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To ensure a reliable energy supply, the evaluation of the insulation condition of key components is a basic need. Today automated partial discharge diagnosis and monitoring systems are able to assess that information. However, also the PD diagnosis has to be reliable to avoid cost intensive misjudgments, even under noisy conditions on-site. This contribution examines the influences of different noise sources on the efficiency and reliability of automated PD defect identification. The different noise sources are investigated to deduce minimum requirements for UHF measurements under noisy conditions to enable an expert independent defect identification. These investigations consider the influence of noise on relevant PD features and diagnostic tools. The enquiries comprise periodic noise sources e.g. WLAN, Bluetooth or mobile and DECT phones. All these disturbances emit signals in the UHF band, which is used for PD-detection. In the lower frequency range the GIS compartment works as a good electric shield, but small apertures (e.g. inspection windows) can open any compartment for UHF interference.