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 .
Responses to Amendments and Arguments
The amendments filed 2/10/2026 have been entered. Claims 1, 10, 11 and 15 are amended. Claims 1-20 remain pending in the application.
Applicant's amendments filed 2/10/2026 has overcome the objection of claim 1.
Applicant's argument and amendments filed 2/10/2026 with respect to
the rejection of claims 1-20 directed to a judicial exception under 35 U.S.C. 101 have been fully considered but are not persuasive.
On pages 9-18 of Applicant’s response, Applicant alleges that the Office Action has improperly identified the claims as a mental processes or mathematical concepts at least because the claims do not fall within one of the enumerated sub-groupings, and moreover that even if the claims could be considered to fall into a sub-grouping, they are integrated into a practical application. … embodiments of the present disclosure are directed toward improvements in cable health management: … The improvements associated with the practical application are directly provided by the claims by, at least, "monitoring health data," "generating profiles," "predicting future health metrics for additional cables," and "performing at least one recommended action for at least one of the one or more additional cables based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables." Accordingly, the practical application of claim I is directed towards at least improving cable health management by generating individual cable profiles using monitored health data to predict future health metrics for additional cables and then address the future health metrics by performing manual repair or replacement activities. … The specification and claims provide a solution to this technical field, namely, performing a recommended manual repair or replacement action for additional cables by generating individual cable profiles using monitored health data to predict future health metrics for the additional cables. As a result, the claims are directed toward an improvement in the field, with the specifically identified problem being directly solved using steps of the claim. … At least one embodiment includes performing recommended repair or replacement actions to improve cable health management. … Applicant respectfully submits that claim 1 provides specific and definite technical improvements to computer system operations. … the claimed invention improves system reliability and availability by reducing downtime through faster problem resolution and preventing cascading failures. Lastly, the claimed system enhances scalability by enabling the managing of larger number of components without proportional data collection and monitoring. These improvements represent significant technical advancements that go beyond merely implementing abstract ideas on a computer, providing measurable benefits to maintenance recommendation systems. … Accordingly, Applicant respectfully submits that claim I reflects specific improvements to the operation computer systems in the context of health metric prediction and cable health management. … The additional elements in claim 1 as described above, when considered in combination, integrate the abstract idea into a practical application because claim 1 improves providing cable health management. … Accordingly, Applicant respectfully requests withdrawal of the rejection under§ 101.
The Examiner respectfully disagrees.
Under 2106.04(a)(2)), the step of "monitoring health data~" which is indicative of mental processes related to concepts performed in the human mind. (MPEP 2106.04(a)(2)). The steps of "automatically generating, using the analyzed health data, profiles ~ " may encompass manually calculating or inferring the health metrics the thereby generate (calculate or infer) the profiles of each cable, which is indicative of mathematical concepts and/or mental processes related to concepts performed in the human mind and/or organized by a human activity which may be performed in a process where, for example, a person may look at cables and components to thereby generate data related to cables health. (MPEP 2106.04(a)(2)). The step of "predicting … future health metrics for related cables ~" manually calculating or inferring the future health metrics of the cables based on the generated (manually calculated or inferred) profiles, which is indicative of mathematical concepts and/or mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)). The step of "performing at least one recommended action ~" may encompass manually inferring the evaluation and/or opinions by recommending action (i.e., action related to evaluation, opinions, and/or maintenance) for the cables based on the mathematically calculated/inferred results of the future health metrics, which is indicative of mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)).
Note that the claims present no limitation of improvements that are indicative of integration into a practical application. The steps of "monitoring health data," "automatically generating profiles," "predicting future health metrics for related cables," and "performing at least one recommended action for the one or more related cables based on the future health metrics" in the context of claim 1 are indicative of mathematical concepts and/or mental processes, because all the steps may encompass manually calculating or inferring health data and the health metrics to thereby generate (calculate or infer) the profiles of each cable and perform recommended action related to cable’s health state/condition (i.e., health metrics) as presented above. (See MPEP 2106.04(a)(2))). The claims do not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how and or with what to monitor the health data and/or, for example, a specific data structure of the health data. (See MPEP 2106.04(d)). Further, the claims do not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how/what to use the health metrics to thereby profiles of the individual cables, and how/what to predict the future health metrics from what specific data/information is used. The claims do not present a technical solution to a technical problem by proving an improvement to the functioning of computer, or to any other technology or technical field related to reducing computational resources as Applicant alleges. (See MPEP 2106.04(d)).
