Equipment failure diagnosis apparatus, equipment failure diagnosis method, smart factory system and application agent

An equipment failure diagnosis method comprising:

• generating a virtual abnormal signal based on a normal signal data stored in a database;
• obtaining an equipment signal generated from a target equipment;
• and
• determining whether the equipment signal is an abnormal signal based on the virtual abnormal signal, and outputting determination result information.

An application agent stored and executed in a storage medium in a computer in order to execute a method for diagnosing equipment failure, the method comprising:

• generating a virtual abnormal signal based on a normal signal data stored in a database;
• obtaining an equipment signal generated from a target equipment through at least one microphone device;
• and
• determining whether the equipment signal is an abnormal signal based on the virtual abnormal signal, and outputting determination result information.

A smart factory system comprising:

• a first sensor installed around a first equipment and configured to sense and output acoustic signals;
• a second sensor installed around a second equipment and configured to sense and output acoustic signals;
• and
• an equipment failure diagnosis apparatus configured to diagnose whether each of the first equipment and the second equipment has a failure,
• wherein the equipment failure diagnosis apparatus is configured to:
• extract a first equipment signal generated by the first equipment from the acoustic signal output from the first sensor,
• extract a second equipment signal generated by the second equipment from the acoustic signal output from the second sensor,
• determine whether each of the first equipment signal and the second equipment signal is an abnormal signal by referring to an artificial intelligence network model in an artificial intelligence archive, and database, and output the determination result information, and
• add a new artificial intelligence network model to the artificial intelligence archive, or label a data for each of the first equipment signal and the second equipment signal as normal signal data or abnormal signal data and store the labeled data in the database.