,service mode,environmental media,mechanical behavior,etc,the special nature and complexity of tailings dam were summarized.The technical approach to safety management for tailings dam was proposed,which is the on-line automated monitoring and early warning information.The results show that a strong theoretical basis can be provided for security monitoring and security management of tailings dam.Online automated monitoring system for tailings dam has full implementation of the information.It is applied widely in Lingnan gold mine,Xiadian gold mine and Hedong gold mine in Zhaoyuan,Shandong Province,and achieves good effect.
基金Science and Technology Projects of Gansu Electric Power Company(No.52274514005W)
文摘The online-monitoring methods for insulation performance of current transformers of 330-750 kV substation are analyzed and compared.The effectiveness and availability of each method are discussed.Main features,advantages and disadvantages of each method and its corresponding standard are also described.
基金supported by the Natural Science Foundation of Shanxi Province,China(202203021211153)National Natural Science Foundation of China(51704205).
文摘The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.
基金Project Supported by the Technique Project of China Southern Power Grid Co.,Ltd.(20142001342)
文摘To promote the accuracy and application of arcing time measurement for SF_6 circuit breaker in substation,five measurement methods are investigated by two cases experimentally. First,the test results of the five methods for a circuit breaker in different stages of wear and a circuit breaker with a component failure were presented. Then,the time error is analyzed by simulation.Finally,the advantage and disadvantage of these methods are discussed.
文摘Comparing and analyzing some volume deformation measuring means for cement-based materials at home and abroad, a continuous online monitor of cement-based material volume deformation in multiple environments is developed. The device is designed based on the environmental simulation technology, micro-distance measuring technology of laser and eddy current, and transmission agent online monitoring the deformation of multi-group samples. This device can be used widely, such as glass, ceramics, walling material, and so on, with high precision, low testing cost, and intellectualization.
文摘Injection molding is a complicated production technique for the manufacturing of polymer products.During injection molding,it's hard to predict molding quality;the injection molding parameters,such as mold temperature,melt temperature,packing pressure and packing time,affect the final properties of product.The cavity pressure is a significant key factor.Residual stress and injection molding weight are significantly affected by the cavity pressure.This study created an approach to predict weight of injection-molded by real-time online cavity pressure monitoring.This study uses a 6-inch with thickness lmm light guide panel and the largest area beneath the pressure curve of time as well as the maximum pressure as its characteristic.The upper and lower limits of the control are set to+2 standard deviations,and GUI(Graphical User Interface)-based LabVIEW software is used to perform calculation and analysis of the pressure curve.The results of the experiment show that the online internal cavity pressure monitoring system can effectively monitor the quality of the molded products.In 500 injection molding cycle tests,its error rate was less than 8%,whereas the deviation in mass of the molded products selected through the system's filtering process was successfully controlled to be within±4%.
文摘Power cable is one of the important components of power system infrastructure and plays an important role infrastructure and plays an important role in power supply process. If power cable runs under high voltage and large current for a long time, it may exceed the temperature limit due to overload, insulation aging and joint failure. If the abnormality cannot be found in time, it will directly affect the service life of the cable. The insulation performance of power cable is the main factor that determines the normal operation of power cable. And the temperature of cable joint and conductor is the key index that affects the insulation performance of power cable. Monitoring the temperature of power cable is one of the key technologies in power system research and development.
基金Funded by the National Natural Science Fund grants 60574012
文摘This paper proposed an online monitoring and early-warning system of dynamic stress of crane metal structure,and designed this system’s hardware,including sensor unit,data gathering unit,and controlling&processing unit of this sys-tem,and discussed the waterproof protection for resistance strain wafer and scheme of data gathering and transmission of dynamic strain gauge,moreover developed system software of real-time and online monitoring dynamic stress,including data gathering by DLL and data display&processing based on Visual C++.The system applies the dynamic strain gauge to gather the data of the stress,and communicates between PLC control system of crane and upper industrial computer,so that realize the real-time online monitoring and early-warning for crane’s metal structure stress.The test results show this system carry on real time and online monitoring to dynamic stress of loud-bearing metal structure longly and stability,and can give an alarm and overload protection on time.So the system has good practice value.
