DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/29/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Claims 1-10 are pending. Claims 1-4 and 7-10 are amended. Claims 5-6 are amended as being dependent on a base amended claim.
Applicant’s arguments, filed 07/22/2026, with respect to specification objections have been fully considered. The objections of the specification have been withdrawn.
Applicant’s arguments, filed 07/22/2026, with respect to claim rejections under 35 U.S.C 112(b) for Claims 4 and 10 have been fully considered and are persuasive. The rejection of Claims 4 and 10 have been withdrawn. New 35 U.S.C. 112(b) rejections are issued for Claims 2 and 8 in light of applicant’s amendments.
Applicant’s arguments, filed 07/22/2026, with respect to claim rejections under 35 U.S.C 101 of Claims 1-10 have been fully considered and are persuasive. The rejection under 35 U.S.C. 101 for claims 1-10 have been withdrawn.
Applicant’s arguments, filed 07/22/2026, with respect to claim rejections under 35 U.S.C 103 of Claims 1-10 have been fully considered and are not persuasive. A new rejection under 35 U.S.C 103 is applied for Claims 1-2 and 7-8 under prior arts Bechhoefer (US 11138816 B1) in view of Patil (US 20160259014 A1) and for Claims 3-4 and 9-10 under prior arts Bechhoefer (US 11138816 B1) and Patil (US 20160259014 A1), further in view of Yuan (US 20080086437 A1) in light of applicant’s amendments.
With regards to Claims 1 and 7 applicant argues that Bechhoefer in view of Patil does not teach ''forming a health indicator curve by obtaining health indicator values over time from the extracted features using principal component analysis", as Bechhoefer obtains the health indicator (HI) based on the condition indicators (CIs) without any use of principal component analysis. Patil discloses using Principal Component Analysis (PCA) as an optional technique by the RUL estimator to optimize the primary and secondary parameters to obtain a set of optimized parameters, but not as a technique for obtaining a health indicator based on extracted features from sensor data. In addition, Applicant notes that Patil’s RUL estimator uses a real-time AI model to indicate an SOH of the battery at an instance of time.
Examiner respectfully disagrees, the combination of Bechhoefer in view of Patil does teach ''forming a health indicator curve by obtaining health indicator values over time from the extracted features using principal component analysis" as the sensor data is recited in Bechhoefer, and it would be obvious to one of ordinary skill in the art to modify Bechhoefer with Patil as they are both in the field of estimating Remaining Useful Life (RUL), where Patil estimates RUL via PCA.
Applicant further argues that “The proposed combination fails to teach determining a dynamic failure threshold in real-time based on degradation parameters unique to the equipment” and “the dynamic failure threshold varying over time as the degradation of the equipment progresses”, where the proposed combination is Bechhoefer in view of Patil for Claims 1 and 7. Examiner notes Applicant’s arguments are directed to proposed claim amendments and are addressed in the 35 U.S.C 103 rejections below.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 and 8 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 line 4 recites “the time”, even though Claim 1 line 5 recites “time”, Claim 1 line 11 recites “time”, and Claim 2 line 3 recites “a time”. It is unclear which “time” is “the time”. Therefore, Claim 2 is indefinite.
Claim 8 line 4 recites “the time”, even though Claim 7 line 5 recites “time”, Claim 7 line 12 recites “time”, and Claim 8 line 3 recites “a time”. It is unclear which “time” is “the time”. Therefore, Claim 8 is indefinite.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2 and 5-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bechhoefer (US 11138816 B1) in view of Patil (US 20160259014 A1).
