Buried pipelines are an essential component of the urban infrastructure of modern cities.Traditional buried pipes are mainly made of metal materials.With the development of material science and technology in recent ye...Buried pipelines are an essential component of the urban infrastructure of modern cities.Traditional buried pipes are mainly made of metal materials.With the development of material science and technology in recent years,non-metallic pipes,such as plastic pipes,ceramic pipes,and concrete pipes,are increasingly taking the place of pipes made from metal in various pipeline networks such as water supply,drainage,heat,industry,oil,and gas.The location technologies for the location of the buried metal pipeline have become mature,but detection and location technologies for the non-metallic pipelines are still developing.In this paper,current trends and future perspectives of detection and location of buried non-metallic pipelines are summarized.Initially,this paper reviews and analyzes electromagnetic induction technologies,electromagnetic wave technologies,and other physics-based technologies.It then focuses on acoustic detection and location technologies,and finally introduces emerging technologies.Then the technical characteristics of each detection and location method have been compared,with their strengths and weaknesses identified.The current trends and future perspectives of each buried non-metallic pipeline detection and location technology have also been defined.Finally,some suggestions for the future development of buried non-metallic pipeline detection and location technologies are provided.展开更多
The aftershocks of the 1975 M_(S)7.3 Haicheng and 1999 M_(S)5.4 Xiuyan earthquakes have persisted for a long time.The ChinArray-III dense stations,deployed in eastern North China from 2018 to 2020,increased seismic mo...The aftershocks of the 1975 M_(S)7.3 Haicheng and 1999 M_(S)5.4 Xiuyan earthquakes have persisted for a long time.The ChinArray-III dense stations,deployed in eastern North China from 2018 to 2020,increased seismic monitoring capability in the Haicheng-Xiuyan region,which can facilitate the construction of high-precision earthquake catalogs to better clarify the fault structures and seismogenic mechanisms of the two earthquakes.In this study,we selected 15 permanent stations and 37 ChinArray-III stations within 150 km of the epicenter of the Haicheng Earthquake.Next,we used deep learning methods to pick P-and S-wave phases from continuous waveforms recorded at these stations from January 2018 to July 2020.Based on these picks,we constructed an automatic earthquake catalog of the Haicheng-Xiuyan region.Compared with the routine manual catalog by China Earthquake Networks Center(CENC),our catalog contains 9.7 times more seismic events,including 98.3%of the seismic events in the CENC catalog,and has a lower magnitude of completeness(M_(c)=1.1 vs M_(c)=1.8 for the CENC catalog).The relocated events indicate that the strike of the Haichenghe-Dayanghe fault varies considerably from northwest to southeast,indicating that the fault bends slightly around the hypocenter of the 1975 M_(S)7.3 Haicheng earthquake which may act as a channel for fluid migration.The weak seismicity in the area between Haicheng and Xiuyan indicates that the fault section may be locked.Furthermore,the 1999 M_(S)5.4 Xiuyan earthquake and its aftershock sequence occurred on the Kangjialing fault and its ENE-trending conjugate fault,and the intersection of the two faults coincides with the source areas of the 1999 M_(S)5.4 and 2000 M_(S)5.1 Xiuyan earthquakes.Therefore,the Xiuyan earthquake sequence may be controlled by the Kangjialing fault and its conjugate fault.This study shows that the automatic earthquake catalog,obtained by deep learning methods and dense seismic array,can provide valuable information for fault structures and the seismogenic mechanisms of moderate-to-strong earthquakes.展开更多
Monitoring the evolution of foreshocks can be a valuable way to analyze the nucleation process.Foreshocks accompanying moderate mainshocks have been recorded in the west of Yunnan Province,China.We obtain the earthqua...Monitoring the evolution of foreshocks can be a valuable way to analyze the nucleation process.Foreshocks accompanying moderate mainshocks have been recorded in the west of Yunnan Province,China.We obtain the earthquake catalog and source parameters of the 2016 Yunlong foreshocks,and discuss the implications for the nucleation processes of the earthquake in western Yunnan,China.By using the matched filter detection,we identify 343 foreshocks with a magnitude of -0.8-4.5,starting with a magnitude 1.0 foreshock approximately 3 months before the 2016 M_(S)5.1 Yunlong mainshock.The spatial distribution of foreshocks doesn’t show localization or directional migration towards the mainshock.Coulomb stress analysis suggests a positive stress perturbation at the mainshock nucleate area.These observations indicate a cascade-triggering mechanism of the 2016 Yunlong earthquakes.We further collect published catalogs of 2021 Yangbi and 2017 Yangbi foreshocks in the adjacent area,and analyze the temporal changes in b values.The temporal changes in b values reveal precursory drops before the mainshocks.展开更多
