Double Gaussian potential stochastic resonance method and its application in centrifugal fan blade crack detection

2021 ◽  
Author(s):  
Tianchi Ma ◽  
Feiyu Xu ◽  
Jianzhong Hu ◽  
Di Song ◽  
Susheng Cao
Keyword(s):  
Stochastic Resonance ◽  
Crack Detection ◽  
Resonance Method ◽  
Centrifugal Fan ◽  
Gaussian Potential ◽  
Fan Blade ◽  
Blade Crack

scholarly journals Blade Crack Detection of Centrifugal Fan Using Adaptive Stochastic Resonance

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Bingbing Hu ◽  
Bing Li
Keyword(s):  
Stochastic Resonance ◽  
Crack Detection ◽  
Current Method ◽  
Ensemble Empirical Mode Decomposition ◽  
Centrifugal Fan ◽  
Blade Vibration ◽  
Transform Method ◽  
Mode Decomposition ◽  
Centrifugal Fans ◽  
Blade Crack

Centrifugal fans are widely used in various industries as a kind of turbo machinery. Among the components of the centrifugal fan, the impeller is a key part because it is used to transform kinetic energy into pressure energy. Crack in impeller’s blades is one of the serious hidden dangers. It is important to detect the cracks in the blades as early as possible. Based on blade vibration signals, this research applies an adaptive stochastic resonance (ASR) method to diagnose crack fault in centrifugal fan. The ASR method, which can utilize the optimization ability of the grid search method and adaptively realize the optimal stochastic resonance system matching input signals, may weaken the noise and highlight weak characteristic and thus can diagnose the fault accurately. A centrifugal fan test rig is established and experiments with three cases of blades are conducted. In comparison with the ensemble empirical mode decomposition (EEMD) analysis and the traditional Fourier transform method, the experiment verified the effectiveness of the current method in blade crack detection.

Blade Incipient Crack Determination for Centrifugal Compressor Based on CWT-Stochastic Resonance Method

2017 ◽  
Author(s):  
Hongkun Li ◽  
Changbo He ◽  
Qiang Zhou ◽  
Fuan Lu
Keyword(s):  
Feature Extraction ◽  
Stochastic Resonance ◽  
Centrifugal Compressor ◽  
Pressure Pulsation ◽  
Resonance Method ◽  
Aerodynamic Load ◽  
Load Effect ◽  
Feature Extraction Method ◽  
Blade Crack ◽  
Incipient Crack

Centrifugal compressor is a piece of key equipment for factories. Among the components of centrifugal compressor, impeller is a pivotal part as it is used to transform kinetic energy to pressure energy. But it usually leads to blade crack or failure as irregular aerodynamic load effect on the blade. Therefore, early crack feature extraction and pattern recognition is important to prevent it from failure. Although time series analysis for monitored signal can be used on feature extraction, incipient weak feature extraction method should be investigated. In this research, pressure pulsation sensors arranged in close vicinity to crack area are used to monitor the blade crack and feature extraction. As there are different kinds of flow interference, the pressure pulsation signal for centrifugal compressor is full of nonlinear characteristics. Therefore, how to obtain the weak information from monitored signal is investigated. Although FFT and envelope analysis have been widely used for rotating equipment, they are not suitable for the determination of incipient crack of a blade as the signal modulation and noise interference. In this research, stochastic resonance is used for the pressure pulsation signal. The results show that it is an effective tool to blade incipient crack classification on centrifugal compressor.

Blade Crack Detection using Blade Tip Timing

2021 ◽  
pp. 1-1
Author(s):  
Shuming Wu ◽  
Zengkun Wang ◽  
Haoqi Li ◽  
Zhibo Yang ◽  
Shaohua Tian ◽  
...  
Keyword(s):  
Crack Detection ◽  
Blade Tip ◽  
Blade Crack

A novel underdamped continuous unsaturation bistable stochastic resonance method and its application

2021 ◽  
Vol 151 ◽  
pp. 111228
Author(s):  
Mengdi Li ◽  
Peiming Shi ◽  
Wenyue Zhang ◽  
Dongying Han
Keyword(s):  
Stochastic Resonance ◽  
Resonance Method

Adaptive Stochastic Resonance Method for Early Fault Detection of Rotating Machinery Based on Alpha Stable Distribution

2014 ◽  
Vol 618 ◽  
pp. 458-462
Author(s):  
Gang Yu ◽  
Ye Chen
Keyword(s):  
Fault Detection ◽  
Stochastic Resonance ◽  
Stable Distribution ◽  
Signal To Noise Ratio ◽  
Resonance Method ◽  
Rotating Machinery ◽  
Sliding Windows ◽  
Alpha Stable Distribution ◽  
Early Fault Detection ◽  
The Impact

