Method and apparatus for identifying erroneous sensor outputs

• US 8,359,178 B2
• Filed: 03/04/2009
• Issued: 01/22/2013
• Est. Priority Date: 03/04/2009
• Status: Expired due to Fees

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Rowe, Eric, Gruer, Mike
• Primary Examiner(s): Nghiem, Michael
• Assistant Examiner(s): Lee, Paul D
• Application Number:
  US12/398,041
• Publication Number:
  US 20100228512A1
• Time in Patent Office: 1,420 Days
• Field of Search: 702/104, 702/85, 702/103, 702/182, 702/189, 702/193, 702/199
• US Class Current: 702/85
• CPC Class Codes: G01D 1/00 Measuring arrangements giving results other than momentary value of variable, of general application G01D3/00 takes precedence; in tariff metering apparatus G01D4/00; transducers not specially adapted for a specific variable G01D5/00
• CPC Class Codes: G01D 15/00 Component parts of recorders for measuring arrangements not specially adapted for a specific variable
• CPC Class Codes: G01D 21/00 Measuring or testing not otherwise provided for

Abstract

A method for identifying erroneous sensor outputs is provided. The method includes obtaining a first plurality of samples from a sensor over a period of time. A mean of the plurality of samples is determined. A first additional sample from the sensor at a time subsequent to times that the first plurality of samples were obtained is also received. A divergence of the first additional sample from the mean is determined. The first additional sample is identified as erroneous when the divergence is greater than a threshold.

Claims

1. A method for identifying erroneous sensor outputs, the method comprising:

with a processing device, obtaining a first plurality of samples from a sensor over a period of time;

determining, with the processing device, a first mean of the first plurality of samples;

with the processing device, obtaining a first additional sample from the sensor at a time subsequent to times that the first plurality of samples were obtained;

determining, with the processing device, a divergence of the first additional sample from the first mean;

identifying, with the processing device, the first additional sample as erroneous when the divergence is greater than a threshold;

determining a second mean of a second plurality of samples including the first additional sample when the first additional sample has been identified as erroneous; and

controlling a mechanism based on only non-erroneous samples obtained from the sensor.

2. The method of claim 1, further comprising:

flagging the first additional sample when the first additional sample has been identified as erroneous.

3. The method of claim 1, wherein the first additional sample is a sample immediately subsequent to a sample obtained last in time of the first plurality of samples.

4. The method of claim 3, wherein

the second plurality of samples includes each of the first plurality of samples, except for a sample obtained first in time of the first plurality of samples, the second plurality of samples including the first additional sample, the method further comprising:

with the processing device, obtaining a second additional sample from the sensor at a time subsequent to a time that the first additional sample was obtained;

determining with the processing device, a second divergence of the second additional sample from the second mean; and

identifying with the processing device, the second additional sample as erroneous when the second divergence is greater than the threshold.

5. The method of claim 1, wherein the samples of the first plurality of samples are consecutive in time.

6. The method of claim 1, wherein determining a divergence comprises determining a coefficient of variance for the first additional sample with respect to the first mean.

7. The method of claim 1, further comprising discarding the first additional sample for further processing except for determination of the second mean when the first additional sample has been identified as erroneous.

8. A system comprising:

a sensor; and

a processing device communicatively coupled to the sensor and configured to;

determine a first mean of a first plurality of samples, each of the samples of the first plurality of samples comprising data obtained by the sensor over a period of time;

determine a divergence between a first additional sample obtained by the sensor at a time subsequent to the period of time and the first mean;

identify the first sample as erroneous when the divergence is greater than a threshold;

determine a second mean of a second plurality of samples including the first additional sample when the first additional sample has been identified as erroneous; and

control a mechanism based on only non-erroneous samples obtained from the sensor.

9. The system of claim 8, wherein the sensor is an acoustic proximity sensor.

10. The system of claim 8, further comprising:

a sample and hold circuit coupled between the sensor and the processing device, the sample and hold circuit configured to convert analog outputs from sensor to digital samples for the processing device.

11. The system of claim 8, wherein the processing device is further configured to:

flag the first additional sample when the first additional sample has been identified as erroneous.

12. The system of claim 8, wherein the second plurality of samples includes each of the first plurality of samples, except for a sample obtained first in time of the plurality of samples, the second plurality of samples including the first additional sample, and the processing device is further configured to:

obtain a second additional sample from the sensor at a time subsequent to a time that the first additional sample was obtained;

determine a second divergence of the second additional sample from the second mean; and

identify the second additional sample as erroneous when the second divergence is greater than the threshold.

13. The system of claim 8, further comprising:

a memory device comprising software embodied thereon, the software operable to instruct the processing device to;

determine the first mean of the first plurality of samples;

determine the divergence between the first additional sample and the first mean; and

identify the first sample as erroneous when the divergence is greater than the threshold.

14. The system of claim 8, wherein the processing device is configured to discard the first additional sample for further processing except for determination of the second mean when the first additional sample has been identified as erroneous.

15. The system of claim 8, wherein the processing device is configured to determine the divergence between the first additional sample and the first mean by at least determining a coefficient of variance for the first additional sample with respect to the first mean.

16. A non-transitory processor-readable medium comprising instructions, that when executed by a processor, cause the processor to:

for a first plurality of samples obtained from a sensor, determine a first mean of a portion of the first plurality of samples using a sliding window;

for a new sample obtained from the sensor, determine a divergence between the new sample and the first mean of the samples within the sliding window;

identify the new sample as erroneous when the divergence is greater than a threshold;

determine a second mean of a second plurality of samples including the new sample when the new sample has been identified as erroneous; and

control a mechanism based on only non-erroneous samples obtained from the sensor.

17. The non-transitory processor-readable medium of claim 16, wherein for each new sample, the sliding window contains samples immediately preceding the new sample.

18. The non-transitory processor-readable medium of claim 16, wherein the instructions, when executed by the processor, cause the processor to

determine the divergence by determining a coefficient of variance for the new sample with respect to the first mean.

19. The non-transitory processor-readable medium of claim 16, wherein the sensor is an acoustic proximity sensor and each sample comprises data relating to a distance from the sensor to an object.

20. The non-transitory processor-readable medium of claim 16, wherein the instructions, when executed by the processor, cause the processor to discard the new sample for further processing except for calculation of the second mean when the divergence is greater than a threshold.