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 .
Response to Amendment
Claims 1, 4-10 and 12-15 are pending
Claims 1, 10, 12 and 15 have been amended
Claim 11 has been cancelled
Response to Arguments
Applicant's arguments filed 11/20/2025 have been fully considered but they are not persuasive. Regarding claim 1, the applicant argues that the human mind is incapable of implementing a trained machine learning algorithm that determines if condition monitoring data is associated with a fault state (Remarks, page 11). However, under the broadest reasonable interpretation (BRI), words of the claim are given their plain meaning. Furthermore, according to MPEP 2106.04, the claim is still directed to an abstract idea without offering significantly more. However, it is possible to mathematically transform an image to add a "hot spot" by manipulating pixel data, often using techniques like kernel filters (which use convolution matrices) to create localized intensity changes or statistical methods like Getis-Ord Gi* to find significant clusters (hot spots) in existing data, then visually representing those areas with heightened intensity or color, effectively adding a math-defined highlight. Applicant, further argues the claim is directed to a practical application (Remarks, page 11). The practical application being generating a more balanced data set that is used to train a machine learning algorithm. However, this is not considered a technological improvement but still an abstract idea. Mentally generating a balanced dataset involves techniques like undersampling (removing majority class data), oversampling (duplicating minority class data or creating synthetic data with methods like SMOTE(synthetic minority oversampling technique)), or using class weights within the algorithm to make it pay more attention to rare classes, aiming for a more equal representation (e.g., 50/50 or a more realistic partial balance like 80/20) rather than a skewed 99/1 split, preventing the model from ignoring minority instances. Accordingly, applicant’s arguments regarding the claim features providing technological improvements and the human mind being incapable of transforming data are not persuasive and the rejection is maintained.
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.
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Regarding claim 1, the claim recites a method for fault state detection, comprising: receiving condition monitoring data comprising vibration data; analyzing, by a trained machine learning algorithm, the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state; transforming non-fault state condition monitoring data to fault state condition monitoring data to generate the fault state condition monitoring data in a subset of a plurality of fault state condition monitoring data, wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises adding a hot spot to a non-fault state infrared image, and wherein the hot spot is added at a random position within the non-fault state infrared image, wherein, the trained machine learning algorithm was trained on a basis of a plurality of non-fault state condition monitoring data and associated ground truth information and on a basis of the plurality of fault state condition monitoring data and associated ground truth information, wherein the plurality of non-fault state condition monitoring data comprises vibration data, the plurality of fault state condition monitoring data comprises vibration data, wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data further comprises an increase in a vibration amplitude peak, wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in different frequency bins, wherein an increase in the vibration amplitude peak comprises an increase in the amplitude in one of the different frequency bins, and wherein the associated round truth information of the plurality of fault state condition monitoring data includes a type of fault; wherein, the subset of the plurality of fault state condition monitoring data was generated from one or more non-fault state condition monitoring data, and determining the type of fault that led to a respective fault state data of the plurality of fault state condition monitoring data.
Step
Analysis
1: Statutory Category?
Yes. The claim recites a method; therefore, it is a process
2A - Prong 1: Judicial Exception Recited?
Yes. The claim recites the limitation of analyzing, via a trained machine learning algorithm, the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components.
The limitation of receiving condition monitoring data comprising vibration data, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind, because it encompasses receiving the data mentally.
The limitation of transforming non-fault state condition monitoring data to fault state condition monitoring data to generate the fault state condition monitoring data in a subset of a plurality of fault state condition monitoring data, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind, because it similar to making a determination, which is a mental step.
The limitation determining the type of fault that led to a respective fault state data of the plurality of fault state condition monitoring data, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in the claim precludes the determining step from practically being performed in the human mind. For example, the claim encompasses mentally making the determination by diagnosis.
2A - Prong 2: Integrated into a Practical Application?
No. the claims recites the additional elements: receiving condition monitoring data comprising vibration data and a trained machine learning algorithm.
The receiving step is recited at a high level of generality (i.e., as a general means of gathering vibration data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
The trained machine learning algorithm is nothing more than code used to implement the abstract idea and does not have a physical embodiment. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The examiner finds that each of the following additional elements merely recites the words “apply it” (or an equivalent) with the abstract idea, or merely includes instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform the abstract idea:
wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises adding a hot spot to a non-fault state infrared image, and wherein the hot spot is added at a random position within the non-fault state infrared image
The claim is directed to the abstract idea.
2B: Claim provides an Inventive Concept?
No. the additional element in the claim amounts to no more than mere instructions to apply the exception in a generic computer environment. Mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claim is ineligible.
