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©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Low pressure environments, situate insulation systems in a challenging position since partial discharges (PDs), corona and arc tracking are more likely to develop. Therefore, specific solutions are required to detect such harmful phenomena before major failure occurrence. This paper deals with three low-cost and small-size sensing methods, i.e., a single loop antenna, a visible-UV imaging sensor and the measurement of the leakage current to detect corona in the early stage, thus anticipating the appearance of severer effects such as arc tracking or disruptive breakdown. The three studied methods can be applied for an on-line monitoring of corona activity under low pressure environments, thus being compatible with predictive maintenance approaches. This on-line monitoring can be used to develop improved electrical protection devices able to detect such effects in an initial stage, thus improving current solutions which are unable to do so. All three studied sensors give consistent linear responses within the studied pressure range, i.e., 10-100 kPa, with almost no drift. The sensitivity of the visible-UV imaging sensor is slightly lower than that of the others, but it has the advantage of directly locating the discharge points. Results presented in this paper can be very useful for the more electrical aircraft (MEA), which is forcing electrical distribution systems to operate at higher voltage levels. Due to the little experience and scarcity of published data, the experimental results presented in this paper can be valuable for a better understanding of the combined action of high voltage and low pressure environments. This work was supported in part by the Generalitat de Catalunya under Project 2017 SGR 967 & in part by the Spanish Ministry of Science and Innovation under Project RTC-2017-6297-3. J.-R. Riba is with the Universitat Politècnica de Catalunya