The increase in the number of sensitive loads in power systems has made power quality,particularly voltage sag,a prominent problem due to its effects on consumers from both the utility and customer perspectives.Thus,t...The increase in the number of sensitive loads in power systems has made power quality,particularly voltage sag,a prominent problem due to its effects on consumers from both the utility and customer perspectives.Thus,to evaluate the effects of voltage sag caused by short circuits,it is necessary to determine the areas of vulnerability(AOVs).In this paper,a new method is proposed for the AOV determination that is applicable to large-scale networks.The false position method(FPM)is proposed for the precise calculation of the critical points of the system lines.Furthermore,a new method is proposed for the voltage sag monitor(VSM)placement to detect the fault locations.A systematic placement scheme is used to provide the highest fault location detection(FLD)index at buses and lines for various short-circuit fault types.To assess the efficiency of the proposed methods for AOV determination and VSM placement,simulations are conducted in IEEE standard systems.The results demonstrate the accuracy of the proposed method for AOV determination.In addition,through VSM placement,the fault locations at buses and lines are detected.展开更多
Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model wit...Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is established.The interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be retained.On this basis,the concept of image flatness is proposed for the first time.An image flatness representation(IFAR)model is established on the basis of an autoencoder with a new structure.The optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation effect.Moreover,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are analyzed.Image flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave image.Lastly,the SLD and IFAR models are used to detect and represent all the real flatness images on the test set.The average processing time for a single image is 11.42 ms,which is suitable for industrial applications.The research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.展开更多
The spread of the worm causes great harm to the computer network. It has recently become the focus of the network security research. This paper presents a local-worm detection algorithm by analyzing the characteristic...The spread of the worm causes great harm to the computer network. It has recently become the focus of the network security research. This paper presents a local-worm detection algorithm by analyzing the characteristics of traffic generated by the TCP-based worm. Moreover, we adjust the worm location algorithm, aiming at the differences between the high-speed and the low-speed worm scanning methods. This adjustment can make the location algorithm detect and locate the worm based on different scanning rate. Finally, we verified the validity and efficiency of the proposed algorithm by simulating it under NS-2.展开更多
In this Letter,we propose an on-line inspection method based on a plenoptic camera to detect and locate flaws of optics.Specifically,due to the extended depth of field of the plenoptic camera,a series of optics can be...In this Letter,we propose an on-line inspection method based on a plenoptic camera to detect and locate flaws of optics.Specifically,due to the extended depth of field of the plenoptic camera,a series of optics can be inspected efficiently and simultaneously.Moreover,the depth estimation capability of the plenoptic camera allows for locating flaws while detecting them.Besides,the detection and location can be implemented with a single snapshot of the plenoptic camera.Consequently,this method provides us with the opportunity to reduce the cost of time and labor of inspection and remove the flaw optics,which may lead to performance degradation of optical systems.展开更多
High voltage direct current (HVDC) transmission is an economical option for transmitting a large amount of power over long distances. Initially, HVDC was developed using thyristor-based current source converters (CSC)...High voltage direct current (HVDC) transmission is an economical option for transmitting a large amount of power over long distances. Initially, HVDC was developed using thyristor-based current source converters (CSC). With the development of semiconductor devices, a voltage source converter (VSC)-based HVDC system was introduced, and has been widely applied to integrate large-scale renewables and network interconnection. However, the VSC-based HVDC system is vulnerable to DC faults and its protection becomes ever more important with the fast growth in number of installations. In this paper, detailed characteristics of DC faults in the VSC-HVDC system are presented. The DC fault current has a large peak and steady values within a few milliseconds and thus high-speed fault detection and isolation methods are required in an HVDC grid. Therefore, development of the protection scheme for a multi-terminal VSC-based HVDC system is challenging. Various methods have been developed and this paper presents a comprehensive review of the different techniques for DC fault detection, location and isolation in both CSC and VSC-based HVDC transmission systems in two-terminal and multi-terminal network configurations.展开更多
