| In recent years,renewable energy generation has been developing very rapidly.One of the important parts is wind power,which is widely studied and applied.The advantages of abundant wind energy resources and more mature technology exist in wind power.The problems of high maintenance costs and serious consequences of failures due to the harsh power generation environment and complex operating conditions also exist in wind power.Therefore,it is necessary to monitor the important components and operating conditions of wind turbines in a timely manner.First,the blades of wind turbines with the longest downtime due to faults are particularly in need of more efficient defect identification methods.This study describes the common types of defects in the blades of wind turbines.Then,based on the characteristics that the defect color of the blade is darker than the blade color and the distribution is blocky or point-like,a blade defect identification algorithm for wind turbines based on the adaptive parameter region growth algorithm is proposed and the effectiveness of the algorithm is verified.Secondly,there are more than a dozen other wind turbine components that can fail to shut down for various reasons,so a system of overall evaluation is needed in addition to special diagnosis.A systematic system of operational evaluation indexes for wind turbines is constructed.A new consistency optimization equation is proposed and optimized by an ant colony algorithm for consistency of the hierarchical analysis method,achieving a reduction in deviation of the index weight values from the expert scoring values.Degrees of deterioration and affiliation are calculated based on the operational data of wind turbines and the characteristics of the operational indicators.The final operating condition evaluation values are obtained for each level and totality of wind turbines.Finally,the disadvantages of poor scalability and high maintenance costs exist in traditional applications of data acquisition and monitoring systems.System visualization based on Canvas rendering technology for browser and server wind power is presented.The structure and functional design of the system,the selection of database field names and the choice of front-end and back-end information exchange techniques are presented.Finally,the system visualization of wind power is implemented,which incorporates the wind turbine blade defect identification algorithm module and the wind turbine operation status evaluation module. |
