Consistency Monitoring of Wind Turbine Blade Loads Based on MEMS Optical Fiber Sensing - Yong Xue; Yang Li; Xiangye Fan; Binshan Xie; Zhiyuan Ma; Lin Lin; Mengnan Cao (EAI Endorsed Transactions on Energy Web, 2025)
INTRODUCTION: This paper presents a comprehensive structural monitoring framework for wind turbine blades based on MEMS-FBG (micro-electro-mechanical systems—fiber Bragg grating) sensor fusion technology.OBJECTIVES: The system integrates high-resolution strain and vibration sensing across multiple blade segments, combined with real-time data processing, fault detection, and SCADA-level visualization.METHODS: A multilayered load consistency model is introduced, incorporating thermal compensation, strain-to-load calibration, and a novel consistency index (η) to quantify inter-blade aerodynamic symmetry.RESULTS: Experimental validation was conducted on a 2.0 MW wind turbine over a 60-day continuous monitoring campaign. Static calibration demonstrated a load reconstruction accuracy within ±3%, while dynamic data revealed a strong correlation between load and blade vibration (R ≥ 0.86).CONCLUSION: Fault simulation through pitch angle manipulation confirmed the system’s rapid alarm response within 3 seconds for major asymmetry events. Additionally, signal drift testing showed MEMS-FBG sensors exhibited 80–95% lower drift than conventional resistance strain gauges under rotating and EMI-intensive conditions.
Keywords: MEMS-FBG Sensors; Wind Turbine Blade Monitoring; Load Consistency Index; Strain-to-Load Calibration; SCADA Integration; Signal Drift Analysis; Anomaly Detection