Social media,including Twitter,has become an important source for disaster response.Yet most studies focus on a very limited amount of geotagged data(approximately 1%of all tweets)while discarding a rich body of data ...Social media,including Twitter,has become an important source for disaster response.Yet most studies focus on a very limited amount of geotagged data(approximately 1%of all tweets)while discarding a rich body of data that contains location expressions in text.Location information is crucial to understanding the impact of disasters,including where damage has occurred and where the people who need help are situated.In this paper,we propose a novel two-stage machine learningand deep learning-based framework for power outage detection from Twitter.First,we apply a probabilistic classification model using bag-ofngrams features to find true power outage tweets.Second,we implement a new deep learning method-bidirectional long short-term memory networks-to extract outage locations from text.Results show a promising classification accuracy(86%)in identifying true power outage tweets,and approximately 20 times more usable tweets can be located compared with simply relying on geotagged tweets.The method of identifying location names used in this paper does not require language-or domain-specific external resources such as gazetteers or handcrafted features,so it can be extended to other situational awareness analyzes and new applications.展开更多
The connectivity of a strongly connected network may be destroyed after link damage.Since many net- works are connected by directed links,the reachability may be restored by altering the direction of one or more of th...The connectivity of a strongly connected network may be destroyed after link damage.Since many net- works are connected by directed links,the reachability may be restored by altering the direction of one or more of the links and thus reconfigoring the network.The location of the failed link must first be determined.In this paper,we examine new methods to determine the location of failed links and nodes in networks.A routing test approach is proposed and the conditions under which communication networks may be tested are discussed. Finally,an adaptive algorithm and a heuristic algorithm that can locate a single failed llnk or a single failed node are presented.展开更多
基金Supported by Downhole Intelligent Measurement and Control Science and Technology Innovation Team of Southwest Petroleum University(Grant No.2018CXTD04)National Natural Science Foundation of China(Grant Nos.61701085,51974273)+1 种基金Chengdu Municipal international science and technology cooperation project of China(Grant Nos.2020-GH02-00016-HZ)2020 National Mountain Highway Engineering Technology Research Center Open Fund Project(Grant No.GSGZJ-2020-01).
文摘Buried pipelines are an essential component of the urban infrastructure of modern cities.Traditional buried pipes are mainly made of metal materials.With the development of material science and technology in recent years,non-metallic pipes,such as plastic pipes,ceramic pipes,and concrete pipes,are increasingly taking the place of pipes made from metal in various pipeline networks such as water supply,drainage,heat,industry,oil,and gas.The location technologies for the location of the buried metal pipeline have become mature,but detection and location technologies for the non-metallic pipelines are still developing.In this paper,current trends and future perspectives of detection and location of buried non-metallic pipelines are summarized.Initially,this paper reviews and analyzes electromagnetic induction technologies,electromagnetic wave technologies,and other physics-based technologies.It then focuses on acoustic detection and location technologies,and finally introduces emerging technologies.Then the technical characteristics of each detection and location method have been compared,with their strengths and weaknesses identified.The current trends and future perspectives of each buried non-metallic pipeline detection and location technology have also been defined.Finally,some suggestions for the future development of buried non-metallic pipeline detection and location technologies are provided.
基金supported by the National Natural Science Foundation of China(No.U2239206)Selfinitiated Project of the Institute of Geophysics of the China Earthquake Administration(JY2022Z48)+1 种基金the Dedicated Fundamental Research Funds of the Institute of Geophysics of the China Earthquake Administration(No.DQJB23X16)the Science and Technology Support Project of Guizhou Province(QKHZC[2022]General 238).
