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 3/10/2026 was in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS is being considered by the examiner.
Claim Objections
Claims 1-2, 9-10, and 15 are objected to because of the following informalities:
In claim 1 line 16 “the first bearing condition data” should read “the first bearing condition monitoring data” in accordance with apparent antecedent relation to “first bearing condition monitoring data” in lines 5-6 of claim 1.
Claim 2 line 2 and claim 9 line 17 include the same informality relating to “the first bearing condition data” as in claim 1.
In claim 1 line 8, claim 9 line 8, and claim 15 line 8, “of the first bearing condition” should read “the first bearing condition.”
In claim 10 line 1, “patters” should read “patterns.”
In claim 15 line 8, “of the first bearing” should read “the first bearing.”
In claim 15 line 12, “comprising of” should read “comprised of.”
Appropriate correction is required.
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.
Claims 1-20 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
In claim 1 lines 13-15 and claim 9 lines 14-16, “so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude” renders claim indefinite because it is unclear from the language whether the claim includes an affirmative step of performing a “maximum matching” step or whether this language merely characterizes an intended effect/result of the “weighting” limitation. Claim 9 includes substantially similar language in lines 14-16. Whereas, for example, independent claim 15 clearly recites “determining a maximum match …” as a function that limits the method, claims 1 and 9 do not clearly indicate such a step as being part of the method. Therefore, and consistent with a broadest reasonable interpretation consistent with the plain language, “so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude” (and similar language in claim 9) is interpreted as conveying an intended result/purpose of the weighting step, such that this language is treated as having no significant limiting effect on the scope of claims 1 and 9. If Applicant intends for “maximum match” to be an affirmative limitation, the claim should be amended to clearly convey that the method includes this step.
Claims 2-8 depending from claim 1 and claims 10-14 depending from claim 9 are likewise rejected for the same reasons.
In claim 1 lines 14-15, “the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude,” and claim 9 lines 15-16 “the one of the plurality of patterns which corresponds to the defect yields a highest value” renders each of claims 1 and 9 indefinite because “one of the plurality of patterns” and “defect” each lacks antecedent basis rendering the meaning of the language unclear. Because it appears that “defect” is intended to refer to a defect in the “first bearing” to which “one of” the plurality of patterns corresponds, “the one of the plurality of patterns which corresponds to the defect” is interpreted as “one of the plurality of patterns which corresponds to a defect in the first bearing.” Examiner notes that such interpretation renders the language “the one of the plurality of patterns having the largest pattern correlation value corresponds to the defect in the bearing” in claim 2 lines 3-4 redundant.
Claim 15 includes similar language “the one of the plurality of patterns which corresponds to the defect,” that similarly renders claim 15 indefinite and is interpreted as “one of the plurality of patterns which corresponds to a defect in the first bearing.”
Claims 2-8 depending from claim 1, claims 10-14 depending from claim 9, and claims 16-20 depending from claim 15 are likewise rejected for the same reasons.
In claim 1 line 17, “compares a first pattern thereto to determine a pattern correlation value” renders claim 1 indefinite because it is not sufficiently clear whether “a first pattern” is encompassed among the “plurality of patterns” referenced in line 11. It appears from the context of the claim language and from Applicant’s specification that “a first pattern” is intended to be encompassed among the “plurality of patterns” but the claim language is insufficiently clear on that point, rendering the scope of claim 1 unclear. For the purpose of examination, “a first pattern” is interpreted as being encompassed within the recited “plurality of patterns.”
Independent claim 9 includes substantially the same language including reciting “a first pattern” in line 18 that appears intended to be encompassed within “a plurality of patterns” in line 11 but such relation is not sufficiently recited, such that claim 9 is rejected for the same reasons as claim 1.
Claims 2-8 depending from claim 1 and claims 10-14 depending from claim 9 are likewise rejected for the same reasons.