On pages 18-19 of Applicant’s response, Applicant alleges that "Claim 11 Not Fully Rejected under 3 5 USC § 10 l ," Applicant notes that the Office Action does not provide a reasoning under 35 U.S.C. 101 for the rejection of the final limitation of claim 11 which recites: apply, based on determining whether the individual component clusters …
The Examiner respectfully disagrees.
The limitation of “apply, based on determining whether the individual component clusters indicate maintenance is to be performed, maintenance schedules for the individual data transmission components” in claim 11 may encompass a mental process to organize human activity for scheduling maintenance and/or indicate insignificant post-solution activity to schedule a maintenance based on the previous steps of abstract idea.
Therefore, the Examiner maintains the claims are ineligible. (See the detailed response presented below).
Applicant's argument and amendments filed 2/10/2026 with respect to
the rejection of claims 1-20 directed to a judicial exception under 35 U.S.C. 102 have been fully considered but are not persuasive.
On pages 20-22 of Applicant’s response, Applicant alleges that Gundel only allegedly discloses performing a recommended action for a monitored cable, however, and is silent toward performing a repair or replacement an additional cable, as recited by currently amended claim 1. … Applicant respectfully submits that at least the cited portions of Gundel do not disclose: predicting, using the generated profiles for the individual cables, future health metrics for one or more additional cables other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables; as recited by currently amended claim 1.
The Examiner respectfully disagrees.
Under the broadest reasonable interpretation, the additional cables may be indicative of a part of cables to perform maintenance in a user preference or interest. Under this interpretation, at least paragraphs 0007, 0046, 0048 and 0135-0138 teach determining (predicting) a health or status of electrical cables and predicting failure events to thereby generate notifications of failure and schedule maintenance or replacement of cables.
With respect to the limitation of “performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables”, at least at Fig. 5 and, paragraphs 0046 and 0135-0138 teach recommended action related to maintenance for repairing or replacing the cable, where the cited paragraphs teach determining a health or status of electrical cables to thereby schedule maintenance or replacement of electrical equipment, such as electrical cables 350, cable accessories 34. Therefore, the Examiner maintains the rejection under 35 U.S.C. 102. (See the detailed response presented below).
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.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether any abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
The 35 USC 101 analysis between each element of claims and its combination is presented in the table below
Claim number and elements
Judicial exception (Step 2A Prong one)
Practical application (Step 2A Prong two)/ Significantly more (Step 2B)
Claim 1
Step 1: Yes, statutory class
Step 2A Prong two: No / Step 2B: No
A computer-implemented method, comprising:
Step2A Prong one: Yes
monitoring health data collected from one or more monitored cables;
abstract idea
mental process
“monitoring health data~” is a mental process.
automatically generating, using the health data
abstract idea
mental process or mathematical concept
“generating, …” is a mental or mathematical process based on the health metrics.
“profiles” are a mental or math concept to present or define various degrees/levels or mathematical values/amounts/parameters related to the cables.
predicting, using the generated profiles for the individual cables, future health metrics for one or more additional cables other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables; and
abstract idea
mental process or mathematical concept
“predicting, …” is a mental or mathematical process based on the profiles.
“future health metrics” is a mental or mathematical process to be indicative of various degrees/levels or mathematical values/amounts/parameters.
performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables.
abstract idea
mental process or mathematical concept
“performing at least one recommended action ~” is a mental or mathematical process based on the mental or math concept (i.e., future health metrics).
