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Author

Lyu Xiongjie

Bio: Lyu Xiongjie is an academic researcher. The author has contributed to research in topics: Heating system & Thermal energy. The author has an hindex of 2, co-authored 4 publications receiving 22 citations.

Papers
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Patent
10 Aug 2016
TL;DR: In this article, a cucumber disease identification method and apparatus based on image information was presented, which is related to the fields of system engineering and information technology and improves the accuracy of identification, and avoids subjectivity and limitation due to artificial identification.
Abstract: The invention discloses a cucumber disease identification method and apparatus based on image information, and relates to the fields of system engineering and information technology. The invention acquires a leaf disease image of a cucumber to be identified; carries out image segmentation for the leaf disease image to obtain segmented leaf patches; extracts features of the leaf patches to obtain disease feature information; carries out disease identification for the disease feature information according to a preset disease feature sample, to obtain the disease of the cucumber to be identified; and therefore, improves the accuracy of identification, and avoids subjectivity and limitation due to artificial identification.

14 citations

Patent
06 Jul 2016
TL;DR: In this paper, a greenhouse vegetable environmental parameter data fusion method, a data fusion device, and data fusion system is presented. But the method does not consider the influence of the arrangement positions of the sensors on the greenhouse integrated environmental parameters.
Abstract: The invention provides a greenhouse vegetable environmental parameter data fusion method, a data fusion device, and a data fusion system. The greenhouse vegetable environmental parameter data fusion method is characterized in that at least one environmental parameter value of greenhouse vegetables on various preset positions in a greenhouse at different moments can be acquired; various environmental parameter values at the same moment can be used to form environmental parameter sequences, and various environmental parameter sequences at different moments can be acquired; the weighting fusion calculation of the environmental parameter sequences can be carried out to acquire the fusion value of various environmental parameter sequences at different moments. By adopting the greenhouse vegetable environmental parameter data fusion method, the data fusion device, and the data fusion system, the technical problems of the prior art of the inaccurate monitoring of the greenhouse integrated environmental parameters caused by the lack of consideration of the influence of the arrangement positions of the sensors on the greenhouse integrated environmental parameters can be solved.

7 citations

Patent
31 Aug 2016
TL;DR: In this paper, the utility model discloses a heating system with greenhouse building integration, this system includes: initiative heating?device, thermal heat storage water tank, auxiliary heating device, solar protection devices, hot water delivery inlet pipeline, heat abstractor and temperature sensing control device, the initiative heating device comprise fresnel lens array, lens array skeleton and absorber, the heating device that takes the initiative installs roof and greenhouse building formation an organic whole between the greenhouse buffering.
Abstract: The utility model discloses a heating system with greenhouse building integration, this system includes: initiative heating?device, thermal heat storage water tank, auxiliary heating device, solar protection devices, hot water delivery inlet pipeline, heat abstractor and temperature sensing control device, the initiative heating?device comprise fresnel lens array, lens array skeleton and absorber, the heating?device that takes the initiative installs roof and greenhouse building formation an organic whole between the greenhouse buffering, the thermal heat storage water tank adopts stainless steel inner in placing between the greenhouse buffering, and middle polyurethane spraying keeps warm, and the outside attachs various steel sheet, auxiliary heating device is arranged in the thermal heat storage water tank. The utility model provides a solar radiation heat can collected and utilize to the thermal system fully, replaces traditional coal fired boiler's heating system, and the heating process does not produce any pollution, the utility model provides a heat storage tank of thermal system can be exothermic at night, makes the higher temperature of water conservation, the utility model provides a hot system cost is cheap.

1 citations

Patent
22 Jun 2016
TL;DR: In this article, an initiative heat collecting device is installed on a roof of a greenhouse buffering room and integrated with the greenhouse building, where solar radiant heat is sufficiently collected and utilized by the heating system, a heating system of a traditional coal-fired boiler is replaced, and no pollution is generated in the heating process.
Abstract: The invention discloses a heating system integrated with a greenhouse building. The system comprises an initiative heat collecting device, a heat insulation and accumulation water tank, an auxiliary heating device, a sun shielding device, a hot water conveying pipeline, a radiating device and a temperature sensing control device. The initiative heat collecting device is composed of a Fresnel lens array, a lens array framework and an absorber. The initiative heat collecting device is installed on a roof of a greenhouse buffering room and integrated with the greenhouse building. The heat insulation and accumulation water tank is arranged in the greenhouse buffering room, a stainless steel inner container is adopted in the heat insulation and accumulation water tank, polyurethane is sprayed to the middle of the heat insulation and accumulation water tank for heat insulation, and a color plate is additionally arranged on the outer face of the heat insulation and accumulation water tank. The auxiliary heating device is located in the heat insulation and accumulation water tank. Solar radiant heat can be sufficiently collected and utilized by the heating system, a heating system of a traditional coal-fired boiler is replaced, and no pollution is generated in the heating process. The heat accumulation water tank of the heating system can release heat at night, and water can be maintained at a high temperature. The heating system is low in manufacturing cost.

