Research on Aero-Engine Gas Path Detection System Based on Electrostatic Induction

2014 ◽  
Vol 529 ◽  
pp. 400-404
Author(s):  
Jian Ying Liu ◽  
Peng Fei Liu
Keyword(s):  
Health Management ◽  
Detection System ◽  
Influence Factors ◽  
Charged Particles ◽  
Signal Process ◽  
Electrostatic Induction ◽  
Intelligent Decision ◽  
Aero Engine ◽  
On Line ◽  
Important Basis

A large number of charged particles exist in the aero-engine gas path, the electrostatic monitoring technology mainly monitors the electrostatic charge in the exhaust gas of aero-engine by arranging an electrostatic sensor, and predicts the performance and working state of gas path components by using signal process algorithms and intelligent decision model. Considering the characteristics of the aero-engine gas path and the requirements of the gas path parameter detection, an electrostatic induction-based electrostatic sensor is built to detect the anomalously charged particles in the gas path on line, providing an important basis for aero-engine Prognostics and Health Management (PHM). Simulation experiments are implemented to investigate the time response and frequency characteristic of the output signals of the sensor and analyze the influence factors.

Online monitoring experiments of turbo-shaft engine based on electrostatic sensor

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiachen Guo ◽  
Heng Jiang ◽  
Zhirong Zhong ◽  
Hongfu Zuo ◽  
Huan Zhang
Keyword(s):  
Online Monitoring ◽  
Health Management ◽  
Charged Particles ◽  
Content Type ◽  
Rotating Speed ◽  
Short Timescale ◽  
Frequency Domain Methods ◽  
Aero Engine ◽  
Component Faults ◽  
Practical Implications

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.

Acquisition of EELS spectra for high-resolution spectroscopy

1993 ◽  
Vol 51 ◽  
pp. 578-579
Author(s):  
Maoxu Qian ◽  
Mehmet Sarikaya ◽  
Edward A. Stern
Keyword(s):  
Energy Loss ◽  
Detection System ◽  
High Resolution Spectroscopy ◽  
High Signal ◽  
Short Report ◽  
Edge Structure ◽  
High Background ◽  
Gain Variation ◽  
Sufficient Energy ◽  
On Line

It is difficult, in general, to perform quantitative EELS to determine, for example, relative or absolute compositions of elements with relatively high atomic numbers (using, e.g., K edge energies from 500 eV to 2000 eV), to study ELNES (energy loss near edge structure) signal using the white lines to determine oxidation states, and to analyze EXELFS (extended energy loss fine structure) to study short range ordering. In all these cases, it is essential to have high signal-to-noise (S/N) ratio (low systematical error) with high overall counts, and sufficient energy resolution (∽ 1 eV), requirements which are, in general, difficult to attain. The reason is mainly due to three important inherent limitations in spectrum acquisition with EELS in the TEM. These are (i) large intrinsic background in EELS spectra, (ii) channel-to-channel gain variation (CCGV) in the parallel detection system, and (iii) difficulties in obtaining statistically high total counts (∽106) per channel (CH). Except the high background in the EELS spectrum, the last two limitations may be circumvented, and the S/N ratio may be attained by the improvement in the on-line acquisition procedures. This short report addresses such procedures.

Development of Glucose On-line Detection System for Fermentation Process

2013 ◽  
Vol 40 (12) ◽  
pp. 1945-1949
Author(s):  
Xue-Jin GAO ◽  
Guang-Sheng LIU ◽  
Li CHENG ◽  
Ling-Xiao GENG ◽  
Ji-Xing XUE ◽  
...  
Keyword(s):  
Fermentation Process ◽  
Detection System ◽  
Line Detection ◽  
On Line

A Copula-Based Sampling Method for Data-Driven Prognostics and Health Management

2013 ◽  
Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Pingfeng Wang ◽  
Chao Hu
Keyword(s):  
Sampling Method ◽  
Failure Time ◽  
Health Management ◽  
Remaining Useful Life ◽  
Training Data ◽  
Data Driven ◽  
Prognostics And Health Management ◽  
Statistical Relationship ◽  
Cooling Fans ◽  
On Line

This paper develops a Copula-based sampling method for data-driven prognostics and health management (PHM). The principal idea is to first build statistical relationship between failure time and the time realizations at specified degradation levels on the basis of off-line training data sets, then identify possible failure times for on-line testing units based on the constructed statistical model and available on-line testing data. Specifically, three technical components are proposed to implement the methodology. First of all, a generic health index system is proposed to represent the health degradation of engineering systems. Next, a Copula-based modeling is proposed to build statistical relationship between failure time and the time realizations at specified degradation levels. Finally, a sampling approach is proposed to estimate the failure time and remaining useful life (RUL) of on-line testing units. Two case studies, including a bearing system in electric cooling fans and a 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology.

Design and Implementation of the Cold-Rolled Aluminum Plate Surface On-Line Defect Detection System

2013 ◽  
Vol 712-715 ◽  
pp. 2323-2326
Author(s):  
Xing Guang Qi ◽  
Hai Lun Zhang ◽  
Xiao Ting Li
Keyword(s):  
High Speed ◽  
Surface Defects ◽  
Detection System ◽  
Aluminum Plate ◽  
Gigabit Ethernet ◽  
Accurate Detection ◽  
High Processing Speed ◽  
Rolled Aluminum ◽  
On Line ◽  
Cold Rolled

This paper presents an on-line surface defects detection system based on machine vision, which has high speed architecture and can perform high accurate detection for cold-rolled aluminum plate. The system consists of high speed camera and industrial personal computer (IPC) array which connected through Gigabit Ethernet, achieved seamless detection by redundant control. In order to acquire high processing speed, single IPC as processor receives from and deals with only one or two cameras' image. Experimental results show that the system with high accurate detection capability can satisfy the requirement of real time detection and find out the defects on the production line effectively.

scholarly journals Electrostatic Sensor Application for On-Line Monitoring of Wind Turbine Gearboxes

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3574 ◽  
Author(s):  
Huijie Mao ◽  
Hongfu Zuo ◽  
Han Wang
Keyword(s):  
Wind Turbine ◽  
Wear Debris ◽  
Bench Test ◽  
Recognition Method ◽  
Wind Turbine Gearbox ◽  
Practical Applications ◽  
Electrostatic Induction ◽  
Oil Flow ◽  
On Line ◽  
Application Potential

The oil-line electrostatic sensor (OLES) is a new online monitoring technology for wear debris based on the principle of electrostatic induction that has achieved good measurement results under laboratory conditions. However, for practical applications, the utility of the sensor is still unclear. The aim of this work was to investigate in detail the application potential of the electrostatic sensor for wind turbine gearboxes. Firstly, a wear debris recognition method based on the electrostatic sensor with two-probes is proposed. Further, with the wind turbine gearbox bench test, the performance of the electrostatic sensor and the effectiveness of the debris recognition method are comprehensively evaluated. The test demonstrates that the electrostatic sensor is capable of monitoring the debris and indicating the abnormality of the gearbox effectively using the proposed method. Moreover, the test also reveals that the background signal of the electrostatic sensor is related to the oil temperature and oil flow rate, but has no relationship to the working conditions of the gearbox. This research brings the electrostatic sensor closer to practical applications.

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