| dc.description.abstract | Load imbalance and uneven wind pressure distribution on wind turbine blades
can induce excessive vibrations that pose a risk to system reliability. This study aims
to analyze the effect of additional mass loads on the blades on the vibration patterns
along the X, Y, and Z axes, as well as to evaluate system reliability using an
exponential distribution model. The monitoring system was designed using an
MPU6050 sensor and an ESP32 microcontroller connected to Blynk and Google
Sheets for real-time observation. Experiments were conducted on a laboratory-scale
five-bladed wind turbine under three load conditions: no load, 5 g & 10 g, and 10 g &
15 g, with wind speeds of 5 m/s, 6 m/s, and 7 m/s. Data were recorded at a frequency
of 10 Hz for approximately 10 minutes per condition. The results indicate that the Yaxis (lateral) consistently exhibited the highest vibration amplitudes, making it the
most sensitive to mass imbalance, while reliability analysis showed that the X-axis
(longitudinal) experienced greater degradation, with the reliability function R(t)
decreasing to 0.55 at 270 minutes (5 g & 10 g) and 125 minutes (10 g & 15 g).
Meanwhile, the Z-axis (vertical) remained relatively stable, with R(t) = 0.55 exceeding
1000 minutes. The IoT-based monitoring system proved effective in detecting vibration
changes in real time and provided a quantitative basis for evaluating wind turbine
reliability, demonstrating that although the largest vibration amplitudes occurred
along the Y-axis, reliability degradation was predominantly influenced by the X-axis
response. | en_US |