Cited by
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Patent
22 Feb 2017
TL;DR: In this article, a crop disease identification method based on incremental learning is presented, where a negative correlation integrated neural network (NIL) classifier is used to identify crop pests and diseases.
Abstract: The invention provides a crop disease identification method based on incremental learning. When new data arrive, continuous learning is carried out based on an original learning result, and the capability of progressive learning is achieved, which means that new knowledge can be obtained from new samples obtained by batch and the performance is gradually improved under a condition that original knowledge is effectively kept. Firstly, a crop disease sample database is collected, and simulation incremental learning of disease images in the sample database is carried out using a negative correlation integrated neural network as main technical means, so that an initial parameter of a negative correlation learning system is determined, an integrated neural network classifier based on negative correlation learning is initialized based on the initial parameter, and the classifier is trained using a sample in an initial stage; in an incremental learning stage, when an expert adds a new sample in the sample database, the integrated neural network classifier based on negative correlation learning only is updated by only training the newly-added sample data, so that the object of incremental learning is achieved; and finally, a diagnosis result of a disease picture and control measures are fed back to a user, so that the pest and disease can be accurately identified and diagnosed, and the object of comprehensive crop control is achieved.

13 citations

Patent
14 Jul 2017
TL;DR: In this article, an instrument positioning method applicable to a substation patrol inspection robot is described, which firstly preliminary positioning is performed on an image to be detected by using an Adaboost classifier, then secondary positioning on a plurality of candidate regions acquired by positioning by using SVM classifier and a region which is judged to be an instruction in the two times of positioning is the regional location of the instrument in the image.
Abstract: The invention discloses an instrument positioning method applicable to a substation patrol inspection robot, which is characterized in that firstly preliminary positioning is performed on an image to be detected by using an Adaboost classifier, then secondary positioning is performed on a plurality of candidate regions acquired by positioning by using an SVM classifier, and a region which is judged to be an instruction in the two times of positioning is the regional location of the instrument in the image. According to the invention, regions similar to the instrument are positioned by using the Adaboost classifier, so that the detection rate of the instrument is greatly improved; deficiencies of the Adaboost classifier are made up by using the SVM classifier, color features and textural features are fused, and finally the candidate regions are accurately classified. The instrument positioning method not only improves the detection rate, but also increases the expandability of the system, and meets requirements of a substation for instrument positioning.

7 citations

Patent
06 Jun 2017
TL;DR: In this paper, a scab segmentation method in a crop disease blade image is presented. But the method is not suitable for field operation, and it cannot be applied to the mobile terminal such as a smart phone.
Abstract: The present invention provides a scab segmentation method in a crop disease blade image. The method comprises the following steps: obtaining a color image including crop disease blades from an image collection device, performing normalization processing, converting the color image to a CIEL*a*b* color space, setting the initial classification number as 2, employing the adaptive feature learning method to learn the scab in the image and the values of the initial classification color features R, G and B of the background blades, calculating the distance from each pixel point to a classification center, and performing data classification; and calculating the distance between a* mean values, and stopping the segmentation if the distance of the a* value obtains the maximum result. The method overcomes the problems that different crops and different scab segmentation results are unstable in the prior art, improves the segmentation precision and the adaptation of the scab segmentation algorithm, can be applied to the mobile terminal such as a smart phone and the like, is suitable for field operation, and widen the application range.

5 citations

Patent
08 Jan 2019
TL;DR: Wang et al. as discussed by the authors presented a rice lesion detection method and system based on deep learning, belonging to the image processing field, the method comprising: providing a photo sample set and a manual labeling sample set, and cutting the photo sample sets and the manual labeling samples set according to a proportion to form a second photo sample subset and a second manual labeling subset, and inputting thesecond photo subset and the second label sample set into the LinkNet network model, and obtaining the optimal model by training the Linknet network model based on the Pytorch deep learning framework; using
Abstract: The invention discloses a rice lesion detection method and system based on deep learning, belonging to the image processing field, the method comprising: providing a photo sample set and a manual labeling sample set, and cutting the photo sample set and the manual labeling sample set according to a proportion to form a second photo sample set and a second manual labeling sample set; inputting thesecond photo sample set and the second label sample set into the Linknet network model, and obtaining the optimal model by training the Linknet network model based on the Pytorch deep learning framework; using the optimal model to identify the rice lesion images needed to be detected at present, and calculating the proportion of rice lesion area and classifying the disease status. Through the Linknet network model of Pytorch deep learning framework, the generalization ability and field practicability of rice leaf lesion identification can be improved, and the utilization rate of information can be improved, which is conducive to the subsequent quantitative application of pesticides and reduce environmental pollution.

4 citations

Patent
14 May 2019
TL;DR: In this article, a method and a device for extracting a leaf scab coverage area is presented, and the method comprises the steps: determining a complete leaf area in an original image according to a Q component segmentation map and a C component edge detection map of the original image of a leaf, the complete cover area comprising a leaf coverage area and a leaf normal coverage area, filtering out a background area in the original images according to the complete leaf cover area, and extracting a scab cover area of the leaf according to complete leaf graph.
Abstract: The embodiment of the invention provides a method and a device for extracting a leaf scab coverage area, and the method comprises the steps: determining a complete leaf area in an original image according to a Q component segmentation map and a C component edge detection map of the original image of a leaf, the complete leaf area comprising a leaf scab coverage area and a leaf normal coverage area; filtering out a background area in the original image according to the complete leaf area in the original image to obtain a complete leaf image; and extracting a scab coverage area of the leaf according to the complete leaf graph. The invention provides a method and equipment, determining a complete leaf area in the original image through the Q component segmentation map and the C component edgedetection map of the original image. According to the method, the background color is extracted to filter out the background area in the original image, the influence of the background color on the scab coverage area at the edge position of the leaf can be completely avoided when the scab coverage area of the leaf is extracted, the extraction accuracy and robustness are improved, and a high-precision leaf scab coverage area map is provided for research on crop diseases.

2 citations