Systems and methods for prediction of component degradation

A system, comprising:

• a center bearing sensor system comprising a temperature sensor, a displacement sensor, and an accelerometer wired to a battery integrally arranged in a bearing compartment;
• a processor and memory with instructions stored therein, including instructions to send real-time data to a remote cloud, the processor and memory coupled with the battery and the bearing sensor system and instructions for a subscription for on-line processing of data generated via the sensor system at the remote cloud, and access to software for receiving analysis results of the data from the cloud;
• wherein:
• the battery is configured to be integrally arranged in a bearing compartment arranged between a top plate and a center bearing bracket and separating the top plate from the center bearing bracket, the center bearing bracket physically coupled to the top plate via two or more coupling elements, the two or more coupling elements configured to physically couple the center bearing bracket and the top plate to an underbody of the vehicle;
• the data is sent to the cloud in response to a connection to the cloud being available;
• and
• a condition of the center bearing and/or a shaft of the center bearing is predicted using a machine learning (ML) model stored at the cloud, the ML model performing a degradation analysis of the shaft, the ML model continuously updated via a second set of data provided from a plurality of vehicles, the second set of data categorized based on driving conditions of each vehicle of the plurality of vehicles, wherein the driving conditions include one or more of a vehicle make, a vehicle model, a vehicle maintenance history, a vehicle location, a driver behavior, a vehicle average speed, an average vehicle weight, a vehicle odometer reading, a terrain driven, a suspension traveled distance, a cargo weight, and aftermarket devices.

A kit for a center bearing of a vehicle, the kit comprising:

• a battery and a sensor system including a temperature sensor, a displacement sensor, and an accelerometer configured to be wired to the battery;
• a processor and memory with instructions stored therein, including instructions to send real-time data to a remote cloud, the processor and memory coupled with the battery and the sensor system;
• and
• instructions for a subscription for on-line processing of data generated via the sensor system at the remote cloud, and access to software for receiving analysis results of the data from the cloud;
• wherein:
• the battery is configured to be integrally arranged in a bearing compartment arranged between a top plate and a center bearing bracket and separating the top plate from the center bearing bracket, the center bearing bracket physically coupled to the top plate via two or more coupling elements, the two or more coupling elements configured to physically couple the center bearing bracket and the top plate to an underbody of the vehicle;
• the data is sent to the cloud in response to a connection to the cloud being available;
• and
• a condition of the center bearing and/or a shaft of the center bearing is predicted using a machine learning (ML) model stored at the cloud, the ML model performing a degradation analysis of the shaft, the ML model continuously updated via a second set of data provided from a plurality of vehicles, the second set of data categorized based on driving conditions of each vehicle of the plurality of vehicles, wherein the driving conditions include one or more of a vehicle make, a vehicle model, a vehicle maintenance history, a vehicle location, a driver behavior, a vehicle average speed, an average vehicle weight, a vehicle odometer reading, a terrain driven, a suspension traveled distance, a cargo weight, and aftermarket devices.