Claims 1-20 are 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. Claims 1-20 are directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as addressed below and presented in the above table.
Step 2A: Prong One
Regarding Claim 1, the limitations recited in Claim 1, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mathematical calculations and/or the mind, as presented in the above table. Nothing in the claim elements precludes the step from practically being performed in the mind and/or the mathematical calculations. For example, “monitoring health data collected from one or more monitored cables” in the context of this claim may encompass manually monitoring or inferring the routine data (i.e., heath data), which is indicative of mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)). Similarly, “automatically generating, using the health data, profiles for individual cables of one or more monitored cables” in the context of this claim may encompass manually calculating or inferring the health data the thereby generate (calculate or infer) the profiles of each cable, which is indicative of mathematical concepts and/or mental processes related to concepts performed in the human mind and/or organized by a human activity which may be performed in a process where, for example, a person may look at cables and components to thereby generate data related to cables health. (MPEP 2106.04(a)(2)). For example, “predicting, using the generated profiles for the individual cables, future health metrics of one or more additional cables, other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables” in the context of this claim may encompass manually calculating or inferring the future health metrics of the additional cables based on the generated (manually calculated or inferred) profiles, which is indicative of mathematical concepts and/or mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)). For example, “performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables” in the context of this claim may encompass manually inferring the evaluation and/or opinions by recommending an action (i.e., action related to evaluation, opinions, and/or maintenance) for the cables based on the mathematically calculated/inferred results of the future health metrics, which is indicative of mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)).
Step 2A: Prong Two
This judicial exception is abstract ideal itself and not integrated into a practical application. In particular, the specification details use of a computer system to perform mathematical calculations or mental processes of “monitoring health data collected from one or more monitored cables”, “automatically generating, using the health data, profiles for individual cables of one or more monitored cables”, “predicting, using the generated profiles for the individual cables, future health metrics of one or more additional cables, other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables” and “performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables”. Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how and or with what to monitor the health data and/or, for example, a specific data structure of the health data. (See MPEP 2106.04(d)). Further, claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how/what to use the health data to thereby generate the profiles of the individual cables, how/what to predict the future health metrics and action from what specific data/information/ is used, and/or how /what, for example, signal/notification/component is used to perform the recommended action. Claim 1 does not present a technical solution to a technical problem by providing an improvement to the functioning of computer, or to any other technology or technical field related to reducing computational resources. (See MPEP 2106.04(d)). Therefore, there is no showing of integration into a practical application such as an improvement to the functioning of a computer, or to any other technology or technical field, or use of a particular machine.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of the abstract idea into a practical application, using the computer system to perform “monitoring health data collected from one or more monitored cables”, “automatically generating, using the health data, profiles for individual cables of one or more monitored cables”, “predicting, using the generated profiles for the individual cables, future health metrics of one or more additional cables, other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables” and “performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables” amounts to no more than mere instructions to apply the exception using a generic computer component. (See MPEP 2106.05). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept cannot provide statutory eligibility. Claim 1 is not patent eligible.