In claim 2 line 2, “compares a second pattern thereto” renders claim 2 indefinite because it is not sufficiently clear from this language what the “second pattern” is compared to. Based on similar language in claim 1 in which a “first pattern” is compared with “first bearing condition [monitoring] data,” the apparent intent is for the second pattern to be compared with the “first bearing condition [monitoring] data,” which is how claim 2 is interpreted for purposes of examination.
In claim 15 line 16, “the first pattern” lacks antecedent basis and it is not clear from the context of the claim what “the first pattern” refers to. For the purpose of examination, “the first pattern” is interpreted as “a first pattern.”
Claims 16-20 depend from claim 15 and are likewise rejected for the same reasons.
Potential Objection to the Claims
Applicant is advised that should claim 7 be found allowable, claim 8 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention in each of these claims is directed to the abstract idea judicial exception without significantly more.
Claim 1, as best understood and interpreted in view of the grounds for rejecting claim 1 under 112(b), recites:
“[a] method of monitoring a bearing on a machine without having to know the speed of operation of the bearing, comprising the steps of:
providing a shaft disposed on the machine, the shaft having a first axial end;
providing a first bearing disposed on the first axial end of the shaft;
providing a first sensor, located on the first bearing and configured to provide first bearing condition monitoring data which comprises vibration data;
providing a computer in communication with the first sensor;
automatically receiving, by the computer, of the first bearing condition monitoring data and processing the vibration data into frequency domain to generate a spectral array of amplitudes and frequencies;
providing a plurality of patterns each representing a particular defect symptom and each comprising an array of relative frequencies and being weighted such that their root-sum-squared is a maximum of 1 regardless of the size of the array of relative frequencies so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude; and
wherein the computer, upon receiving the first bearing condition data from the first bearing, compares a first pattern thereto to determine a pattern correlation value for the first pattern.”
The claim limitations considered to fall within in the abstract idea are highlighted in bold font above and the remaining features are “additional elements.”
Step 1 of the subject matter eligibility analysis entails determining whether the claimed subject matter falls within one of the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. Claims 1, 9, and 15 recite methods and therefore each falls within a statutory category.
Step 2A, Prong One of the analysis entails determining whether the claim recites a judicial exception such as an abstract idea. Under a broadest reasonable interpretation, the highlighted portions of claim 1 fall within the abstract idea judicial exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, the highlighted subject matter falls within the mental processes category (including an observation, evaluation, judgment, opinion) and the mathematical concepts category (mathematical relationships, mathematical formulas or equations, mathematical calculations). MPEP § 2106.04(a)(2).
The recited functions “monitoring a bearing on a machine without having to know the speed of operation of the bearing” and “compares a first pattern thereto to determine a pattern correlation value for the first pattern” may be performed as mental processes (e.g., evaluating bearing condition including comparative evaluation of first bearing condition data and a first pattern and judgment in determining a resultant pattern correlation value).
The recited functions “processing the vibration data into frequency domain to generate a spectral array of amplitudes and frequencies” and “providing a plurality of patterns each representing a particular defect symptom and each comprising an array of relative frequencies and being weighted such that their root-sum-squared is a maximum of 1 regardless of the size of the array of relative frequencies so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude” falls within the mathematical relationships sub-category of mathematical concepts (MPEP 2106.04(a)(2)) because converting vibration data into frequency domain to provide (e.g., generate) patterns each comprising an array of relative frequencies is fundamentally characterized by mathematical calculations (e.g., Fourier transform) and such provisioning/generating further including weighting the pattern (spectral components) in accordance with a root sum squared metric is also fundamentally characterized by mathematical calculations/relations.
Step 2A, Prong Two of the analysis entails determining whether the claim includes additional elements that integrate the recited judicial exception into a practical application. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception” (MPEP § 2106.04(d)).
