Pipeline Monitoring System Based on Acoustic and Vibration

EasyChair Preprint no. 9229

Abstract

Modern pipeline network faces a critical problem with liquid leakage that affects both industrial production and worker safety. We have developed a unique approach that takes advantage of acoustic-induced vibration in the pipeline to address this important problem. When the condition of turbulent flow is met, data of the Acoustically Induced Vibration of the Pipeline have been extracted using the Dytran Accelerometer 3055D2 and cDAQ (NI 9174). In LabView, we extract 100 samples of data every second for a total of 120 seconds. By assessing the acoustically generated vibration and projecting the leak by positioning the accelerometer in certain places on the surface of the pipeline, we are programming the logic of machine learning software. We can forecast or ascertain whether the pipeline is leaking or not thanks to this machine learning algorithm. Therefore, the sole goal of our project is to reduce fluid leakage and subsequenceModern pipeline network faces a critical problem with liquid leakage that affects both industrial production and worker safety. We have developed a unique approach that takes advantage of acoustic-induced vibration in the pipeline to address this important problem. When the condition of turbulent flow is met, data of the Acoustically Induced Vibration of the Pipeline have been extracted using the Dytran Accelerometer 3055D2 and cDAQ (NI 9174). In LabView, we extract 100 samples of data every second for a total of 120 seconds. By assessing the acoustically generated vibration and projecting the leak by positioning the accelerometer in certain places on the surface of the pipeline, we are programming the logic of machine learning software. We can forecast or ascertain whether the pipeline is leaking or not thanks to this machine learning algorithm. Therefore, the sole goal of our project is to reduce fluid leakage and subsequence

Keyphrases: 1.ACOUSTIC-INDUCED VIBRATION, 2.LIQUID LEAKAGE, 3.Machine Learning, 4.LABVIEW

@Booklet{EasyChair:9229,
  author = {M Saravanabalaji and E Praveen and Samritha Sivakumar and S Shakthi Raagavi},
  title = {Pipeline Monitoring System Based on Acoustic and Vibration},
  howpublished = {EasyChair Preprint no. 9229},

  year = {EasyChair, 2022}}