Jiachen Guo, Heng Jiang, Zhirong Zhong, Hongfu Zuo and Huan Zhang
Electrostatic monitoring technology is a useful tool for monitoring and detecting component faults and degradation, which is necessary for engine health management. This paper…
Abstract
Purpose
Electrostatic monitoring technology is a useful tool for monitoring and detecting component faults and degradation, which is necessary for engine health management. This paper aims to carry out online monitoring experiments of turbo-shaft engine to contribute to the practical application of electrostatic sensor in aero-engine.
Design/methodology/approach
Combined with the time and frequency domain methods of signal processing, the authors analyze the electrostatic signal from the short timescale and the long timescale.
Findings
The short timescale analysis verifies that electrostatic sensor is sensitive to the additional increased charged particles caused by abnormal conditions, which makes this technology to monitor typical failures in aero-engine gas path. The long scale analysis verifies the electrostatic sensor has the ability to monitor the degradation of the engine gas path performance, and water washing has a great impact on the electrostatic signal. The spectrum of the electrostatic signal contains not only the motion information of the charged particles but also the rotating speed information of the free turbine.
Practical implications
The findings in this article prove the effectiveness of electrostatic monitoring and contribute to the application of this technology to aero-engine.
Originality/value
The research in this paper would be the foundation to achieve the application of the technology in aero-engine.
Details
Keywords
Zhirong Zhong, Heng Jiang, Jiachen Guo and Hongfu Zuo
The aero-engine array electrostatic monitoring technology (AEMT) can provide more and more accurate information about the direct product of the fault, and it is a novel condition…
Abstract
Purpose
The aero-engine array electrostatic monitoring technology (AEMT) can provide more and more accurate information about the direct product of the fault, and it is a novel condition monitoring technology that is expected to solve the problem of high false alarm rate of traditional electrostatic monitoring technology. However, aliasing of the array electrostatic signals often occurs, which will greatly affect the accuracy of the information identified by using the electrostatic sensor array. The purpose of this paper is to propose special solutions to the above problems.
Design/methodology/approach
In this paper, a method for de-aliasing of array electrostatic signals based on compressive sensing principle is proposed by taking advantage of the sparsity of the distribution of multiple pulse signals that originally constitute aliased signals in the time domain.
Findings
The proposed method is verified by finite element simulation experiments. The simulation experiments show that the proposed method can recover the original pulse signal with an accuracy of 96.0%; when the number of pulse signals does not exceed 5, the proposed method can recover the pulse peak with an average absolute error of less than 5.5%; and the recovered aliased signal time-domain waveform is very similar to the original aliased signal time-domain waveform, indicating that the proposed method is accurate.
Originality/value
The proposed method is one of the key technologies of AEMT.