一种基于局部加权回归的润滑油磨粒在线分析算法

摘要

The oil debris size and density information can reflect the lubrication condition of the rotating equipments, which can help to take appropriate measures to prevent premature failure. The disturbance generated when the ferromagnetic debris passed through is converted to corresponding voltage signals based on the electromagnetic oil debris sensor and then is transformed into true RMS signal by a hardware circuit. An oil debris online identification algorithm is proposed based on a locally weighted regression scatter plot smoother( LOWESS) to noise reduction and feature extraction in order to obtain the real-time information of the size and density of the ferromagnetic particles in the temperature drift, zero drift, electromagnetic interference and other noise environments. Finally, the feasibility and effectiveness of the proposed method is proved by the contrast between the detected results of the MetalSCAN3110 sensor and our method.%掌握润滑油中磨粒的尺寸和浓度信息可以获知设备的润滑状态，从而可以采取针对性的维护措施，预防设备过早失效。本研究以自制的在线润滑油磨粒检测传感器为平台，将油液中铁磁性磨粒经过时产生的电磁扰动转换为相对应的电压信号，并设计硬件电路将此电压信号转化成真有效值信号；同时提出一种基于局部加权回归的平滑滤波算法( LOWESS)对信号进行降噪和特征提取，以在温漂、零漂、电磁干扰等噪声环境下实时获取润滑油中磨粒的尺寸和浓度信息；最后将检测结果与MetalSCAN3110磨粒传感器的结果对比，证明了该方法的可行性。