IP Library Granted Patent US 12,601,658
Granted Patent B2
US 12,601,658 · App. 18/329,154 · Granted Apr 14, 2026

Determining the condition of moving parts of aircraft

Inventors: Daniel David Gilbertson (Florissant, MO); John Lyle Vian (Renton, WA)
Assignee: THE BOEING COMPANY
G01M99/005
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Quick Facts
Patent No.
US 12,601,658
App. No.
18/329,154
Granted
Apr 14, 2026
Kind
B2
Abstract

Techniques for assessing an operational condition of an uncrewed air transport platform are presented. The techniques include: arranging the uncrewed air transport platform and at least one external sensor in proximity to each other, where the at least one external sensor includes a vibration sensor; executing a sequence of operations of the uncrewed air transport platform; acquiring sensor data of the uncrewed air transport platform from the at least one external sensor; automatically analyzing the sensor data to detect at least one non-normal health signature of the uncrewed air transport platform; automatically diagnosing one or more degradation condition in the uncrewed air transport platform based on the at least one non-normal health signature; and providing an indication of the one or more degradation condition.

Claims (53)

1 . A method of assessing an operational condition of an uncrewed air transport platform, the method comprising:

arranging the uncrewed air transport platform and at least one external sensor in proximity to each other, wherein the at least one external sensor comprises a vibration sensor;

directing the at least one external sensor to the uncrewed air transport platform to sense at an indicated location on the uncrewed air transport platform;

executing a sequence of operations of the uncrewed air transport platform;

acquiring sensor data of the uncrewed air transport platform from the at least one external sensor;

automatically analyzing the sensor data to detect at least one non-normal health signature of the uncrewed air transport platform;

automatically diagnosing one or more degradation condition in the uncrewed air transport platform based on the at least one non-normal health signature; and

providing an indication of the one or more degradation condition.

2 . The method of claim 1 , wherein the vibration sensor comprises a stand-off vibration sensor.

3 . The method of claim 1 ,

wherein the uncrewed air transport platform comprises at least one internal sensor that is electrically unconnected to any uncrewed air transport platform system,

the method further comprising acquiring internal sensor data from the internal sensor,

wherein the sensor data comprises the internal sensor data.

4 . The method of claim 3 , wherein the acquiring the internal sensor data from the internal sensor comprises:

electrically connecting a wireless transceiver to the internal sensor; and

wirelessly acquiring the internal sensor data.

5 . The method of claim 1 , wherein the indication of the degradation condition comprises an indication of a fault, the method further comprising remediating the fault based on the indication of the fault.

6 . The method of claim 1 , wherein the indication of the degradation condition comprises an indication of a potential future fault, the method further comprising performing conditional maintenance on the uncrewed air transport platform based on the indication of the potential future fault.

7 . The method of claim 1 , further comprising providing a fiducial marker of the indicated location on an image of the uncrewed air transport platform.

8 . The method of claim 1 ,

wherein the sequence of operations comprises an activation of an actuator,

wherein the sensor data comprises actuator data of the actuator, and

wherein the at least one non-normal health signature comprises an indication of a degradation condition of the actuator.

9 . The method of claim 1 , wherein the automatically analyzing the sensor data comprises providing the sensor data to a trained machine learning system.

10 . A non-transitory computer readable medium comprising computer readable instructions that, when executed by an electronic processor, configure the electronic processor to assess an operational condition of an uncrewed air transport platform by performing actions comprising:

directing that at least one external sensor sense at an indicated location on the uncrewed air transport platform;

acquiring sensor data of the uncrewed air transport platform from the at least one external sensor, wherein the sensor data is obtained while executing a sequence of operations of the uncrewed air transport platform after arranging the uncrewed air transport platform and the at least one external sensor in proximity to each other, wherein the at least one external sensor comprises a vibration sensor;

automatically analyzing the sensor data to detect at least one non-normal health signature of the uncrewed air transport platform;

automatically diagnosing one or more degradation condition in the uncrewed air transport platform based on the at least one non-normal health signature; and

providing an indication of the one or more degradation condition.

11 . The computer readable medium of claim 10 , wherein the vibration sensor comprises a stand-off vibration sensor.

12 . The computer readable medium of claim 11 ,

wherein the uncrewed air transport platform comprises at least one internal sensor that is electrically unconnected to any uncrewed air transport platform system,

wherein the actions further comprise acquiring internal sensor data from the internal sensor,

wherein the sensor data comprises the internal sensor data.

13 . The computer readable medium of claim 10 , wherein the indication of the degradation condition comprises an indication of a fault.

14 . The computer readable medium of claim 10 , wherein the indication of the degradation condition comprises an indication of a potential future fault.

15 . The computer readable medium of claim 10 ,

wherein the sequence of operations comprises an activation of an actuator,

wherein the sensor data comprises actuator data of the actuator, and

wherein the at least one non-normal health signature comprises an indication of a degradation condition of the actuator.

16 . The computer readable medium of claim 10 , wherein the automatically analyzing the sensor data comprises providing the sensor data to a trained machine learning system.

17 . The non-transitory computer readable medium of claim 10 , wherein the directing comprises providing a fiducial marker of the indicated location on an image of the uncrewed air transport platform.

18 . A system for assessing an operational condition of an uncrewed air transport platform, the system comprising:

at least one external sensor configured to be arranged in proximity to the uncrewed air transport platform, wherein the at least one external sensor comprises a vibration sensor; and

an electronic processor communicatively coupled to the at least one external sensor, the electronic processor configured to perform actions comprising:

directing that the at least one external sensor sense at an indicated location on the uncrewed air transport platform;

acquiring sensor data of the uncrewed air transport platform from the at least one external sensor while the uncrewed air transport platform executed a sequence of operations;

automatically analyzing the sensor data to detect at least one non-normal health signature of the uncrewed air transport platform;

automatically diagnosing one or more degradation condition in the uncrewed air transport platform based on the at least one non-normal health signature; and

providing an indication of the one or more degradation condition.

19 . The system of claim 18 , wherein the vibration sensor comprises a stand-off vibration sensor.

20 . The system, of claim 18 , wherein the directing comprises providing a fiducial marker of the indicated location on an image of the uncrewed air transport platform.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 5, 2023
From: GILBERTSON, DANIEL DAVID; VIAN, JOHN LYLE
To: THE BOEING COMPANY
Reel/Frame 063855/0080 →
Continuity (1)
Related Publication 20240402053A1 · Dec 5, 2024
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