Research On Health Monitoring Of Wind Turbine Mechanical System

As human society being dependent on energy more and more, the energy problem has already become the main factors restricting economic development, and new energy technology is concerned by each area of world. Because of high safety, small environmental pollution, high utilization efficiency; the wind turbine technology is becoming the renewable energy mainstream development direction. However, due to wind turbine working complicated environment, the maintenance is difficult. Wind turbine breakdown may cause long downtime if it cannot be discover in time. Especially wind turbine mechanical fault, in recent years of data analysis, is become the main cause of breakdown rate. Therefore, establishing a wind turbine mechanical health monitoring system is important. This topic is established in the background of wind turbine industry development needs.The characteristic frequency and structure is studied in various state of large wind turbine in this paper. The main components such as Growth gear box are modeling optimization and analyzed to get the structure and vibration characteristics, such as gear with the fundamental harmonics frequency, gear meshing frequency and so on, in order to determine the wind turbine abnormal working parameters, so that, The real-time monitoring platform of wind turbine vibration detection based on DSP core can be built by these information. The signal acquisition system based on DSP processor is designed which contain amplifier circuit, analog to digital circuit, DSP and CPLD connection circuit, DSP power supply circuit clock circuit and reset circuit. The method communication between PC and DSP can be realized in the platform of Lab VIEW compiler. In the end the surveying of the wind turbine gearbox, generator spindle vibration signal proves that the method of monitor wind turbine built by this subject can detect fault feature spectrum to locate the fault type and parts accurately. The purposes of founding monitoring large wind turbine health status and fault diagnosis are reached in this thesis.