Regarding Claims 2-10, the limitations are further directed to an abstract idea, as described in claim 1. The limitation of “collecting the health data using one or more physical sensors that provide physical condition of the one or more monitored cables” recited in Claim 2 is insignificant extra-solution activities to merely gather routine data (i.e., “the health data”) used for performing abstract idea. The sensors recited in Claim 2 are recited at high-level of generalities to merely collect routine data (i.e., health data), which are used to perform abstract idea itself and performed by a generic computer component (i.e., sensors). The data center in Claim 4 and the interface panel in Claim 5 are recited at high-level of generalities to perform generic computer functions of a generic computer component. For the reasons described above with respect to Claim 1, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Regarding Claim 11, it is a system type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. The additional elements of the processors and the memory are high-level of generalities recited to perform a generic computer functions of a generic computer component. The additional limitation of “analyze physical condition data monitored from one or more data transmission components to determine one or more anomalies” in the context of this claim may encompass manually calculating or inferring health states (i.e., anomalies) based on the physical condition data. (MPEP 2106.04(a)(2)). The additional limitation of “categorize the analyzed physical condition data and the one or more anomalies for individual data transmission components of the one or more data transmission components to determine corresponding individual health profiles” in the context of this claim may encompass manually calculating or inferring (i.e., categorizing) data and health states (i.e., physical condition data and anomalies) via mathematical calculation or mental process to thereby infer/determine the health profiles. (MPEP 2106.04(a)(2)). The additional limitation of “create, using the individual health profiles, one or more component clusters to group the individual data transmission components with similar profiles, wherein the individual health profiled are associated with individual component clusters of the one or more component clusters” in the context of this claim may encompass manually calculating or inferring component clusters, where the creating step may be computer data process itself performed by arithmetic operations of a generic computer function and the component clusters may be indicative of a programable data structure. (MPEP 2106.04(a)(2)). The additional limitation of “apply, based on determining whether the individual component clusters indicate maintenance is to be performed, maintenance schedules for the individual data transmission components” in claim 11 may encompass a mental process to organize human activity for scheduling maintenance and/or indicate insignificant post-solution activity to schedule a maintenance based on the previous steps of abstract idea. For the reasons described above, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Regarding Claims 12-14, the limitations are further directed to an abstract idea, as described in claim 1-11. For the reasons described above with respect to Claims 1-11, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Regarding Claim 15, it is a device type claim having similar limitations as of claims 1 and 11 above. Therefore, it is rejected under the same rationale as of claims 1 and 11 above. The additional element of the circuits is a high-level of generality recited to perform a generic computer functions of a generic computer component. The additional limitation of “perform at least one recommended action including manually servicing one or more data transmission components using one or more logical clusters …” in the context of this claim may encompass manually calculating or inferring if the indication of maintenance is provided based on the collected data (i.e., logical clusters), which is indicative of mental processes related to concepts performed in the human mind and/or organized by a human activity. (MPEP 2106.04(a)(2)).
Regarding Claims 16-20, the limitations are further directed to an abstract idea, as described in claim 1-15. For the reasons described above with respect to claims 1-15, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
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 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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gundel et al. (US 20210190850 A1, hereinafter referred to as “Gundel”).
Regarding Claim 1, Gundel teaches a computer-implemented method, comprising:
monitoring health data collected from one or more monitored cables (Abstract, “monitoring electrical equipment of a power grid”; Para 0043, “Monitoring devices 33 may communicate event data indicative of the health or status of electrical cables 32, cable accessories 34. Event data may include data indicative of the sensor data generated by sensors of the electrical equipment 20”), wherein the health data includes individual cables of the one or more monitored cables having one or more physical characteristics of the cables (Para 0043, “event data indicative of the health or status of electrical cables 32 …Event data may include data indicative of the sensor data generated by sensors of the electrical equipment 20, device data for electrical equipment 20, analysis data, or a combination therein. …, conclusions or results of analyses performed on the sensor data, … Device data (also referred to as equipment data) may include identification data (e.g., a unique identifier corresponding to a particular article of electrical equipment 20), device type (e.g., transformer, joint, termination joint, etc.), an event timestamp, location data (e.g., GPS coordinates of the particular article of electrical equipment 20), manufacturing data (e.g., manufacturer, lot number, serial number, date of manufacture, etc.), installation data (e.g., date of installation, identity of an installer or installation team)”);
