US6898585B2
Expired / Lapsed
US
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Fuzzy logic method for adaptively evaluating the validity of sensor data
Assignee: CNH Industrial America LLC
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Filing: 2001-02-02
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Granted: 2005-05-24
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Expires: 2021-02-02
Abstract
Abstract Machine operators rely on intuition and experience to evaluate vehicle performance. As we increasingly turn to automation, it is important to automatically evaluate sensor data and system performance. Fuzzy logic allows us to take advantage of domain knowledge to evaluate data and to describe a system linguistically. In this application a fuzzy quality module evaluates output from a noisy sensor. It compares the sensor data with an estimated sensor value, and based on that comparison, dynamically adapts a fuzzy logic rulebase used to determine whether the sensor value is valid or not.
Inventors
- 👤 Eric R. Benson
- 👤 Qin Zhang
- 👤 John F. Reid
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-26 00:30
CPC Classifications
G; G05; G05B; G05B9/00; G05B9/02
Claims Analysis
Total Claims: 17
Claim 1
Independent Claim
88 words
A method for determining the validity of a sensor signal of a sensor including the steps of: providing a sensor signal from a sensor; providing an estimated sensor signal of the sensor; determining the difference between the sensor signal and the estimated sensor signal; calculating a standard deviation of the difference; scaling the points of inflection of a fuzzy logic membership function proportional to the standard deviation; and processing the sensor signal using the fuzzy logic membership function to determine whether the sensor signal is valid or not.
Claim 2
Independent Claim
88 words
A method for determining the validity of a sensor signal of a sensor including the steps of: providing a sensor signal from a sensor; providing an estimated sensor signal of the sensor; determining the difference between the sensor signal and the estimated sensor signal; calculating a standard deviation of the difference; scaling the points of inflection of a fuzzy logic membership function proportional to the standard deviation; and processing the sensor signal using the fuzzy logic membership function to determine whether the sensor signal is valid or not.
Claim 3
Dependent Claim
17 words
The method of claim 1 , wherein the step of processing occurs before the step of scaling.
Claim 4
Dependent Claim
17 words
The method of claim 1 , wherein the step of scaling occurs before the step of processing.
Claim 5
Dependent Claim
41 words
The method of claim 1 , wherein the fuzzy logic membership function has at least two domains, including at least one domain that evaluates a sensor signal as acceptable, and at least one domain that evaluates a sensor signal as unacceptable.
Claim 6
Dependent Claim
32 words
The method of claim 4 , wherein the step of scaling includes the step of multiplying a plurality of points of inflection of the fuzzy logic membership function by the standard deviation.
Claim 7
Independent Claim
207 words
A method for determining the quality of a sensor signal of a sensor in a fuzzy logic controller including the steps of: providing a first cumulative scatter value indicative of a cumulative degree of difference between a plurality of sensor signal values of the sensor and estimated sensor signal values of the sensor corresponding to each of the sensor signal values; providing a fuzzy logic membership function in which the x-axis values of the points of inflection of a plurality of fuzzy logic domains are derived from the first cumulative scatter value; retrieving a further sensor signal value of the sensor; comparing the further sensor signal value with a further estimated sensor signal value of the sensor; calculating a further scatter value indicative of the individual degree of difference between the further sensor signal value and the further estimated sensor signal value; combining the further scatter value with the first cumulative scatter value to provide a second cumulative scatter value indicative of the cumulative degree of difference and the individual degree of difference in combination; and amending the fuzzy logic membership function such that the x-axis values of the points of inflection of the plurality of fuzzy logic domains are derived from the second cumulative scatter value.
Claim 8
Independent Claim
207 words
A method for determining the quality of a sensor signal of a sensor in a fuzzy logic controller including the steps of: providing a first cumulative scatter value indicative of a cumulative degree of difference between a plurality of sensor signal values of the sensor and estimated sensor signal values of the sensor corresponding to each of the sensor signal values; providing a fuzzy logic membership function in which the x-axis values of the points of inflection of a plurality of fuzzy logic domains are derived from the first cumulative scatter value; retrieving a further sensor signal value of the sensor; comparing the further sensor signal value with a further estimated sensor signal value of the sensor; calculating a further scatter value indicative of the individual degree of difference between the further sensor signal value and the further estimated sensor signal value; combining the further scatter value with the first cumulative scatter value to provide a second cumulative scatter value indicative of the cumulative degree of difference and the individual degree of difference in combination; and amending the fuzzy logic membership function such that the x-axis values of the points of inflection of the plurality of fuzzy logic domains are derived from the second cumulative scatter value.
Claim 9
Dependent Claim
84 words
The method of claim 6 , wherein the step of providing a first cumulative value includes the steps of: a. calculating a first difference between a first of the plurality of sensor signal values and a first of the estimated sensor signal values; b. calculating a second difference between a second of the plurality of sensor signal values and a second of the estimated sensor signal values; and c. calculating the first cumulative scatter value from at least the [foregoing] first and second differences.
Claim 10
Dependent Claim
25 words
The method of claim 7 , wherein the first cumulative scatter value is a function of the standard deviation of the first and second differences.
Claim 11
Independent Claim
128 words
A method of individually determining whether a plurality of sequential sensor values of a sensor are valid comprising the steps of: a. reading a sensor value of the sensor; b. determining a degree of difference between the sensor value and an estimated sensor value of the sensor; c. revising the x-axis values of a fuzzy logic membership function that responds to the degree of difference as an input and produces a signal indicative of the validity of the sensor value as an output; d. determining whether the sensor value is valid; e. repeating steps a through d for each of the plurality of sequential sensor values; and f. calculating a value indicative of a collective degree of scatter of the individual degrees of difference calculated in step b.
Claim 12
Independent Claim
128 words
A method of individually determining whether a plurality of sequential sensor values of a sensor are valid comprising the steps of: a. reading a sensor value of the sensor; b. determining a degree of difference between the sensor value and an estimated sensor value of the sensor; c. revising the x-axis values of a fuzzy logic membership function that responds to the degree of difference as an input and produces a signal indicative of the validity of the sensor value as an output; d. determining whether the sensor value is valid; e. repeating steps a through d for each of the plurality of sequential sensor values; and f. calculating a value indicative of a collective degree of scatter of the individual degrees of difference calculated in step b.
Claim 13
Dependent Claim
42 words
The method of claim 9 , wherein the step of calculating is performed after each step of determining a degree of difference, and wherein the value indicative of the collective degree of scatter incorporates all of the previous individual degrees of difference.
Claim 14
Dependent Claim
29 words
The method of claim 10 , wherein the value indicative of the collective degree of scatter is a standard deviation of degrees of difference calculated prior in step b.
Claim 15
Dependent Claim
20 words
The method of claim 11 , wherein x-axis values of the membership function are themselves functions of the standard deviation.
Claim 16
Dependent Claim
33 words
The method of claim 12 , further comprising the step of calculating a plurality of the x-axis values every time the step of calculating a value indicative of the degree of scatter occurs.
Claim 17
Dependent Claim
32 words
The method of claim 13 , wherein each of the x-axis values of the points of inflection is associated with a value that is a function of the collective degree of scatter.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2008-05-23 | 2008-11-22 | 2009-05-24 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2012-05-23 | 2012-11-22 | 2013-05-24 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2016-05-23 | 2016-11-22 | 2017-05-24 | $7700.00 | Window Closed / Lapsed |