Aero-Engine Over Vibration Monitoring Method Based on Fuzzy Logic

Author(s):  
Li Ludan ◽  
Yi Fang ◽  
Sun Juanping
2021 ◽  
Vol 3 (1) ◽  
pp. 52-65
Author(s):  
Thomas Amanuel ◽  
Amanuel Ghirmay ◽  
Huruy Ghebremeskel ◽  
Robel Ghebrehiwet ◽  
Weldekidan Bahlibi

This research article focuses on industrial applications to demonstrate the characterization of current and vibration analysis to diagnose the induction motor drive problems. Generally, the induction motor faults are detected by monitoring the current and proposed fine-tuned vibration frequency method. The stator short circuit fault, broken rotor bar fault, air gap eccentricity, and bearing fault are the common faults that occur in an induction motor. The detection process of the proposed method is based on sidebands around the supply frequency in the stator current signal and vibration. Moreover, it is very challenging to diagnose the problem that occur due to the complex electromagnetic and mechanical characteristics of an induction motor with vibration measures. The design of an accurate model to measure vibration and stator current is analyzed in this research article. The proposed method is showing how efficiently the root cause of the problem can be diagnosed by using the combination of current and vibration monitoring method. The proposed model is developed for induction motor and its circuit environment in MATLAB is verified to perform an accurate detection and diagnosis of motor fault parameters. All stator faults are turned to turn fault; further, the rotor-broken bar and eccentricity are structured in each test. The output response (torque and stator current) is simulated by using a modified winding procedure (MWP) approach by tuning the winding geometrical parameter. The proposed model in MATLAB Simulink environment is highly symmetrical, which can easily detect the signal component in fault frequencies that occur due to a slight variation and improper motor installation. Finally, this research article compares the other existing methods with proposed method.


2012 ◽  
Vol 229-231 ◽  
pp. 1459-1463 ◽  
Author(s):  
Ahmed M. Abdelrhman ◽  
M. Salman Leong ◽  
Somia Alfatih M. Saeed ◽  
Salah M. Ali Al-Obiadi Al Obiadi

Vibration monitoring is widely recognized as an effective tool for the detection and diagnosis of incipient failures of gas turbines. This paper presents a review of vibration based methods for turbine blade faults. Methods typically involved analysis of blade passing frequencies, and extraction of dynamic signals from the measured vibration response. This includes frequency analysis, wavelet analysis, neural networks and fuzzy logic and model based analysis. The literature reviewed showed that vibration could detect most types of blade faults on the basis that dynamic signals are correctly extracted using the most appropriate signal processing method.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yi Yu ◽  
Xing Shen ◽  
Yun Huang

In wind tunnel tests, the cantilever sting is usually used to support aircraft models because of its simple structure and low aerodynamic interference. However, in some special conditions, big-amplitude and low-frequency vibration would occur easily on the model not only in the pitch direction but also in the yaw direction, resulting in inaccurate data and even damage of the supporting structure. In this paper, aiming at suppressing the vibration in pitch and yaw plane, a multidimensional system identification and active vibration control system on the basis of piezoelectric actuators is established. A vibration monitoring method based on the strain-displacement transformation (SDT) matrix is proposed, which can transform strain signals into vibration displacements. The system identification based on chirp-Z transform (CZT) is applied to improve the adaptability and precision of the building process for the system model. After that, the hardware platform as well as the software control system based on the classical proportional-derivative (PD) algorithm is built. A series of experiments are carried out, and the results show the exactness of the vibration monitoring method. The system identification process is completed, and the controller is designed. Vibration control experiments verify the effectiveness of the controller, and the results indicate that vibrations in pitch and yaw directions are attenuated apparently. The spectrum power is reduced over 14.8 dB/Hz, which prove that the multidimensional identification and active vibration control system has the capability to decline vibration from different directions.


2013 ◽  
Author(s):  
Fei Wu ◽  
Lei Liang ◽  
Junya Xing ◽  
Lin Wang ◽  
Lang Jia

2020 ◽  
Vol 148 (4) ◽  
pp. 2793-2793
Author(s):  
Mingxin Hui ◽  
Jing Wang ◽  
Bin Liu ◽  
Xun Wang ◽  
Xiaobin Cheng ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3235 ◽  
Author(s):  
Zhongsheng Chen ◽  
Jianhua Liu ◽  
Chi Zhan ◽  
Jing He ◽  
Weimin Wang

On-line vibration monitoring is significant for high-speed rotating blades, and blade tip-timing (BTT) is generally regarded as a promising solution. BTT methods must assume that rotating speeds are constant. This assumption is impractical, and blade damages are always formed and accumulated during variable operational conditions. Thus, how to carry out BTT vibration monitoring under variable rotation speed (VRS) is a big challenge. Angular sampling-based order analyses have been widely used for vibration signals in rotating machinery with variable speeds. However, BTT vibration signals are well under-sampled, and Shannon’s sampling theorem is not satisfied so that existing order analysis methods will not work well. To overcome this problem, a reconstructed order analysis-based BTT vibration monitoring method is proposed in this paper. First, the effects of VRS on BTT vibration monitoring are analyzed, and the basic structure of angular sampling-based BTT vibration monitoring under VRS is presented. Then a band-pass sampling-based engine order (EO) reconstruction algorithm is proposed for uniform BTT sensor configuration so that few BTT sensors can be used to extract high EOs. In addition, a periodically non-uniform sampling-based EO reconstruction algorithm is proposed for non-uniform BTT sensor configuration. Next, numerical simulations are done to validate the two reconstruction algorithms. In the end, an experimental set-up is built. Both uniform and non-uniform BTT vibration signals are collected, and reconstructed order analysis are carried out. Simulation and experimental results testify that the proposed algorithms can accurately capture characteristic high EOs of synchronous and asynchronous vibrations under VRS by using few BTT sensors. The significance of this paper is to overcome the limitation of conventional BTT methods of dealing with variable blade rotating speeds.


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