automatically generating, using the health data, profiles for the individual cables (Para 0046 “, monitoring device 33A may analyze sensor data generated by the sensors of monitoring device 33A to determine a health of cable accessory 34A”; Para 0046, “perform analytics locally. In some examples, monitoring device 33A may analyze sensor data generated by the sensors of monitoring device 33A to determine a health of cable accessory 34A. Monitoring device 33A may determine a health of cable accessory 34A by determining whether cable accessory 34A is predicted to fail (e.g., experience a failure event) within a threshold amount of time, determine an estimated remaining lifespan, etc. Monitoring device 33A may output analysis data based on the results of the analysis. For example, the analysis data may include data indicative of a health of cable accessory 34A. Monitoring device 33A may output event data that includes the analysis data t”); and
predicting, using the generated profiles for the individual cables, future health metrics of one or more additional cables, other than the one or more monitored cables, the one or more additional cables being similar to at least one of the individual cables (Under the broadest reasonable interpretation, the additional cables may be indicative of a part of cables to perform maintenance in a user preference or interest. Under this interpretation, at least paragraphs 0007, 0046, 0048 and 0135-0138 teach determining (predicting) a health or status of electrical cables and predicting failure events to thereby generate notifications of failure and schedule maintenance or replacement of cables.; Para 0007, “By determining a health status of electrical equipment and predicting failure events before they occur, a computing system may proactively and preemptively generate notifications and/or alter the operation of a power grid before a failure event occurs”; Para 0048, “control and actively manage many aspects of electrical equipment 20, … review event data acquired and stored by EEMS 6. In addition, users 18 may interact with EEMS 6 to perform asset tracking and to schedule maintenance or replacement for individual pieces of electrical equipment 20, e.g., monitoring devices 33, cables 32 and/or cable accessories 34”; paragraph 0043, 0135-0138); and
performing at least one recommended action for the one or more additional cables other than the one or more monitored cables, based on the future health metrics, the at least one recommended action including repair or replacement of at least one of the one or more additional cables (At least at Fig. 5 and, paragraphs 0046 and 0135-0138 teach recommended action related to maintenance for repairing or replacing the cable, where the cited paragraphs teach determining a health or status of electrical cables to thereby schedule maintenance or replacement of electrical equipment, such as electrical cables 350, cable accessories 34).
Regarding Claim 2, Gundel teaches further comprising: collecting the health data using one or more physical sensors that provide physical condition of the one or more monitored cables (Para 0043, “Monitoring devices 33 may communicate event data indicative of the health or status of electrical cables 32, cable accessories 34. Event data may include data indicative of the sensor data generated by sensors of the electrical equipment 20, device data for electrical equipment 20, …, conclusions or results of analyses performed on the sensor data, … Device data (also referred to as equipment data) may include identification data (e.g., a unique identifier corresponding to a particular article of electrical equipment 20), device type (e.g., transformer, joint, termination joint, etc.), an event timestamp, …, manufacturing data (e.g., manufacturer, lot number, serial number, date of manufacture, etc.), installation data (e.g., date of installation, identity of an installer or installation team)”).
Regarding Claim 3, Gundel teaches wherein monitoring the health data occurs continuously during operation of the one or more monitored cables (Under the broadest reasonable interpretation, at least paragraphs 0039 and 0043 teaches the data related to the cable are collected/generated during the operation of Monitoring devices 33, “Monitoring devices 33 may communicate event data indicative of the health or status of electrical cables 32, cable accessories 34. Event data may include data indicative of the sensor data generated by sensors of the electrical equipment 20”; Para 0039, “Monitoring devices 33 include sensors that generate sensor data indicative of the operating characteristics of one or more electrical cables 32 and/or cable accessories 34 or the condition of electrical equipment”).
Regarding Claim 4, Gundel teaches wherein the one or more monitored cables transmit data in a data center (Para 0043, “Monitoring devices 33 may communicate event data indicative of the health or status of electrical cables 32, cable accessories 34).
Regarding Claim 5, Gundel teaches wherein the one or more monitored cables connect to an interface panel (Fig. 1, able accessories 34).
Regarding Claim 6, Gundel teaches wherein the health metrics include one or more types of cable failures (Para 0043, “event data indicative of the health or status of electrical cables 32 …the event data includes analysis data, such as data indicating whether the electrical equipment is predicted to fail (e.g., whether a failure event is predicted to occur)”).
