{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T19:44:38Z","timestamp":1780688678990,"version":"3.54.1"},"reference-count":55,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T00:00:00Z","timestamp":1616371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities. Dissolved gas analysis (DGA), as well as partial discharge (PD) tests considering different intelligent sensors for the measurement process, are used as diagnostic techniques for detecting the oil insulation level. This paper includes two parts; the first part is about the integration among the diagnosis results of recognized dissolved gas analysis techniques, in this part, the proposed techniques are classified into four techniques. The integration between the different DGA techniques not only improves the oil fault condition monitoring but also overcomes the individual weakness, and this positive feature is proved by using 532 samples from the Egyptian Electricity Transmission Company (EETC). The second part overview the experimental setup for (66\/11.86 kV\u201340 MVA) power transformer which exists in the Egyptian Electricity Transmission Company (EETC), the first section in this part analyzes the dissolved gases concentricity for many samples, and the second section illustrates the measurement of PD particularly in this case study. The results demonstrate that precise interpretation of oil transformers can be provided to system operators, thanks to the combination of the most appropriate techniques.<\/jats:p>","DOI":"10.3390\/s21062223","type":"journal-article","created":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T12:55:07Z","timestamp":1616417707000},"page":"2223","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":84,"title":["Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors"],"prefix":"10.3390","volume":"21","author":[{"given":"Sayed A.","family":"Ward","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Delta University for Science and Technology, Mansoura 11152, Egypt"},{"name":"Department of Electrical Engineering, Shoubra Faculty of Engineering, Benha University, Cairo 11629, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adel","family":"El-Faraskoury","sequence":"additional","affiliation":[{"name":"Extra High Voltage Research Centre, Egyptian Electricity Holding Company, Cairo 11517, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Badawi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Shoubra Faculty of Engineering, Benha University, Cairo 11629, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shimaa A.","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Shoubra Faculty of Engineering, Benha University, Cairo 11629, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6729-6809","authenticated-orcid":false,"given":"Karar","family":"Mahmoud","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, 02150 Espoo, Finland"},{"name":"Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9979-7333","authenticated-orcid":false,"given":"Matti","family":"Lehtonen","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, 02150 Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9782-8813","authenticated-orcid":false,"given":"Mohamed M. F.","family":"Darwish","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Shoubra Faculty of Engineering, Benha University, Cairo 11629, Egypt"},{"name":"Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, 02150 Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bustamante, S., Manana, M., Arroyo, A., Castro, P., Laso, A., and Martinez, R. (2019). Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review. Sensors, 19.","DOI":"10.3390\/s19194057"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dong, H., Yang, X., Li, A., Xie, Z., and Zuo, Y. (2019). Bio-Inspired PHM Model for Diagnostics of Faults in Power Transformers Using Dissolved Gas-in-Oil Data. 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