Estimation of Flow Rate Through Analysis of Pipe Vibration

Abstract

In this paper, implementation of soft sensing technique for measurement of fluid flow rate is reported. The objective of the paper is to design an estimator to physically measure the flow in pipe by analysing the vibration on the walls of the pipe. Commonly used head type flow meter causes obstruction to the flow and measurement would depend on the placement of these sensors. In the proposed technique vibration sensor is bonded on the pipe of liquid flow. It is observed that vibration in the pipe varies with the control action of stem. Single axis accelerometer is used to acquire vibration signal from pipe, signal is passed from the sensor to the system for processing. Basic techniques like filtering, amplification, and Fourier transform are used to process the signal. The obtained transform is trained using neural network algorithm to estimate the fluid flow rate. Artificial neural network is designed using back propagation with artificial bee colony algorithm. Designed estimator after being incorporated in practical setup is subjected to test and the result obtained shows successful estimation of flow rate with the root mean square percentage error of 0.667.

Fault Detection of a Flow Control Valve Using Vibration Analysis and Support Vector Machine

“…An accelerometer is placed at the outlet to obtain the vibration data needed for the detection. Since it is possible to estimate the flow rate using a vibration sensor as mentioned in [28], it will also be possible to detect a fault in the flow rate.…”

“…The novelty of this process is that the methods generally used for vibration data analysis are being used to detect control valve faults. By placing the accelerometer on the wall of the pipe, the flow rate can be estimated as described in [28]. It can be inferred that the fault in the control valve will lead to a change in flow rate, which can be detected using vibration data from an accelerometer.…”

Metrological Advantages of Applying Vibration Analysis to Pipelines: A Review

“…Such stage regards basically with a filtering procedure, to remove interferences and disturbances that the signal may contain, such as noise from the electrical network, measurement devices or the booster pump, in order to reduce the effect of noise on the representation space. In the pre-processing stage implementation, different types of filters have been used, such as Butterworth and "notch comb" digital filters [2] [3], Sallen-Key architectures [8], median filters [34] and Wavelet transform based filters [1], which have demonstrated good performance for this type of signals.…”

“…This approach is based in the idea that the fundamental natural frequency of a pipe containing a flowing fluid decreases as the flow rate increases [6], and thus, some authors have used the spectrum of the signal as an input to the inference algorithm [8].…”

“…Venkata & Navada performed test with two different fluids: water and sugar solution. Their proposed model was valid for both fluid, with no need for adjusting parameters [8].…”