Open AccessANN‐based liquid level transmitter using force resistive sensor for minimisation of hysteresis and non‐linearity error
Author(s) -
Lata Anamika,
Mandal Nirupama
Publication year - 2020
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2020.0009
Subject(s) - linearity , resistive touchscreen , transmitter , hysteresis , repeatability , materials science , acoustics , electrical engineering , electronic engineering , control theory (sociology) , computer science , engineering , physics , chemistry , chromatography , artificial intelligence , channel (broadcasting) , quantum mechanics , control (management)
The proposed liquid level transmitter using a force resistive sensor as a secondary sensor is simple, cost‐effective, and applicable for all types of liquid. The force resistive sensor is located at the bottom of a liquid measuring tank. The pressure exerted by the liquid height on the measuring tank changes the force resistive sensor's resistance. In the long term application, due to the creeping behaviour of force resistive sensor, the proposed level transmitter has low repeatability, hysteresis, and non‐linearity. In this study, the artificial neural network (ANN) has been used to eliminate the hysteresis and non‐linearity present in the proposed liquid level transmitter. The performance of the proposed technique has been experimentally verified. The hysteresis and non‐linearity error has been decreased from 7 to 0.89% of full‐scale observation (FSO) and 9 to 0.14%, respectively.