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

Deep Learning for Pipeline Damage Detection: an Overview of the Concepts and a Survey of the State-of-the-Art

Pipelines have been extensively implemented to transfer oil as well as gas products at wide distances as they are safe, and suitable. However, numerous sorts of damages may happen to the pipeline, for instance erosion, cracks, and dent. Hence, if these faults are not properly refit will result in the pipeline demolitions having leak or segregation which leads to tremendously environment risks. Deep learning methods aid operators to recognize the earliest phases of threats to the pipeline, supplying them time and information in order to handle the problem efficiently. This paper illustrates fundamental implications of deep learning comprising convolutional neural networks. Furthermore the usages of deep learning approaches for hampering pipeline detriment through the earliest diagnosis of threats are introduced

Adaptive Fuzzy-PID Controller for Liquid Flow Control in the Heating Tank System

Liquid flow control systems are often used in some industrial processes. One of the problems is the existence of disturbance that can cause the flow response to become unstable. Thus, it is necessary to re-tuning the controller when the disturbance occurs. This study aims to design and implement an Adaptive Fuzzy-PID (AF-PID) controller for the liquid flow control in the heating tank system. We develop an industrial plant prototype of a heating tank process to test the designed controller on a laboratory scale. AF-PID controller is used to controlling the flow rate when the disturbance occurs. The nominal PID controller constants will adjust by additional PID constants when there is a disturbance based on the Mamdani type fuzzy logic rule. The hardware experimental result shows that the designed controller can maintain the stability of the liquid flow when given 50% and 100% pipe leakages with maximum undershot by 3.33% and 24% respectively

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

Leakage Detection in Pipeline Based on Second Order Extended Kalman Filter Observer

In this paper, a new technique is proposed in order to detect, locate, as well as approximate the fluid leaks in a straight pipeline (without branching) by taking into consideration the pressure and flow evaluations at the ends of pipeline on the basis of data fusion from two methods: a steady-state approximation and Second-order Extended Kalman Filter (SEKF). The SEKF is on the basis of the second-order Taylor expansion of a nonlinear system unlike to the more popular First-order Extended Kalman Filter (FEKF). The suggested technique in this paper deals with just pressure head and flow rate evaluations at the ends of pipeline that has intrinsic sensor as well as process noise. A simulation example is given for demonstrating the validity of the proposed technique. It shows that the extended Kalman particle filter algorithm on the basis of the second-order Taylor expansion is effective and performs well in decreasing systematic deviations as well as running time