Pipeline Monitoring Architecture based on observability and controllability Analysis

Recently many techniques with different applicability have been developed for damage detection in the pipeline. The pipeline system is designed as a distributed parameter system, where the state space of the distributed parameter system has infinite dimension. This paper is dedicated to the problem of observability as well as controllability analysis in the pipeline systems. Some theorems are presented in order to test the observability and controllability of the system. Computing the rank of the controllability and observability matrix is carried out using Matlab

Modelling and Analysis of Flow Rate and Pressure Head in Pipelines

Currently, various approaches with several utilities are proposed to identify damage in the pipeline. The pipeline system is modeled in the form of a distributed parameter system, such that the state space related to the distributed parameter system contains infinite dimension. In this paper, a novel technique is proposed to analyze and model the flow in the pipeline. Important theorems are proposed for testing the observability as well as controllability of the proposed model

Control of Flow Rate in Pipeline Using PID Controller

In this paper a PID controller is utilized in order to control the flow rate of the heavy-oil in pipelines by controlling the vibration in motor-pump. A torsional actuator is placed on the motor-pump in order to control the vibration on motor and consequently controlling the flow rates in pipelines. The necessary conditions for asymptotic stability of the proposed controller is validated by implementing the Lyapunov stability theorem. The theoretical concepts are validated utilizing numerical simulations and analysis, which proves the effectiveness of the PID controller in the control of flow rates in pipelines

Blockage Detection in Pipeline Based on the Extended Kalman Filter Observer

Currently numerous approaches with various applicability have been generated in order to detect damage in pipe networks. Pipeline faults such as leaks and partial or complete blockages usually create serious problems for engineers. The model-based leak, as well as block detection methods for the pipeline systems gets more and more attention. Among these model-based methods, the state observer and state feedback based methods are usually used. While the observability, as well as controllability, are taken to be the prerequisites for utilizing these techniques. In this work, a new technique based on the extended Kalman filter observer is proposed in order to detect and locate the blockage in the pipeline. Furthermore, the analysis of observability and controllability in the pipe networks is investigated. Important theorems are given for testing the observability as well as controllability of the pipeline system

The Effect of Baffles on Heat Transfer

For a long time technicians and engineers have used geometric changes of objects for the purpose of enhancement of heat transfer. The discovery and use of nanofluids and their unique properties lead to a new revolution on the heat transfer. This paper presents the simulation of Ansis software applied to the flow tube with a constant flux, also studies the effect of baffles and the use of nano particles on heat transfer

Leakage Detection for Pipe Systems with Fuzzy Monitoring Strategy

A Pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behavior inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real-time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. To address this issue, in this paper an auto regressive with exogenous input (ARX)-Laguerre fuzzy proportional -derivative (PD) observation system is pro-posed to detect and estimate a leak in pipelines. In this work, the ARX-Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

A pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry, from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behaviour inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. In this work, the ARX–Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively