Examination of the sensitivity parameters to detect automatic cavitation in Hydro-turbines of the SefidRood dam considering remaining useful life

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.

Kohansal Sara; MARDOOKHPOUR ALIREZA

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

Journal Paper

Paper Information

Journal: JOURNAL OF HYDRAULICS Year:2019 | Volume:14 | Issue:1 (141) Page(s): 79-89

Download Full-Text

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

Persian Verion

View:

417

Download:

Cites:

Information Journal Paper

Title

Examination of the sensitivity parameters to detect automatic cavitation in Hydro-turbines of the SefidRood dam considering remaining useful life

Author(s)

Kohansal Sara | MARDOOKHPOUR ALIREZA | Issue Writer Certificate

Keywords

Hydro power plantQ1

Cavitation detectionQ1

Remaining useful life (RUL)Q1

Kaplan turbineQ1

MATLAB programQ1

Abstract

In this research, the evaluation of cavitation threshold detection and the automation of the detection process with regard to the Remaining Useful Life (RUL) of the Sefidrood power plant turbine, has been studied. The input of generated model by MATLAB program includes data driven from kaplan hydro turbine located on Tarik Hydro power plant. The proposed model is based on 61 features resulting from 6 cavitation sensitivity parameters and 17 operational conditions. For training in MATLAB program, 12 individual data sets and 4095 unique combinations were created and 408 data were selected for examination. The training data combined with sensor rating and cavitation sensitivity feature were employed to predict the cavitation and the best training data set with 98% accuracy. The results showed that the use of a fully automated process for sensitivity determination and cavitation classification was more suitable than the use of a process based on manually selected thresholds. Furthermore, considering the operational conditions and RUL, the automation of determination of cavitation threshold without human intervention was much more accurate.

Cites

No record.

References

No record.

Cite

APA: Copy

Kohansal, Sara, & MARDOOKHPOUR, ALIREZA. (2019). Examination of the sensitivity parameters to detect automatic cavitation in Hydro-turbines of the SefidRood dam considering remaining useful life. JOURNAL OF HYDRAULICS, 14(1 (141) ), 79-89. SID. https://sid.ir/paper/124222/en

Vancouver: Copy

Kohansal Sara, MARDOOKHPOUR ALIREZA. Examination of the sensitivity parameters to detect automatic cavitation in Hydro-turbines of the SefidRood dam considering remaining useful life. JOURNAL OF HYDRAULICS[Internet]. 2019;14(1 (141) ):79-89. Available from: https://sid.ir/paper/124222/en

IEEE: Copy

Sara Kohansal, and ALIREZA MARDOOKHPOUR, “Examination of the sensitivity parameters to detect automatic cavitation in Hydro-turbines of the SefidRood dam considering remaining useful life,” JOURNAL OF HYDRAULICS, vol. 14, no. 1 (141) , pp. 79–89, 2019, [Online]. Available: https://sid.ir/paper/124222/en

Related Journal Papers