Laboratory robustness validation of a humidity sensor system for the condition monitoring of grease-lubricated components for railway applications

Author:

Dubek KrisztiánORCID,Schneidhofer Christoph,Dörr NicoleORCID,Schmid Ulrich

Abstract

Abstract. The condition monitoring of the health status of lubricating greases used in axle box bearings can be realized by applying well-established electrical or optical measurement principles. Furthermore, some novel methods have been reported that make use of humidity sensors or of dielectric thermoscopy. One of the most important grease condition parameters is the water content of the lubricating grease, as water can degrade grease to the point that it is no longer able to provide suitable lubrication and can also damage the bearing due to corrosion and cavitation. In this study, a new approach for water detection in lubricated wagon components is presented that is based on commercially available humidity sensors. The core element of this sensor system is a robust humidity sensor mounted in the immediate atmosphere of the grease-lubricated wagon axle bearing. In the case of water intake, the humidity of the gaseous atmosphere above the grease increases and can be detected by the customized sensor concept Humidity Sensor in Axle Bearings (HSAB). As this sensor system has to be sufficiently robust, it must be able to withstand environmental impact factors. The most important of these factors are temperature, relative humidity, and mechanical load, like vibrations and shocks, depending on the relevant railway application. To mimic these field effects under controlled laboratory conditions, the “lab-to-field” approach was set up and employed. Of the utmost importance was the installation of a development environment for the sensors that enabled the transfer of laboratory results to the respective rail field application. As a result, the HSAB system shows promise with respect to enhancing the reliability of railway wagons and decreasing maintenance costs, thereby reducing the downtime of railway wagons significantly.

Funder

Österreichische Forschungsförderungsgesellschaft

Horizon 2020

Publisher

Copernicus GmbH

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