Early detection and prediction of mechanical malfunction of machinery by sound analysis

Información del proyecto

neuronSW

Identificador del acuerdo de subvención: 808225

DOI 10.3030/808225

Proyecto cerrado

Fecha de la firma de la CE 22 Enero 2018

Fecha de inicio 1 Febrero 2018

Fecha de finalización 31 Mayo 2018

Financiado con arreglo a

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Coste total € 71 429,00

Aportación de la UE € 50 000,00

Coordinado por

NEURONSW LTD
United Kingdom

Objetivo

This project is intended to resolve the hurdle of lack of predictive maintenance in industries. The elimination of the risk of downtime and the reduction of maintenance costs are precious for the industry, because it is currently a barrier for increasing the production and accelerating creation of better products that can provide higher profits. Therefore, the industry has strong need to adapt an easy-to-implement and easy-to-use solution. This led NEURONSW LTD. to the concept of prediction of mechanical malfunction of machinery by mechanical sound analysis.

Neuron soundware (NeuronSW) is an innovative breakthrough solution combining advanced algorithms, machine learning and big data analysis to emulate the human auditory cortex enabling the early detection and prediction of mechanical malfunction of machinery. Through NeuronSW, manufacturers achieve intelligent audio diagnostics to monitor the key machinery equipment using the sound they generate. The integrated hardware and software platform automatically gathers sound of machines in real time and continuously assess the equipment health and operates similarly how experienced technicians use their ears to diagnose broken machines. It works offline and online and can be integrated into existing software or third party IoT platforms. This effectively transforms data into knowledge and actions. Sound and vibration sensors (microphones) can be quickly and cheaply installed on all types of machinery, enabling assets without digital interface or operated by legacy systems to be digitalized without expensive upgrades.

Ámbito científico

Not validated

• natural sciences › computer and information sciences › internet › internet of things
• natural sciences › computer and information sciences › software
• natural sciences › computer and information sciences › data science › big data
• engineering and technology › electrical engineering, electronic engineering, information engineering › electronic engineering › sensors
• natural sciences › computer and information sciences › artificial intelligence › machine learning

Programa(s)

• H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) Main Programme
• H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument

Tema(s)

• SMEInst-01-2016-2017 - Open Disruptive Innovation Scheme

Convocatoria de propuestas

H2020-SMEInst-2016-2017

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-SMEINST-1-2016-2017

Régimen de financiación

SME-1 - SME instrument phase 1

Coordinador

NEURONSW LTD

• Aportación neta de la UEn: € 50 000,00
• Dirección: 71-75 SHELTON STREET, COVENT GARDEN ; WC2H 9JQ LONDON ; Reino Unido
• Pyme Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención. Sí:
  Región
  London › Inner London — West › Camden and City of London
• Región: London › Inner London — West › Camden and City of London
• Tipo de actividad: Private for-profit entities (excluding Higher or Secondary Education Establishments)
• Coste total: € 71 429,00