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

Project Information

neuronSW

Grant agreement ID: 808225

DOI 10.3030/808225

Project closed

EC signature date 22 January 2018

Start date 1 February 2018

End date 31 May 2018

Funded under

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

Total cost € 71 429,00

EU contribution € 50 000,00

Coordinated by

NEURONSW LTD
United Kingdom

Objective

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.

Fields of science

• 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

Programme(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

Topic(s)

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

Call for proposal

H2020-SMEInst-2016-2017

See other projects for this call

Sub call

H2020-SMEINST-1-2016-2017

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

NEURONSW LTD

• Net EU contribution: € 50 000,00
• Address: 71-75 SHELTON STREET, COVENT GARDEN ; WC2H 9JQ LONDON ; United Kingdom
• SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes:
  Region
  London › Inner London — West › Camden and City of London
• Region: London › Inner London — West › Camden and City of London
• Activity type: Private for-profit entities (excluding Higher or Secondary Education Establishments)
• Total cost: € 71 429,00