scholarly journals An improved smooth-windowed Wigner-Ville distribution analysis for voltage variation signal

2020 ◽  
Vol 10 (5) ◽  
pp. 4982
Author(s):  
Mustafa Manap ◽  
Abdul Rahim Abdullah ◽  
Srete Nikolovski ◽  
Tole Sutikno ◽  
Mohd Hatta Jopri
Keyword(s):  
Embedded System ◽  
Side Lobe ◽  
Good Time ◽  
Percentage Error ◽  
Distribution Analysis ◽  
Time Frequency ◽  
Voltage Variation ◽  
Separable Kernel ◽  
Optimal Kernel ◽  
Kernel Parameters

This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth-windowed wigner-ville distribution (SWWVD) used to represent time-varying signals in time-frequency representation (TFR). Good time and frequency resolutions offer superiority in SWWVD to analyze voltage variation signals that consist of variations in magnitude. The separable kernel parameters are estimated from the signal in order to get an accurate TFR. The TFR for various kernel parameters is compared by a set of performance measures. The evaluation shows that different kernel settings are required for different signal parameters. Verification of the TFD that operated at optimal kernel parameters is then conducted. SWWVD exhibits a good performance of TFR which gives high peak-to-side lobe ratio (PSLR) and signal-to-cross-terms ratio (SCR) accompanied by low main-lobe width (MLW) and absolute percentage error (APE). This proved that the technique is appropriate for voltage variation signal analysis and it essential for development in an advanced embedded system.

scholarly journals An innovative image fusion algorithm based on wavelet transform and discrete fast curvelet transform

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Curvelet Transform ◽  
Relevant Information ◽  
Good Time ◽  
Discrete Wavelet ◽  
Fusion Algorithm ◽  
Time Frequency ◽  
Fused Image

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.

scholarly journals Designing a waveform using LFM, NLFM for MIMO radar

2017 ◽  
Vol 7 (1.5) ◽  
pp. 84
Author(s):  
G S Krishnam Naidu Yedla ◽  
D. Siva Sankar Prasad ◽  
P. Raghavendra Rao ◽  
M Siva Kumar ◽  
M VenuGopala Rao
Keyword(s):  
Frequency Modulation ◽  
Frequency Component ◽  
Side Lobe ◽  
Mimo Radar ◽  
Linear Frequency Modulation ◽  
Wave Form ◽  
Boundary Segment ◽  
Middle Segment ◽  
Time Frequency ◽  
Linear Frequency

We propose a waveform that includes Linear frequency modulation and non linear frequency modulation wave applicable for MIMO radar. The wave form consists of three segments where the boundary segment consists of LFM content and the middle segment consists of NLFM. The time frequency component in the middle segment is controlled. The range and Doppler side lobe suppression is improved. The genetic algorithm is implemented to suppress the side lobes in the auto correlation and cross correlation functions. The performance is analysed by using ambiguity function.

Zoom Synchrosqueezing Transform for Instantaneous Speed Estimation of High Speed Spindle

2016 ◽  
Vol 836-837 ◽  
pp. 310-317 ◽  
Author(s):  
Song Tao Xi ◽  
Hong Rui Cao ◽  
Xue Feng Chen
Keyword(s):  
Frequency Shift ◽  
High Speed ◽  
Frequency Component ◽  
Frequency Region ◽  
Frequency Resolution ◽  
Good Time ◽  
Heisenberg Uncertainty Principle ◽  
Time Frequency ◽  
Synchrosqueezing Transform ◽  
Instantaneous Speed

Instantaneous speed (IS) is of great significance of fault diagnosis and condition monitoring of the high speed spindle. In this paper, we propose a novel zoom synchrosqueezing transform (ZST) for IS estimation of the high speed spindle. Due to the limitation of the Heisenberg uncertainty principle, the conventional time-frequency analysis (TFA) methods cannot provide both good time and frequency resolution at the whole frequency region. Moreover, in most cases, the interested frequency component of a signal only locates in a narrow frequency region, so there is no need to analyze the signal in the whole frequency region. Different from conventional TFA methods, the proposed method arms to analyze the signal in a specific frequency region with both excellent time and frequency resolution so as to obtain accurate instantaneous frequency (IF) estimation results. The proposed ZST is an improvement of the synchrosqueezing wavelet transform (SWT) and consists of two steps, i.e., the frequency-shift operation and the partial zoom synchrosqueezing operation. The frequency-shift operation is to shift the interested frequency component from the lower frequency region to the higher frequency to obtain better time resolution. The partial zoom synchrosqueezing operation is conducted to analyze the shifted signal with excellent frequency resolution in a considered frequency region. Compared with SWT, the proposed method can provide satisfactory energy concentrated time-frequency representation (TFR) and accurate IF estimation results. Additionally, an application of the proposed ZST to the IS fluctuation estimation of a motorized spindle was conducted, and the result showed that the IS estimated by the proposed ZST can be used to detect the quality of the finished workpiece surface.