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.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52404343 and 52274326)the Fundamental Research Funds for the Central Universities(Grant Nos.N2425031 and N25BJD007)+1 种基金the China Postdoctoral Science Foundation(Grant No.2024M760370)the Liaoning Province Science and Technology Plan Joint Program(Key Research and Development Program Project)(Grant No.2023JH2/101800058).
文摘The operation furnace profile for the high heat load zone was one of the important factors affecting the stable and high-quality production of the blast furnace,but it was difficult to monitor directly.To address this issue,an online calculation model for the operation furnace profile was proposed based on a dual-driven approach combining data and mechanisms,by integrating mechanism experiment,numerical simulation,and machine learning.The experimentally determined slag layer hanging temperature was 1130℃,and the thermal conductivity ranged from 1.32 to 1.96 m^(2)℃^(-1).Based on the 3D slag-hanging numerical simulation model,a database was constructed,containing 2294 sets of mechanism cases for the slag layer.The fusion of data modeling,heat transfer theory,and expert experience enabled the online calculation of key input variables for the operation furnace profile,particularly the quantification of the“black-box”variable of gas temperature.Simulated data were used as inputs,and light gradient boosting machine was applied to construct the online calculation model for the operation furnace profile.This model facilitated the online calculation of the slag layer thickness and other key indices.The coefficient of determination of the model exceeded 0.98,indicating high accuracy.A slag layer state judgment model was constructed,categorizing states as shedding,too thin,normal,and too thick.Real-time data were applied,and the average slag thickness in the high heat load area of the test data ranged from 40 to 80 mm,which was consistent with field experience.The absolute value of the Pearson correlation coefficient between slag layer thickness,thermocouple temperature,and heat load data was above 0.85,indicating that the calculated results closely aligned with the actual trends.A 3D visual online monitoring system for the operation furnace profile was created,and it has been successfully implemented at the blast furnace site.
基金supported by Key S&T Special Project of Yunan Province(202202AE090034,202402AE090024)National Natural Science Foundation of China(42107410,42477441)+1 种基金Hebei Financial Aid Program for Introduced Overseas Scholars(C20230337)Local Science and Technology Development Fund Projects Guided by the Central Government in Hebei Province(246Z3607G).
文摘Non-point source(NPS)pollution has been the major cause of water quality degradation.However,there are still shortcomings in the current monitoring methods for NPS pollution,such as small monitoring range,error of monitoring data,time-consuming and laborious monitoring process.Although the established method,field experiment plots,was used effectively in the first and second national pollution source census in China.However,when the results obtained by monitoring experimental plots are extrapolated to a field or larger scale,there are considerable uncertainties because of the characteristics of large spatial and temporal variation of farmland.To optimize the farmland surface runoff monitoring methods,an online monitoring system for continuous cropping based on a serial pipeline was developed,which takes diversion trench,online flowmeter and dynamic acquisition device as the main body.Compared with the current farmland monitoring methods,this system can realize more precise automatic monitoring of water quantity and quality,and lower costs.This innovative method will provide greater confidence in the actual monitoring of NPS pollution from farmland and wider practical application.This new method could prove particularly valuable for the next national pollution source census in China.
基金supported by the Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization Open Projects(SDXTZX-05).
文摘Aiming at the problems in the traditional peanut sowing operation process, such as single monitoring mode, lack of online monitoring function, inability to deeply utilize data, and difficulty in tracing the sowing quality, an online monitoring system for peanut sowing parameters based on the Internet of Things (IoT) was designed. The online monitoring system for peanut sowing parameters consists of a peanut seed-metering monitoring device, an on-board monitoring terminal, and an online monitoring cloud platform. The system can monitor parameters such as seed spacing, seeding rate, missed seeding, vehicle speed, temperature, and humidity. It transmits data through RS485 and IoT communication, and supports local interaction and cloud data storage and analysis. The seed-metering monitoring device uses laser opposite reflection and window fiber optic sensors to monitor the missed seeding and seed-metering status in real time. The on-board terminal uses an optoelectronic rotary encoder to collect the rotational speed and calculate the parameters. The operation status is displayed through the human-machine interaction module, and the data is packaged and sent to the cloud server via a wireless network. The online monitoring cloud platform selects the Alibaba Cloud IoT platform, connects with it through the MQTT protocol, and conducts visual development using IoT-studio to achieve data display, analysis, and statistics. Through the test on the simulated test bench, the accuracy rates of the seed spacing, seeding rate, and missed seeding monitoring of the seed-metering monitoring module of the system exceed 98.02%, 98.03%, and 99%, respectively. The field test based on the actual seeder shows that the monitoring effect of the seed spacing of 16 cm and 20 cm is good. The accuracy rate of the 27 cm seed spacing decreases slightly with the increase of the speed but still exceeds 97%. The accuracy rates of the missed seeding and seeding rate monitoring exceed 98%, and the online monitoring module transmits data normally. After testing, each part of the system has good performance, meeting the functional and accuracy requirements of the online monitoring of peanut sowing operation parameters.
