Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-sol...Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-solid TENG(O-TENG).Here,oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties.The designed O-TENG can generate an excellent electricity(with a charge density of 9.1μC m^(−2) and a power density of 1.23 mW m^(−2)),which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide.It also has a significant durability(30,000 cycles)and can power a digital thermometer for self-powered sensor applications.Further,a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils.The O-TENG can detect particle contaminants at least down to 0.01 wt%and water contaminants down to 100 ppm,which are much better than previous online monitoring methods(particle>0.1 wt%;water>1000 ppm).More interesting,the developed O-TENG can also distinguish water from other contaminants,which means the developed O-TENG has a highly water-selective performance.This work provides an ideal strategy for enhancing the output and durability of TENGs for oil-solid contact and opens new intelligent pathways for oil-solid energy harvesting and oil condition monitoring.展开更多
Fusarium head blight is one of the most important diseases affecting wheat yield and quality.It is of great significance to carry out intelligent monitoring of wheat Fusarium head blight for high yield,high quality an...Fusarium head blight is one of the most important diseases affecting wheat yield and quality.It is of great significance to carry out intelligent monitoring of wheat Fusarium head blight for high yield,high quality and sustainable development of wheat.On the basis of identifying the harms of wheat Fusarium head blight,this paper analyzed the monitoring technology of wheat Fusarium head blight based on satellite remote sensing,hyperspectral,near-infrared,Internet of things and photoelectric system,to provide a reference for the intelligent monitoring of wheat Fusarium head blight.展开更多
To overcome the limitations of traditional dairy cow's rumination detection methods,a video-based analysis on the intelligent monitoring method of cow ruminant behavior was proposed in this study.The Mean Shift al...To overcome the limitations of traditional dairy cow's rumination detection methods,a video-based analysis on the intelligent monitoring method of cow ruminant behavior was proposed in this study.The Mean Shift algorithm was used to track the jaw motion of dairy cows accurately.The centroid trajectory curve of the cow mouth motion was subsequently extracted from the video.In this way,the monitoring of the ruminant behavior of dairy cows was realized.To verify the accuracy of the method,six videos,a total of 99'00",24000 frames were selected.The test results demonstrated that the success rate of this method was 92.03%,despite the interference of behaviors,such as raising or turning of the cow’s head.The results demonstrate that this method,which monitors the ruminant behavior of dairy cows,is effective and feasible.展开更多
The development and application of internet plus modern tea industry technology is more and more extensive.As an important part of the development process of tea industry,intelligent tea garden plays an important role...The development and application of internet plus modern tea industry technology is more and more extensive.As an important part of the development process of tea industry,intelligent tea garden plays an important role in the development of the whole industry.At present,intelligent tea garden technology is widely used in many fields such as intelligent monitoring,water and fertilizer integration,green prevention and control,quality and safety traceability.In this paper,the application of intelligent tea garden technology in tea gardens was reviewed.On this basis,the development trend of new information technology and tea industry was prospected,in order to provide some reference and thinking for the innovative research of new technology in tea garden in the future.展开更多
[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelli...[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelligent insect sexual attraction monitoring system,manual survey and traditional pest monitoring tool were compared and analyzed,and the application effect of guiding field pest control was investigated.[Results]The statistical data of intelligent insect sexual attraction monitoring system were highly consistent with that of manual survey,and were consistent with that of traditional pest monitoring tool,which had good effect in guiding field control.[Conclusions]The monitoring data of intelligent insect sexual attraction monitoring system are accurate,efficient,real-time and practical.It can solve the problem of high monitoring intensity for the monitoring personnel and conform to the development direction of modern agriculture.展开更多
The effective monitoring of tool wear status in the milling process of a five-axis machining center is important for improving product quality and efficiency,so this paper proposes a CNN convolutional neural network m...The effective monitoring of tool wear status in the milling process of a five-axis machining center is important for improving product quality and efficiency,so this paper proposes a CNN convolutional neural network model based on the optimization of PSO algorithm to monitor the tool wear status.Firstly,the cutting vibration signals and spindle current signals during the milling process of the five-axis machining center are collected using sensor technology,and the features related to the tool wear status are extracted in the time domain,frequency domain and time-frequency domain to form a feature sample matrix;secondly,the tool wear values corresponding to the above features are measured using an electron microscope and classified into three types:slight wear,normal wear and sharp wear to construct a target Finally,the tool wear sample data set is constructed by using multi-source information fusion technology and input to PSO-CNN model to complete the prediction of tool wear status.The results show that the proposed method can effectively predict the tool wear state with an accuracy of 98.27%;and compared with BP model,CNN model and SVM model,the accuracy indexes are improved by 9.48%,3.44%and 1.72%respectively,which indicates that the PSO-CNN model proposed in this paper has obvious advantages in the field of tool wear state identification.展开更多
基金want to thank Swedish Kempe Scholarship Project(No.JCK-1903.1)the Swedish Research Council for Environment,Agricultural Sciences and Spatial Planning(Formas,No.2019-00904)+1 种基金the Swedish Research Council(No.2019-04941)and the National Natural Science Foundation of China(Grant No.51905027).