MPEP § 2106.04(d) sets forth considerations to be applied in Step 2A, Prong Two for determining whether or not a claim integrates a judicial exception into a practical application. Based on the individual and collective limitations of claim 1 and applying a broadest reasonable interpretation, the most applicable of such considerations appear to include: improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)); applying the judicial exception with, or by use of, a particular machine (MPEP 2106.05(b)); and effecting a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)).
Regarding improvements to the functioning of a computer or other technology, none of the “additional elements” including “providing a shaft disposed on the machine, the shaft having a first axial end,” “providing a first bearing disposed on the first axial end of the shaft,” “providing a first sensor, located on the first bearing and configured to provide first bearing condition monitoring data which comprises vibration data,” “providing a computer in communication with the first sensor,” “automatically receiving, by the computer, of the first bearing condition monitoring data,” and “upon receiving the first bearing condition data from the first bearing” in any combination appear to integrate the abstract idea in a manner that technologically improves any aspect of a device or system that may be used to implement the highlighted steps or a device for implementing the highlighted steps such as a signal processing device or a generic computer.
Providing the target elements to be monitored (bearing disposed on an axial end of a shaft on a machine) and providing the monitoring elements (sensor on the bearing and configured to provide vibration data) constitutes high level data collection having no particularized functional relation to the manner in which the vibration data is processed by the steps falling within the judicial exception. Therefore, these aspects, individually or in combination with the other elements of claim 1, constitute insignificant extra solution activity that fails to integrate the judicial exception into a practical application. Using a computer to perform part of the data collection (receiving), including receiving the first bearing condition data, and to implement the processing steps represents non-particularized computer program instruction implementation of the functions falling within the judicial exception and therefore also constitutes extra solution activity that fails to integrate the judicial exception into a practical application.
As indicated in the grounds for rejecting claim 1 under 112(b), the language “so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude” conveys an intended result/purpose that does not further characterize the function of or structure associated with the recited method.
Regarding application of the judicial exception with, or by use of, a particular machine, the additional elements are not configured or otherwise implemented a particularized manner of implementing bearing health monitoring.
Regarding a transformation or reduction of a particular article to a different state or thing, claim 1 does not include any such transformation or reduction. Instead, claim 1 as a whole entails receiving input information (vibration data from sensors and converted frequency domain data), applying standard processing techniques (e.g., spectral analysis) to the information to determine bearing health information with the additional elements failing to provide a meaningful integration of the abstract idea (weighting defect spectral data and comparing spectral data of the bearing with a spectral pattern) in an application that transforms an article to a different state. Instead, the additional elements represent extra-solution activity that does not integrate the judicial exception into a practical application. In view of the various considerations encompassed by the Step 2A, Prong Two analysis, claim 1 does not include additional elements that integrate the recited abstract idea into a practical application.
Therefore, claim 1 is directed to a judicial exception and requires further analysis under Step 2B.
Regarding Step 2B, and as explained in the Step 2A Prong Two analysis, the additional elements, individually and in combination with the other claim elements, constitute extra solution activity such that the additional elements fail to result in the claim as a whole amounting to significantly more than the judicial exception as well as failing to integrate the judicial exception into a practical application. Furthermore, the additional elements in claim 1 appears to be generic and well understood as evidenced by the disclosures of Hayzen (US 2020/0225117 A1) and Thomson (US 2022/0057296 A1), each of which teach virtually the same data collection and processing functionality for bearing defect monitoring.
