Claims:WE CLAIM
1. A method for detecting an anomaly in an aircraft, the method comprising:
obtaining, by a big data analytic computing device, aircraft flight data acquired from multiple aircraft sensor devices;
clustering, by the big data analytic computing device, the obtained aircraft flight data into two or more data groups;
determining, by the big data analytic computing device, a distance between the clustered aircraft flight data in one of the two or more groups associated with a part of the aircraft and stored baseline flight data for the part of the aircraft; and
executing, by the big data analytic computing device, a statistical model analysis on the determined distance to detect any anomaly with the part of the aircraft.

2. The method as set forth in claim 1 wherein the clustering the obtained aircraft flight data further comprises grouping, by the big data analytic computing device, the obtained aircraft flight data into a resilient distributed dataset.

3. The method as set forth in claim 1 wherein the determining the distance further comprises computing, by the big data analytic computing device, one or more of a Euclidean distance, a dynamic time warping distance or a correlation-based distance between the clustered aircraft flight data in one of the two or more groups associated with the part of the aircraft and the stored baseline flight data for the part of the aircraft.

4. The method as set forth in claim 1 wherein the executing further comprises executing, by the big data analytic computing device, at least one of a regression model, a Markovian model, or a compression model on the determined distance to detect the anomaly with the part of the aircraft.

5. The method as set forth in claim 1 further comprising computing, by the big data analytic computing device, at least one of a mean time between failure, mean time between critical failure, or mean time to repair for the part based on the detected anomaly with the part of the aircraft.

6. The method as set forth in claim 1 further comprising generating and providing, by the big data analytic computing device, a graphical display of the detected anomaly with the part of the aircraft.

7. A big data analytic computing device, comprising:
one or more processors;
a memory coupled to the one or more processors which are configured to be capable of executing programmed instructions stored in the memory to and that comprise:
obtain aircraft flight data acquired from multiple aircraft sensor devices;
cluster the obtained aircraft flight data into two or more data groups;
determine a distance between the clustered aircraft flight data in one of the two or more groups associated with a part of the aircraft and stored baseline flight data for the part of the aircraft; and
execute a statistical model analysis on the determined distance to detect any anomaly with the part of the aircraft.

8. The device as set forth in claim 7 wherein the programmed instruction to cluster the obtained aircraft flight data comprises an instruction to group the obtained aircraft flight data into a resilient distributed dataset.

9. The device as set forth in claim 7 wherein the instruction to determine the distance comprises an instruction to compute one or more of a Euclidean distance, a dynamic time warping distance or a correlation-based distance between the clustered aircraft flight data in one of the two or more groups associated with the part of the aircraft and the stored baseline flight data for an part of the aircraft.

10. The device as set forth in claim 7 wherein the instruction to execute the statistical model analysis comprises an instruction to execute at least one of a regression model, a Markovian model, or a compression model on the determined distance to detect the anomaly with the part of the aircraft.

11. The device as set forth in claim 7 wherein the processor is further configured to be capable of executing programmed instructions stored in the memory to compute at least one of a mean time between failure, mean time between critical failure, or mean time to repair for the part based on the detected anomaly with the part of the aircraft.

12. The device as set forth in claim 7 wherein the processor is further configured to be capable of executing programmed instructions stored in the memory to generate and provide a graphical display of the detected anomaly with the part of the aircraft.

Dated this 30th day of October, 2015
Shwetha A Chimalgi
Of K&S Partners
Agent for the Applicant
, Description:FIELD
This technology generally relates to methods and devices for detecting anomalies and, more particularly, to methods for detecting one or more aircraft anomalies and devices thereof.