文摘The core objectives of intelligent manufacturing are to enhance product quality,reduce production costs,and improve manufacturing efficiency.One of the key technologies to achieve this goal is the monitoring and control of the machining process.Traditional offline tool condition monitoring(TCM)methods are prone to human error and require additional downtime.By contrast,tool condition online monitoring technology enables real-time monitoring throughout the machining process.This study reviews the progress of research on online monitoring of tool conditions and process parameter control based on tool status.It provides a detailed analysis from three perspectives:tool condition perception,algorithms for monitoring and control,and applications of monitoring and control.In terms of tool condition perception,the advantages and drawbacks of various sensing methods are explored.In terms of monitoring and control algorithms,developments from traditional monitoring algorithms to intelligent monitoring and parameter control algorithms are progressively reviewed.With regard to applications,the review focuses on how to adjust process parameters online on the basis of TCM by building on abnormal detection,tool wear monitoring,and life prediction to protect tools and improve machining efficiency.Then,the main development trends in tool condition online monitoring and control are introduced.Unlike previous reviews,this work extends the discussion beyond TCM to include recent progress in process parameter control on the basis of tool condition.The integration of tool online monitoring and process parameter control is recognized as one of the essential technologies for realizing intelligent manufacturing.
基金supported by the Natural Science Foundation of China(52167008)Outstanding Youth Fund Project of Jiangxi Natural Science Foundation(20202ACBL214021)+1 种基金Key Research and Development Plan of Jiangxi Province(20202BBGL73098)Science and Technology Project of Education Department of Jiangxi Province(GJJ210650)。
文摘Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on edge computing and DL(deep learning).In order to solve the high amount of computation brought by the deep neural network and meet the limited computing resources at the edge,a lightweight SSD(Single Shot MultiBox Detector)target recognition network is designed at the edge,which adopts the MobileNets network to replace VGG16 network in the original model to reduce redundant computing.In the cloud,three detection algorithms(Faster-RCNN,Retinanet,YOLOv3)with obvious differences in detection performance are selected to obtain the coordinates and confidence of the insulator self-explosion area,and then the self-explosion fault detection of the overhead transmission line is realized by a novel multimodel fusion algorithm.The experimental results show that the proposed scheme can effectively reduce the amount of uploaded data,and the average recognition accuracy of the cloud is 95.75%.In addition,it only increases the power consumption of edge devices by about 25.6W/h in their working state.Compared with the existing online monitoring technology of insulator selfexplosion at home and abroad,the proposed scheme has the advantages of low transmission delay,low communication cost and high diagnostic accuracy,which provides a new idea for online monitoring research of power internet of things equipment.
基金This work was supported by the National Key R&D Program of China(Grant Nos.2022YFB4600402 and 2022YFE0199100)the Natural Science Foundation of Shandong(Grant Nos.ZR2022MF030 and ZR2020ME164)the Natural Science Foundation of Zhejiang(Grant No.LY21F050002).
文摘Laser-induced breakdown spectroscopy(LIBS)is widely used for elemental analysis.However,its application for monitoring and analyzing a laser machining process by examining the changes in spectral information warrants further investigation.In this study,we investigate the effect of laser parameters on the spectra,variations in the time-resolved plasma emission spectra,and the relationship between the morphology of craters and plasma plume evolution during the femtosecond(fs)laser ablation of sapphire.The Boltzmann plot method and Stark’s broadening model are employed to estimate the temporal temperature and electron density of the plasma plume,revealing the process of plasma evolution.This study aims to demonstrate the feasibility of LIBS for online monitoring of laser processing through experimental data and theoretical explanations.