文摘The aftershocks of the 1975 M_(S)7.3 Haicheng and 1999 M_(S)5.4 Xiuyan earthquakes have persisted for a long time.The ChinArray-III dense stations,deployed in eastern North China from 2018 to 2020,increased seismic monitoring capability in the Haicheng-Xiuyan region,which can facilitate the construction of high-precision earthquake catalogs to better clarify the fault structures and seismogenic mechanisms of the two earthquakes.In this study,we selected 15 permanent stations and 37 ChinArray-III stations within 150 km of the epicenter of the Haicheng Earthquake.Next,we used deep learning methods to pick P-and S-wave phases from continuous waveforms recorded at these stations from January 2018 to July 2020.Based on these picks,we constructed an automatic earthquake catalog of the Haicheng-Xiuyan region.Compared with the routine manual catalog by China Earthquake Networks Center(CENC),our catalog contains 9.7 times more seismic events,including 98.3%of the seismic events in the CENC catalog,and has a lower magnitude of completeness(M_(c)=1.1 vs M_(c)=1.8 for the CENC catalog).The relocated events indicate that the strike of the Haichenghe-Dayanghe fault varies considerably from northwest to southeast,indicating that the fault bends slightly around the hypocenter of the 1975 M_(S)7.3 Haicheng earthquake which may act as a channel for fluid migration.The weak seismicity in the area between Haicheng and Xiuyan indicates that the fault section may be locked.Furthermore,the 1999 M_(S)5.4 Xiuyan earthquake and its aftershock sequence occurred on the Kangjialing fault and its ENE-trending conjugate fault,and the intersection of the two faults coincides with the source areas of the 1999 M_(S)5.4 and 2000 M_(S)5.1 Xiuyan earthquakes.Therefore,the Xiuyan earthquake sequence may be controlled by the Kangjialing fault and its conjugate fault.This study shows that the automatic earthquake catalog,obtained by deep learning methods and dense seismic array,can provide valuable information for fault structures and the seismogenic mechanisms of moderate-to-strong earthquakes.
基金supported by the Laoshan Laboratory project(LSKJ202204100)National Natural Science Foundation of China(Nos.U2344221,92158205,42406064)+2 种基金Hong Kong Research Grant Council Grants(14306122)the Taishan Scholar Foundation of Shandong Province(tstp20230638)Shandong Province Outstanding Youth Science Fund Project Overseas(2023HWYQ-099).
文摘Monitoring the evolution of foreshocks can be a valuable way to analyze the nucleation process.Foreshocks accompanying moderate mainshocks have been recorded in the west of Yunnan Province,China.We obtain the earthquake catalog and source parameters of the 2016 Yunlong foreshocks,and discuss the implications for the nucleation processes of the earthquake in western Yunnan,China.By using the matched filter detection,we identify 343 foreshocks with a magnitude of -0.8-4.5,starting with a magnitude 1.0 foreshock approximately 3 months before the 2016 M_(S)5.1 Yunlong mainshock.The spatial distribution of foreshocks doesn’t show localization or directional migration towards the mainshock.Coulomb stress analysis suggests a positive stress perturbation at the mainshock nucleate area.These observations indicate a cascade-triggering mechanism of the 2016 Yunlong earthquakes.We further collect published catalogs of 2021 Yangbi and 2017 Yangbi foreshocks in the adjacent area,and analyze the temporal changes in b values.The temporal changes in b values reveal precursory drops before the mainshocks.
文摘The increase in the number of sensitive loads in power systems has made power quality,particularly voltage sag,a prominent problem due to its effects on consumers from both the utility and customer perspectives.Thus,to evaluate the effects of voltage sag caused by short circuits,it is necessary to determine the areas of vulnerability(AOVs).In this paper,a new method is proposed for the AOV determination that is applicable to large-scale networks.The false position method(FPM)is proposed for the precise calculation of the critical points of the system lines.Furthermore,a new method is proposed for the voltage sag monitor(VSM)placement to detect the fault locations.A systematic placement scheme is used to provide the highest fault location detection(FLD)index at buses and lines for various short-circuit fault types.To assess the efficiency of the proposed methods for AOV determination and VSM placement,simulations are conducted in IEEE standard systems.The results demonstrate the accuracy of the proposed method for AOV determination.In addition,through VSM placement,the fault locations at buses and lines are detected.
基金supported by the National Natural Science Foundation of China(No.U21A20118)the National Key Laboratory of Metal Forming Technology and Heavy Equipment,China National Heavy Machinery Research Institute Co.,Ltd.(No.S2208100.W04).
