Pattern classification
Development of an automated pattern classification for interpretable evaluation of machine data
| Funding: |
Bundesministerium für Wirtschaft und Klimaschutz (BMWK) |
| Funding code: | IGF-Vorhaben Nr. 22483 BR |
| Research association: |
Forschungskuratorium Maschinenbau e.V. Forschungsvereinigung Baumaschinen- und Baustoffanlagen e. V (FVB) |
| Partner: |
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| Duration: |
07/2022 – 09/2024 |
| Contact: |
The operation of mobile machines is characterised by changing environmental and operating conditions. Added to this is the influence of the operating personnel, who exert considerable influence on the machine with their control signals. Hydraulic drives have efficiency characteristics that depend on the operating point, resulting in different primary energy requirements depending on the user. Therefore, in addition to knowing the application profile of each construction machine, it is important to obtain information about the efficiency of each activity performed, so-called operating patterns, in order to incorporate this data into the development process or current operation.
The objectives of the research project are therefore, building on the results of the previous project, Frequency-based efficiency evaluation, to increase the recognition rate of operating patterns for a wide range of occurring activities, to recognise unknown operating patterns and their cycle time and, above all, to enrich the operating patterns with further practice-relevant features without greater sensory effort in order to generate statements that can be easily interpreted by the user (case I "offline": development engineer; case II "online": machine operating personnel). This can reduce the effort of a manual evaluation process of machine data (case I "offline").
In particular, smaller and medium-sized companies in the supplier industry and in the service sector are thus provided with a directly usable basis for interpretation. With the online assistant, it will be possible, in relation to the property "efficiency", to give the operator recommendations for action during operation in order to save fuel and optimise his process (case II "online"). This will benefit the many SMEs in the construction industry due to lower fuel costs and higher productivity.