An Evaluation of Linear Time Frequency Distribution Analysis for VSI Switch Faults Identification

2017 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
M.F. Habban ◽  
M. Manap ◽  
A.R. Abdullah ◽  
M.H. Jopri ◽  
T. Sutikno
Keyword(s):  
Fault Detection ◽  
Frequency Distribution ◽  
Linear Time ◽  
Harmonic Distortion ◽  
Voltage Source ◽  
Distribution Analysis ◽  
Voltage Source Inverter ◽  
Time Frequency ◽  
S Transform ◽  
Time Frequency Distribution

This paper present an evaluation of linear time frequency distribution analysis for voltage source inverter system (VSI). Power electronic now are highly demand in industrial such as manufacturing, industrial process and semiconductor because of the reliability and sustainability. However, the phenomenon that happened in switch fault has become a critical issue in the development of advanced. This causes problems that occur study on fault switch at voltage source inverter (VSI) must be identified more closely so that problems like this can be prevented. The TFD which is STFT  and S-transform method are analyzed the switch fault of VSI.  To identify the VSI switches fault, the parameter of fault signal such as instantaneous of average current, RMS current, RMS fundamental current, total waveform distortion, total harmonic distortion and total non-harmonic distortion can be estimated from TFD. The analysis information are useful especially for industrial application in the process for identify the switch fault detection. Then the accuracy of both method, which mean STFT and S-transform are identified by the lowest value of mean absolute percentage error (MAPE). In addition, the S-transform gives a better accuracy compare with STFT and it can be implement for fault detection system.

scholarly journals Fault Detection for the Scraper Chain Based on Vibration Analysis Using the Adaptive Optimal Kernel Time-Frequency Representation

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Xing Zhang ◽  
Wei Li ◽  
Zhencai Zhu ◽  
Shanguo Yang ◽  
Fan Jiang
Keyword(s):  
Fault Detection ◽  
Vibration Analysis ◽  
Large Scale ◽  
Experimental Testing ◽  
Operating Conditions ◽  
Mining Equipment ◽  
Time Frequency ◽  
Failure Patterns ◽  
Frequency Representation ◽  
Optimal Kernel

A scraper conveyor is a key component of large-scale mechanized coal mining equipment, and its failure patterns are mainly caused by chain jam and chain fracture. Due to the difficulties with direct measurement for multiple performance parameters of the scraper chain, this paper deals with a novel strategy for fault detection of the scraper chain based on vibration analysis of the chute. First, a chute vibration model (CVM) is applied for modal analysis, and the hammer impact test (HIT) is conducted to validate the accuracy of the CVM; second, the measuring points for vibration analysis of the chute are determined based on the modal assurance criterion (MAC); and third, to simulate the actual vibration properties of the chute, a dynamic transmission system model (DTSM) is constructed based on finite element modeling. The fixed-point experimental testing (FPET) is then conducted to indicate the correctness of simulation results. Subsequently, the DTSM-based vibration responses of the chute under different operating conditions are obtained. In this paper, the proposed strategy is employed to determine the occurrence of chain faults by amplitude comparisons, while failure patterns are distinguished by the adaptive optimal kernel time-frequency representation (AOKR).

Performance Comparison of VSI Switches Faults Analysis Using STFT and S Transform

2015 ◽  
Vol 785 ◽  
pp. 210-214 ◽  
Author(s):  
M. Manap ◽  
A.R. Abdullah ◽  
N.Z. Saharuddin ◽  
N.A. Abidullah ◽  
Nur Sumayyah Ahmad ◽  
...  
Keyword(s):  
Power Converter ◽  
Performance Comparison ◽  
Voltage Source ◽  
Percentage Error ◽  
Identification System ◽  
Time Frequency ◽  
Signal Parameters ◽  
Detection And Identification ◽  
Frequency Representation ◽  
S Transform

Switches fault in power converter has become compelling issues over the years. To reduce cost and maintenance downtime, a good fault detection technique is an essential. In this paper, the performance of STFT and S transform techniques are analysed and compared for voltage source inverter (VSI) switches faults. The signal from phase current is represented in jointly time-frequency representation (TFR) to estimate signal parameters and characteristics. Then, the degree of accuracy for both STFT and S transform are determined by the lowest value of mean absolute percentage error (MAPE). The results demonstrate that S transform gives better accuracy compare to STFT and is suitable for VSI switches faults detection and identification system.

Vibration-Based Fault Diagnosis of Pump Using WPT

2008 ◽  
Author(s):  
Pan Hong ◽  
Zheng Yuan
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Accurate Method ◽  
Singularity Analysis ◽  
Good Time ◽  
Signal Denoising ◽  
Good Tool ◽  
Time Frequency ◽  
Diagnosis Method

A vibration-based fault diagnosis method of pump units based on wavelet packet transform (WPT) is proposed in this paper. Compared with Fourier transform (FT) and wavelet transform (WT), WPT can subdivide the whole time-frequency domain. It can perform signals with good time resolution at high frequency and vice versa. WPT is considered as a good tool to signal denoising, accounting for its perfect ability in decomposing and reconstructing signal and its characteristic of no redundancy and divulges after denoising. In addition, WPT modulus maximal coefficient provides a simple but accurate method in calculating the Lipschitz exponents, which is the measurement of signal singularity. According to the singularity analysis results of vibration signal, we can recognize the fault pattern of pump units. This paper makes a detail research on signal denoising and singularity analysis based on WPT. Taking the main shaft and thrust bearing vibration signal for example, the experimental results show that WPT is effectively in the fault diagnosis system of pump unit.

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