Systems and methods for processing data collected in an industrial environment using neural networks

An expert system for processing a plurality of inputs collected from sensors in an industrial environment, comprising:

• a modular neural network, including at least two types of independent neural networks,
• wherein the modular neural network classifies a component of the industrial environment and predicts a state of the component of the industrial environment,
• wherein a first type of neural network of the at least two types of independent neural networks receives the plurality of inputs from the sensors and classifies the component of the industrial environment in real-time, resulting in a component classification,
• wherein a second type of neural network of the at least two types of neural networks predicts the state of the component in real-time based, at least in part, on the component classification from the first type of neural network, and
• wherein the state of the component is at least one of:
• a fault state, an operational state, an anticipated state, or a maintenance state.

A method for processing a plurality of inputs collected from sensors in an industrial environment, comprising:

• recognizing a pattern relating to at least one of the sensors or corresponding components in the industrial environment using a first type of neural network;
• adapting a structure of a second type of neural network, based, at least in part, on the pattern recognized using the first type of neural network;
• and
• self-organizing a data collection activity related to the at least one of the sensors or the corresponding components in the industrial environment using the second type of neural network.