Inter-plant heat integration is an effective way for energy recovery in process industry. Although inter-plant heat integration can significantly reduce energy consumption, it is not widely applied in the multiple sta...Inter-plant heat integration is an effective way for energy recovery in process industry. Although inter-plant heat integration can significantly reduce energy consumption, it is not widely applied in the multiple stakeholders’ situation due to profit or cost distribution problems. Therefore, this work considers both the technique aspects of heat integration and its business aspects between stakeholders simultaneously. The new proposed methodology consists of three steps. Firstly the optimal matching of heat integration between plants is obtained through mathematical programming. Then the cost distribution is decided through game theory. Finally the cost distribution obtained previous is corrected by an ideal expert model. A case study is used to illustrate the effectiveness of the method in the end of the work.展开更多
Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green fea...Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green feature algorithm and maximum betweenclass variance method(OTSU)were used to segment maize corn,weeds,and land;the segmentation effect was significant and can meet the following shape feature extraction requirements.Finally,the identification and positioning of corn were achieved by morphological reconstruction and pixel projection histogram method.The experiment reveals that when a weeding robot travels at a speed of 1.6 km/h,the recognition accuracy can reach 94.1%.The technique used in this study is accessible for normal cases and can make a good recognition effect;the accuracy and real-time requirements of robot recognition are improved and reduced the calculation time.展开更多
基金Financial supports from Science Foundation of China University of PetroleumBeijing (No. 2462018BJC004)。
文摘Inter-plant heat integration is an effective way for energy recovery in process industry. Although inter-plant heat integration can significantly reduce energy consumption, it is not widely applied in the multiple stakeholders’ situation due to profit or cost distribution problems. Therefore, this work considers both the technique aspects of heat integration and its business aspects between stakeholders simultaneously. The new proposed methodology consists of three steps. Firstly the optimal matching of heat integration between plants is obtained through mathematical programming. Then the cost distribution is decided through game theory. Finally the cost distribution obtained previous is corrected by an ideal expert model. A case study is used to illustrate the effectiveness of the method in the end of the work.
基金the National Key Research and Development Program of China[Grant numbers:2019YFB1312303].
文摘Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green feature algorithm and maximum betweenclass variance method(OTSU)were used to segment maize corn,weeds,and land;the segmentation effect was significant and can meet the following shape feature extraction requirements.Finally,the identification and positioning of corn were achieved by morphological reconstruction and pixel projection histogram method.The experiment reveals that when a weeding robot travels at a speed of 1.6 km/h,the recognition accuracy can reach 94.1%.The technique used in this study is accessible for normal cases and can make a good recognition effect;the accuracy and real-time requirements of robot recognition are improved and reduced the calculation time.
