{"title":"考虑树木倒塌风险的架空配电系统综合损害建模和评估框架","authors":"Q. Lu, Wei Zhang","doi":"10.1080/15732479.2022.2053552","DOIUrl":null,"url":null,"abstract":"Abstract The overhead power distribution system (OPDS) is vulnerable to strong winds, such as hurricanes. Due to the challenges of including tree damage risks to the OPDS, tree failures are usually ignored in the risk assessment of the OPDS against strong winds. In the present study, an integrated damage modeling and assessment framework for the OPDS is proposed considering tree failure risks. The geographical information of trees surrounding the OPDS is extracted from satellite images using computer vision techniques, including CNN-based (convolutional neural network) image classifier and sliding window approach. The tree failure risk models are developed using tree geographical information in conjunction with tree height data, tree allometry and finite element analysis. With further integration of the conditional probability failure of poles under fallen tree impacts, the pole’s failure probability considering the combined wind and fallen trees is obtained using series system reliability analysis. The failure probability of the pole is obtained using physics-based modeling facilitated by Bayesian regularisation neural network (BRNN) algorithm. The poles and wires are connected for system reliability assessment using connectivity-based theory. When the wind direction is counterclockwise from the east and the wind speed is 57 m/s, tree-failure can introduce 68.6% differences in OPDS’ failure probabilities compared with that without consideration of fallen trees.","PeriodicalId":49468,"journal":{"name":"Structure and Infrastructure Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An integrated damage modeling and assessment framework for overhead power distribution systems considering tree-failure risks\",\"authors\":\"Q. Lu, Wei Zhang\",\"doi\":\"10.1080/15732479.2022.2053552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The overhead power distribution system (OPDS) is vulnerable to strong winds, such as hurricanes. Due to the challenges of including tree damage risks to the OPDS, tree failures are usually ignored in the risk assessment of the OPDS against strong winds. In the present study, an integrated damage modeling and assessment framework for the OPDS is proposed considering tree failure risks. The geographical information of trees surrounding the OPDS is extracted from satellite images using computer vision techniques, including CNN-based (convolutional neural network) image classifier and sliding window approach. The tree failure risk models are developed using tree geographical information in conjunction with tree height data, tree allometry and finite element analysis. With further integration of the conditional probability failure of poles under fallen tree impacts, the pole’s failure probability considering the combined wind and fallen trees is obtained using series system reliability analysis. The failure probability of the pole is obtained using physics-based modeling facilitated by Bayesian regularisation neural network (BRNN) algorithm. The poles and wires are connected for system reliability assessment using connectivity-based theory. When the wind direction is counterclockwise from the east and the wind speed is 57 m/s, tree-failure can introduce 68.6% differences in OPDS’ failure probabilities compared with that without consideration of fallen trees.\",\"PeriodicalId\":49468,\"journal\":{\"name\":\"Structure and Infrastructure Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Structure and Infrastructure Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/15732479.2022.2053552\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structure and Infrastructure Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/15732479.2022.2053552","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
An integrated damage modeling and assessment framework for overhead power distribution systems considering tree-failure risks
Abstract The overhead power distribution system (OPDS) is vulnerable to strong winds, such as hurricanes. Due to the challenges of including tree damage risks to the OPDS, tree failures are usually ignored in the risk assessment of the OPDS against strong winds. In the present study, an integrated damage modeling and assessment framework for the OPDS is proposed considering tree failure risks. The geographical information of trees surrounding the OPDS is extracted from satellite images using computer vision techniques, including CNN-based (convolutional neural network) image classifier and sliding window approach. The tree failure risk models are developed using tree geographical information in conjunction with tree height data, tree allometry and finite element analysis. With further integration of the conditional probability failure of poles under fallen tree impacts, the pole’s failure probability considering the combined wind and fallen trees is obtained using series system reliability analysis. The failure probability of the pole is obtained using physics-based modeling facilitated by Bayesian regularisation neural network (BRNN) algorithm. The poles and wires are connected for system reliability assessment using connectivity-based theory. When the wind direction is counterclockwise from the east and the wind speed is 57 m/s, tree-failure can introduce 68.6% differences in OPDS’ failure probabilities compared with that without consideration of fallen trees.
期刊介绍:
Structure and Infrastructure Engineering - Maintenance, Management, Life-Cycle Design and Performance is an international Journal dedicated to recent advances in maintenance, management and life-cycle performance of a wide range of infrastructures, such as: buildings, bridges, dams, railways, underground constructions, offshore platforms, pipelines, naval vessels, ocean structures, nuclear power plants, airplanes and other types of structures including aerospace and automotive structures.
The Journal presents research and developments on the most advanced technologies for analyzing, predicting and optimizing infrastructure performance. The main gaps to be filled are those between researchers and practitioners in maintenance, management and life-cycle performance of infrastructure systems, and those between professionals working on different types of infrastructures. To this end, the journal will provide a forum for a broad blend of scientific, technical and practical papers. The journal is endorsed by the International Association for Life-Cycle Civil Engineering ( IALCCE) and the International Association for Bridge Maintenance and Safety ( IABMAS).