Time-frequency representation based on robust local mean decomposition for multicomponent AM-FM signal analysis

2017 ◽  
Vol 95 ◽  
pp. 468-487 ◽  
Author(s):  
Zhiliang Liu ◽  
Yaqiang Jin ◽  
Ming J. Zuo ◽  
Zhipeng Feng
Keyword(s):  
Signal Analysis ◽  
Local Mean Decomposition ◽  
Time Frequency ◽  
Frequency Representation ◽  
Local Mean

Gear Pitting Corrosion Fault Diagnosis Based on Local Mean Decomposition

2012 ◽  
Vol 562-564 ◽  
pp. 812-815 ◽  
Author(s):  
Ya Nong Chen ◽  
Tian He ◽  
Deng Hong Xiao ◽  
Hai Tao Cui
Keyword(s):  
Fault Diagnosis ◽  
Pitting Corrosion ◽  
Simulation Analysis ◽  
Analysis Method ◽  
Local Mean Decomposition ◽  
Time Frequency ◽  
Gear Fault ◽  
Modulation Signal ◽  
Adaptive Time ◽  
Local Mean

The local mean decomposition (LMD), a new adaptive time-frequency analysis method, is the research focus in the fault diagnosis field in recent years. In this paper, the LMD’s characteristics are obtained by processing multi-component frequency and amplitude modulation signal, which are usually used to describe the gear pitting corrosion fault signals. Base on the simulation analysis, LMD is presented to deal with the vibration signals of gear pitting corrosion fault, comparing with traditional method. The results show that the gear pitting corrosion defect can be diagnosed by LMD effectively, and LMD can eliminate the false composition effect, thus improving the accuracy of gear fault diagnosis.

scholarly journals Evaluation of Seven Time-Frequency Representation Algorithms Applied to Broadband Echolocation Signals

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Josefin Starkhammar ◽  
Maria Hansson-Sandsten
Keyword(s):  
Signal Analysis ◽  
Time Difference ◽  
Frequency Difference ◽  
Transient Signals ◽  
Signal Component ◽  
Time Frequency ◽  
Exact Location ◽  
Frequency Representation ◽  
Different Types ◽  
Echolocation Signal

Time-frequency representation algorithms such as spectrograms have proven to be useful tools in marine biosonar signal analysis. Although there are several different time-frequency representation algorithms designed for different types of signals with various characteristics, it is unclear which algorithms that are best suited for transient signals, like the echolocation signals of echolocating whales. This paper describes a comparison of seven different time-frequency representation algorithms with respect to their usefulness when it comes to marine biosonar signals. It also provides the answer to how close in time and frequency two transients can be while remaining distinguishable as two separate signals in time-frequency representations. This is, for instance, relevant in studies where echolocation signal component azimuths are compared in the search for the exact location of their acoustic sources. The smallest time difference was found to be 20 µs and the smallest frequency difference 49 kHz of signals with a −3 dB bandwidth of 40 kHz. Among the tested methods, the Reassigned Smoothed Pseudo Wigner-Ville distribution technique was found to be the most capable of localizing closely spaced signal components.

scholarly journals Improved ensemble local mean decomposition based on cubic trigonometric cardinal spline interpolation and its application for rotating machinery fault diagnosis

2020 ◽  
Vol 12 (7) ◽  
pp. 168781402094195
Author(s):  
Pei Chen ◽  
Huanguo Chen ◽  
Wenhua Chen ◽  
Jun Pan ◽  
Jianmin Li ◽  
...  
Keyword(s):  
Signal Analysis ◽  
Spline Interpolation ◽  
Moving Average ◽  
Local Mean Decomposition ◽  
Advantages And Disadvantages ◽  
Cardinal Spline ◽  
Controlling Parameter ◽  
Local Mean ◽  
Shape Controlling ◽  
Cardinal Spline Interpolation

Ensemble local mean decomposition has been gradually introduced into mechanical vibration signal processing due to its excellent performance in electroencephalogram signal analysis. However, an unsatisfactory problem is that ensemble local mean decomposition cannot effectively process vibration signals of complex mechanical system due to the constraints of moving average. The process of moving average is time-consuming and inaccurate in complex signal analysis. Therefore, an improved ensemble local mean decomposition method called C-ELMD with modified envelope algorithm based on cubic trigonometric cardinal spline interpolation is proposed in this article. First, the shortcomings in sifting process of ensemble local mean decomposition is discussed and, furthermore, advantages and disadvantages of the common interpolation methods adopted to improve ensemble local mean decomposition are compared. Then, cubic trigonometric cardinal spline interpolation is employed to construct the local mean and envelope curves in a more precise way. In addition, the influence of shape-controlling parameter on envelope estimation accuracy in cubic trigonometric cardinal spline interpolation is also discussed in detail to select an optimal shape-controlling parameter. The effectiveness of cubic trigonometric cardinal spline interpolation for improving the accuracy of ensemble local mean decomposition is demonstrated using a synthetic signal. Finally, the proposed cubic trigonometric cardinal spline interpolation is tested to be effective in gear and bearing fault detection and diagnosis.

Sign in / Sign up

Export Citation Format

Share Document