Regarding Claim 7, Gundel teaches further comprising: determining a relative location of the one or more monitored cables based on the analyzed health metrics (Para 0043, “event data indicative of the health or status of electrical cables 32 … data indicative of the sensor data …, location data (e.g., GPS coordinates of the particular article of electrical equipment 20)”).
Regarding Claim 8, Gundel teaches wherein predicting the future health metrics utilizes machine learning (Para 0079, “utilizes machine learning when operating on event streams so as to perform real-time analytics. That is, analytics service 68F may include executable code generated by application of machine learning to training data of event streams and known failure events to detect patterns”; Para 0125 and 0117).
Regarding Claim 9, Gundel teaches wherein predicting the future health metrics applies cross-correlation of the generated profiles (Para 0050, “EEMS 6 may apply analytics to identify relationships or correlations between sensed data from sensors of monitoring devices 33 monitoring electrical equipment 20”).
Regarding Claim 10, Gundel teaches further comprising: sending instructions for servicing of the one or more additional cables in response to the predicted future health metric (At least paragraphs 0046-0051 teach controlling/scheduling maintenance, repair or replacement of cables).
Regarding Claim 11, Gundel teaches a system, comprising:
one or more processors (Fig. 2, processor 58C 58D); and
memory (Fig. 3, storage device; Para 0113) including instructions that, when executed by the one or more processors, cause the system to:
analyze physical condition data monitored from one or more data transmission components (Fig. 1, power lines 24, electrical cables 32, cable accessory 34A) to determine one or more anomalies (At least paragraphs 0046 and 0049-0050 teach analyzing sensor data generated by the sensors of monitoring device 33A to determine a health of cable accessory 34A and applies historical data and models to the inbound streams to compute assertions, such as identified anomalies or predicted occurrences of failure events based on data from sensors of electrical equipment 20);
categorize the analyzed physical condition data and the one or more anomalies for individual data transmission components of the one or more data transmission components to determine corresponding individual health profiles (At least paragraphs 0048-0049 teaches processing hundreds, thousands, or even millions of concurrent streams of events from monitoring devices 33 that monitor respective articles of electrical equipment 20 and identifying anomalies or predicted occurrences of failure events based on data from sensors of electrical equipment 20);
create, using the individual health profiles, one or more component clusters to group the individual data transmission components having similar profiles, wherein the grouping associates the individual data transmission components health profiled are associated with individual component clusters of the one or more component clusters (At least paragraph 0082 teaches generating models 74C such as Clustering algorithms. Paragraph 0241 teaches EEMS 6 or monitoring devices 720 may correlate known failure events to signal magnitude, inception voltage, phase angle of the discharge (e.g., power delivery), frequency content, among others. As another example, EEMS 6 or monitoring device 720 may correlate known failure events based groups or cluster of partial discharge events, time between partial discharge events or clusters of partial discharge events, quantity of discharge events per time, quantity of discharge events per phase angle, min or max inception voltage, or any other variable.); and
apply, based on determining whether the individual health profiles associated with the individual component clusters indicate maintenance is to be performed, maintenance schedules including manually servicing the individual data transmission components (At least paragraphs 0046-0051 teaches controlling/scheduling maintenance, repair or replacement of cables by reviewing event data acquired and stored by EEMS 6, and by performing asset tracking and to schedule maintenance or replacement for individual pieces of electrical equipment 20, e.g., monitoring devices 33, cables 32 and/or cable accessories 34).
Regarding Claim 12, Gundel teaches wherein the maintenance schedules are predicted utilizing machine learning (Para 0006, “the monitoring system may implement one or more machine learning techniques … more accurate prediction the health status of an article of equipment when applying the model to subsequent partial discharge data”) at least in part (Para 0048, “perform asset tracking and to schedule maintenance or replacement for individual pieces of electrical equipment 20”; Para 0089, “EEMS 6 may schedule maintenance (e.g., repair or replacement) operations of electrical equipment 20 based on event data”).
