Fault degradation assessment of water hydraulic motor by impulse vibration signal with Wavelet Packet Analysis and Kolmogorov–Smirnov Test

2008 ◽  
Vol 22 (7) ◽  
pp. 1670-1684 ◽  
Author(s):  
H.X. Chen ◽  
Patrick S.K. Chua ◽  
G.H. Lim
Keyword(s):  
Wavelet Packet ◽  
Vibration Signal ◽  
Hydraulic Motor ◽  
Wavelet Packet Analysis ◽  
Kolmogorov Smirnov ◽  
Water Hydraulic ◽  
Smirnov Test

Cutting Institutions Running State Estimation Strategy Based on Wavelet Packet Analysis Technology

2014 ◽  
Vol 574 ◽  
pp. 696-701
Author(s):  
Fu Zhong Wang ◽  
Xiao Ying Tian
Keyword(s):  
Control Strategy ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Frequency Characteristics ◽  
Wavelet Packet Analysis ◽  
Cutting Mechanism ◽  
Estimation Strategy ◽  
Working Face ◽  
Signal Characteristics ◽  
Mine Roadway

During robotic heading machine working, it often encounters the coal seam hardness changing tremendously. So the cutting mechanism will be easy to break down. For this problem, put forward a strategy, which using wavelet packet technology to study the vibration signal of cutting mechanism. Filtered the signal with wavelet packet; extracted vibration signal characteristics; established the energy eigenvector; used the Hilbert technology to extract frequency characteristics. According to the energy eigenvector and the frequency characteristics, estimated the cutting mechanism running status. The simulation in MATLAB proves that the control strategy can estimate the running state of cutting mechanism real-time, and lay an important foundation for the realization of coal mine roadway drivage unmanned working face.

Study on Energy Distribution of Single-Hole Blasting Vibration Signal Based on Wavelet Packet Transform

2013 ◽  
Vol 321-324 ◽  
pp. 1284-1289
Author(s):  
Dong Tao Li ◽  
Li Xin Xu ◽  
Yuan Yuan Sun ◽  
Qiu Rui Jia ◽  
Jing Long Yan
Keyword(s):  
Energy Distribution ◽  
Concentration Distribution ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Vibration Signal ◽  
Vibration Velocity ◽  
Blasting Vibration ◽  
Wavelet Packet Analysis ◽  
Vibration Signals ◽  
Single Hole

It is conducive to reducedamage of blasting vibration to realize energy distribution and attenuation lawof single-hole blasting vibration signal. With the measured single-holeblasting vibration velocity curves, used wavelet packet analysis technologywith high-resolution character, the law of energy distribution of single-holeblasting vibration signals in different frequency bands, and the effect ofblasting source and distance from the source on single-hole blasting vibrationsignal energy distribution were analysised. The results show that the energy ofsingle-hole blasting vibration signals attenuation very quickly in thefrequency domain concentration distribution in 0~100Hz; and distance from thesource has significant influence on energy distribution in the frequencydomain; The energy is mainly distributed in the low frequency band whendistance from the source is larger, which has guiding significance inmitigation of blast-induced vibrations.

Fault Degradation Assessment of Water Hydraulic Components by Noise Signal with Wavelet Packet Analysis

2008 ◽  
Vol 36 (5) ◽  
pp. 101688
Author(s):  
M. R. Mitchell ◽  
R. E. Link ◽  
H. X. Chen ◽  
Patrick S. K. Chua ◽  
G. H. Lim
Keyword(s):  
Wavelet Packet ◽  
Noise Signal ◽  
Wavelet Packet Analysis ◽  
Water Hydraulic

scholarly journals Fault diagnosis of synchronous hydraulic motor based on acoustic signals

2020 ◽  
Vol 12 (4) ◽  
pp. 168781402091610
Author(s):  
Jiaoyi Hou ◽  
Hongyu Sun ◽  
Aoyu Xu ◽  
Yongjun Gong ◽  
Dayong Ning
Keyword(s):  
Fault Diagnosis ◽  
Nearest Neighbor ◽  
Wavelet Packet ◽  
Pearson Correlation ◽  
Vibration Signal ◽  
Economic Loss ◽  
Acoustic Signals ◽  
Hydraulic Motor ◽  
Automatic Calculation ◽  
Hydraulic Motors

Synchronous hydraulic motors are used in high load conditions. Therefore, the failure of such motors must be promptly detected to avoid severe accidents and economic loss. The automation of signal processing and diagnostic processes in practical engineering applications can help improve engineering efficiency and reduce hazards. As a non-contact acquisition signal, an acoustic signal has easier acquisition than a vibration signal. This article proposes an automatic fault detection method for synchronous hydraulic motors, which uses acoustic signals. The proposed method includes the automatic calculation and pattern recognition of the parameters of fault feature vectors. The automatic calculation of the fault feature vector is based on the combination of wavelet packet energy and the Pearson correlation coefficient. Then, the nearest-neighbor classifier is used for fault diagnosis. This study verifies that the proposed method can effectively identify the normal state, gear wear, gear rust, and barrier block wear. This method provides a solution for the automatic fault diagnosis of synchronous hydraulic motors and other types of quasi-period rotating machinery.

A Method of False Component Discriminant of EMD Based on Kolmogorov-Smirnov Test

2013 ◽  
Vol 427-429 ◽  
pp. 2005-2008
Author(s):  
Wang Can Yang ◽  
Pei Lin Zhang ◽  
Ding Hai Wu ◽  
Zhou Xin
Keyword(s):  
Vibration Signal ◽  
Threshold Value ◽  
Signal Decomposition ◽  
Original Signal ◽  
Intrinsic Mode Functions ◽  
The Real ◽  
Similarity Threshold ◽  
Mode Decomposition ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

In order to solve the problem that empirical mode decomposition (EMD) will cause false components in the process of signal decomposition, a method of false component discriminant of EMD based on Kolmogorov-Smirnov test was put forward. First, the original signal was decomposed into several intrinsic mode functions (IMFs) by EMD. Then the K-S test was used to calculate the similarity between each IMF and the original signal. The reasonable similarity threshold was selected for judging the authenticity of the IMFs. The IMFs of which the similarity values were less than the threshold value were determined to be the false components. The others of which the similarity values were greater than the threshold value were determined to be the real components. As a result, the false components were removed and the real components were remained. The vibration signal of bearing experiment indicated that the method of K-S test could discriminate the real components and the false components obviously. Then the false components were removed quickly and accurately and the real components of the original signal were obtained.

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