Airflow Estimation Of A Laboratory Anemometer Via Fisher Statistical Technique

Techniques for multisensor data fusion are drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation and other areas. In this paper a method for measuring airflow is presented using three different sensors, Windmill Anemometer, Thermal Anemometer, and Venturi tube with the help of Data Fusion technique. It is necessary and critical to obtain the most accurate measurements in many industrial applications, or as an example in medical centers which utilize ventilators to help patients breathe. The aim is to demonstrate that by combining data gained from different sensors using Data Fusion, the results are more accurate and reliable compared to single-sensor measurements. To gather all data gained by sensors and transferring them to computer, an interface circuit consisting a microcontroller is put in use and for sampling data we use MATLAB software. Then using Fisher method we estimate the airflow from different data obtained from the sensors. To conclude, we show that the results from data fusion is more reliable and accurate.