Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately ...Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.展开更多
The residue curve maps are considered as a powerful tool for the preliminary design of reactive distillation. The residue curve maps of ethyl acetate synthesis reaction were calculated based on the pseudo-homogeneous ...The residue curve maps are considered as a powerful tool for the preliminary design of reactive distillation. The residue curve maps of ethyl acetate synthesis reaction were calculated based on the pseudo-homogeneous rate-based kinetic model and the NRTL activity coefficient model. The results show that the unstable node branch emerges from the ethyl acetate/water edge, moving toward the chemical equilibrium surface with the increase of Damkoeler value （D）, and the node reaches the ternary reactive azeotrope when D-∞ eventually. Conceptual design for the ethyl acetate synthesis of reactive distillation based on the residue curve maps is presented at last.展开更多
基金This work was supported in part by the National Key R&D Program of China 2021YFE0110500in part by the National Natural Science Foundation of China under Grant 62062021in part by the Guiyang Scientific Plan Project[2023]48-11.
文摘Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.
基金Project(2008-XY-6) supported by the Development of Science and Technology Start-up Fund of Fuzhou University, ChinaProject(XRC-0826) supported by the Talents Fund of Fuzhou University, China
文摘The residue curve maps are considered as a powerful tool for the preliminary design of reactive distillation. The residue curve maps of ethyl acetate synthesis reaction were calculated based on the pseudo-homogeneous rate-based kinetic model and the NRTL activity coefficient model. The results show that the unstable node branch emerges from the ethyl acetate/water edge, moving toward the chemical equilibrium surface with the increase of Damkoeler value （D）, and the node reaches the ternary reactive azeotrope when D-∞ eventually. Conceptual design for the ethyl acetate synthesis of reactive distillation based on the residue curve maps is presented at last.
