Anomaly prediction and detection for aircraft equipment

Patent metadata

Field	Value
Publication number	US-11580794-B2
Application number	US-202016843220-A
Country	US
Kind code	B2
Filing date	Apr 8, 2020
Priority date	Apr 8, 2020
Publication date	Feb 14, 2023
Grant date	Feb 14, 2023

Abstract

A method includes obtaining sensor data captured by a sensor of an aircraft during a power up event. The sensor data includes multiple parameter values, each corresponding to a sample period. The method further includes determining a set of delta values, each indicating a difference between parameter values for consecutive sample periods of the sensor data. The method further includes determining a set of quantized delta values by assigning the delta values to quantization bins based on magnitudes of the delta values. The method further includes determining a normalized count of delta values for each quantization bin. The method further includes comparing the normalized counts of delta values to anomaly detection thresholds. The method further includes generating, based on the comparisons, output indicating whether the sensor data is indicative of an operational anomaly.

First claim

What is claimed is:

1. A method comprising:
obtaining, at a computing device, sensor data captured by a sensor of an aircraft during a power up event, wherein the sensor data includes multiple parameter values, and wherein each parameter value corresponds to a respective sample period during the power up event;
determining, by the computing device, a set of delta values, wherein each delta value from the set of delta values indicates a difference between a first parameter value and a second parameter value from a pair of parameter values corresponding to consecutive sample periods of the sensor data;
determining, by the computing device, a set of quantized delta values by assigning delta values from the set of delta values to quantization bins based on magnitudes of the delta values;
determining, by the computing device, a normalized count of delta values for each of the quantization bins by:
determining a power up duration of the power up event represented by the sensor data;
determining a normalization factor based on the power up duration of the power up event and based on a normalization standard;
determining a count of delta values assigned to each quantization bin; and
adjusting the count of delta values assigned to each quantization bin based on the normalization factor to determine the normalized count of delta values;

performing, by the computing device, a comparison of the normalized count of delta values for a particular quantization bin to an anomaly detection threshold of the particular quantization bin; and
generating, by the computing device and based on the comparison, an output indicating whether the sensor data is indicative of an operational anomaly for aircraft equipment associated with the sensor.

2. The method of claim 1 , further comprising comparing, by the computing device, each delta value to a difference threshold, wherein only delta values that satisfy the difference threshold are assigned to quantization bins.

3. The method of claim 1 , wherein the normalization standard indicates a benchmark duration of a standardized power up event.

4. The method of claim 1 , further comprising selecting the anomaly detection threshold for each quantization bin based on an operating condition associated with the power up event.

5. The method of claim 4 , wherein the aircraft equipment corresponds to a component of an environmental system, and wherein the operating condition is associated with ambient environmental conditions.

6. The method of claim 1 , wherein the anomaly detection threshold for each quantization bin includes a first threshold and a second threshold, and wherein the output includes a first indication responsive to the comparison indicating that a normalized count of delta values associated with the particular quantization bin is greater than or equal to the first threshold associated with the particular quantization bin and less than the second threshold associated with the particular quantization bin.

7. The method of claim 6 , wherein the output includes a second indication responsive to the comparison indicating that the normalized count of delta values associated with the particular quantization bin is greater than or equal to the second threshold associated with the particular quantization bin.

8. A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations including:
obtaining sensor data captured by a sensor of an aircraft during a power up event, wherein the sensor data includes multiple parameter values, and wherein each parameter value corresponds to a respective sample period during the power up event;
determining a set of delta values, wherein each delta value from the set of delta values indicates a difference between a first parameter value and a second parameter value from a pair of parameter values corresponding to consecutive sample periods of the sensor data;
determining a set of quantized delta values by assigning delta values from the set of delta values to quantization bins based on magnitudes of the delta values;
determining a normalized count of delta values for each of the quantization bins by:
determining a power up duration of the power up event represented by the sensor data;
determining a normalization factor based on the power up duration of the power up event and based on a normalization standard;
determining a count of delta values assigned to each quantization bin; and
adjusting the count of delta values assigned to each quantization bin based on the normalization factor to determine the normalized count of delta values;

performing a comparison of the normalized count of delta values for a particular quantization bin to an anomaly detection threshold of the particular quantization bin; and
generating, based on the comparison, an output indicating whether the sensor data is indicative of an operational anomaly for aircraft equipment associated with the sensor.

9. The non-transitory computer-readable storage medium of claim 8 , wherein the operations further comprise comparing each delta value to a difference threshold, and wherein only delta values that satisfy the difference threshold are assigned to quantization bins.

10. The non-transitory computer-readable storage medium of claim 8 , wherein the normalization standard indicates a benchmark duration of a standardized power up event.

11. The non-transitory computer-readable storage medium of claim 8 , wherein the operations further comprise selecting the anomaly detection threshold for each quantization bin based on an operating condition associated with the power up event.

12. The non-transitory computer-readable storage medium of claim 8 , wherein performing the comparison comprises:
comparing the normalized count of delta values to a first threshold associated with the particular quantization bin and to a second threshold associated with the particular quantization bin, wherein the output includes a first indication responsive to the comparison indicating that the normalized count of delta values associated with the particular quantization bin is greater than or equal to the first threshold and less than the second threshold.

13. The non-transitory computer-readable storage medium of claim 12 , wherein the output further includes a second indication responsive to the comparison indicating that the normalized count of delta values is greater than or equal to the second threshold.

14. An aircraft comprising:
a sensor configured to capture sensor data during a power up event, wherein the sensor data includes multiple parameter values, and wherein each parameter value corresponds to a respective sample period during the power up event;
one or more processors; and
a memory device configured to store the sensor data and instructions that are executable by the one or more processors to detect operational anomalies for aircraft equipment associated with the sensor, wherein the instructions, when executed by the one or more processors, cause the one or more processors to perform operations including:
determining a set of delta values, wherein each delta value from the set of delta values indicates a difference between a first parameter value and a second parameter value from a pair of parameter values corresponding to consecutive sample periods of the sensor data;
determining a set of quantized delta values by assigning delta values of the set of delta values to quantization bins based on magnitudes of the delta values;
determining a normalized count of delta values for each of the quantization b

Assignees

• Boeing Co

Inventors

• Korchev Dmitriy
• Martin Charles E
• Lu Tsai-Ching
• Slaughter Steve C
• Murphy Alice A
• Fok Derek Samuel

Classifications

• B64F5/60 Primary

  Testing or inspecting aircraft components or systems · CPC title

• B64D2045/0085

  Devices for aircraft health monitoring, e.g. monitoring flutter or vibration · CPC title

• G05B23/0221

  Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods · CPC title

• G05B23/0224 Primary

  Process history based detection method, e.g. whereby history implies the availability of large amounts of data · CPC title

• G07C5/0808 Primary

  Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005) · CPC title