베이지안 S-파라미터 모델을 이용한 시간영역반사계 기반 파이프 다중누수 감지 시스템 개발

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2016. 2. 윤병동.Leaks in water distribution systems cause economic, environmental, and social problems. In order to detect leaks in pipelines, techniques have been developed based on time-domain reflectometry (TDR) combined with Bayesian inference. However, these techniques are not practical for applications involving long-distance pipelines due to the large size and significant time required to build the training sample data set required for Bayesian inference in these settings. To solve these challenges, this study proposes two approaches: (a) an S-parameter based forward model to reduce the size of sample data, and (b) an algorithm to estimate the time required to build an training sample data set. Unlike existing methods that model the voltage from both the TDR instrument and the sensing cable, the proposed S-parameter based model has only to estimate the voltage measured at only the input port of TDR instrument without considering the sensing cable. Thus, the voltage of the sensing cable is not required for modeling the TDR signal in this proposed detection system. In terms of the amount of training data required by each method, therefore, the S-parameter based model is much more efficient than existing models from a computational point of view. In addition, the algorithm proposed here to predict the time required to build the sample data allows the user to determine the feasibility of the TDR-based leak detection technique for a particular setting. To validate the proposed method, lab experiments were conducted using a pipeline, leak detectors, sensing cable, and TDR instrument. Through the experiments, the applicability of the suggested S-parameter based model in a long-distance pipeline was validated.Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Overview of existed TDR Leak Detection System 3 1.3 Thesis Outline 4 Chapter 2. Background & Literature Review 6 2.1 Principles of TDR 6 2.2 S-parameters 10 2.3 Bayesian Inference 11 Chapter 3. Forward Model using S-parameters for Generating a TDR Signal Corresponding to Leakage 12 3.1 Advantages of a Forward Model utilizing S-parameters 12 3.2 Concept of the Forward Model using S-parameters 14 3.3 Modeling the Sensing Cable 16 Chapter 4. Estimation Algorithm to Determine the Time required to Build the Trained Sample Data Set 20 Chapter 5. Case Study 22 5.1 Description of the Experimental Test Bed 22 5.2 Validation of Accuracy of the Forward Model and the Bayesian Inference 26 5.3 Estimating the Time required to Build Sample Data Set for a Long-Distance Pipeline 32 Chapter 6. Conclusion 35Maste

TDR-based Multiple Leak Detection System using an S-parameter Transmission Line Model for Long-Distance Pipelines

Leaks in water distribution systems should be detected to avoid economic, environmental, and social problems. Existing Bayesian Inference based time-domainreflectometry (TDR) methods for leak detection have a limitation for real applications due to the lengthy time in building sample data. As the pipeline distance becomes longer and multiple leaks must be considered in long distance pipelines, the computational time for building training data gets larger. This paper proposes a scattering-parameter-based forward model to relieve computational burden of the existing TDR methods. It was shown that the proposed model outperformed the existing RLGC-based forward model in terms of computational time. The proposed model that is combined with Bayesian inference and TDR signal modeling is validated with an experimental pipeline, leak detectors, transmission line, and TDR instrument for leak detection. In summary, the proposed method is promising for leak detection in long pipelines as well as multiple leaks