Fault prediction method based on linear weighted summation

Article type: Research Article

Authors: Wang, Xinjun^{a; *} | Ke, Zhiliang^b

Affiliations: [a] Aviation Maintenance NCO Academy, Air Force Engineering University, Xinyang, Henan, China | [b] Unit No. 95903 of PLA, Wuhan, Hubei, China

Correspondence: [*] Corresponding author: Xinjun Wang, Aviation Maintenance NCO Academy, Air Force Engineering University, Xinyang 464000, Henan, China. Tel.: +86 18603766996; E-mail: [email protected].

Abstract: A method to calculate the threshold of the wear particle concentration in lubricating oil was proposed, and it can also be used to predict the debris concentration in oil system. The concentration of the selected 6 elements was used as the monitoring object, and a linear weighted summation process was used to enhance numerical stability of the object value, the monitoring threshold was calculated using the Student distribution model. The computational process needs only the latest 7 ∼ 10 samples, so it is easy to update the monitoring threshold. The method was tested by some samples from aircraft engines and helicopter gear reducers. The test results show that the accuracy of the proposed prediction model is higher than traditional linear model. The proposed monitoring threshold algorithm can forecast wear out failure in advance.

Keywords: Wear particle concentration, prediction, threshold, dynamic adjustment

DOI: 10.3233/JCM-204319

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 20, no. 4, pp. 1211-1220, 2020