Method of monitoring a state of a machine learning classifier

An aircraft system comprising:

• a machine learning classifier configured to determine an operational mode of the aircraft system, the machine learning classifier having an input layer comprising input nodes, an output layer comprising output nodes, at least one hidden layer between the input layer, and the output layer, wherein the at least one hidden layer comprising hidden layer nodes, and the machine learning classifier is configured to provide an output for determining the operational mode;
• and
• a controller configured to run the machine learning classifier that causes one or more hardware processors to perform operations comprising:
• loading data for a model of the aircraft system, wherein the model comprises representations of:
• a) components configured to operate as part of the aircraft system, and b) connections between the components of the aircraft system, wherein each component in the aircraft system is associated with an operational mode status, and the connections between the components defining a plurality of series component paths within the representations of the aircraft system, each respective series component path of the plurality of series component paths having an order of priority for the respective components in the respective series component path and a set of operational mode status combinations;
• applying, to each input node of the machine learning classifier, an operational mode status of a respective component and a node priority of the order of priority of the respective series component path;
• varying, for an operational mode status combination, an input node state of at least one of the input nodes having a relatively low node priority;
• and
• determining a state of the machine learning classifier based on determining whether a hidden layer node state and/or an output node state vary in response to the varying of the input node state;
• wherein the state of the machine learning classifier is determined to be a normal state as a result of determination that output node states do not vary in response to the varying of the input node state,
• wherein the state of the machine learning classifier is determined to be an altered state as a result of determination that a hidden layer node state and an output node state vary in response to the varying of the input node state.

A non-transitory machine readable storage medium storing machine-readable instructions for use with one or more processors of an aircraft system that comprises a machine learning classifier, the machine learning classifier configured to determine an operational mode of an aircraft system, the machine learning classifier having an input layer comprising input nodes, an output layer comprising output nodes, at least one hidden layer between the input layer and the output layer, the at least one hidden layer comprising hidden layer nodes, and the machine learning classifier configured to provide an output for determining the operational mode, the machine-readable instructions comprising instructions that cause the one or more processors to perform operations comprising:

• loading a model of the aircraft system, wherein the model comprises representations of:
• a) components configured to operate as part of the aircraft system, and b) connections between the components of the aircraft system, wherein each component in the aircraft system is associated with an operational mode status, and the connections between the components defining a plurality of series component paths within the representations of the aircraft system, each respective series component path of the plurality of series component paths having an order of priority for the respective components in the respective series component path and a set of operational mode status combinations;
• applying, to each input node of the machine learning classifier, an operational mode status of a respective component and a node priority of the order of priority of the respective series component path;
• varying, for an operational mode status combination, an input node state of at least one of the input nodes having a relatively low node priority;
• and
• determining a state of the machine learning classifier based on determining whether a hidden layer node state and/or an output node state vary in response to the varying of the input node state;
• wherein the state of the machine learning classifier is a normal state based on determination that output node states do not vary in response to the varying of the input node state,
• wherein the state of the machine learning classifier is an altered state based on determination that a hidden layer node state and an output node state vary in response to the varying of the input node state.