Increasing the availability of mobile work machines by forecasting machine status based on global data
- Mobile work machines are part of a logistical chain in which the failure of one machine can result in the standstill of other machines. Even relatively small failures can therefor cause high costs for the operator. Reliability and availability of the machines are therefore important parameters that have a decisive impact on planning certainty within construction and extraction processes. Mobile work machines are already equipped with a variety of sensors nowadays. Yet cost reasons and a lack of evaluation methods mean that these have so far not been systematically used for condition diagnosis and forecasting. The combination of lifetime estimation and failure diagnosis should lead to an on-board condition monitoring system.
- This project will link together all of the sensor data available on the machine to detect correlations between component damage and signal patterns and in parallel to determine the remaining service life of individual machines based on the operating loads actually encountered.
- Identification of typical damage signal patterns by means of test bed trials
- Development of a simulation model to determine internal loads based on globally available sensor data
- Development of a reliability model to determine the remaining service life of individual vehicles
- Transfer of the results to an on-board diagnostic system and implementation on a real test vehicle
Another aspect is the analysis of the effects of diverse winding configurations. Depending on the arrangement of the conductors of a winding, different voltage peaks occur between the conductors. This influence is investigated using a developed simulation model. The aim is to identify conductor configuration that enables a reduced ageing process of electrical equipment.
01.03.2017 - 28.02.2019