With regards to Claim 1, Bechhoefer teaches
A method (See Figure 10, the process 1000) to predict a remaining useful life (See Figure 10 step 1016) of an equipment (See Figure 10 Component 1), said equipment provided with at least one sensor (See Abstract), the method comprising:
receiving sensor data from the at least one sensor (See Abstract “The processor receives data from the plurality of sensors (i.e. receiving sensor data from the at least one sensor)”);
extracting features from the sensor data (See Abstract, where the features are the condition indicators for the sensor data) of the at least one sensor (See Abstract “plurality of sensors”);
forming a health indicator curve by obtaining health indicator values over time from the extracted features (See Abstract “a health indicator from the plurality of condition indicators”. See also Fig. 6, where the health indicator curve is the filtered health 608 based on the obtained health indicator values over time from the extracted features, where the extracted features are the condition indicators, see Abstract.);
determining a critical time beyond which degradation initiates in the equipment (See Column 4 lines 63-67 “a model of the component degradation process that calculates the time (or number of cycles) until maintenance should be performed (i.e. the critical time) based on the current health of the component and the estimated future load for the component (i.e. the equipment)”);
predicting a future degradation curve (See Fig. 6 the predicted health curve 612) based on the health indicator curve (See Fig. 6 the Filtered Health 608 is the health indicator curve which is used as a basis for the Predicted Health 612); and
determining a dynamic failure threshold in real-time (See Column 7 lines 23-26 “Because a condition monitoring plan is not static, as feedback from depot level repairs/inspections is gathered the thresholds should be updated (i.e. a dynamic failure threshold is determined in real-time of the individual condition indicators, which are combined to provide the health indicator and correspondingly determine the dynamic failure threshold of the entire component, see Column 5 lines 2-3 “As noted, a health index (HI) for a component is based on one or more condition indicators (CIs)”) to reflect operator/maintainer appropriateness for maintenance.” Examiner notes that the threshold of the entire component in Bechhoefer determines the usability of the component, see Column 4 lines 9 -12 “An HI of 1.0 or greater indicates an alarm situation, where continued operation with the component will result in a lower reliability of the system, and potentially collateral damage to other components within the system”) based on degradation parameters of the equipment, the degradation parameters being unique to the equipment (See Column 6 lines 51-52 “With these parameters in place (i.e. the degradation parameters, the values of which are unique to the equipment, as these parameters are used to determine the RUL for the specific component/equipment being tested), the procedure for calculating thresholds is described below”. Again, these thresholds are the individual thresholds for the condition indicators, which are used as a basis for determining the health indicator and whether the corresponding threshold has been crossed for the health indicator.), the dynamic failure threshold varying over time as the degradation of the equipment progresses (See Equation 37, where the equation is dependent on an exponential relationship (i.e. an exponential curve) of dHI/dt and log (HI) (i.e. since the HIt is the health indicator curve, and HI is dependent on the threshold in Bechhoefer (See Column 7 lines 27-28 “Once the thresholds are determined, the CIs can be used to determine an HI for the component.”), the dynamic failure threshold varies over time as the degradation of the equipment progresses.)).
Patil teaches
using principal component analysis (See Para[0086] “Examples of the techniques to be used by the RUL estimator are as follows. Principal Component Analysis PCA”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Bechhoefer wherein using principal component analysis is used like in Patil to obtain the health indicator in order to optimize the degradation parameters for more accurate calculations of the health indicator (See Patil Para[0086]).
With regards to Claim 2, Bechhoefer and Patil teach the limitations of Claim 1. Bechhoefer further teaches
wherein determining the critical time uses a threshold, calculated using a Pauta criterion, based on (i) a mean of the health indicator values until a time, and (ii) a standard deviation of the health indicator values until the time (See Column 5 lines 8-10 “The HI function is valid if and only if the distributions (i.e., the probability distributions of the CIs) are independent and identically distributed (IID)”. See also Column 13 lines 28-33 “To estimate the confidence interval, the distribution of the HI and the change in load must be accounted for. For example, in a scenario where the load is 10% higher than average (i.e., an aggressive flight regime) and given that one standard deviation for the HI is calculated as 0.03, the future HIt would be…”. In other words, the HI is also a distribution (where the distribution is composed of health indicator values which compose the distribution) and is based on a mean and standard deviation of the health indicator values up to the time of the data gathered (interpreted here as a Pauta criterion) of the CIs. In addition, the 10% load functions as a threshold that serves as an input to eventually determine the critical time for the component. To visualize the effect of this threshold, see Fig. 6, the band between the low and high load health curves 620 and 616 respectively.).
With regards to Claim 5, Bechhoefer and Patil teach the limitations of Claim 1. Bechhoefer further teaches
wherein the future degradation curve for the equipment is updated based on the sensor data received over time (“See also Column 13 lines 28-33 “To estimate the confidence interval, the distribution of the HI and the change in load must be accounted for. For example, in a scenario where the load is 10% higher than average (i.e., an aggressive flight regime) and given that one standard deviation for the HI is calculated as 0.03, the future HIt would be” and equation 38, where the value of HIt is updated with the new 10% increase in load and the .03 standard deviation of HI. This would be reflected in Fig. 6, the plot for the predicted health 612.).
With regards to Claim 6, Bechhoefer and Patil teach the limitations of Claim 1. Bechhoefer further teaches
the dynamic failure threshold is determined in real time based on the degradation parameters (See equation 36, where HI can be solved in terms of the real time t (See Claim 1 above, where the threshold is dynamically determined as the CI threshold is updated), and HI is dependent on the degradation parameters, see Claim 1 above), and
the degradation parameters are unique to the equipment (See Column 3 lines 56-58 “For example, the thresholds for CIs for one shaft (i.e. the equipment) will often be different than the thresholds for the same CIs for another shaft.” In other words, each equipment is uniquely parametrized by a separate CI which is determined by its own degradation parameters, see Claim 1 above.).