Hayzen teaches a method of monitoring a bearing on a machine ([0005]; method described with reference to FIGS. 3-5) including providing a shaft disposed on the machine (FIG. 2 shaft 14 disposed within machine 12), the shaft having a first axial end (FIG. 2 shaft 14 includes axial ends); providing a first bearing disposed on the first axial end of the shaft (FIG. 2 bearing B1 disposed proximate to an axial end of shaft 14); providing a first sensor (FIG. 2 either of sensors 16), located on the first bearing (FIG. 2 both of sensors 16 attached to machine 12 and located proximate to bearing B1, [0053] sensors 16 place at each bearing location) and configured to provide first bearing condition monitoring data which comprises vibration data ([0053] sensors 16 are vibration sensors generating vibration signals representative of vibration of machine); providing a computer in communication with the first sensor (FIG. 2 vibration analysis computer 24 communicatively coupled with sensors 16); automatically receiving, by the computer, of the first bearing condition monitoring data (FIG. 2 vibration analysis computer 24 configured to receive vibration data stored within vibration database 22 and originating from sensors 16, [0054] vibration analysis computer 24 processes the vibration data),” as does Thomson (FIG. 1 depicting sensor device 110 on bearing 105 that is mounted to shaft 107 of rail car 101, with sensor data received and processed the computing device 120).
Therefore, the additional element is insufficient to amount to significantly more than the judicial exception.
Claim 1 is therefore not patent eligible under 101.
Independent claim 9 includes substantially the same combination of elements as claim 1 with a slight variation in terms of how “relative frequencies” is characterized in claim 9. Claim 9 recites no further additional elements that either integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception. Therefore, claim 9 is also not patent eligible under 101.
Independent claim 15, as best understood and interpreted in view of the grounds for rejecting claim 15 under 112(b), includes substantially the same the combination of elements recited in claim 1, including the same combination of “additional elements” and excluding the “weighting” limitations. Claim 15 further recites “determining a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect which is most probable in view of the first bearing condition monitoring data,” which falls within the mental processes exception because determining a maximum match between bearing condition monitoring data and a defect pattern may be performed via mental processes (e.g., evaluating graphically displayed bearing spectral data and graphically displayed reference defect spectral data and judgment in determining maximum correlations). This step also falls within the mathematical relations sub-category of the mathematical concepts exception, because the comparing inherent to determining matches between spectral components is fundamentally characterized by mathematical calculations/relations in terms of quantifying overlapping spectral components (e.g., distances between corresponding spectral components). Claim 15 includes no further additional elements that either integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception. Therefore, claim 15 is also not patent eligible under 101.
Dependent claims 2-8, 10-14, and 16-20 provide additional features/steps that are part of an expanded algorithm that includes the abstract idea of the respective independent claim (Step 2A, Prong One). None of dependent claims 2-8, 10-14, and 16-20 recite additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two), and all fail the “significantly more” test under the step 2B for substantially similar reasons as discussed with regards to the independent claims.
For example, claim 2 further recites “after comparing the first pattern to the first bearing condition data, the computer compares a second pattern thereto to determine a pattern correlation value for the second pattern, the one of the plurality of patterns having the largest pattern correlation value corresponds to the defect in the bearing,” which forms part of the abstract idea because it may be performed via mental processes (evaluation and judgment) and also/alternatively is fundamentally characterized by mathematical calculations/relations.
Claims 3-6, 10-13, and 16-19 further characterize the nature (e.g., source) of the data processed by the steps falling within the judicial exception and therefore themselves fall within the same judicial exception.
Claims 7, 14, and 20 further characterize the nature of the “machine” as being a “railcar” and the bearing as located in an axle box, neither of which appears to play a significant functional role in the manner in which the steps falling within the judicial exception are performed, such that these features essentially entail a part of high level data collections that neither integrate the judicial exception into a practical application nor result in the claim as a whole amounting to significantly more than the judicial exception.
Dependent claims 2-8, 10-14, and 16-20 therefore also constitute ineligible subject matter under 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 15-16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hayzen (US 2020/0225117 A1).
