Experienced operators can easily tell if the machine they’re currently working on is facing a malfunction just by listening to the sounds it makes. A new sound software let us hope that, soon, everyone will have this capacity.

Indeed, EU-funded researchers have been developing an advanced technology based on the human auditory system. This tool can analyze if the industrial machinery is due for maintenance thanks to a sound analysis.

This is a very great news for anyone who wants to eliminate the risk of downtime and reducing maintenance costs. They are actually very important for the industry as these factors affect quality and productivity while decreasing profits. The solution seems to be easy to implement and simple to use.

The EU-funded Horizon2020 neuronSW project resulted in developing an innovative ground-breaking approach for predicting mechanical malfunction in industrial machinery.

Researchers combined machine learning, advanced algorithms, and Big Data analysis to imitate the human auditory cortex and enable the early detection and prediction of mechanical breakdown. The result is very promising

“The technology leverages machine learning, the cloud and the Internet of Things (IoT) to deliver a detection service which emulates human intuition about sound,” says Jiří Čermák, technical manager of project partner SME NeuronSW Ltd.

What is the Neuron Soundware Technology?

Thanks to the Neuron soundware technology (neuronSW), manufacturers can conduct intelligent audio diagnostics and monitor key items of machinery by the sounds they produce.

“The integrated hardware and software platform automatically gather the sound of machines in real time and continuously assesses the equipment’s health. It works in a similar way to experienced operators who use their ears to diagnose broken machines,” explains Čermák.

A big advantage of the system is that it works both online and offline and can be integrated into third-party IoT platforms or existing software.

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“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.”

There are almost no limits to the application of the audio diagnostic technology, which can be used for anything that has a moving part and produces sound.

“However, it makes the most sense to first focus on critical pieces of machinery, expensive assets, quality control, and on assets in remote areas with difficult access” Čermák points out.

He continues: “Different industries cooperated with NeuronSW to create solutions for heavy machinery, including cogeneration engines, automotive fuel pumps, wind turbines, escalators, AC systems, PC assembly, quality control of electric motors, and predictive maintenance of packaging machines.”

What is the future of a predictive sound maintenance feature? 

According to NeuronSW Ltd’s Sales Manager, Michal Bambušek, the project also focused on marketing plans and sales.

“We made some new important business contacts that helped us discover some new areas and uses for our technology, which helped to enhance it and allowed us to progress.”

“We trained sales staff and identified key markets and go-to-market strategies for the neuronSW technology and conducted case studies to develop and adapt it to different fields,” he says.

Both people and machine are having a clear benefit from the technology developed through this initiative.

“We believe that in the future predictive sound maintenance will become a standard feature of most machines with moving parts, helping manufacturers and operators alike.

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