OPTIMAL PARAMETER ESTIMATION OF ULTRASONIC SIGNALS BY USING A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND GAUSS-NEWTON ALGORITHMS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

GHOLAMI ALI; HONARVAR FARHANG; ABRISHAMI MOGHADDAM HAMID

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Modares Mechanical Engineering Year:2015 | Volume:15 | Issue:1 Page(s): 236-244

Download Full-Text

Persian Verion

View:

657

Download:

Cites:

Information Journal Paper

Title

OPTIMAL PARAMETER ESTIMATION OF ULTRASONIC SIGNALS BY USING A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND GAUSS-NEWTON ALGORITHMS

Author(s)

GHOLAMI ALI | HONARVAR FARHANG | ABRISHAMI MOGHADDAM HAMID | Issue Writer Certificate

Keywords

ULTRASONIC TESTINGQ2

SIGNAL PROCESSINGQ2

GAUSS-NEWTON ALGORITHMQ2

PARTICLE SWARM OPTIMIZATION ALGORITHMQ2

GENETICS ALGORITHMQ2

Abstract

The echoes obtained from ULTRASONIC TESTING of materials contain valuable information about the geometry and grain structure of the test specimen. These echoes can be modeled by Gaussian pulses in a model-based estimation process. For precise modeling of an echo, the parameters of the Gaussian pulse should be estimated as accurately as possible. There are a number of algorithms that can be used for this purpose. In this study, three different algorithms are used: Gauss-Newton (GN), particle swarm optimization (PSO), and genetic algorithm (GA). The pros and cons of each of these three algorithms are reviewed and by combining them, the benefits of each algorithm are used while its shortcomings are avoided. For signals containing multiple echoes, the minimum description length (MDL) principle is used to estimate the numbers of required Gaussian echoes followed by space alternating generalized expectation maximization (SAGE) technique to translate it to separate echoes and to estimate the parameters of each echo. The performance of the proposed algorithms for simulated and experimental signals with overlapping and non-overlapping echoes is evaluated and is shown to be quite effective.

Cites

No record.

References

No record.

Cite

APA: Copy

GHOLAMI, ALI, HONARVAR, FARHANG, & ABRISHAMI MOGHADDAM, HAMID. (2015). OPTIMAL PARAMETER ESTIMATION OF ULTRASONIC SIGNALS BY USING A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND GAUSS-NEWTON ALGORITHMS. MODARES MECHANICAL ENGINEERING, 15(1), 236-244. SID. https://sid.ir/paper/179291/en

Vancouver: Copy

GHOLAMI ALI, HONARVAR FARHANG, ABRISHAMI MOGHADDAM HAMID. OPTIMAL PARAMETER ESTIMATION OF ULTRASONIC SIGNALS BY USING A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND GAUSS-NEWTON ALGORITHMS. MODARES MECHANICAL ENGINEERING[Internet]. 2015;15(1):236-244. Available from: https://sid.ir/paper/179291/en

IEEE: Copy

ALI GHOLAMI, FARHANG HONARVAR, and HAMID ABRISHAMI MOGHADDAM, “OPTIMAL PARAMETER ESTIMATION OF ULTRASONIC SIGNALS BY USING A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND GAUSS-NEWTON ALGORITHMS,” MODARES MECHANICAL ENGINEERING, vol. 15, no. 1, pp. 236–244, 2015, [Online]. Available: https://sid.ir/paper/179291/en

Related Journal Papers