This paper proposes an adaptive stochastic resonance (SR) method based on alpha stable distribution for early fault detection of rotating machinery. By analyzing the SR characteristic of the impact signal based on sliding windows, SR can improve the signal to noise ratio and is suitable for early fault detection of rotating machinery. Alpha stable distribution is an effective tool for characterizing impact signals, therefore parameter alpha can be used as the evaluating parameter of SR. Through simulation study, the effectiveness of the proposed method has been verified.

scholarly journals A New Second-Order Tristable Stochastic Resonance Method for Fault Diagnosis

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 965 ◽  
Author(s):  
Lu Lu ◽  
Yu Yuan ◽  
Heng Wang ◽  
Xing Zhao ◽  
Jianjie Zheng
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
Fitness Function ◽  
Resonance Method ◽  
Poor Performance ◽  
Rolling Bearing ◽  
Second Order ◽  
Weak Signals ◽  
Rolling Bearings ◽  
Sr Method

Vibration signals are used to diagnosis faults of the rolling bearing which is symmetric structure. Stochastic resonance (SR) has been widely applied in weak signal feature extraction in recent years. It can utilize noise and enhance weak signals. However, the traditional SR method has poor performance, and it is difficult to determine parameters of SR. Therefore, a new second-order tristable SR method (STSR) based on a new potential combining the classical bistable potential with Woods-Saxon potential is proposed in this paper. Firstly, the envelope signal of rolling bearings is the input signal of STSR. Then, the output of signal-to-noise ratio (SNR) is used as the fitness function of the Seeker Optimization Algorithm (SOA) in order to optimize the parameters of SR. Finally, the optimal parameters are used to set the STSR system in order to enhance and extract weak signals of rolling bearings. Simulated and experimental signals are used to demonstrate the effectiveness of STSR. The diagnosis results show that the proposed STSR method can obtain higher output SNR and better filtering performance than the traditional SR methods. It provides a new idea for fault diagnosis of rotating machinery.

A Novel Adaptive Stochastic Resonance Method Based on Tristable System and its Applications

2020 ◽  
pp. 2150004
Author(s):  
Gang Zhang ◽  
Chuan Jiang ◽  
Tian Qi Zhang
Keyword(s):  
Signal Detection ◽  
Stochastic Resonance ◽  
Piecewise Linear ◽  
Correlation Coefficients ◽  
Resonance Method ◽  
Resonance System ◽  
Signal Energy ◽  
Noise Energy ◽  
Novel Model ◽  
Output Snr

Stochastic resonance systems have the advantages of converting noise energy into signal energy, and have great potential in the field of signal detection and extraction. Aiming at the problems of the performance of classical stochastic resonance system whose model is not perfect enough and the correlation coefficients between parameters is too large to be optimized by algorithm, then a novel model of the tristable potential stochastic resonance system is proposed. The output SNR formula of the model is derived and analyzed, and the influence of its parameters on the model is clarified. Compared with the piecewise linear model by numerical simulation, the correctness of the formula and the superiority of the model are verified. Finally, the model and the classical tristable model are applied to bearing fault detection in which the genetic algorithm is used to optimize the parameters of the two systems. The results show that the model has better detection effects, which prove that the model has a strong potential in the field of signal detection.

Weak-fault diagnosis using state-transition-algorithm-based adaptive stochastic-resonance method

2019 ◽  
Vol 26 (7) ◽  
pp. 1910-1920 ◽  
Author(s):  
Jin-tian Yin ◽  
Yong-fang Xie ◽  
Zhi-wen Chen ◽  
Tao Peng ◽  
Chun-hua Yang
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
State Transition ◽  
Resonance Method ◽  
State Transition Algorithm ◽  
Weak Fault

Parametric Design of Wind Turbine Blades Based on Pro/E

2012 ◽  
Vol 580 ◽  
pp. 415-418
Author(s):  
Xi Cang Wang ◽  
Shou Zhen Guo
Keyword(s):  
Wind Turbine ◽  
Parametric Design ◽  
Turbine Blades ◽  
Centrifugal Fan ◽  
3D Mapping ◽  
Wind Turbine Blades ◽  
Improve Design ◽  
Fan Blade

Based on the analysis of formation theories and constructive characteristics of centrifugal fan blade, with advanced 3D mapping design softwares, a integration parametric design is realized by putting the modeling, calculating, mapping and processing into an organic whole with computers, to get accurate drawings and improve design precision.

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