System and method for predicting failures of train components

A method of predicting failure and initiating one or more of repair, replacement, or operational protocols for a train component, the method comprising:

• acquiring real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a train operating under a variety of different conditions and in different geographical areas for use as training data from a data acquisition hub communicatively connected to a plurality of sensors associated with one or more locomotives of the train and one or more systems or components of the train;
• receiving results of a non-destructive evaluation of the train component at a virtual system modeling engine;
• using the virtual system modeling engine to simulate in-train forces using physics-based equations, kinematic or dynamic modeling of behavior of the train or components of the train during operation, and inputs derived from real time and historical contextual data comprising one or more of a number of locomotives in the train, age or amount of usage of one or more locomotives of the train or other components of the train, weight distribution of the train, length of the train, speed of the train, control configurations for one or more locomotives or consists of the train, power notch settings of one or more locomotives of the train, braking implemented in the train, and characteristics of train track on which the train is operating;
• determining a predicted time of failure for the train component based on an evaluation of stresses that have already been applied to the component, as determined by one or more of the non-destructive evaluation or physics-based equations, and expected future stresses to be applied to the train component, based on the simulated in-train forces;
• and
• implementing one or more of repair, replacement, or operational protocols for the train component before or at a repair facility that will be reached by the train ahead of a predetermined minimum threshold time period before the predicted time of failure.

A system, comprising:

• a data acquisition hub communicatively connected to one or more of databases and a plurality of sensors associated with one or more locomotives, systems, or components of a train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains with the same or similar types of locomotives as the one or more locomotives under a variety of different conditions and in different geographical areas for use as training data;
• and
• a virtual system modeling engine configured to:
• receive results of a non-destructive evaluation of a train component;
• simulate in-train forces using physics-based equations, kinematic or dynamic modeling of behavior of the train or components of the train during operation, and inputs derived from real time and historical contextual data comprising one or more of a number of locomotives in the train, age or amount of usage of one or more locomotives of the train or other components of the train, weight distribution of the train, length of the train, speed of the train, control configurations for one or more locomotives or consists of the train, power notch settings of one or more locomotives of the train, braking implemented in the train, and characteristics of train track on which the train is operating;
• determine a predicted time of failure for the train component based on an evaluation of stresses that have already been applied to the component, as determined by one or more of the non-destructive evaluation or physics-based equations, and expected future stresses to be applied to the train component, based on the simulated in-train forces;
• and
• implement one or more of repair, replacement, or operational protocols for the train component before or at a repair facility that will be reached by the train ahead of a predetermined minimum threshold time period before the predicted time of failure.