Specific emitter identification based on Hilbert–Huang transform-based time–frequency–energy distribution features

2014 ◽  
Vol 8 (13) ◽  
pp. 2404-2412 ◽  
Author(s):  
Yingjun Yuan ◽  
Hao Wu ◽  
Xiang Wang ◽  
Zhitao Huang
Keyword(s):  
Energy Distribution ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Distribution Features ◽  
Specific Emitter Identification

Simulation Study of Damage Identification Method Based on Lamb Wave Scattering in Aluminium Plate

2012 ◽  
Vol 433-440 ◽  
pp. 2611-2618
Author(s):  
Zhen Hua Tian ◽  
Hong Yuan Li ◽  
Hong Xu
Keyword(s):  
Energy Distribution ◽  
Lamb Wave ◽  
Damage Identification ◽  
Optimization Method ◽  
Propagation Path ◽  
Transient Dynamic Analysis ◽  
Time Frequency ◽  
Damage Location ◽  
Identification Method ◽  
Short Time

The propagation of scattering Lamb wave in plate was simulated using transient dynamic analysis in ANSYS. In order to extract the characteristic information of received signal for damage identification, the short time Fourier transform based on time-frequency analysis was utilized, and then the energy distribution and envelop of received signal were obtained. Based on the displacement contour of simulation and energy distribution, the propagation of scattering wave in plate with a through hole was examined. Also, a mathematic relationship between damage location and scattering signal was developed, with the help of wave propagation path through actuator, damage and sensor. A nonlinear optimization method was applied on the mathematic relationship to obtain the damage location. The damage identification method using scattering Lamb wave was therefore established.

Characterization of Cavitation During Pump Operation Based on Hilbert-Huang Transform

2018 ◽  
Author(s):  
Hui Sun ◽  
Shouqi Yuan ◽  
Yin Luo ◽  
Bo Gong
Keyword(s):  
Centrifugal Pump ◽  
Longitudinal Vibration ◽  
Process Time ◽  
Current Signal ◽  
Vibration Signals ◽  
Pump Operation ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Cavitation Process ◽  
Non Stationary Signal

Cavitation has negative influence on pump operation. In order to detect incipient cavitation effectively, experimental investigation was conducted to through acquisition of current and vibration signals during cavitation process. In this research, a centrifugal pump was modeled for research. The data was analyzed by HHT method. The results show that Torque oscillation resulted from unsteady flow during cavitation process could result in energy variation. Variation regulation of RMS of IMF in current signal is similar to that in axial vibration signal. But RMS of IMF in current signal is more sensitive to cavitation generation. It could be regarded as the indicator of incipient cavitation. RMS variation of IMF in base, radial, longitudinal vibration signals experiences an obvious increasing when cavitation gets severe. Such single variation regulation could be selected as the indicator of cavitation stage recognition. Hilbert-Huang transform is suitable for transient and non-stationary signal process. Time-frequency characteristics could be extracted from results of HHT process to reveal pump operation condition. The contents of current work could provide valuable references for further research on centrifugal pump operation detection.

Vibration Fatigue Test Based on Fiber Bragg Grating Sensors and HHT

2013 ◽  
Vol 328 ◽  
pp. 193-197
Author(s):  
Si Jin Xin ◽  
Zhen Tong
Keyword(s):  
Titanium Alloy ◽  
Fiber Bragg Grating ◽  
Fatigue Test ◽  
Alloy Sheet ◽  
Bragg Grating ◽  
Metal Fatigue ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Vibration Fatigue ◽  
Fbg Sensors

The metal fatigue is an important factor to cause an accident in machine operation, so metal fatigue test is a significant procedure in manufacturing. Fiber Bragg Grating (FBG), as an innovative sensor, has been applied to the measurement of various rotating machines. In this paper, the time-frequency analysis is used to detect the fatigue feature of a titanium alloy measured by FBG sensors. Furthermore, the Hilbert-Huang transform (HHT) is more effective to observe the fatigue limit of the titanium alloy sheet, compared to the Wavelet transform (WT).

scholarly journals Common Crossing Structural Health Analysis with Track-Side Monitoring