文摘Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is established.The interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be retained.On this basis,the concept of image flatness is proposed for the first time.An image flatness representation(IFAR)model is established on the basis of an autoencoder with a new structure.The optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation effect.Moreover,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are analyzed.Image flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave image.Lastly,the SLD and IFAR models are used to detect and represent all the real flatness images on the test set.The average processing time for a single image is 11.42 ms,which is suitable for industrial applications.The research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.
基金the National Natural Science Foundation of China (Grant No. 60403028)
文摘The spread of the worm causes great harm to the computer network. It has recently become the focus of the network security research. This paper presents a local-worm detection algorithm by analyzing the characteristics of traffic generated by the TCP-based worm. Moreover, we adjust the worm location algorithm, aiming at the differences between the high-speed and the low-speed worm scanning methods. This adjustment can make the location algorithm detect and locate the worm based on different scanning rate. Finally, we verified the validity and efficiency of the proposed algorithm by simulating it under NS-2.
基金supported by the Key Scientific Equipment Develop Project of China(No.ZDYZ20132)the National“863”Program of China(Nos.G158603 and G158201)
文摘In this Letter,we propose an on-line inspection method based on a plenoptic camera to detect and locate flaws of optics.Specifically,due to the extended depth of field of the plenoptic camera,a series of optics can be inspected efficiently and simultaneously.Moreover,the depth estimation capability of the plenoptic camera allows for locating flaws while detecting them.Besides,the detection and location can be implemented with a single snapshot of the plenoptic camera.Consequently,this method provides us with the opportunity to reduce the cost of time and labor of inspection and remove the flaw optics,which may lead to performance degradation of optical systems.
文摘High voltage direct current (HVDC) transmission is an economical option for transmitting a large amount of power over long distances. Initially, HVDC was developed using thyristor-based current source converters (CSC). With the development of semiconductor devices, a voltage source converter (VSC)-based HVDC system was introduced, and has been widely applied to integrate large-scale renewables and network interconnection. However, the VSC-based HVDC system is vulnerable to DC faults and its protection becomes ever more important with the fast growth in number of installations. In this paper, detailed characteristics of DC faults in the VSC-HVDC system are presented. The DC fault current has a large peak and steady values within a few milliseconds and thus high-speed fault detection and isolation methods are required in an HVDC grid. Therefore, development of the protection scheme for a multi-terminal VSC-based HVDC system is challenging. Various methods have been developed and this paper presents a comprehensive review of the different techniques for DC fault detection, location and isolation in both CSC and VSC-based HVDC transmission systems in two-terminal and multi-terminal network configurations.
基金the financial support received from Oak Ridge National Laboratory(ORNL)’s Liane Russell Distinguished Early Career Fellowship and grant no.TG0100000.
文摘Social media,including Twitter,has become an important source for disaster response.Yet most studies focus on a very limited amount of geotagged data(approximately 1%of all tweets)while discarding a rich body of data that contains location expressions in text.Location information is crucial to understanding the impact of disasters,including where damage has occurred and where the people who need help are situated.In this paper,we propose a novel two-stage machine learningand deep learning-based framework for power outage detection from Twitter.First,we apply a probabilistic classification model using bag-ofngrams features to find true power outage tweets.Second,we implement a new deep learning method-bidirectional long short-term memory networks-to extract outage locations from text.Results show a promising classification accuracy(86%)in identifying true power outage tweets,and approximately 20 times more usable tweets can be located compared with simply relying on geotagged tweets.The method of identifying location names used in this paper does not require language-or domain-specific external resources such as gazetteers or handcrafted features,so it can be extended to other situational awareness analyzes and new applications.
文摘The connectivity of a strongly connected network may be destroyed after link damage.Since many net- works are connected by directed links,the reachability may be restored by altering the direction of one or more of the links and thus reconfigoring the network.The location of the failed link must first be determined.In this paper,we examine new methods to determine the location of failed links and nodes in networks.A routing test approach is proposed and the conditions under which communication networks may be tested are discussed. Finally,an adaptive algorithm and a heuristic algorithm that can locate a single failed llnk or a single failed node are presented.
