# A Wear Debris Signal Processing Method Based on Inductive Monitoring for Aero-Engine
## 6 Conclusions  
In view of the high false alarm rate in the oil debris monitoring results of the triple-coil inductive sensor in the transmission lubrication system of the aero-engine, a new debris signal processing method based on inductive monitoring is proposed. A time domain analysis is carried out first, and the signal energy is the most effective index to distinguish the debris signature from the noise signature. On this basis, signal energy values within a fixed-length sliding window are processed through the histogram. Finally, a threshold is set for the detection of the debris signature, which is based on the distribution of data within the histogram. This method is applied to the experimental data from a test run of an aero-engine, and the results show that all of the debris is detected even if some of it appears during the change in the working condition of the aero-engine. Detailed conclusions are given below.  
1. The signal energy is the most effective index to distinguish the debris signature from the noise signature in the step of time domain analysis.
2. The determination of time interval in the step of time domain analysis is significant. It is set as the ratio of the axial length of the sensitive space of the inductive sensor to the velocity of the oil flow. An excessively large time interval will reduce the difference between the debris signature and noise signature, while an excessively small time interval may split a complete characteristic signature into several parts.
3. The data distributions within the histogram of the debris signature and the noise signature differ significantly. For the debris signature, only a few data fall into the highest bin, while most of the data are concentrated into the lowest bin, and therefore, there are several blank bins in the middle. In sharp contrast, for the noise signature, the data distribution is more even.  
In summary, the proposed method shows satisfactory results in debris detection accuracy and especially the inhibition of false alarms. It is also applicable for real-time monitoring due to the similarity between the movement of the sliding window and real-time data acquisition. Moreover, it is applicable for various sensing principles, including but not limited to the inductive sensor signal, since the detection performance is only related to the signal itself.  
Conceptualization, H.J. and H.Z.; methodology, H.J. and H.Z.; software, Z.Z. and J.G.; validation, H.J., H.Z., Z.Z. and J.G.; formal analysis, H.J. and H.Z.; investigation, H.J. and H.Z.; resources, H.Z.; data curation, H.J., Z.Z. and J.G.; writing--original draft preparation, H.J. and Z.Z.; writing--review and editing, H.Z. and J.G.; visualization, H.J.; supervision, H.Z.; project administration, H.Z.; funding acquisition, H.Z. All authors have read and agreed to the published version of the manuscript.  
Figure 14: Detection results of 3\(\sigma\) method: (**a**) detection results of 3\(\sigma\) method and (**b**) detail enlargement on the detection results.  
This work was supported by National Natural Science Foundation of China (No. U1933202).  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
**Conflicts of Interest**: The authors declare no conflicts of interest.