2019 ◽  
Vol 21 (3) ◽  
pp. 77-84
Author(s):  
Mykola Sysyn ◽  
Olga Nabochenko ◽  
Franziska Kluge ◽  
Vitalii Kovalchuk ◽  
Andriy Pentsak
Keyword(s):  
Gaussian Process Regression ◽  
Ensemble Empirical Mode Decomposition ◽  
Frequency Resolution ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Structural Health ◽  
Rolling Surface ◽  
Mode Decomposition ◽  
Inertial Measurements ◽  
Common Crossing

Track-side inertial measurements on common crossings are the object of the present study. The paper deals with the problem of measurement's interpretation for the estimation of the crossing structural health. The problem is manifested by the weak relation of measured acceleration components and impact lateral distribution to the lifecycle of common crossing rolling surface. The popular signal processing and machine learning methods are explored to solve the problem. The Hilbert-Huang Transform (HHT) method is used to extract the time-frequency features of acceleration components. The method is based on Ensemble Empirical Mode Decomposition (EEMD) that is advantageous to the conventional spectral analysis methods with higher frequency resolution and managing nonstationary nonlinear signals. Linear regression and Gaussian Process Regression are used to fuse the extracted features in one structural health (SH) indicator and study its relation to the crossing lifetime. The results have shown the significant relation of the derived with GPR indicator to the lifetime.

scholarly journals Seismo-Deformation Anomalies Associated with the M6.1 Ludian Earthquake on August 3, 2014

2020 ◽  
Vol 12 (7) ◽  
pp. 1067 ◽  
Author(s):  
Chieh-Hung Chen ◽  
Xiaoning Su ◽  
Kai-Chien Cheng ◽  
Guojie Meng ◽  
Strong Wen ◽  
...  
Keyword(s):  
Temporal Evolution ◽  
Numerical Models ◽  
Material Failure ◽  
Frequency Method ◽  
Pass Filter ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Terminal Stage ◽  
Ludian Earthquake ◽  
Stress Accumulation

A time-frequency method retrieving the acceleration changes in the terminal stage of theM6.1 Ludian earthquake in China is discussed in this article. The non-linear, non-stationaryseismo-demformation was obtained by using the Hilbert–Huang transform and followed by aband-pass filter. We found that the temporal evolution of the residual GNSS-derived orientationexhibits a unique disorder-alignment-disorder sequence days before the earthquake whichcorresponds well with the four stages of an earthquake: elastic strain buildup, crack developments,deformation, and the terminal stage of material failure. The disordering orientations are graduallyaligned with a common direction a few days before the terminal stage. This common direction isconsistent with the most compressive axis derived from the seismological method. In addition, theregion of the stress accumulation, as identified by the size of the disordered orientation, isgenerally consistent with the earthquake preparation zones estimated by using numerical models.

Research of Aircraft Cable Fault Detecting Method Based on Hilbert Huang Transformation

2011 ◽  
Vol 214 ◽  
pp. 138-143
Author(s):  
Tao Jing ◽  
Lu Zhang ◽  
Xu Dong Shi ◽  
Li Wen Wang
Keyword(s):  
Frequency Domain ◽  
Short Circuit ◽  
Reference Signal ◽  
Open Circuit ◽  
Time Domain Reflectometry ◽  
Transform Method ◽  
Hilbert Huang Transform ◽  
Intermittent Faults ◽  
Time Frequency ◽  
Frequency Domain Reflectometry

Aircraft cable fault diagnosing is considered to be most important for engineering maintenance. Several methods for cables testing have been developed, such as TDR, FDR and TFDR. Time Domain Reflectometry (TDR) relays much on impedance changes on the fault position, which is hard to using in detecting high resistance defects, intermittent defects; Time Frequency Domain Reflectometry (TFDR) method is used to locate intermittent faults, continuous faults and cross-connection faults aircraft wire, however, the algorithm of TFDR is complex. To the "Hard Fault"(short circuit and open circuit), the Hilbert-Huang Transform method is used in determining the optimal bandwidth of the incident reference signal and analyzing the phase and amplitude difference of superimposed signal which from the incident signal and the reflected signal on defects. To the "Fray Fault", Time and Frequency Domain Reflectometry method can be used with the signal processing method with Hilbert-Huang Transform. The experimental results indicate that this method effectively detect all types of aircraft cable fault, particularly for short lengths of cable.