As to claim 15, as best understood and interpreted in view of the grounds for rejecting claim 15 under 112(b), Hayzen teaches “[a] method of monitoring a bearing on a machine ([0005]; method described with reference to FIGS. 3-5)” “comprising the steps of:
providing a shaft disposed on the machine (FIG. 2 shaft 14 disposed within machine 12), the shaft having a first axial end (FIG. 2 shaft 14 includes axial ends);
providing a first bearing disposed on the first axial end of the shaft (FIG. 2 bearing B1 disposed proximate to an axial end of shaft 14);
providing a first sensor (FIG. 2 either of sensors 16), located on the first bearing (FIG. 2 both of sensors 16 attached to machine 12 and located proximate to bearing B1, [0053] sensors 16 place at each bearing location) and configured to provide first bearing condition monitoring data which comprises vibration data ([0053] sensors 16 are vibration sensors generating vibration signals representative of vibration of machine);
providing a computer in communication with the first sensor (FIG. 2 vibration analysis computer 24 communicatively coupled with sensors 16);
automatically receiving, by the computer, [of] the first bearing condition monitoring data (FIG. 2 vibration analysis computer 24 configured to receive vibration data stored within vibration database 22 and originating from sensors 16, [0054] vibration analysis computer 24 processes the vibration data) and processing the vibration data into frequency domain to generate a spectral array of amplitudes and frequencies ([0054] analyzer 18 and/or vibration monitoring system 20 performs FFT on sensor data to provide spectral data (i.e., frequency domain). Examiner notes spectral data intrinsically includes amplitudes and frequencies. [0056] and [0059 frequency spectrum includes amplitude peaks; FIG. 3 block 110);
providing a plurality of patterns each representing a particular defect symptom (FIG. 2 bearing fault frequency library 26; [0059] and [0061] library is database of bearing and associated fault frequencies corresponding to BPFI, BPFO, BSF, etc.) and each comprising of arrays of relative frequencies (FIG. 5 blocks 130 and 132, [0066] fault frequencies Ff for each pattern (e.g., BPFI) includes frequencies corresponding to different harmonics (relative frequencies with respect to a fundamental frequency)), determining a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect which is most probable in view of the first bearing condition monitoring data ([0068]-[0071] determine/select bearing (error) having lowest matching error (equivalent to greatest correlation/probability value)); and
wherein the computer, upon receiving the first bearing condition data from the first bearing, automatically determines a pattern correlation value for [a] first pattern ([0068]-[0071] determine/select bearing (error) having lowest matching error (equivalent to correlation value); [0011]; FIG. 3 blocks 116 and 118, [0059] compare measured amplitudes with library of fault frequencies to determine match (correlation)).
Regarding the feature “without having to know the speed of operation of the bearing,” the foregoing steps implemented as disclosed by Hayzen do not directly apply speed of operation of the bearing (e.g., shaft/bearing speed) and such that these aspects of the monitoring method are performed without having to know the speed of operation of the bearing.
As to claim 16, Hayzen teaches “[t]he method of claim 15, wherein the step of providing the plurality of patters comprises the design of the plurality of patterns being determined by prior bearing data for bearings having known operating conditions (FIG. 2 bearing fault frequency library 26 (prior bearing data related to faults (operating conditions), [0059]-[0060]).”
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.
Claims 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Hayzen in view of Zhang (US 2019/0353557 A1).
As to claim 17, Hayzen teaches “[t]he method of claim 15, wherein the step of providing the plurality of patterns further comprises the design of the plurality of patterns being determined by prior bearing data for bearings having known operating conditions (FIG. 2 bearing fault frequency library 26 (prior bearing data related to faults (operating conditions), [0059]-[0060]).”
Hayzen at least implicitly teaches that the fault patterns are for types of bearings that are used in the same machine but does not appear to expressly teach that the prior bearing data is for bearings that themselves are “used in the same machine.”
Zhang discloses a method for detecting bearing failure that includes determining whether vibration data matches a known vibration signature for abnormal operation of elements of a hydraulic fracturing rig (same machine for which vibration data obtained) ([0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Zhang’s teaching of using fault signature (fault pattern) data obtained from an element of an overall machine as the fault patterns against with to compare measured vibration data of the machine to determine faults to the method taught by Hayzen, such that Hayzen’s disclosed bearing fault frequency library includes bearing data that is for bearings used in the same machine.