文摘Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-solid TENG(O-TENG).Here,oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties.The designed O-TENG can generate an excellent electricity(with a charge density of 9.1μC m^(−2) and a power density of 1.23 mW m^(−2)),which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide.It also has a significant durability(30,000 cycles)and can power a digital thermometer for self-powered sensor applications.Further,a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils.The O-TENG can detect particle contaminants at least down to 0.01 wt%and water contaminants down to 100 ppm,which are much better than previous online monitoring methods(particle>0.1 wt%;water>1000 ppm).More interesting,the developed O-TENG can also distinguish water from other contaminants,which means the developed O-TENG has a highly water-selective performance.This work provides an ideal strategy for enhancing the output and durability of TENGs for oil-solid contact and opens new intelligent pathways for oil-solid energy harvesting and oil condition monitoring.
文摘Fusarium head blight is one of the most important diseases affecting wheat yield and quality.It is of great significance to carry out intelligent monitoring of wheat Fusarium head blight for high yield,high quality and sustainable development of wheat.On the basis of identifying the harms of wheat Fusarium head blight,this paper analyzed the monitoring technology of wheat Fusarium head blight based on satellite remote sensing,hyperspectral,near-infrared,Internet of things and photoelectric system,to provide a reference for the intelligent monitoring of wheat Fusarium head blight.
基金supported by the National Key Technology R&D Program of China(No.2017YFD0701603)the Natural Science Foundation of China(No.60975007).
文摘To overcome the limitations of traditional dairy cow's rumination detection methods,a video-based analysis on the intelligent monitoring method of cow ruminant behavior was proposed in this study.The Mean Shift algorithm was used to track the jaw motion of dairy cows accurately.The centroid trajectory curve of the cow mouth motion was subsequently extracted from the video.In this way,the monitoring of the ruminant behavior of dairy cows was realized.To verify the accuracy of the method,six videos,a total of 99'00",24000 frames were selected.The test results demonstrated that the success rate of this method was 92.03%,despite the interference of behaviors,such as raising or turning of the cow’s head.The results demonstrate that this method,which monitors the ruminant behavior of dairy cows,is effective and feasible.
基金Supported by Yibin Science and Technology Project(2021NY001).
文摘The development and application of internet plus modern tea industry technology is more and more extensive.As an important part of the development process of tea industry,intelligent tea garden plays an important role in the development of the whole industry.At present,intelligent tea garden technology is widely used in many fields such as intelligent monitoring,water and fertilizer integration,green prevention and control,quality and safety traceability.In this paper,the application of intelligent tea garden technology in tea gardens was reviewed.On this basis,the development trend of new information technology and tea industry was prospected,in order to provide some reference and thinking for the innovative research of new technology in tea garden in the future.
文摘[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelligent insect sexual attraction monitoring system,manual survey and traditional pest monitoring tool were compared and analyzed,and the application effect of guiding field pest control was investigated.[Results]The statistical data of intelligent insect sexual attraction monitoring system were highly consistent with that of manual survey,and were consistent with that of traditional pest monitoring tool,which had good effect in guiding field control.[Conclusions]The monitoring data of intelligent insect sexual attraction monitoring system are accurate,efficient,real-time and practical.It can solve the problem of high monitoring intensity for the monitoring personnel and conform to the development direction of modern agriculture.
基金financed with the means of Basic Scientific Research Youth Program of Education Department of Liaoning Province,No.LJKQZ2021185Yingkou Enterprise and Doctor Innovation Program (QB-2021-05).
文摘The effective monitoring of tool wear status in the milling process of a five-axis machining center is important for improving product quality and efficiency,so this paper proposes a CNN convolutional neural network model based on the optimization of PSO algorithm to monitor the tool wear status.Firstly,the cutting vibration signals and spindle current signals during the milling process of the five-axis machining center are collected using sensor technology,and the features related to the tool wear status are extracted in the time domain,frequency domain and time-frequency domain to form a feature sample matrix;secondly,the tool wear values corresponding to the above features are measured using an electron microscope and classified into three types:slight wear,normal wear and sharp wear to construct a target Finally,the tool wear sample data set is constructed by using multi-source information fusion technology and input to PSO-CNN model to complete the prediction of tool wear status.The results show that the proposed method can effectively predict the tool wear state with an accuracy of 98.27%;and compared with BP model,CNN model and SVM model,the accuracy indexes are improved by 9.48%,3.44%and 1.72%respectively,which indicates that the PSO-CNN model proposed in this paper has obvious advantages in the field of tool wear state identification.