Wavelet Frequency Estimation Parameter Of Energy Distribution For Electrooculograph Signal Analysis

2012 ◽  
Author(s):  
Wan Mohd. Bukhari Wan Daud ◽  
Rubita Sudirman
Keyword(s):  
Wavelet Transform ◽  
Energy Distribution ◽  
Eye Movement ◽  
Signal Analysis ◽  
Frequency Estimation ◽  
Data Acquisition System ◽  
Wavelet Method ◽  
Distribution Features ◽  
Eeg Data ◽  
Recorded Data

Pengajian ini mengkaji electrooculograph (EOG) isyarat pola gerakan mata. Perilaku dari isyarat gerakan mata dijelaskan menggunakan kaedah wavelet dan digabungkan dengan ciriciri pengedaran tenaga. Ciri–ciri yang berasal dari isyarat EOG daripada empat jenis pergerakan mata dan dicatat menggunakan Sistem Akuisisi Data EEG, EEG Neurofax–9200. Elektrodelektrod tersebut diletakkan di dahi dan di bawah mata. Data diperolehi daripada 15 subjek di dalam bilik yang senyap, di mana data yang tercatat terdiri daripada empat gerakan mata yang berbeza, iaitu pergerakan ke atas, ke bawah, ke kiri dan ke kanan. Algoritma Wavelet scalogram digunakan untuk menganalisa isyarat yang direkodkan kerana ia mampu untuk menunjukkan amaun tenaga isyarat EOG pergerakan mata dengan perubahan masa dan frekuensi. Hasil kajian menunjukkan bahawa amaun tenaga isyarat EOG menunjukkan pola yang berbeza dalam gerakan–gerakan berikut: tahap 6 (8–16 Hz) untuk gerakan mata ke kiri; tahap 7 (4–8 Hz) untuk gerakan ke atas; tahap 8 (2 – 4 Hz) untuk gerakan ke kanan dan peringkat 9 (1–2 Hz) untuk gerakan ke bawah. Kata kunci: Electro–oculogram; gerakan mata; tenaga isyarat; transformasi wavelet; scalogram The study investigates the electrooculograph (EOG) signals of eye movement patterns. The behaviours of the eye movement signal is described using wavelet method and combined with the energy distribution features. The features are derived from EOG signals of four type eye movement and recorded using the EEG Data Acquisition System Neurofax EEG–9200. The electrodes were attached to the subjects on the forehead and below the eye. The data is acquired from 15 subjects in a quiet room, in which the recorded data is composed by four different eye movements that are upward, downward, towards to left and towards to right. Wavelet scalogram algorithm is used as the tool because of its capable to distribute the EOG signals energy of eye movement with the change of time and frequency. From the results, it indicated that the energy distribution of EOG signals exhibit different patterns in their corresponding movements as follow: level 6 (8–16 Hz) for left eye movement; level 7 (4–8 Hz) for upward; level 8 (2–4 Hz) for right and level 9 (1–2 Hz) for downward. Key words: Electro–oculogram; eye movement; signal potentials; wavelet transform; scalogram

Comparison Between Time-Frequency Techniques to Predict Ball Bearing Faults in Drives Executing Arbitrary Motion Profiles

2008 ◽  
Author(s):  
Marco Cocconcelli ◽  
Cristian Secchi ◽  
Riccardo Rubini ◽  
Cesare Fantuzzi ◽  
Luca Bassi
Keyword(s):  
Velocity Profile ◽  
Cross Correlation ◽  
Fault Prediction ◽  
Variable Velocity ◽  
Outer Race ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Bearing Diagnostics ◽  
Packaging Machine ◽  
Expected Signal

In this paper Wavelet Transform (WT) and Hilbert-Huang Transform (HHT) are used as bearing diagnostics tools in drives executing arbitrary motion profiles. This field is increasingly drawing the attention of the industries because the modern electric motors work as electric cams inducing the shaft to move with a cyclic variable-velocity profile. The literature papers take into account only a constant velocity profile and they are not suitable for such applications. In fact literature methods analyse the signal only in the frequency domain, while in variable-velocity condition the bearing diagnostics should be performed in time domain. Both WT and HHT are time-frequency techniques which describe an input signal as a sum of specific functions. These functions are compared with a signal which simulates the expected vibrations of a bearing with a given fault, e.g. on the outer race. The comparison is done through a cross-correlation between the expected signal and the time-frequency techniques output. WT and HHT are used separately in an industrial case, which consists in bearing fault prediction in an automated packaging machine. In the end of the paper the WT and HHT results are discussed to analyse the different responses.

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