Predictive analysis system and method for analyzing and detecting machine sensor failures

1. A system for performing predictive analysis and diagnostics, the system comprising:

a plurality of sensors communicatively coupled to a vehicle electronics unit, the plurality of sensors each being configured to generate at least one first signal indicative of a first sensed condition and at least one second signal indicative of a second sensed condition;

a remote central processing system coupled to the vehicle electronics unit, the remote central processing system comprising a remote processor and a remote data storage device, wherein the remote central processing system is configured to receive each of the at least one first and second signals;

storing a digital representation of the first signal in a data storage device; and

a predictive diagnostic unit arranged in the remote data storage device, the predictive diagnostic unit comprising machine readable instructions that, when executed by the remote processor, cause the system to:

partition the second signal into a predetermined number of successive time intervals;

generate a similarity value based on a comparative analysis of the second signal and the first signal; and

determine an estimated degree of failure of a machine component based in part on a computed average of the similarity value.

2. The system of claim 1 , wherein the first signal is a baseline signal and the second signal is a failure analysis signal, and wherein the first sensed condition corresponds to a healthy signal condition and the second sensed condition corresponds to a degenerative signal condition.

3. The system of claim 1 , wherein the predictive diagnostic unit comprises a data acquisition module, a comparison module, and a failure analysis module.

4. The system of claim 3 , wherein the failure analysis module comprises a classifier unit that generates groups of data related to anticipated events based on a comparative analysis of a failure analysis signal and a baseline signal.

5. The system of claim 4 , wherein the failure of analysis module is configured to generate a threshold value for estimating failures based on a determined estimated degree of failure.

6. The system of claim 1 , wherein the plurality of sensors comprises one or more of the following: a speed sensor, a temperature sensor, an engine operation sensor, an engine controller sensor, an oxygen sensor, or combinations thereof.

7. The system of claim 1 , wherein the predetermined number of successive time intervals and a duration of each time interval is determined based on a duration of a triggering event.

8. The system of claim 7 , wherein the triggering event includes a fuel injection period of an engine.

9. A method for performing predictive analysis and diagnostics, the method comprising:

generating a first and a second signal relating to a sensed condition;

transmitting the first and the second signal to a remote central processing system from a vehicle electronics unit;

receiving the first and the second signal by a predictive diagnostic unit arranged in a remote data storage device of the remote central processing system;

sampling each of the first and second signals at a predetermined sampling rate to generate a plurality of sampling segments;

analyzing the plurality of sampling segments with respect to at least one first signal during a predetermined time window to determine a similarity value; and

determining an estimated degree of failure based at least in part on the determined similarity value.

10. The method of claim 9 , wherein analyzing the plurality of sampling segments with respect to at least one first signal comprises generating groups of data sets related to anticipated events.

11. The method of claim 9 , wherein determining a similarity value comprises computing an angle between at least two vectors of the first and second signals.

12. The method of claim 9 , wherein the predetermined sampling rate is determined based on a triggering event.

13. The method of claim 9 further comprising computing a weight ratio based on a determined root mean square (RMS) value of the first and the second signal.

14. The method of claim 9 further comprising generating a threshold value based on the determined estimated degree of failure.