Regarding Claim 13, Gundel teaches wherein the maintenance schedules are predicted utilizing cross-correlation of the individual health profiles (Para 0080, “EEMS 6 may apply analytics to identify relationships or correlations between sensed data from sensors of monitoring devices 33 monitoring electrical equipment 20, … generate status indications, determine performance analytics, and/or perform prospective/preemptive actions based on a likelihood of a failure event (e.g., scheduling maintenance or replacement)”).
Regarding Claim 14, Gundel teaches wherein the one or more anomalies include one or more types of failures, each of the types of failures being associated with specific physical condition data values (Para 0075, “detect anomalies, transform incoming event data values, or trigger alerts upon predicting a possible failure event (e.g., failure of an article of electrical equipment 20). Historical data and models 74C may include, for example, one or more trained models configured to predict whether a failure vent will occur, an expected remaining lifespan for one or more articles of electrical equipment 20, and/or prioritize maintenance (e.g., repair or replacement) of articles of electrical equipment”).
Regarding Claim 15, it is a device type claim having similar limitations as of claims 1 and 11 above. Therefore, it is rejected under the same rationale as of claims 1 and 11 above.
Regarding Claim 16, Gundel teaches wherein the characteristic data includes one or more physical metrics taken from one or more physical sensors that collect data related to the one or more data transmission components (Para 0043, “event data indicative of the health or status of electrical cables 32 …Event data may include data indicative of the sensor data generated by sensors of the electrical equipment 20, device data for electrical equipment 20, analysis data, or a combination therein. …, conclusions or results of analyses performed on the sensor data, … Device data (also referred to as equipment data) may include identification data (e.g., a unique identifier corresponding to a particular article of electrical equipment 20), device type (e.g., transformer, joint, termination joint, etc.), an event timestamp, location data (e.g., GPS coordinates of the particular article of electrical equipment 20), manufacturing data (e.g., manufacturer, lot number, serial number, date of manufacture, etc.), installation data (e.g., date of installation, identity of an installer or installation team)”)
Regarding Claim 17, Gundel teaches wherein the characteristic data includes the location of the one or more data transmission component data (Para 0043, “event data indicative of the health or status of electrical cables 32 … data indicative of the sensor data …, location data (e.g., GPS coordinates of the particular article of electrical equipment 20)”).
Regarding Claim 18, it is dependent on claim 15 and has similar limitations as of claim 3 above. Therefore, it is rejected under the same rationale as of claim 3 above.
Regarding Claim 19, Gundel teaches wherein the maintenance recommendations include preventative maintenance for an individual data transmission component of the one or more data transmission components based on the monitored characteristic data of an individual logical cluster of the one or more logical clusters (At least paragraphs 0046-0051 teaches controlling/scheduling maintenance, repair or replacement of cables by reviewing event data acquired and stored by EEMS 6, and by performing asset tracking and to schedule maintenance or replacement for individual pieces of electrical equipment 20, e.g., monitoring devices 33, cables 32 and/or cable accessories 34).
Regarding Claim 20, Gundel teaches wherein the one or more logical clusters are visualized (Para 0062, “the client applications may output (e.g., for display) data received from EEMS 6 to visualize such data for users of clients 63”).
Citation of Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
GUNDEL et al. (CN 112673265 A) teaches a system, comprising: one or more sensors, the one or more sensors are coupled to the electrical device article, the one or more sensors are configured to generate sensor data indicative of one or more conditions of the electrical device article; and at least one processor; and a storage device, the storage device comprises instructions, the instructions when executed by the at least one processor such that the at least one processor: receiving the sensor data; determining a health status of the electrical device article based at least in part on the sensor data; and in response to determining the health status of the electrical device article, performing an operation; wherein execution of the instructions causes the at least one processor to determine the health state of the electrical device article by at least causing the at least one processor to predict whether the electrical device article will fail to occur within a predetermined amount of time; and wherein execution of the instructions causes the at least one processor to perform the operation in response to predicting that the electrical device product will fail within the predetermined amount of time.
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.
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/BYUNG RO LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858
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