The phase-sensitive time-domain reflectometer [φ-OTDR] has been popularly used for events detection over a long period of time.In this study,the events classification methods based on convolutional neural networks [C...The phase-sensitive time-domain reflectometer [φ-OTDR] has been popularly used for events detection over a long period of time.In this study,the events classification methods based on convolutional neural networks [CNNs] with different features,i.e.,the temporal-spatial features and time-frequency features,are compared and analyzed comprehensively inφ-OTDR.The developed CNNs aim at distinguishing three typical events:wind blowing,knocking,and background noise.The classification accuracy based on temporal-spatial images is higher than that based on time-frequency images[99.49% versus 98.23%).The work here sets a meaningful reference for feature extraction and application in the pattern recognition of φ-OTDR.展开更多
In order to uniformly disperse the ceramic reinforcements synthesized in-situ in the copper matrix composites,this study used Carbon Polymer Dot(CPD)as the carbon source and Cu–1.0%Ti alloy powder as the matrix for s...In order to uniformly disperse the ceramic reinforcements synthesized in-situ in the copper matrix composites,this study used Carbon Polymer Dot(CPD)as the carbon source and Cu–1.0%Ti alloy powder as the matrix for supplying Ti source to prepare in-situ synthesized TiC/Cu composites.The results show that TiC nano-precipitates,having the similar particle sizes with the CPD,form at the grains interior and grain boundaries,and maintain a uniform distribution state.Compared with the matrix,0.3 wt%CPD/Cu composite displays the best strengthplastic compatibility,the ultimate tensile strength achieves 385 MPa accompanied with a corresponding elongation of 21%,owing to the dislocation hindrance caused by nano-carbide and excellent interface bonding between nano TiC and the Cu matrix.The density function theory calculation supports our experimental results by showing a tighter and stronger interface contact.This work presents a new approach for studying in-situ carbide precipitates.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.FRF-TP-20-067A1Z)。
文摘The phase-sensitive time-domain reflectometer [φ-OTDR] has been popularly used for events detection over a long period of time.In this study,the events classification methods based on convolutional neural networks [CNNs] with different features,i.e.,the temporal-spatial features and time-frequency features,are compared and analyzed comprehensively inφ-OTDR.The developed CNNs aim at distinguishing three typical events:wind blowing,knocking,and background noise.The classification accuracy based on temporal-spatial images is higher than that based on time-frequency images[99.49% versus 98.23%).The work here sets a meaningful reference for feature extraction and application in the pattern recognition of φ-OTDR.
基金supported by the Chinese National Science Foundation(Grant No.52174345,52064032)the Yunnan Science and Technology Projects(Grant No.202002AB080001)Science and Technology Major Project of Yunnan Province(Grant No.202202AG050004).
文摘In order to uniformly disperse the ceramic reinforcements synthesized in-situ in the copper matrix composites,this study used Carbon Polymer Dot(CPD)as the carbon source and Cu–1.0%Ti alloy powder as the matrix for supplying Ti source to prepare in-situ synthesized TiC/Cu composites.The results show that TiC nano-precipitates,having the similar particle sizes with the CPD,form at the grains interior and grain boundaries,and maintain a uniform distribution state.Compared with the matrix,0.3 wt%CPD/Cu composite displays the best strengthplastic compatibility,the ultimate tensile strength achieves 385 MPa accompanied with a corresponding elongation of 21%,owing to the dislocation hindrance caused by nano-carbide and excellent interface bonding between nano TiC and the Cu matrix.The density function theory calculation supports our experimental results by showing a tighter and stronger interface contact.This work presents a new approach for studying in-situ carbide precipitates.