The motivation would have been to provide more accurate defect patterns (for bearings in same operational context) as suggested by Zhang.
As to claim 18, Hayzen teaches “[t]he method of claim 15, wherein the step of providing the plurality of patterns further comprises the design of the plurality of patterns being determined by prior bearing data for bearings having known operating conditions (FIG. 2 bearing fault frequency library 26 (prior bearing data related to faults (operating conditions), [0059]-[0060]).”
Hayzen at least implicitly teaches that the fault patterns are for types of bearings that are used in a comparable class of machines but does not appear to expressly teach that the prior bearing data is for bearings that themselves are “used in a comparable class of machines.”
Zhang discloses a method for detecting bearing failure that includes determining whether vibration data matches a known vibration signature for abnormal operation of elements of a hydraulic fracturing rig (same machine, and therefore comparable class of machines, for which vibration data obtained) ([0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Zhang’s teaching of using fault signature (fault pattern) data obtained from an element of an overall machine as the fault patterns against with to compare measured vibration data of the machine to determine faults to the method taught by Hayzen, such that Hayzen’s disclosed bearing fault frequency library includes bearing data that is for bearings used in a comparable class of machines.
The motivation would have been to provide more accurate defect patterns (for bearings in similar operational context) as suggested by Zhang.
As to claim 19, Hayzen teaches “[t]he method of claim 15, wherein the step of providing the plurality of patterns further comprises the design of the plurality of patterns being determined by prior bearing data from multiple bearings having a known operating condition (FIG. 2 bearing fault frequency library 26 (prior bearing data related to faults (operating conditions), [0059] library include databased of 100,000 bearings).”
Hayzen at least implicitly teaches that the fault patterns are for types of bearings that are used in multiple machines (absent any indication that the bearings are custom designed for use in a single machine) but does not appear to expressly teach that the prior bearing data is for multiple bearings that themselves are “used in multiple machines.”
Zhang discloses a method for detecting bearing failure that includes determining whether vibration data matches a known vibration signature for abnormal operation of elements of a hydraulic fracturing rig (multiple sub-elements of the overall rig which itself constitutes multiple machines ([0014] hydraulic fracturing system may include multiple machines), for which vibration data obtained) ([0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Zhang’s teaching of using fault signature (fault pattern) data obtained from multiple elements of an overall machine that includes multiple machines as the fault patterns against with to compare measured vibration data of the machine to determine faults to the method taught by Hayzen, such that Hayzen’s disclosed bearing fault frequency library includes bearing data that is for bearings used in multiple machines.
The motivation would have been to provide defect patterns that more comprehensively represent a multi-machine operational environment as suggested by Zhang.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Hayzen in view of Thomson (US 2017/0108406 A1).
As to claim 20, Hayzen teaches “[t]he method of claim 15,” and further discloses that the first bearing is located on an axle (FIG. 2 bearing B1 on shaft 14). Hayzen discloses the machine as a generic machine (FIG. 2 machine 12), such that Hayzen does not specifically characterize the machine as being a railcar and the first bearing being located in an “axle box.”
Thomson discloses a method for assessing bearing defects and discloses as background that railcars having axle-boxes may be the machine for which vibration testing may be implemented ([0008] rail axle bearing monitoring in contexts that include an axle-box. Examiner notes that a rail axle is attached to an overall rail car).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Thomson’s teaching of monitoring bearings of a railcar including axle box to the method taught by Hayzen, such that Hayzen’s method is applied to a railcar in which the first bearing is located in an axle box. Such a combination would amount to applying Hayzen’s general method of monitoring a bearing in a known bearing monitoring context to achieve predictable results.
Subject Matter Patentably Distinguishable Over the Prior Arts
Claims 1-14 are found to be patentably distinct from the prior arts for the following reasons.
