Signal analysis and time-frequency representation using SSA and adaptive AR methods

2018 ◽  
Author(s):  
Milton J. Porsani ◽  
Bjorn Ursin ◽  
Michelângelo G. Silva
Keyword(s):  
Signal Analysis ◽  
Time Frequency ◽  
Frequency Representation

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.

Signal Analysis for the Condition Monitoring of a Check Valve Using a Time-Frequency Representation

2004 ◽  
Vol 270-273 ◽  
pp. 209-214
Author(s):  
C.K. Lee ◽  
Dai Bum Cha ◽  
Jung Taek Kim ◽  
Joo Sun Kim ◽  
Sang J. Lee ◽  
...  
Keyword(s):  
Condition Monitoring ◽  
Signal Analysis ◽  
Check Valve ◽  
Time Frequency ◽  
Frequency Representation

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Extending Acoustic Microscopy for Comprehensive Failure Analysis Applications

2010 ◽  
Author(s):  
Sebastian Brand ◽  
Matthias Petzold ◽  
Peter Czurratis ◽  
Peter Hoffrogge
Keyword(s):  
Image Processing ◽  
Failure Analysis ◽  
Signal Analysis ◽  
Flip Chip ◽  
Fault Isolation ◽  
Acoustic Microscopy ◽  
Specific Information ◽  
Full Potential ◽  
Time Frequency ◽  
Non Destructive

Abstract In industrial manufacturing of microelectronic components, non-destructive failure analysis methods are required for either quality control or for providing a rapid fault isolation and defect localization prior to detailed investigations requiring target preparation. Scanning acoustic microscopy (SAM) is a powerful tool enabling the inspection of internal structures in optically opaque materials non-destructively. In addition, depth specific information can be employed for two- and three-dimensional internal imaging without the need of time consuming tomographic scan procedures. The resolution achievable by acoustic microscopy is depending on parameters of both the test equipment and the sample under investigation. However, if applying acoustic microscopy for pure intensity imaging most of its potential remains unused. The aim of the current work was the development of a comprehensive analysis toolbox for extending the application of SAM by employing its full potential. Thus, typical case examples representing different fields of application were considered ranging from high density interconnect flip-chip devices over wafer-bonded components to solder tape connectors of a photovoltaic (PV) solar panel. The progress achieved during this work can be split into three categories: Signal Analysis and Parametric Imaging (SA-PI), Signal Analysis and Defect Evaluation (SA-DE) and Image Processing and Resolution Enhancement (IP-RE). Data acquisition was performed using a commercially available scanning acoustic microscope equipped with several ultrasonic transducers covering the frequency range from 15 MHz to 175 MHz. The acoustic data recorded were subjected to sophisticated algorithms operating in time-, frequency- and spatial domain for performing signal- and image analysis. In all three of the presented applications acoustic microscopy combined with signal- and image processing algorithms proved to be a powerful tool for non-destructive inspection.

scholarly journals Strain Sensitivity Enhancement of Broadband Ultrasonic Signals in Plates Using Spectral Phase Filtering

2021 ◽  
Vol 11 (6) ◽  
pp. 2582
Author(s):  
Lucas M. Martinho ◽  
Alan C. Kubrusly ◽  
Nicolás Pérez ◽  
Jean Pierre von der Weid
Keyword(s):  
Fourier Transform ◽  
Guided Waves ◽  
Strain Level ◽  
Energy Concentration ◽  
Short Time Fourier Transform ◽  
Time Frequency ◽  
Frequency Representation ◽  
The Fourier Transform ◽  
Short Time ◽  
Sensitivity Gain

The focused signal obtained by the time-reversal or the cross-correlation techniques of ultrasonic guided waves in plates changes when the medium is subject to strain, which can be used to monitor the medium strain level. In this paper, the sensitivity to strain of cross-correlated signals is enhanced by a post-processing filtering procedure aiming to preserve only strain-sensitive spectrum components. Two different strategies were adopted, based on the phase of either the Fourier transform or the short-time Fourier transform. Both use prior knowledge of the system impulse response at some strain level. The technique was evaluated in an aluminum plate, effectively providing up to twice higher sensitivity to strain. The sensitivity increase depends on a phase threshold parameter used in the filtering process. Its performance was assessed based on the sensitivity gain, the loss of energy concentration capability, and the value of the foreknown strain. Signals synthesized with the time–frequency representation, through the short-time Fourier transform, provided a better tradeoff between sensitivity gain and loss of energy concentration.

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