# A Wear Debris Signal Processing Method Based on Inductive Monitoring for Aero-Engine
## 1 Introduction  
Rotating machinery has become essential in the modern industry, and its health is a constant desire, which is of significance in improving mechanical system reliability, along with avoiding costly maintenance and unnecessary shutdown. Therefore, the implementation of condition monitoring has become vitally important [1; 2; 3]. Condition monitoring technologies utilized in rotating machinery have so far mainly included vibration monitoring, thermography, and oil analysis [4; 5; 6; 7]. Vibration monitoring can listen for the \"noises\" caused by the fault in the mechanical structure consisting of the rolling surface. However, the vibration sensors are usually mounted far away from the fault source, and the fault signal propagation process is easily affected. Therefore, the vibration signal is usually weak and difficult to identify. Thermography can monitor the health status by the system temperature, but due to the hysteresis and attenuation of temperature changes, thermography is often insensitive. Therefore, both vibration monitoring and thermography are insensitive to the abnormal changes at the early stage of failure. Most rotating machinery has a lubrication system for mitigating friction and wear on contacting surfaces. The debris carried by the lubricating oil is the direct product of the wear on contacting surfaces, which directly reports the wear condition of oil-wetted components [8]. Due to the sensitivity to the abnormal changes at the early stage of failure, wear debris analysis is fast becoming the most powerful oil analysis strategy for assessing a machine's condition [9; 10]. Moreover,due to the flow of lubricating oil throughout the system, lubricant condition monitoring enables monitoring of all oil-wetted elements at one certain location, which is an advantage not available in other technologies. Therefore, online oil debris monitoring for rotating machinery has always been a focus of research [8].  
In-line/On-line oil debris sensors, which monitor in the main loop and bypass, respectively, acquire signals related to the health of rotating machinery in real-time and are continuously being extensively sought [11]. Among them, the in-line full-flow inductive wear debris sensor is a development for the condition monitoring of oil-wetted machinery [12]. Inductive sensors detect wear debris through the disruption to the magnetic field caused by the passage of the wear debris, and its signal processing has always been one of the important research directions [12]. Envelope-demodulation and phase-sensitive detection are two basic methods for inductive monitoring of a signal. In addition, [PERSON] et al. proposed several signal processing methods based on integral enhanced empirical mode decomposition and correlated reconstruction, adaptive subband filtering, wavelet analysis, verified by the simulated and experimental signal [13; 14; 15]. However, the signal processing method in engineering applications for identifying the debris signatures is still threshold-based, whose false alarm is the major problem. Therefore, a signal processing method that can reduce the false alarm rate and is applicable for real-time monitoring is being extensively sought. Inductive sensors have already been widely applied to the oil debris monitoring in an aero-engine, wind turbine, etc. In recent years, the electromagnetic induction imaging of metallic objects based on the inductive sensors are well developed, mainly applied in industrial high conductive flow imaging, which is a major trend of the development of inductive sensors [16; 17; 18].