# Fault Diagnosis Approach of Main Drive Chain in Wind Turbine Based on Data Fusion
## 2 Fault Features Extraction of Wind Turbine Main Drive Chain Based on Data Fusion
### Process of Fault Features Extraction of the Main Drive Chain in Wind Turbine  
The supervisory control and data acquisition (SCADA) system of a wind farm collects real-time operating status data of each wind turbine in the wind farm comprehensively, with the sampling frequency of 1 s. Specifically, it comprehensively monitors the parameters and operating status of each operation control module in a wind turbine, including pitch, yaw, gearbox, generator, hydraulic pump station, nacelle, converter, power grid, safety chain, torque, main shaft, tower base, anemometer, and other modules. With the analysis and judgment for each module's operating status parameters, faults, and trend, normal operation of the turbine is maintained through the approaches of over-limit alarm and over-limit shutdown. However, the fault has already risen to a certain extent when the parameters and trends of modules of the wind turbine exceed the limit, and, therefore, how to trigger early warning becomes a core concern of wind farm owners. In recent years, many wind farm owners have equipped a high-frequency vibration signal acquisition system specifically for the main drive chain in order to improve the accuracy of fault diagnosis to the main drive chain of the wind turbine. They use acceleration sensors and other high-speed sensors to collect the high-frequency vibration signal of the main points of the main drive chain and do time-domain analysis, frequency domain analysis, as well as time-frequency domain analysis to extract more detailed fault features to locate the main drive chain faults more accurately. However, sometimes the added high-frequency vibration signal acquisition system gets noisy result data because it is susceptible to interference from different operating conditions, such as the yaw state of the unit, the rotational speed, and the icing of blades or anemometers. The added high-frequency vibration signal acquisition system is unable to deal with the operating status of the wind turbine or to remove the noise of the vibration data in a well-targeted manner. These deficiencies all make it difficult to reflect the fault state of the main drive chain accurately and comprehensively based on the fault eigenvector extracted from a single data source. That in turn reduces the accuracy of diagnosis results. Therefore, this paper proposes a method to transform two types of systems technically, the main drive chain vibration fault diagnosis system and the wind turbine SCADA system, to establish a data interface between them and use a method of fusing two kinds of data to extract the fault features of the wind turbine main drive chain. On the one hand, the wind turbine SCADA system has the ability to monitor the overall situation of the wind turbine in real time, which is used to extract low-frequency vibration signals related to drive chain faults, the rotational speed of main shaft and generator, and the operation control mode of the wind turbine. The last two types of signals, the rotational speed of main shaft and generators and the operation control mode of the wind turbine, are highly related to the vibration mode of the main drive chain and provide supplementary knowledge for the denoising of high-frequency vibration signals of the main drive chain. On the other hand, taking advantage of pertinence and depth of the main drive chain vibration fault diagnosis system for real-time monitoring of the wind turbine main drive chain, the high-frequency vibration signals of all added measurement points of the main drive chain can be extracted and use two types of signal, rotational speed of main shaft and generator of the wind turbine and wind turbine operation control mode, to classify the background noises of high-frequency vibration signals. The used sensors and method to equip them are shown in Figures 2 and 3. High-frequency vibration signals are clearly different between different speed ranges of the main shaft and generators and between the power-up and power-down operation intervals of the wind turbine.