APA 6th Edition Daemisch, G. (2015). Condition based (re)investment in transformer populations. Transformers Magazine, 2 (1), 42-48. Preuzeto s https://hrcak.srce.hr/182926
MLA 8th Edition Daemisch, Georg. "Condition based (re)investment in transformer populations." Transformers Magazine, vol. 2, br. 1, 2015, str. 42-48. https://hrcak.srce.hr/182926. Citirano 30.11.2020.
Chicago 17th Edition Daemisch, Georg. "Condition based (re)investment in transformer populations." Transformers Magazine 2, br. 1 (2015): 42-48. https://hrcak.srce.hr/182926
Harvard Daemisch, G. (2015). 'Condition based (re)investment in transformer populations', Transformers Magazine, 2(1), str. 42-48. Preuzeto s: https://hrcak.srce.hr/182926 (Datum pristupa: 30.11.2020.)
Vancouver Daemisch G. Condition based (re)investment in transformer populations. Transformers Magazine [Internet]. 2015 [pristupljeno 30.11.2020.];2(1):42-48. Dostupno na: https://hrcak.srce.hr/182926
IEEE G. Daemisch, "Condition based (re)investment in transformer populations", Transformers Magazine, vol.2, br. 1, str. 42-48, 2015. [Online]. Dostupno na: https://hrcak.srce.hr/182926. [Citirano: 30.11.2020.]
Sažetak Slowly but surely, condition-based maintenance is coming to be understood worldwide as the number-one choice for optimising the reliability and cost-effective service of transformers. Up to now, however, it has remained difficult to understand the actual condition of a transformer based only on traditional methods like water-in-oil or dissolved gas analysis (DGA) data. Also, widely used furan analysis for evaluating the paper degradation usually provides less than clear results. Many users try to work with any of the “standard methods” based on IEC or IEEE, or any other generalised method. Considering the problem of significantly different transformer designs and service data, this attempt will rarely be accurate and is usually doomed to fail. To this day, it remains in the realm of long-experienced specialists to truly understand the complete and complex data, and to also understand the defects and weakness of normally available values, and to finally come up with a reliable result which can be validly used as a basis for further maintenance decisions.