When the machine emits an abnormal noise, the AI application helps people to identify the signs of equipment malfunction or the need of maintenance.
The world once witnessed many incidents that caused great damage to people, materials due to broken, unsafe equipment was not detected early for maintenance. The most recent example is the explosion of a chemical plant in Hebei Province (China), killed 22 people, injured 22 people in late November.
In the factories, when operating the machines often emit sounds generated by moving parts in the machine. Some parts make sounds such as electric motors, compressors, gearboxes, blowers, pumps, starter motors …
For this unit, when operating under normal conditions, the sound will emit at a certain threshold. If the device is operating long with high frequency, it starts to make abnormal sounds or loud sounds, indicating that the engine is unstable and there is a risk of broken.
In large manufacturing companies, when a device in the operation line is not good, it can cause slow progress, even leading to pitiful incidents.
The advantage of technology, especially the AI applications in manufacturing, helps people build an automated, safe and efficient process.
With the aim of “Bringing technology to life, making life better”, the technology experts of FPT Software applied Deep Learning techniques to find solutions to monitor the status of equipment in the factory through the sound analysis process.
By the sound analysis from vacuum cleaners to determine whether they work well or not, the FPT Software engineers expand the scope of application to other machines in the factory.
The application of equipment monitoring technology through engine audio analysis helps the companies easily manage and monitor 24/7 status of machines, especially in Smart Factory factories without the participation of human. Thereby contributing to create a closed and stable production process to produce high quality products.