Fault Detection & Classification using Machine Learning

In process & manufacturing applications identifying the onset of system abnormality / failure at the earliest is very crucial. Models which help in determining the occurrences of such abnormalities as "fault detection" models. The techniques to isolate the variables which are causing the abnormality is generally known as "fault identification". Along with these there are scenarios where the type of fault needs to be determined, this generally known as "Fault Classification or Diagnosis".

There are techniques in AI/ML to solve all of the above challenges. For example Recurrent Neural Network (RNN) can be used to process the time evolution data to build a classification model. As the system's behavior under each type of fault can be different , now with the Fault classification model using RNN whenever a fault occurs and the subsequent pattern of data helps in determining the type of fault. This is also know as Fault Diagnosis.