With regards to Claim 7,
A processor (See Abstract) to predict a remaining useful life (See Figure 10 step 1016) of an equipment (See Figure 10 Component 1), said equipment provided with at least one sensor (See Abstract), said processor configured to:
receive sensor data from the at least one sensor (See Abstract);
extract features from the sensor data (See Abstract, where the features are the condition indicators);
form a health indicator curve by obtaining health indicator values over time from the extracted features (See Abstract “a health indicator from the plurality of condition indicators”. See also Fig. 6, where the health indicator curve is the filtered health 608 which is formed based on the obtained health indicator values over time from the extracted features, where the extracted features are the condition indicators, see Abstract.);
determine a critical time beyond which a degradation initiates in the equipment (See Column 4 lines 63-67 “a model of the component degradation process that calculates the time (or number of cycles) until maintenance should be performed (i.e. the critical time) based on the current health of the component and the estimated future load for the component (i.e. the equipment)”) using a Pauta criterion (See Column 5 lines 8-10 “The HI function is valid if and only if the distributions (i.e., the probability distributions of the CIs) are independent and identically distributed (IID)”. In other words, the HI is based on a mean and standard deviation up to the time of observation (interpreted here as a Pauta criterion) of the CIs.);
predict a future degradation curve (See Fig. 6 the predicted health curve 612) based on the health indicator curve (See Fig. 6 the Filtered Health 608 is the health indicator curve which is used as a basis for the Predicted Health 612); and
determine a dynamic failure threshold in real-time (See Column 7 lines 23-26 “Because a condition monitoring plan is not static, as feedback from depot level repairs/inspections is gathered the thresholds should be updated (i.e. a dynamic failure threshold is determined in real-time of the individual condition indicators, which are combined to provide the health indicator and correspondingly determine the dynamic failure threshold of the entire component, see Column 5 lines 2-3 “As noted, a health index (HI) for a component is based on one or more condition indicators (CIs)”) to reflect operator/maintainer appropriateness for maintenance.” Examiner notes that the threshold of the entire component in Bechhoefer determines the usability of the component, see Column 4 lines 9 -12 “An HI of 1.0 or greater indicates an alarm situation, where continued operation with the component will result in a lower reliability of the system, and potentially collateral damage to other components within the system”) based on degradation parameters of the equipment, the degradation parameters being unique to the equipment (See Column 6 lines 51-52 “With these parameters in place (i.e. the degradation parameters, the values of which are unique to the equipment, as these parameters are used to determine the RUL for the specific component/equipment being tested), the procedure for calculating thresholds is described below”. Again, these thresholds are the individual thresholds for the condition indicators, which are used as a basis for determining the health indicator and whether the corresponding threshold has been crossed for the health indicator.), the dynamic failure threshold varying over time as the degradation of the equipment progresses (See Equation 37, where the equation is dependent on an exponential relationship (i.e. an exponential curve) of dHI/dt and log (HI) (i.e. since the HIt is the health indicator curve, and HI is dependent on the threshold in Bechhoefer (See Column 7 lines 27-28 “Once the thresholds are determined, the CIs can be used to determine an HI for the component.”), the dynamic failure threshold varies over time as the degradation of the equipment progresses.)).
Patil teaches
using principal component analysis (See Para[0086] “Examples of the techniques to be used by the RUL estimator are as follows. Principal Component Analysis PCA”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Bechhoefer wherein using principal component analysis is used like in Patil to obtain the health indicator in order to optimize the degradation parameters for more accurate calculations of the health indicator (See Patil Para[0086]).
With regards to Claim 8, Bechhoefer and Patil teach the limitations of Claim 7. Bechhoefer further teaches
wherein the processor is configured to determine the critical time using a threshold, calculated using the Pauta criterion, based on (i) a mean of the health indicator values until a time, and (ii) a standard deviation of the health indicator values until the time (See Column 5 lines 8-10 “The HI function is valid if and only if the distributions (i.e., the probability distributions of the CIs) are independent and identically distributed (IID)”. See also Column 13 lines 28-33 “To estimate the confidence interval, the distribution of the HI and the change in load must be accounted for. For example, in a scenario where the load is 10% higher than average (i.e., an aggressive flight regime) and given that one standard deviation for the HI is calculated as 0.03, the future HIt would be…”. In other words, the HI is also a distribution (where the distribution is composed of health indicator values which compose the distribution) and is based on a mean and standard deviation of the health indicator values up to the time of the data gathered (interpreted here as a Pauta criterion) of the CIs. In addition, the 10% load functions as a threshold that serves as an input to eventually determine the critical time for the component. To visualize the effect of this threshold, see Fig. 6, the band between the low and high load health curves 620 and 616 respectively. Examiner notes that the processor in Bechhoefer is used to complete the method steps in Fig. 10, see Abstract.).
