Ultra low power wireless multi-sensor platform dedicated to machine tool condition monitoring
| Autor: | Axel Boness, Johannes Ellinger, Adrien Faucon, Anne Sanz Arrizabalaga, Tristan Caroff, Sebastien Brulais |
|---|---|
| Přispěvatelé: | Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Zentrum Mathematik [Munchen] (TUM), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Technische Universität München [München] (TUM) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Moving parts business.product_category business.industry Computer science Frame (networking) Real-time computing Condition monitoring 02 engineering and technology Accelerometer Preventive maintenance Industrial and Manufacturing Engineering Machine tool [SPI]Engineering Sciences [physics] 020303 mechanical engineering & transports 020901 industrial engineering & automation 0203 mechanical engineering Artificial Intelligence Wireless business Communications protocol |
| Zdroj: | Procedia Manufacturing Procedia Manufacturing, 2020, 51, pp.296-301. ⟨10.1016/j.promfg.2020.10.042⟩ Procedia Manufacturing, Elsevier, 2020, 51, pp.296-301. ⟨10.1016/j.promfg.2020.10.042⟩ |
| ISSN: | 2351-9789 |
| DOI: | 10.1016/j.promfg.2020.10.042⟩ |
| Popis: | The H2020 PreCoM project aims at developing and deploying a predictive cognitive maintenance decision-support system for production equipment such as machine tools. The PreCoM system intends to identify and localize damage, predict its evolution, assess remaining lifetime, and increase in-service efficiency of machines by conducting preventive maintenance actions. In this PreCoM system, additional sensors are needed to gather measurements close to critical parts/tools in order to improve failure detection. Commercial wireless sensor nodes are too restrictive regarding requirements for condition monitoring on industrial machine tools (50 g acceleration, 50 m long wireless range, several month lifetime, presence of cooling fluid and hot metal chips projection). Therefore, a dedicated wireless multi-sensor platform has been designed and developed in the frame of this project in order to provide additional measurements on highly moving parts, such as spindle head. The PreCoM wireless sensor nodes are integrating a 50 g/10 kHz - 3 axes accelerometer and a temperature sensor. They have been designed to be standalone devices with lifetime of around 1 year, and to fit all the machine tool environment requirements. The wireless sensor nodes are based on ultra-low power electronic devices and communication protocols to minimize their power consumption during all phases: sensing, communication and sleeping mode. Those sensor nodes and their associated wireless platform have been successfully developed and tested in representative environment in laboratory, and then deployed on pilot machine tools within the PreCoM maintenance system. |
| Databáze: | OpenAIRE |
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