Correction of Load Cell Output using Particle Swarm Optimization
Banashree Debnath1, Indranil Sarkar2, Srabanti Chakraborty3, Rajesh Dey4, Sandip Roy5
1Banashree Debnath, Dept. of ECE, BGI, Kolkata, India.
2Indranil Sarkar, Dept. of CSS, BWU, Kolkata, India.
3Srabanti Chakraborty, Dept. of CST, EIEM, Kolkata, India.
4Rajesh Dey, Dept. of ECE, BGI, Kolkata, India.
5Dr. Sandip Roy, Dept. of CSS, BWU, Kolkata, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 4451-4453 | Volume-9 Issue-2, December, 2019. | Retrieval Number: A1330109119/2019©BEIESP | DOI: 10.35940/ijeat.A1330.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A load cell is a type of force transducers that transform force and mechanical stress into electrical signal. But the output becomes distorted due to the presence of transient response. Particle Swarm Optimization (PSO) based correction of load cell output is presented this paper. PSO is a robust stochastic optimization technique that considers a swarm of particle (data) as its search space and looks for the best solution. The current approach optimizes a load cell output based on the median value of the signal. The optimization algorithm tries to bring the output response near to the median value.
Keywords: Artificial Neural Network (ANN), Damper System, Mass Spring Damper (MSD).