Autonomous fault diagnosis system using learning with queries

We propose a powerful method of building a neural network fault diagnosis system that automatically collects training data (failure examples) to improve diagnosis. The learning-with-queries technique in a neural network is used to select the fault position and create training data that will improve the recognition rate of the diagnosis system. This technique is applicable to a fault diagnosis of a large-scale systems such as telecommunication switching systems