Adaptive radial sinc kernel distribution and its application in mechanical fault diagnosis

2016 ◽  
Vol 231 (3) ◽  
pp. 485-493 ◽  
Author(s):  
Zhinong Li ◽  
Ming Zhu ◽  
Fulei Chu ◽  
Xuping He
Keyword(s):  
Fault Diagnosis ◽  
Frequency Distribution ◽  
Kernel Function ◽  
Rolling Bearing ◽  
Kernel Functions ◽  
Frequency Resolution ◽  
Good Time ◽  
Time Frequency ◽  
Fixed Kernel ◽  
Time Frequency Distribution

Based on the deficiency of fixed-kernel in the traditional time–frequency distribution, which is lack of adaptability, a new adaptive kernel function, which is named as the adaptive radial sinc kernel, is proposed according to design criteria of adaptive optimal kernel. The definition and algorithm of radial sinc kernel are given, and the proposed method is compared with the tradition time–frequency distribution. The simulation results show that the proposed method is superior to the traditional fixed-kernel functions, such as Wigner–Ville distribution, Choi–Williams distribution, cone-kernel distribution and continuous wavelet transform. The adaptive radial sinc kernel can overcome the deficiency of fixed-kernel function in traditional time–frequency distribution, adopt the optimizing method to filter the cross-terms adaptively according to the signal distribution, obtain good time–frequency resolution and has extensive adaptability for an arbitrary signal. Finally, the proposed method has been applied to the fault diagnosis of rolling bearing, and the experiment result shows that the proposed method is very effective.

Adaptive Signal Analysis Based on Radial Parabola Kernel

2007 ◽  
Vol 10-12 ◽  
pp. 737-741 ◽  
Author(s):  
S.C. Wang ◽  
J. Han ◽  
Jian Feng Li ◽  
Zhi Nong Li
Keyword(s):  
Kernel Functions ◽  
Frequency Resolution ◽  
Good Time ◽  
Signal Distribution ◽  
Time Frequency ◽  
Frequency Representation ◽  
Fixed Kernel ◽  
Limited Class ◽  
Adaptive Kernel ◽  
Adaptive Signal

Because of the deficiency of fixed kernel in bilinear time-frequency distribution (TFD), i.e. for each mapping, the resulting time-frequency representation is satisfactory only for a limited class of signals, a new adaptive kernel function named the radial parabola kernel (RPK), is proposed. The RPK can adopt the optimizing method to filter cross-terms adaptively according to the signal distribution, obtain good time-frequency resolution, and offer improved TFD for a large class of signals. Compared with traditional fixed -kernel functions, such as Wigner-Ville distribution, Choi-Willams distribution and Cone-kernel distribution, the superiority of the RPK function is obvious. At last, the RPK function is applied to the analysis of vibration signals of bearing, and the result proves the RPK function an effective method in analyzing signals.

The application of time–frequency reconstruction and correlation matching for rolling bearing fault diagnosis

2015 ◽  
Vol 229 (17) ◽  
pp. 3291-3295 ◽  
Author(s):  
Jian Xu ◽  
Shuiguang Tong ◽  
Feiyun Cong ◽  
Yidong Zhang
Keyword(s):  
Fault Diagnosis ◽  
Frequency Distribution ◽  
Noise Suppression ◽  
Rolling Bearing ◽  
Time Frequency ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Original Time ◽  
Correlation Matching ◽  
Time Frequency Distribution

There are still some remaining issues for time–frequency distribution application in rolling bearing fault diagnosis, such as noise suppression and resolution improvement. In this paper, we proposed a novel time–frequency correlation matching and reconstruction method to enhance the ability of rolling bearing fault identification. Firstly, we use the optimal simulated bearing fault signal to obtain the matching template through time–frequency distribution. Then, correlation matching operation is conducted between the obtained matching template and the original time–frequency distribution of analyzed signal. Finally, the original time–frequency distribution is reconstructed with the correlation coefficients and matching template using the template reconstruction algorithm. The reconstructed time–frequency distribution has inherited the capability of matching template in noise suppression, and can reveal the fault impulses of interest in a unified scale. The effectiveness of the proposed method has been proved by experimental result.

