Developing innovative technology for Industry 4.0
TWave is a company specialized in the design and manufacture of supervising and monitoring systems for industrial machinery.
We develop innovative solutions that integrate the most advanced technologies, helping our clients to protect their critical assets through online diagnosis. In this sense, our products are designed for Industry 4.0, applying the Internet of Things to the industrial sphere.
Predictive maintenance by vibration analysis is the main area of application of TWave devices, whose versatility makes them compatible with other predictive techniques such as ultrasonic analysis. The TWave technical team has been developing vibration monitoring systems for ten years. Hundreds of units have been successfully installed in industrial sectors such as wind, chemical, petrochemical or solar-thermal.
C/ Secundino Roces Riera 1, 2-P8
Parque Empresarial de Asipo
33428 Llanera, Asturias (Spain)
(+34) 984 508 934
info@twave.io
TWave, S.L. is developing the project "Autonomous and modular data acquisition system oriented to the condition monitoring of wind turbines" with reference IDE/2023/000382, within the framework of the call for grants for the implementation of R&D projects in the Principality of Asturias for the year 2023, co-financed by the Government of the Principality of Asturias through the SEKUENS AGENCY and the Science, Technology and Innovation Plan (PCTI) 2018-2022, as well as the European Union through the ERDF fund.
The main objective of the HYDROSES project is to increase the energy storage capacity of hydroelectric plants, which will make it possible to increase the share of renewable energy in the energy mix and promote the reduction of GHG emissions without disturbing the stability of the energy network. This objective will be addressed through various modifications and improvements in the operation of hydroelectric turbines to transform conventional hydroelectric plants into PHS facilities, improving their responsibility, flexibility and performance in both generating and pumping modes by developing of innovative predictive maintenance strategies and operation control, taking advantage of an innovative Digital Twin approach.
Project CPP2021-009116, financed by MCIN/AEI/10.13039/501100011033 and by the European Union-NextGenerationEU/PRTR
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