Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Flowmeter based on capillary tubes trough 3D stereolithography fabrication for test mechanical ventilation equipment

Gutarra J.D.S.; Laureano J.L.M. · Proceedings of the 2022 IEEE 29th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2022 (2022) · DOI: 10.1109/intercon55795.2022.9870053

Resumen

Mechanical ventilators and high-flow machines are medical devices with important measuring instruments for monitoring patients with respiratory failure. The most common monitoring parameters are lung proximal pressure, inspiratory flow, expiratory flow, inspiratory oxygen fraction, etc. The present work delves into the design, fabrication, and experimental measurement of a proximal flow sensor based on the theory of capillary tubes and stereolithography. The design was carried out in Inventor Professional 2020 software and then the computational study by CFD ANSYS to compare the dynamic pressure states of the geometric measurement points. The manufacturing was carried out using SLA 3D printing technology on an ANYCUBIC FHOTON MONO X.The fabricated FM SLA prototype has radially positioned latex tubing lines to achieve differential pressure measurement at two points separated by capillary tubes. These hoses are connected to a developmental embedded system based on a HONEYWELL 001PG7A5 differential pressure sensor and Arduino Uno Microcontroller. Finally, experimental tests of the Flow Meter Stereolithography (FM SLA) protype measurements were performed with flow rates from 0 to 44.5 lpm in 1 lpm increments. From the collected data we have an R2: 0.9983 in quadratic polynomial approximation with the actual measurement data.

Instituciones: Universidad Nacional de Ingeniería