US 9,944,404 B1Granted

Prognostic failure detection system

AssigneeAmazon Technologies, Inc.

InventorNicholas Kristofer Gentry

Life of this patent

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Abstract

A prognostic failure detection system may be implemented for an unmanned aerial vehicle(s) (UAV). A prognostic failure detection system may include a process of predicting failure conditions that may affect an UAV physical system or structure before they occur. By predicting failure conditions before they occur, the prognostic system allows maintenance centers to perform corrective actions in a timely and cost-effective manner. The prognostic system is intended to monitor and support the functionality of several physical systems and physical structures associated with an UAV. A physical system includes, but is not limited to, the electrical system, power system including the power supply, motor and propeller assemblies including motor controllers, navigation system, and flight controller system.

Claims20

Dependent claims

A computer implement method comprising:

receiving sensor data from a plurality of sensors associated with an unmanned aerial vehicle (UAV), wherein the receiving occurs during an in-progress phase of a flight cycle of the UAV;
determining that the sensor data indicates a likelihood of a failure condition occurring on a physical structure or a physical system of the UAV during the in-progress phase of the flight cycle, wherein determining the sensor data indicates the likelihood of the failure condition further comprises comparing at least the sensor data to trend data, and wherein the trend data includes historical sensor data from at least one of the UAV, a second UAV, or a fleet of UAVs during normal operating conditions;
determining a failure condition classification based at least in part on the sensor data, the failure condition classification selected from a predetermined set of failure condition classifications that includes at least a flight non-critical classification, a flight critical non-priority classification, and a flight critical priority classification, wherein:
the flight non-critical classification indicates that the UAV can sustain continued flight without damage to an affected physical structure or an affected physical system,
the flight critical non-priority classification indicates that the UAV can sustain continued flight with predetermined performance restrictions without damage to an affected physical structure or an affected physical system, and
the flight critical priority classification indicates that the UAV cannot sustain continued flight without damage to an affected physical structure or an affected physical system;
determining a corrective action during the in-progress phase of the flight cycle based at least on the failure condition classification;
causing a modification to an operational characteristic that is associated with the flight cycle of the UAV based at least in part on the corrective action;
determining a plurality of ground tests to conduct on the UAV at a completion phase of the flight cycle based at least in part on the sensor data;
prioritizing a subset of ground tests from the plurality of ground tests based at least in part on the failure condition classification and on-ground time constraints associated with the UAV;
and
transmitting a signal to an operations center, the signal modifying a maintenance plan by scheduling the prioritized subset of ground tests associated with the UAV.

9 more elements

A unmanned aerial vehicle (UAV) comprising:

an airframe;
physical systems coupled to the airframe, the physical systems comprising at least a propulsion system to provide thrust, a control system to control at least the propulsion system, and a power system to power at least the control system and the propulsion system;
a plurality of sensors distributed throughout the airframe and the physical systems, the plurality of sensors configured to monitor at least the operation of the airframe and the physical systems;
and
a diagnostic controller to process sensor data associated with the plurality of sensors, the diagnostic controller performing acts comprising:
receive sensor data from a plurality of sensors during an in-progress phase of a flight cycle of the UAV;
determine that the sensor data indicates a probability of a failure condition occurring on the airframe or at least one of the physical systems;
determine a failure condition classification based at least in part on the sensor data, the failure condition classification selected from a predetermined set of failure condition classifications that includes at least one of a flight non-critical classification, a flight critical non-priority classification, and a flight critical priority classification;
determine a corrective action during the in-progress phase of the flight cycle based at least on the failure condition classification;
cause a modification to an operational characteristic that is associated with the flight cycle of the UAV based at least in part on the corrective action;
determine a plurality of ground tests to conduct on the UAV at a completion phase of the flight cycle based at least in part on the sensor data;
prioritize a subset of ground tests from the plurality of ground tests based at least in part on the failure condition classification and on-ground time constraints associated with the UAV;
and
transmit a signal to an operations center, the signal modifying a maintenance plan by scheduling the prioritized subset of ground tests associated with the UAV.

11 more elements

A system comprising:

one or more processors;
and
memory to store computer-executable instructions that, when executed, cause the one or more processors to perform acts comprising:
receiving sensor data from a plurality of sensors during an in-progress phase of a flight cycle of an unmanned aerial vehicle (UAV);
determining that the sensor data indicates a probability of a failure condition occurring on the airframe or at least one of the physical systems during the in-progress phase of the flight cycle, wherein determining the sensor data indicates the likelihood of the failure condition further comprises comparing at least the sensor data to trend data that includes historical sensor data from at least one UAV;
determining a failure condition classification based at least in part on the sensor data, the failure condition classification selected from a predetermined set of failure classifications, each of the predetermined failure classifications having at least a predetermined flight plan modification;
causing a modification to a flight plan that is associated with the flight cycle of the UAV based at least in part on the failure condition classification;
and
determining a plurality of ground tests to conduct on the UAV at a completion of the flight cycle based at least in part on the sensor data;
and
prioritizing a subset of ground tests from the plurality of ground tests based at least in part on the failure condition classification and on-ground time constraints associated with the UAV.

8 more elements

Dependencies are inferred from the claim text.

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Abstract

A computer implement method comprising:

receiving sensor data from a plurality of sensors associated with an unmanned aerial vehicle (UAV), wherein the receiving occurs during an in-progress phase of a flight cycle of the UAV;
determining that the sensor data indicates a likelihood of a failure condition occurring on a physical structure or a physical system of the UAV during the in-progress phase of the flight cycle, wherein determining the sensor data indicates the likelihood of the failure condition further comprises comparing at least the sensor data to trend data, and wherein the trend data includes historical sensor data from at least one of the UAV, a second UAV, or a fleet of UAVs during normal operating conditions;
determining a failure condition classification based at least in part on the sensor data, the failure condition classification selected from a predetermined set of failure condition classifications that includes at least a flight non-critical classification, a flight critical non-priority classification, and a flight critical priority classification, wherein:
the flight non-critical classification indicates that the UAV can sustain continued flight without damage to an affected physical structure or an affected physical system,
the flight critical non-priority classification indicates that the UAV can sustain continued flight with predetermined performance restrictions without damage to an affected physical structure or an affected physical system, and
the flight critical priority classification indicates that the UAV cannot sustain continued flight without damage to an affected physical structure or an affected physical system;
determining a corrective action during the in-progress phase of the flight cycle based at least on the failure condition classification;
causing a modification to an operational characteristic that is associated with the flight cycle of the UAV based at least in part on the corrective action;
determining a plurality of ground tests to conduct on the UAV at a completion phase of the flight cycle based at least in part on the sensor data;
prioritizing a subset of ground tests from the plurality of ground tests based at least in part on the failure condition classification and on-ground time constraints associated with the UAV;
and
transmitting a signal to an operations center, the signal modifying a maintenance plan by scheduling the prioritized subset of ground tests associated with the UAV.

9 more elements