文摘Online diagnosis methods for high-voltage(HV)cable faults have been extensively studied.Power cable fault monitoring is not accurate,and the degree of data fusion analysis of current methods is insufficient.To address these problems,an online monitoring method based on the locus-analysis for HV cable faults is developed.By simultaneously measuring two circulating currents in a coaxial cable,a two-dimensional locus diagram is drawn.The fault criteria and database are established to detect the fault by analyzing the changes of the locus characteristic parameters.A cross-connected grounding simulation model of a high-voltage cable is developed,and several faults at different locations are simulated.Fault identification is established based on the changes in the long axis,short axis,eccentricity,and tilt angle of the track.The simulation and field experiments show that this method can provide an increased amount of fault-monitoring reference information,which can improve the monitoring accuracy and provide a new approach to cable fault monitoring.
文摘The condition of bolted connections significantly affects the structural safety.However,conventional bolt tension sensors fail to provide precise measurements due to their bulky size or inadequate stability.This study employs the piezoresistive effect of crystalline silicon material to fabricate an ultrathin sensor.The sensor exhibits a linear relationship between pressure and voltage,an exceptional stability at varying temperatures,and a superior resistance to corrosion,making it adaptable and user-friendly for applications of high-strength bolt tension monitoring.A monitoring system,incorporating the proposed sensor,has also been developed.This system provides real-time display of bolt tension and enables the assessment of sensor and structural conditions,including bolt loosening or component failure.The efficacy of the proposed sensor and monitoring system was validated through a project carried out at the Xiluodu Hydropower Plant.According to the results,the sensor and online monitoring system effectively gauged and proficiently conveyed and stored bolt tension data.In addition,correlations were created between bolt tensions and essential unit parameters,such as water head,active power,and pressures at vital points,facilitating anomaly detection and early warning.
基金Funded by the National Science and Technology Support Project of China (No. 2006BAA03B02-03)
文摘A method based on solution of the inverse heat conduction problem was presented for online stress monitoring and fatigue life analysis of boiler drums. The mathematical model of the drum temperature distribution is based on the assumptions that the difference of temperature along the longitudinal axis of the boiler drum is negligible with changes only in the radial direction and the circumferential direction, and that the outer surface of drum is thermaUy insulated. Combining this model with the control-volume method provides temperatures at different points on a cross-section of the drum. With the temperature data, the stresses and the life expectancy of the boiler drum are derived according to the ASME code. Applying this method to the cold start-up process of a 300 MW boiler demonstrated the absence of errors caused by the boundary condition assumptions on the inner surface of the drum and testified that the method is an applicable technique for the online stress monitoring and fatigue life analysis of boiler drums.
基金the Korea Research Foundation Grant Funded by the Korean Government (MOEHRD) (KRF-2007-331-D00089) Funded by Seoul Development Institute (CS070160)
文摘A new on-line predictive monitoring and prediction model for periodic biological processes is proposed using the multiway non-Gaussian modeling. The basic idea of this approach is to use multiway non-Gaussian modeling to extract some dominant key components from daily normal operation data in a periodic process, and subsequently combining these components with predictive statistical process monitoring techniques. The proposed predictive monitoring method has been applied to fault detection and diagnosis in the biological wastewater-treatment process, which is based on strong diurnal characteristics. The results show the power and advantages of the proposed predictive monitoring of a continuous process using the multiway predictive monitoring concept, which is thus able to give very useful conceptual results for a daily monitoring process and also enables a more rapid detection of the process fault than other traditional monitoring methods.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61871062and Grant 61771082the Natural Science Foundation of Chongqing of China under Grant cstc2013jcyjA40066+3 种基金the Program for Innovation Team Building at Institutions of Higher Education in Chongqing under Grant CXTDX201601020the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant KJQN201801316the Key Industrial Technology Development Project of Chongqing of China Development and Reform Commission under Grant 2018148208the Innovation and Entrepreneurship Demonstration Team of Yingcai Program of Chongqing of China under Grant CQYC201903167.
文摘A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cells)could become the anchor of linkage attacks to re-identify the users.Focusing on trajectory privacy in online health monitoring,we propose the User Trajectory Model(UTM),a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data(e.g.,number of individuals covered by each small cell),and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness(i.e.,the expectation and the variance).Eventually,exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation,confirm our theoretical deductions and present counter-intuitive insights.