Claim(s) 3-4 and 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bechhoefer (US 11138816 B1) and Patil (US 20160259014 A1) and further in view of Yuan (US 20080086437 A1).
With regards to Claim 3, Bechhoefer and Patil teach the limitations of Claim 1. Bechhoefer further teaches
fitting an exponential curve into the health indicator curve (See Fig. 6, where the exponential curve is the Predicted Health curve 612 (see equation 37) and the health indicator curve is the Filtered Health 608) by estimating values of parameters of the exponential curve (See transition from equation 37 to 38, where the HI (i.e. a parameter) is shifted by “+.03” and dHI/dt (i.e. a second parameter) is multiplied by a factor of 1.1 as an estimate of the change caused by the standard deviation of 0.03 of HI and the 10% higher load than the average, see Column 13 lines 28-33. Therefore, the parameters of the exponential curve are estimated.);
Bechhoefer and Patil are silent to the language of
such that an error between the existing health indicator curve and the exponential curve is a minimum.
Yuan teaches
such that an error between the existing curve and the modeled curve is a minimum (See Yuan Fig. 5, where the scatter plot is the existing curve, and Para[0030] “Selecting a next kernel from the library of kernels and adding the next kernel to the regression network (i.e. the modeled curve) may be repeated until a regression error (i.e. an error) has been minimized” and Para[0038] “FIG. 5 shows the fit of the network 57 after refining”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Bechhoefer and Patil wherein such that an error between the existing curve and the modeled curve is a minimum like in Yuan in order to more accurately reflect the existing data gathered by the sensors.
With regards to Claim 4, Bechhoefer and Patil teach the limitations of Claim 1. Bechhoefer further teaches
wherein, the dynamic failure threshold is determined based on (i) the exponential curve, (ii) the health indicator curve, (iii) the critical time, and (iv) the parameters of the exponential curve at a current time (See Equation 37, where the equation is dependent on an exponential relationship (i.e. an exponential curve) of dHI/dt and log (HI) (i.e. since the Hit is the health indicator curve, and HI is dependent on the threshold in Bechhoefer (See Column 7 lines 27-28 “Once the thresholds are determined, the CIs can be used to determine an HI for the component.”), the dynamic failure threshold in Bechoeffer is determined based on the health indicator curve as there exists a relationship between the HI, which represents the health indicator curve, and the threshold.)).
With regards to Claim 9, Bechhoefer and Patil teach the limitations of Claim 7. Bechhoefer further teaches
fitting an exponential curve into the health indicator curve (See Fig. 6, where the exponential curve is the Predicted Health curve 612 (see equation 37) and the health indicator curve is the Filtered Health 608) by estimating values of parameters of the exponential curve (See transition from equation 37 to 38, where the HI (i.e. a parameter) is shifted by “+.03” and dHI/dt (i.e. a second parameter) is multiplied by a factor of 1.1 as an estimate of the change caused by the standard deviation of 0.03 of HI and the 10% higher load than the average, see Column 13 lines 28-33. Therefore, the parameters of the exponential curve are estimated.);
Bechhoefer and Patil are silent to the language of
such that an error between the existing health indicator curve and the exponential curve is a minimum.
Yuan teaches
such that an error between the existing curve and the modeled curve is a minimum (See Yuan Fig. 5, where the scatter plot is the existing curve, and Para[0030] “Selecting a next kernel from the library of kernels and adding the next kernel to the regression network (i.e. the modeled curve) may be repeated until a regression error (i.e. an error) has been minimized” and Para[0038] “FIG. 5 shows the fit of the network 57 after refining”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Bechhoefer and Patil wherein an error between the existing curve and the modeled curve is a minimum like in Yuan in order to more accurately reflect the existing data gathered by the sensors.
With regards to Claim 10, Bechhoefer and Patil teach the limitations of Claim 7. Bechhoefer further teaches
wherein the dynamic failure threshold is determined based on (i) the exponential curve, (ii) the health indicator curve, (iii) the critical time, and (iv) the parameters of the exponential curve at a current time (See Equation 37, where the equation is dependent on an exponential relationship (i.e. an exponential curve) of dHI/dt and log (HI) (i.e. since the Hit is the health indicator curve, and HI is dependent on the threshold in Bechhoefer (See Column 7 lines 27-28 “Once the thresholds are determined, the CIs can be used to determine an HI for the component.”), the dynamic failure threshold in Bechoeffer is determined based on the health indicator curve as there exists a relationship between the HI, which represents the health indicator curve, and the threshold..)).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOSTOFA AHMED HISHAM whose telephone number is (571)272-8773. The examiner can normally be reached Monday - Friday, 7:00 a.m. - 4 p.m. ET.
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/MOSTOFA AHMED HISHAM/ Examiner, Art Unit 2857
/YOSHIHISA ISHIZUKA/Primary Examiner, Art Unit 2857
