In order to improve the efficiency of automatic warehouse control system,the experimental platform of stereoscopic warehouse with s7-1500plc is designed.The manipulator is driven by stepper motor and servo motor to re...In order to improve the efficiency of automatic warehouse control system,the experimental platform of stereoscopic warehouse with s7-1500plc is designed.The manipulator is driven by stepper motor and servo motor to realize x,y and Z three-axis space motion.The material transmission system is built by general-purpose G120 inverter.HMI KTP700 realizes control and status monitoring.The materials are identified and classified by RFID sensor and other sensors.TIAV15 software build PROFINET communication and PROFIBUS communication network.Using the GRAPH language programming can improve the visualization degree of application and solve the complex problems of program design and debugging of the warehouse control system.Through the design of hardware and software,a set of complete control system design scheme is formed,which has high practical value and provides an excellent teaching and experiment platform for the intelligent storage system.展开更多
An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） imm...An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） immobilized in a plasticized poly（vinyl chloride） （PVC） membrane. The optimum membrane of the sensor consists of 100 mg of PVC, 200 mg of bis （2-ethytbexyl） sebacate （BOS） and 3.0 mg of LiTOE. The maximum response of the optode membrane for iodine is obtained in Tris-HCl buffer solutlon （pH 8.0）. With the optimum conditions described, the proposed sensor responds linearly in the measuring range of 3.90×10^-2 to 3.90×10^-4 mol/L, and has a detection limit of 6.0×10^-8 mol/L. The response time of the sensor is less than I rain. In addition to high reproducibility and reversibility of the fluorescence signal, the sensor also exhibits good selectivity. It is not interfered by some common anions and cations. It is applied for the determination of iodine in table salt samples. The results agree with those obtained by another method.展开更多
To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and...To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.展开更多
The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing concerns.This impact has significantly led to a notable incre...The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing concerns.This impact has significantly led to a notable increase in mortality in the highly industrialized zones.Therefore,monitoring air quality and creating public awareness are important for a safer future,which led the governments globally to investmulti-billion in policymaking and solution stratification to address the problem.This study aims to design a realtime Internet of Things low-cost air quality monitoring system.The system utilizes air quality and carbon monoxide sensors for monitoring gaseous pollutants.Moreover,the system utilizes an Arduino Nano development board equipped with a WiFi module to effectively send readings to a ThingSpeak online channel platformfor instantaneous and real-time display of air quality.The ThingSpeak uses HTTP protocols to send emails in raising awareness of poor air quality.The level of concentration is monitored graphically through channels with the help of ThingSpeak to aid remote communication.Athreshold value is set.Thus,when pollutants have become unhealthy and harmful,the system trips off an alarm,and e-mail notifications are sent to the officials.The results have shown that the work was successfully implemented a design of a low-cost air quality monitoring system using Arduino and ThingSpeak,showing that an air quality system can be implemented using a low-cost technology,Arduino and ThingSpeak.展开更多
文摘In order to improve the efficiency of automatic warehouse control system,the experimental platform of stereoscopic warehouse with s7-1500plc is designed.The manipulator is driven by stepper motor and servo motor to realize x,y and Z three-axis space motion.The material transmission system is built by general-purpose G120 inverter.HMI KTP700 realizes control and status monitoring.The materials are identified and classified by RFID sensor and other sensors.TIAV15 software build PROFINET communication and PROFIBUS communication network.Using the GRAPH language programming can improve the visualization degree of application and solve the complex problems of program design and debugging of the warehouse control system.Through the design of hardware and software,a set of complete control system design scheme is formed,which has high practical value and provides an excellent teaching and experiment platform for the intelligent storage system.
文摘An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） immobilized in a plasticized poly（vinyl chloride） （PVC） membrane. The optimum membrane of the sensor consists of 100 mg of PVC, 200 mg of bis （2-ethytbexyl） sebacate （BOS） and 3.0 mg of LiTOE. The maximum response of the optode membrane for iodine is obtained in Tris-HCl buffer solutlon （pH 8.0）. With the optimum conditions described, the proposed sensor responds linearly in the measuring range of 3.90×10^-2 to 3.90×10^-4 mol/L, and has a detection limit of 6.0×10^-8 mol/L. The response time of the sensor is less than I rain. In addition to high reproducibility and reversibility of the fluorescence signal, the sensor also exhibits good selectivity. It is not interfered by some common anions and cations. It is applied for the determination of iodine in table salt samples. The results agree with those obtained by another method.
基金supported by the National Natural Science Foundation of China(No.51876114)the Shanghai Engineering Research Center of Marine Renewable Energy(Grant No.19DZ2254800).
文摘To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.
基金This work was supported by SUT Research and Development Funds and by Thailand Science Research and Innovation(TSRI).In addition,this work supported by the Taif University Researchers Supporting Project number(TURSP-2020/77),Taif University,Taif,Saudi Arabia.
文摘The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing concerns.This impact has significantly led to a notable increase in mortality in the highly industrialized zones.Therefore,monitoring air quality and creating public awareness are important for a safer future,which led the governments globally to investmulti-billion in policymaking and solution stratification to address the problem.This study aims to design a realtime Internet of Things low-cost air quality monitoring system.The system utilizes air quality and carbon monoxide sensors for monitoring gaseous pollutants.Moreover,the system utilizes an Arduino Nano development board equipped with a WiFi module to effectively send readings to a ThingSpeak online channel platformfor instantaneous and real-time display of air quality.The ThingSpeak uses HTTP protocols to send emails in raising awareness of poor air quality.The level of concentration is monitored graphically through channels with the help of ThingSpeak to aid remote communication.Athreshold value is set.Thus,when pollutants have become unhealthy and harmful,the system trips off an alarm,and e-mail notifications are sent to the officials.The results have shown that the work was successfully implemented a design of a low-cost air quality monitoring system using Arduino and ThingSpeak,showing that an air quality system can be implemented using a low-cost technology,Arduino and ThingSpeak.