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 4 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 4 is further recites the element(s) “… wherein the received condition monitoring data comprises the vibration data and the plurality of non-fault state condition monitoring data comprises the vibration data and the plurality of fault state condition monitoring data comprises the vibration data, and wherein the transformation of the non-fault state condition monitoring data to fault state condition monitoring data comprises a decrease in the vibration amplitude peak.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 4 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 5 depends on claim 4, which depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 5 is further recites the element(s) “… wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in the different frequency bins, and wherein the decrease in the vibration amplitude peak comprises a decrease in the amplitude in one of the different frequency bins.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 5 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 6 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 6 is further recites the element(s) “… wherein the received condition monitoring data comprises the vibration data and the plurality of non-fault state condition monitoring data comprises the vibration data and the plurality of fault state condition monitoring data comprises the vibration data, and wherein the transformation of the non-fault state condition monitoring data to fault state condition monitoring data comprises a shift in the vibration amplitude peak.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 6 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 7 depends on claim 6, which depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 7 is further recites the element(s) “… wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in the different frequency bins, and wherein the shift in the vibration amplitude peak comprises an increase in the amplitude in a first one of the different frequency bins and an associated decrease in the amplitude in a second one of the different frequency bins.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 7 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 8 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 8 is further recites the element(s) “… wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises a preservation of a total vibrational energy.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 8 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 9 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 9 is further recites the element(s) “… wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises a change of a total vibrational energy.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 9 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 10 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 10 is further recites the element(s) “… wherein the received condition monitoring data comprises infrared image data and the plurality of non-fault state condition monitoring data comprises infrared image data and the plurality of fault state condition monitoring data comprises infrared image data, and wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises the addition of the hot spot to the non-fault state infrared image.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 10 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 12 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 12 is further recites the element(s) “… wherein the hot spot is added at a position within the non-fault state infrared image associated with a conductive part of an imaged object.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 12 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 13 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 13 is further recites the element(s) “… wherein the received condition monitoring data comprises visible image data and the plurality of non-fault state condition monitoring data comprises visible image data and the plurality of fault state condition monitoring data comprises visible image data, and wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises an addition of a scratch or dent to an object in a non-fault state visible image.”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 13 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 14 depends on claim 1, therefore, it has the abstract idea and also has the routine and conventional structure above said claims.
In addition, claim 14 is further recites the element(s) “… an input unit and a processing unit executing the method according to an input unit and a processing unit executing the method according to receiving by an input unit condition monitoring data;”, which are/is simply more calculations/mental-steps, value numbers, extra solution activities routine and/or conventional structure(s) previously known to the pertinent industry.
Furthermore, Claim 14 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these/this limitation(s) are/is simply routine and conventional structures previously known to the pertinent industry that serve to generate the data to be processed by implementing the idea on a computer, and/or recitation of generic computer structure and also serve to perform generic computer functions that are well-understood routine, and conventional activities previously known to the pertinent industry.
Regarding claim 15, the claim recites a method of training a machine learning algorithm for a fault state detection apparatus, the method comprising: providing a plurality of non-fault state condition monitoring data and associated ground truth information; providing a plurality of fault state condition monitoring data and associated ground truth information, the providing comprising generating a subset of the plurality of fault state condition monitoring data from one or more non-fault state condition monitoring data, and wherein the generating of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises transforming non-fault state condition monitoring data to fault state condition monitoring data, wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises adding a hot spot to a non-fault state infrared image, and wherein the hot spot is added at a random position within the non-fault state infrared image; implementing a machine learning algorithm; training the machine learning algorithm on the basis of the plurality of non-fault state condition monitoring data and the associated ground truth information and on the basis of the plurality of fault state condition monitoring data and the associated ground truth information; receiving condition monitoring data comprising vibration data; analyzing, by the trained machine learning algorithm, the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state, wherein the plurality of non-fault state condition monitoring data comprises vibration data, the plurality of fault state condition monitoring data comprises vibration data, wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data further comprises an increase in a vibration amplitude peak, wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in different frequency bins, wherein the increase in the vibration amplitude peak comprises an increase in the amplitude in one of the different frequency bins, and wherein the associated ground truth information of the plurality of fault state condition monitoring data includes a type of fault; and determining the type of fault that led to a respective fault state data of the plurality of fault state condition monitoring data.
Step
Analysis
1: Statutory Category?
Yes. The claim recites a method; therefore, it is a process
2A - Prong 1: Judicial Exception Recited?
Yes. The limitation of training the machine learning algorithm on the basis of monitoring data is, drafted, is a process dictated by code which is an idea without physical embodiment.
The claim recites the limitation of analyzing, via a trained machine learning algorithm, the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components.
The limitation of transforming non-fault state condition monitoring data to fault state condition monitoring data to generate the fault state condition monitoring data in a subset of a plurality of fault state condition monitoring data, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind, because it similar to making a determination, which is a mental step.
The limitation determining the type of fault that led to a respective fault state data of the plurality of fault state condition monitoring data, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in the claim precludes the determining step from practically being performed in the human mind. For example, the claim encompasses mentally making the determination by diagnosis.
2A - Prong 2: Integrated into a Practical Application?
No. the claims recites the additional elements: providing a plurality of non-fault state condition monitoring data and associated ground truth information; providing a plurality of fault state condition monitoring data and associated ground truth information, implementing a machine learning algorithm and receiving condition monitoring data comprising vibration data
The providing steps are recited at a high level of generality (i.e., as a general means for providing data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Implementing a machine learning algorithm is nothing more than code used to implement the abstract idea and does not have a physical embodiment. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The receiving step is recited at a high level of generality (i.e., as a general means of gathering vibration data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
The claim is directed to the abstract idea.
2B: Claim provides an Inventive Concept?
No. the additional elements in the claim amounts to no more than mere instructions to apply the exception in a generic computer environment. Mere instructions to apply an exception in a generic computer environment cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claim is ineligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US 20140176152 A1; Wolbank; Thomas Method and Device for Detecting a Deterioration in the State of an Insulation in an Operating Electric Machine
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 CARL F.R. TCHATCHOUANG whose telephone number is (571)272-3991. The examiner can normally be reached Monday - Friday 8:00am -5:00am.
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, Huy Phan can be reached at 571-272-7924. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CARL F.R. TCHATCHOUANG/Examiner, Art Unit 2858
/HUY Q PHAN/Supervisory Patent Examiner, Art Unit 2858