What is the blind failure detection ?
What is the blind mode?
Blind failure detection is a machine learning method that enables the detection of equipment failure without having to rely on historical failure data or knowing the type of equipment or sensors being monitored.
It is based on the creation of a nominal operating space for the device when implementing the solution. The software uses the equipment’s healthy data to establish a normality space, with any result outside this space being considered as an anomaly and reported to the maintenance teams: this is what we call anomaly detection.
Our DiagFit software, based on a unique know-how and scientific intellectual property from the French National Centre for Scientific Research (CNRS), can detect faults with high accuracy and low error rates.
Blind mode, an asset for failure detection in Industry 4.0
At Amiral Technologies, “blind” has several meanings when it comes to our DiagFit failure detection software
DiagFit does not need to know the type of equipment or sensor it is monitoring. All this information can be anonymized.
DiagFit does not need to be enriched by the equipment failure history. Learning is based on the nominal operation of the equipment (unsupervised approach).
DiagFit does not need the imported training data to be labeled beforehand.
“ These advantages allow our customers to quickly deploy an automatic failure detection solution for their equipment. ”
Katia Hilal – Amiral Technologies CEO
Chalk & talk
Antoine Vignon, Data Scientist
Blind failure prediction
“Creating a blind failure prediction model comes down to characterizing the set of operating points [of the equipment] as best as possible.”
