QUANTIFICAÇÃO DE INCERTEZA E CALIBRAÇÃO DE CÉLULAS DE CARGA COM SISTEMA DE AQUISIÇÃO POR ARDUINO

: In laboratories and industries it is common to find processes that perform mass or load measurement to verify the standardization of production or to monitor experiments. However, when employing such methods as data acquisition systems for continuous monitoring, the cost becomes high, especially when high accuracy and reliability are required. In order to overcome this difficulty, load cells can be used, which are low-cost sensors that work by converting the deformation of a bar, measured by strain gages, into tension that can be read and interpreted by an Arduino™ system. For this system to be used reliably, it is necessary to evaluate the measurement uncertainties through controlled tests, making the system calibration based on instruments certified by INMETRO and developing models that correct the systematic errors. The equations for calculating uncertainty in mass measurements with a load cell and an Arduino™ based acquisition system were entirely developed based on the GUM method, and the procedures described serve as a reference for determining uncertainties for similar acquisition systems. This methodology is applicable in various branches of engineering such as in the standardization of manufacturing processes and construction of more complex equipment that relies on static load measurement, such as tensile, compression, and bending test machines, or in tribometers. When using a load cell with a maximum load of 5 kg connected to an HX711 module and Arduino Uno, it was found that the stability of the measurement system was the main limitation, because although the system has a resolution of 0.01 g, there were standard deviations close to 0.5 g and an absolute variation of the scale indication of up to 3 g when the sample was kept in the tray for several minutes. However, these errors are in accordance with the manufacturer's specified maximum limits of 0.1 % of the maximum rated load. The main advantage of the system was the cost benefit, since the system has a total cost of approximately R$50. Thus, the strategy used configures an interesting alternative for measurements and recording of load and mass data in laboratory or industrial devices whose tolerance requirements are more sparse. In addition, the uncertainty measurement was transformed into a computational routine, which allows easy estimation of the measurement precision and reliability, in accordance with the metrological recommendations of the International Committee on Weights and Measures.