چکیده مقاله
This study aims at introducing a general framework for leak detection in pipelines by coupling machine learning to transient hydraulics For this purpose, the Support Vector Machine SVM as a superior pattern recognition algorithm is applied to transient based leak detection problems First, a transient simulation model based on unsteady friction modeling and Method of Characteristics MOC is developed for the pipeline at hand Then, the model is exploited to generate datasets containing the transient hydraulic responses at the measurement points Afterward, the most efficient features and optimum SVM algorithm are selected through sensitivity analysis To evaluate the performance of the proposed model, an experimental reservoir pipe valve system is constructed in the Hydraulics Lab of the Shahid Chamran University of Ahvaz The model is finally applied to the case study, and the impact of applied kernels, size of datasets, and the length of the applied response signal are investigated The results indicated that the model has high performance and could detect leaks accurately
کلیدواژهها
نویسندگان
Amir Houshang Ayati
Ph D Candidate, Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz,Ahvaz, Iran
Ali Haghighi
Professor, Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz,Ahvaz, Iran
Hamid Reza Ghafouri
Professor, Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz,Ahvaz, Iran
شیوه ارجاع
Ayati, Amir Houshang and Haghighi, Ali and Ghafouri, Hamid Reza,1400,Application of Support Vector Machines to Leak Detection of Pressurized Pipelines,The first national conference on water quality management and the third national conference on water consumption management,Tehran
ارائهشده در
مجموعه مقالات اولین همایش ملی مدیریت کیفیت آب و سومین همایش ملی مدیریت مصرف آب9 آذر 1400 · تهران