Research On Wind Turbine Monitoring Technology Based On Doppler Radar

The amount of wind turbines has experienced an explosive growth with the rapid development of wind power industry,which increase people's attention to the health condition of wind power and also the demand for high-efficient damage monitoring technology for wind turbine blades.Several methods including manual inspection,acoustic emission technology,vibration detection technology,ultrasonic technology,infrared thermal imaging technology,audio sensors and machine vision technology have been used to monitor.However,these methods suffer shortcomings of low efficiency,poor reliability,potential safety hazards,destruction to the original structure of the blade,the need to disassemble the blade to the factory and the vulnerability to natural conditions.Therefore,non-contact,non-machine-stop,allweather and reliable method for wind turbine monitoring is of practical significance.A wind turbine monitoring technology based on Doppler radar is proposed in this paper which detect wind turbines with Doppler radar to achieve operating parameters and damage condition of the blades through analyzing the time-frequency domain information of radar echo signals of wind turbine and extracting relevant features.The main work is as follows:1?Doppler radar system used in this paper is introduced which consist of controlling module,transmitting module,receiving module and signal acquisition module.The mathematical modeling of the received signal for Doppler radars when illuminating a wind turbine is presented.Characteristics and their explanations of the echo signal in Time-Doppler diagram are analyzed.Simulation experiments show the differences between Time-Doppler diagrams when parameters like rotation rate,aspect angle,ground range from radar to turbine and radar center frequency vary.2 ? A parameter estimation algorithm based on time-frequency feature extraction is proposed to obtain information of rotation rate,standby and yaw.Real-time rotation rate is obtained by extracting the period of flashes in the spectrum,time and frequency of standby mode are obtained by extracting energy near zero frequency,same two parameters of yaw mode are obtained by extracting the maximum Doppler frequency of flashes.Simulation experiments show the accuracy of the algorithm for monitoring rotation rate,standby and yaw are 96%,97%and 99%,respectively.3 ? Fracture damage,surface damage and angle mismatch damage are modeled and simulated according to the mathematical modeling of the received signal for Doppler radars when illuminating a wind turbine.Then a blade damage detection algorithm based on multiple time-frequency feature extraction is proposed.Whether the blade is damaged or not and the type can be grasped through dividing the time-frequency signal into periods and extracting period,maximum Doppler frequency,energy and time interval of flashes.Simulation experiments show that the accuracy of the algorithm for detecting blade length and the angle between blades is more than 99% and the accuracy of judging damage types is more than 90%,which verifies the reliability of each damage detection module.4?Experiments on real wind turbines are conducted in coastal wind farms,the parameter estimation algorithm based on time-frequency feature extraction are used to monitor wind power operating parameters and the results show that the accuracy of the rotation rate monitoring module and standby monitoring module are over 94.5% and 90%,respectively.The blade damage detection algorithm based on multiple time-frequency feature extraction are applied to monitor the health condition of wind turbines and one with fracture damage and the other one with angle mismatch damage are successfully detected.The experimental results verify the correctness of the algorithm.