| dc.description.abstract | In Wind Turbines, of course there are many potential factors or parameters that affect the performance and failure of the system. This study developed a system to measure and analyze data on Wind Turbines based on ADXL345 sensors, Anemometer Sensors, Digital Anemometers and Arduino Uno and ESP8266 microcontrollers. In this case, wind speed and vibration acceleration are parameters to determine the results of data analysis in the form of turbine efficiency, RMS data and Z-Score on the X, Y and Z axes as a basis for estimating reliability and predicting potential turbine failures based on Betz Limit Theory, ISO 10816 and IEC 61400 Standards. The study was conducted by measuring wind speed for ±1 hour when heading to the blade (v1) which was found to range from 2.7 to 4.8 m/s. with an average of around 3.53 m/s. and after passing the turbine blade (v2) which ranged from 1.52 to 2.79 m/s. with an average of around 2.07 m/s. The results obtained are Wind Power ranging from 26.39 to 148.29 Watts, Turbine Power ranging from 11.03 to 67.49 Watts, Wind Power Conversion Coefficient ranging from 0.374 to 0.592 Betz. Reliability Estimation based on Turbine Efficiency Value has an interval between 37.49 to 59.25% and Reliability Estimation with Betz Theory comparison has an interval between 63.06 to 99.831%. For prediction of potential failure, the RMS and Z-Score values obtained are classified as category A (Normal) ISO 10816 and IEC 61400 Standards in the form of percentages as follows, on the X-axis RMS: 1.82 to 4.06% with an average of 2.89%, Y-axis: 6.51 to 6.51%. 8.85% with an average of 7.59%, Z-axis: 3.66 to 6.66% with an average of 4.81%. And for the minimum Z-Score value of -1.3206 (66.03% of -2) and the maximum Z-Score 1.5514 (77.57% of 2) | en_US |
