System, apparatus and method of condition based management of one or more electro-mechanical systems

1. A computer implemented method of condition-based management of an electro-mechanical system, the method comprising:

generating a stress profile for the electro-mechanical system based on operating or simulating operation of the electro-mechanical system in accordance with a load profile, wherein the stress profile is indicative of a distribution of stress on the electro-mechanical system during operation or during simulation of the operation, wherein the distribution of stress is a distribution of electrical stress, mechanical stress, and process stress applied to the electro-mechanical system, and wherein the load profile is indicative of operation duration and load capacity of the electro-mechanical system;

receiving condition data associated with the electro-mechanical system in operation from a plurality of sensing units;

generating an accelerated degradation model using a digital twin of the electro-mechanical system when the electro-mechanical system is operated above a rated stress defined for the electro-mechanical system, wherein the digital twin comprises a cumulative damage model of the electro-mechanical system, wherein the cumulative damage model is formed by computing a life probability distribution for the electro-mechanical system and determining a time-damage accumulation of the electro-mechanical system based on historical condition data of the electro-mechanical system;

predicting a failure instance of the electro-mechanical system using the accelerated degradation model based on at least one of the stress profile and the condition data; and

comparing the predicted failure instance with an actual failure instance upon failure of the electro-mechanical system to tune the accelerated degradation model.

2. The method of claim 1 , further comprising:

predicting a new remaining life of the electro-mechanical system based on the tuned accelerated degradation model.

3. The method of claim 2 , further comprising:

predicting a fleet life of a fleet of electro-mechanical systems using the accelerated degradation model.

4. The method of claim 1 , further comprising:

determining an accelerated-mechanical response from the electro-mechanical system,

wherein the accelerated-mechanical response comprises condition data that reflect a mechanical fault in the electro-mechanical system, and

wherein the mechanical fault comprises a misalignment of components of the electro-mechanical system, a loss of structural integrity of the components, or a combination thereof.

5. The method of claim 4 , further comprising:

predicting a fleet life of a fleet of electro-mechanical systems using the accelerated degradation model.

6. The method of claim 1 , further comprising:

determining an accelerated-electrical response from the electro-mechanical system,

wherein the accelerated-electrical response comprises condition data that reflect an electric fault in the electro-mechanical system, and

wherein the electric fault comprises a high voltage, a low voltage, a high current, a low current, a short-circuit, or a combination thereof.

7. The method of claim 6 , further comprising:

predicting a fleet life of a fleet of electro-mechanical systems using the accelerated degradation model.

8. The method of claim 1 , further comprising:

determining an accelerated-process response from the electro-mechanical system,

wherein the accelerated-process response comprises condition data that reflect a process fault due to overload of the electro-mechanical system.

9. The method of claim 8 , further comprising:

predicting a fleet life of a fleet of electro-mechanical systems using the accelerated degradation model.

10. The method of claim 1 , wherein the accelerated degradation model based on the digital twin is generated by:

simulating an accelerated-mechanical response, an accelerated-electrical response, and an accelerated-process response on the digital twin of the electro-mechanical system to generate simulation responses; and

predicting an accelerated remaining life of the electro-mechanical system based on the simulation responses.

11. The method of claim 1 , further comprising:

predicting a fleet life of a fleet of electro-mechanical systems using the accelerated degradation model.

12. The method of claim 11 , further comprising:

updating the fleet life based on variability between the electro-mechanical systems in the fleet,

wherein the fleet life is updated using a neural network.

13. An apparatus for condition-based management of an electro-mechanical system, the apparatus comprising:

one or more processing units; and

a memory communicative coupled to the one or more processing units, wherein the memory is configured, with the one or more processing units, to:

generate a stress profile for the electro-mechanical system based on operating or simulating operation of the electro-mechanical system in accordance with a load profile, wherein the stress profile is indicative of a distribution of stress on the electro-mechanical system during operation or during simulation of the operation, wherein the distribution of stress is a distribution of electrical stress, mechanical stress, and process stress applied to the electro-mechanical system, and wherein the load profile is indicative of operation duration and load capacity of the electro-mechanical system;

receive condition data associated with the electro-mechanical system in operation from a plurality of sensing units;

generate an accelerated degradation model using a digital twin of the electro-mechanical system when the electro-mechanical system is operated above a rated stress defined for the electro-mechanical system, wherein the digital twin comprises a cumulative damage model of the electro-mechanical system, wherein the cumulative damage model is formed by computing a life probability distribution for the electro-mechanical system and determining a time-damage accumulation of the electro-mechanical system based on historical condition data of the electro-mechanical system;

predict a failure instance of the electro-mechanical system using the accelerated degradation model based on at least one of the stress profile and the condition data; and

compare the predicted failure instance with an actual failure instance upon failure of the electro-mechanical system to tune the accelerated degradation model.

14. A system comprising:

one or more devices capable of providing condition data associated with condition of one or more electro-mechanical systems;

a server communicatively coupled to the one or more devices, wherein the server is configured to:

generate a stress profile for the one or more electro-mechanical systems based on operating or simulating operation of the one or more electro-mechanical systems in accordance with a load profile, wherein the stress profile is indicative of a distribution of stress on the or more electro-mechanical systems during operation or during simulation of the operation, wherein the distribution of stress is a distribution of electrical stress, mechanical stress, and process stress applied to the electro-mechanical system, and wherein the load profile is indicative of operation duration and load capacity of the one or more electro-mechanical systems;

receive condition data associated with the one or more electro-mechanical systems in operation from a plurality of sensing units;

generate an accelerated degradation model using a digital twin of the electro-mechanical system when the electro-mechanical system is operated above a rated stress defined for the electro-mechanical system, wherein the digital twin comprises a cumulative damage model of the electro-mechanical system, wherein the cumulative damage model is formed by computing a life probability distribution for the electro-mechanical system and determining a time-damage accumulation of the electro-mechanical system based on historical condition data of the electro-mechanical system;

predict a failure instance of the one or more electro-mechanical systems using the accelerated degradation model based on at least one of the stress profile and the condition data; and

compare the predicted failure instance with an actual failure instance upon failure of the one or more electro-mechanical systems to tune the accelerated degradation model.