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首页> 外文会议>Sensors and systems for reliability, safety and affordability >APPLICATION OF ADAPTIVE FILTERING IN BEARING FAULT DETECTION IN WIND TURBINE GEAR TRANSMISSION SYSTEM
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APPLICATION OF ADAPTIVE FILTERING IN BEARING FAULT DETECTION IN WIND TURBINE GEAR TRANSMISSION SYSTEM

机译：自适应滤波在风轮机传动系统轴承故障检测中的应用

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摘要

Wind turbines are developing and deploying fast, as wind power is becoming the world's fastest growing renewable energy source. In the future, reducing the operating cost of wind turbines is one of the critical issues with the growth of wind power. Maintenance of the wind turbine systems is high. Condition monitoring of transmission system of the wind turbines greatly reduce the maintenance cost, avoid catastrophic failure, and improve the reliability of the whole system. Bearing faults are one of the most common faults in wind turbines and bearings generate relatively weak signals which are usually buried in the background noise and vibration generated from other components. Also wind turbine transmission systems work under dynamic operating conditions. Thus developing advanced signal processing methods to effectively extract the bearing fault information is very important. In this paper, an adaptive filtering technique will be applied for bearing fault detection in wind turbine gear transmission systems. The periodic components are removed from the original vibration signal to enhance the bearing fault signal-to-noise ratio. Statistical features of the processed signal are extracted to quantify the bearing states. Simple linear classifier is trained to classify the healthy gearbox from the gearbox with bearing damage. Real wind turbine vibration signals were used to demonstrate the effectiveness of the presented method.
机译：随着风力发电成为世界上增长最快的可再生能源，风力涡轮机正在快速发展和部署。未来，随着风力发电的增长，降低风机的运行成本是关键问题之一。风力涡轮机系统的维护费用很高。风机传动系统的状态监测大大降低了维护成本，避免了灾难性故障，提高了整个系统的可靠性。轴承故障是风力涡轮机中最常见的故障之一，轴承会产生相对较弱的信号，这些信号通常被掩盖在背景噪声和其他组件产生的振动中。风力涡轮机传动系统也在动态运行条件下工作。因此，开发先进的信号处理方法以有效地提取轴承故障信息非常重要。在本文中，自适应滤波技术将应用于风力涡轮机齿轮传动系统中的轴承故障检测。从原始振动信号中去除了周期性分量，以提高轴承故障信噪比。提取处理信号的统计特征以量化轴承状态。简单的线性分类器经过训练，可以从带有轴承损坏的齿轮箱中对健康的齿轮箱进行分类。真实的风力发电机振动信号被用来证明所提出方法的有效性。

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