61 / 2025-03-29 23:13:13

Research on Intelligent Monitoring and Fault Diagnosis Methods for Wind Turbines Based on Data Mining

data-driven methodology, wind power, intelligent monitoring systems

Under the impetus of China's 14th Five-Year Plan, the renewable energy sector has experienced accelerated development, with wind power—a mature and commercially viable clean energy source—facing significant challenges in operation and maintenance (O&M) amid its large-scale deployment. Wind turbines, predominantly deployed in complex climatic environments, suffer accelerated fatigue degradation of critical components due to the coupling effects of dynamic meteorological parameters and mechanical loads. This study focuses on the application of data mining and artificial intelligence (AI) technologies in establishing intelligent monitoring and fault diagnosis systems for wind turbines. A data-driven methodology is proposed to enhance fault detection accuracy and predictive maintenance capabilities. Looking ahead, big data technologies are poised to drive intelligent upgrades within the wind power industry, achieving strategic breakthroughs in cross-system collaborative optimization and autonomous decision-making, thereby empowering the sustainable development of renewable energy.