scholarly journals Study on Vibration Characteristics of Natural Gas Pipeline Explosion Based on Improved MP-WVD Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Huayuan Ma ◽  
Yuan Long ◽  
Xinghua Li ◽  
Mingshou Zhong ◽  
Jianyuan Wu ◽  
...  
Keyword(s):  
Natural Gas ◽  
Frequency Distribution ◽  
Gas Pipeline ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Natural Gas Pipeline ◽  
Precise Analysis ◽  
Nature Gas ◽  
Control State ◽  
Time Frequency Distribution

In order to meet the requirement of precise analysis of nature gas pipeline explosion, authors combined MP algorithm and WVD distribution to improve the time-frequency resolution and to solve the problem of cross-terms interference. The HHT algorithm was applied to the data preprocessing of MP algorithm to reduce the computational complexity of the MP algorithm. It improved the computing efficiency and laid the foundation for big data analysis. In this paper, authors carried out a full-size pipeline explosion experiment at the CNPC pipeline fracture control State Key Laboratory. Advantages of the improved MP-WVD algorithm were taken to obtain the time-frequency distribution characteristics of the pipeline explosion vibration. The research provided a new algorithm for the time-frequency distribution of nonstationary random vibration, and the result provided a reference for the safe operation and construction of natural gas pipeline.

The Parameter Estimation of Non-Cooperative Frequency Hopping Signals Based on the Algorithm of RSPWVD

2014 ◽  
Vol 556-562 ◽  
pp. 4779-4783 ◽  
Author(s):  
Jin Fei Lv ◽  
Yu Han ◽  
Xiao Peng Liang
Keyword(s):  
Computer Simulation ◽  
Parameter Estimation ◽  
Frequency Distribution ◽  
Basic Principle ◽  
Frequency Hopping ◽  
Good Time ◽  
Time Frequency ◽  
Signal Parameters ◽  
Time Frequency Distribution

How to get good time-frequency distribution of FH signals is crucial to detect and to trace the FH signals. The theory about the rearrangement of time-frequency distribution is summarized in the paper, then the basic principle of detecting the signals using the algorithm of rearrangement of the smooth pseudo Wigner-Ville distribution (RSPWVD) is analyzed in detail, and the algorithm expression are given at the same time. The analysis results show that the RSPWVD algorithm not only has more ideal anti-jamming effects, but also can enhance the time-frequency aggregation of the signal, so the signal parameters are estimated more accurately. In the end, the computer simulation is shown to test the feasibility and effectiveness of the algorithm.

scholarly journals A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Yajun Li ◽  
Yinsheng Wei ◽  
Rujiang Guo ◽  
Rongqing Xu ◽  
Zhuoqun Wang ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Large Amplitude ◽  
Gradient Algorithm ◽  
Frequency Resolution ◽  
Good Effect ◽  
Distribution Method ◽  
Phase Gradient ◽  
Time Frequency ◽  
Phase Perturbation ◽  
Time Frequency Distribution

Ionospheric phase perturbation with large amplitude causes broadening sea clutter’s Bragg peaks to overlap each other; the performance of traditional decontamination methods about filtering Bragg peak is poor, which greatly limits the detection performance of HF skywave radars. In view of the ionospheric phase perturbation with large amplitude, this paper proposes a cascaded approach based on improved S-method to correct the ionospheric phase contamination. This approach consists of two correction steps. At the first step, a time-frequency distribution method based on improved S-method is adopted and an optimal detection method is designed to obtain a coarse ionospheric modulation estimation from the time-frequency distribution. At the second correction step, based on the phase gradient algorithm (PGA) is exploited to eliminate the residual contamination. Finally, use the measured data to verify the effectiveness of the method. Simulation results show the time-frequency resolution of this method is high and is not affected by the interference of the cross term; ionospheric phase perturbation with large amplitude can be corrected in low signal-to-noise (SNR); such a cascade correction method has a good effect.

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