Regarding independent claims 1 and 9, the most pertinent prior arts are represented by Hayzen (US 2020/0225117 A1) and Thomson (US 2022/0057296 A1).
Regarding claim 1, Hayzen teaches “[a] method of monitoring a bearing on a machine ([0005]; method described with reference to FIGS. 3-5)” “comprising the steps of:
providing a shaft disposed on the machine (FIG. 2 shaft 14 disposed within machine 12), the shaft having a first axial end (FIG. 2 shaft 14 includes axial ends);
providing a first bearing disposed on the first axial end of the shaft (FIG. 2 bearing B1 disposed proximate to an axial end of shaft 14);
providing a first sensor (FIG. 2 either of sensors 16), located on the first bearing (FIG. 2 both of sensors 16 attached to machine 12 and located proximate to bearing B1, [0053] sensors 16 place at each bearing location) and configured to provide first bearing condition monitoring data which comprises vibration data ([0053] sensors 16 are vibration sensors generating vibration signals representative of vibration of machine);
providing a computer in communication with the first sensor (FIG. 2 vibration analysis computer 24 communicatively coupled with sensors 16);
automatically receiving, by the computer, [of] the first bearing condition monitoring data (FIG. 2 vibration analysis computer 24 configured to receive vibration data stored within vibration database 22 and originating from sensors 16, [0054] vibration analysis computer 24 processes the vibration data) and processing the vibration data into frequency domain to generate a spectral array of amplitudes and frequencies ([0054] analyzer 18 and/or vibration monitoring system 20 performs FFT on sensor data to provide spectral data (i.e., frequency domain)). Examiner notes spectral data inherently includes amplitudes and frequencies. [0056] and [0059 frequency spectrum includes amplitude peaks; FIG. 3 block 110);
providing a plurality of patterns each representing a particular defect symptom (FIG. 2 bearing fault frequency library 26; [0059] and [0061] library is database of bearing and associated fault frequencies corresponding to BPFI, BPFO, BSF, etc.) and each comprising an array of relative frequencies (FIG. 5 blocks 130 and 132, [0066] fault frequencies Ff for each pattern (e.g., BPFI) includes frequencies corresponding to different harmonics (relative frequencies))” “so that a maximum match between the first bearing condition monitoring data and the one of the plurality of patterns which corresponds to the defect yields a pattern correlation value of greatest magnitude ([0068]-[0071] select bearing (error) having lowest matching error (equivalent to greatest correlation)); and
wherein the computer, upon receiving the first bearing condition data from the first bearing, compares a first pattern thereto to determine a pattern correlation value for the first pattern ([0011]; FIG. 3 blocks 116 and 118, [0059] compare measured amplitudes with library of fault frequencies to determine match (correlation)).”
Prior to the effective filing date, weighting defect spectral patterns was known in the art, such as disclosed by Thomson ([0024] defect test patterns can be weighted, such that a maximum match (e.g., between a frequency and a defect component/symptom) gives a highest value with respect to the others). Thomson ‘296 further explained in [0024] that each defect component/symptom in a defect test pattern has a maximum but generally lower value than 1.
However, the prior arts do not teach a manner of weighting a defect/reference spectral pattern of frequencies in which the weighting results in the root-sum-squared of the pattern of frequencies being confined to a maximum of one, such that the prior arts do not fairly disclose or suggest “each” [pattern] “being weighted such that their root-sum-squared is a maximum of 1” taken in combination with the other limitations of claim 1.
Claim 9 includes substantially similar elements as claim 1 including the same features that distinguish claim 1 from the prior arts.
Claims 2-8 and 10-14 depend from claims 1 and 9 respectively and are likewise distinguishable over the prior arts for the same reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W BACA whose telephone number is (571)272-2507. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached at (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MATTHEW W. BACA/Examiner, Art Unit 2857
/ANDREW SCHECHTER/Supervisory Patent Examiner, Art Unit 2857
Prosecution Insights