Research About the Impact of Cms on the Reliability of Wind Turbines in Application Scenarios

This paper proposes a reliability assessment method for wind turbines based on CMS data. Combined with multi-scenario applications in complex operating environments, the role of CMS technology in fault diagnosis and early warning is analyzed. In terms of vibration signal processing, an improved wavelet transform algorithm and a health index quantification model were adopted, and their adaptability and accuracy under complex nonlinear conditions were verified through case studies. It is proposed a standardized data analysis framework and optimization strategies in response to the issue of non-uniform data in CMS systems of wind turbines from different brands; through practical verification of early fault warning and diagnostic functions, solutions to optimize the factors affecting the stability of wind turbines were studied and proposed. This provides technical support for wind farms to move towards intensive and intelligent management and offers a scientific basis for enterprises to improve quality and efficiency.