DETAILED ACTIONS
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/02/2026 has been entered.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 12/11/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Response to Amendment
This office action is in response to the amendments/arguments submitted by the Applicant(s) on 03/02/2026.
Status of the Claims
Claims 1-10, and 12-24 are pending.
Claims 1-4, 7,12,17, 20, and 23 are amended.
Claim 11 is cancelled.
Response to Arguments
Rejections Under 35 U.S.C. 103
Applicant's amendments/arguments, see remarks pages 8-11, filed on 03/02/2026. in regards to the independent claim 1 and claim 20 rejections under 35 U.S.C. §103 have been considered, and are moot because the amendment has necessitated a new ground of rejections. The new rejections are set forth below.
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 1-4, 6-24 are rejected under 35 U.S.C. 103 as being unpatentable over Bickel et al. (US 2017/0285114 A1, hereinafter Bickel”114) and in view of Capote et al. (US 2021/0055839 A1, hereinafter Capote).
Regarding Claim 1, Bickel”114 teaches,
A method for automatically identifying, analyzing and reducing extraneous waveform captures (WFCs) (Bickel”114, Figure 2, [0003] “At least one aspect of the disclosure is directed to a method for analyzing waveform capture data”) comprising:
capturing at least one energy-related waveform (Bickel”114, Figure 2, Step 204, Receive waveform data) in an electrical system using at least one waveform capture device (Bickel”114, Figure 2, “the method comprising receiving, by a controller from an intelligent electronic device. [0019] FIG. 1 illustrates a power monitoring system 100 for monitoring voltage, current, frequency, power, energy and/or other related values measured by one or more IEDs”).
comparing the at least one captured energy-related waveform to a previously captured energy-related waveform to determine whether the at least one captured energy-related waveform meets the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC (Bickel”114, Figure 2, Step 212, [0032], At act 212, the controller 110 compares the evaluated symptoms (e.g., represented by a partial classification, additional event data, metadata and IED information) to a lookup table including previously-stored electrical event symptoms and a diagnosed cause of the electrical event. the controller 110 may compare the evaluated symptoms to a waveform library in lieu of, or in addition to, the lookup table to diagnose a cause of an electrical event”) (Bickel, Figure 2, At act 214, the controller 110 diagnoses at least one potential electrical event responsible for causing the observed waveform symptoms” [0040]” FIG. 4 illustrates a table 400 of power quality event phenomena categories proposed by a first power quality classification standard, and types section 406”. a typical duration section 404 404, [0042] NOTE: electrical events are categorized based on standard classified events. However, additional or alternate possible categories of electrical events determination is possible. see [0042], [0049] (fig 5, step 510) [0049]).
performing one or more actions to reduce WFC data to be stored or analyzed, in response to determining the at least one captured energy-related waveform meets the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC (Bickel Figure 2, 114, ‘The selected power quality classification standard can provide information that assists in determining actions that may be taken to reduce or eliminate the possibility of the identified electrical event from occurring again. Step 216 Correct or Mitigate and store information step220”);
Bickel”114 is silent on identifying events as an extraneous WFC, a redundant WFC, or a provisional WFC
However, Capote teaches the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 2, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches wherein the one or more actions that are performed (Bickel”114, Figure 2, step 216-step 220) in response to determining the at least one captured energy-related waveform meets the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC, include at least one of:
deleting or otherwise removing the at least one captured energy-related waveform, tagging (Bickel”114, 0047] For example, the encoded information can include an electrical event identification tag (e.g., El, E2, E3, etc.) that uniquely identifies an electrical event, a selected electrical event category (e.g., Category 1, CAT2, Category 8, etc.) or otherwise indicating the defined status of the at least one captured energy- related waveform, storing the at least one captured energy-related waveform in specific location(s) (Bickel”114,[0044] By analyzing the characteristics of a waveform produced by an electrical event with known causes, the controller 110 is operable to store the analysis information in a data storage format (e.g., in a lookup table format) that associates a cause of an electrical event with the characteristic(s) of the electrical event. [0047],
recommending or updating waveform capture setting(s) or configuration(s) in the at least one waveform capture device capturing the at least one captured energy- related waveform (Bickel, Figure 2, step 216, “correct and mitigate causes [0035] At act 216, the controller 110 automatically initiates corrective or mitigative steps to fix the diagnosed cause of the electrical event”).
lowering or reducing the priority or importance of the at least one captured energy-related waveform, compressing the at least one captured energy-related waveform, or reducing the at least one captured energy-related waveform by one or more cycles to minimize its memory requirements (Bickel, Figures 1-2, 216-220, “[0039], The selected power quality classification standard can provide information that assists in determining actions that may be taken to reduce or eliminate the possibility of the identified electrical event from occurring again”.” In some examples, the controller 110 may be operable to automatically execute the prescribed actions, while in other examples, the controller 110 may display the recommendation(s) to an operator in a textual, graphical or other descriptive format”).
Regarding Claim 3, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches comprising: taking one or more additional actions subsequent to or in parallel to performing the at least one of the actions in response to determining the at least one captured energy- related waveform meets the criteria of being deemed/considered an extraneous WFC, a redundant WFC (Bickel, “[0026] Event data includes data descriptive of the electrical event. Event data includes data descriptive of the electrical event. For example, the event data can include instantaneous time-series waveform data recurrence and repetition information (e.g., whether or not the event is repetitive, how often the event recurs, etc.), date and time data, onset rate characteristics”) or a provisional WFC, the one or more additional actions including at least one of:
extracting associated alarm data, (Bickel, Figure 2, (“[0036] At act 218, the controller 110 notifies a user(s) of the occurrence of the electrical event and the steps taken to correct the cause of the electrical event. The notification can be sent graphically, textually, or by any other means to convey information to the user”) using data or information associated with the at least one captured energy-related waveform for other purposes (Bickel, “[0026] Event data includes data descriptive of the electrical event). such as a sample of the electrical system's post-event response ([0026] post-event data), changing other settings in association with alarm settings for more efficient alarms and alarm prioritization and using data or information associated with the at least one captured energy-related waveform to enhance segment- related analytics in cloud-based applications or to simplify what is presented to users in reports or on displays. (Bickel, [0037] “The notification can further include recommended steps to be taken to replace or repair the disconnected component accordingly. Furthermore, the notification can include recommended steps suggesting, for example, that a user install additional components to help mitigate an electrical event. At act 220, the analysis information is stored for use in subsequent diagnoses. For example, analysis information stored from previous diagnoses is at least partially used by the controller 110 to determine an electrical event diagnosis at act 212 ”. Figure 8, [0058] “The disclosure is not limited to a particular memory system 810 or a storage system 812.”)
Regarding Claim 4, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches, wherein a point-by-point comparison is performed between: at least one data point in at least one first cycle of the at least one captured energy-related waveform, and at least one or more corresponding data points in at least one second cycle of the at least one captured energy-related waveform or other WFCs (Bickel, Figure 4, [0041] A waveform capture data can be classified into at least one of the categories ( e.g., one of the categories from the categories section 402) during the partial classification stage. For example, after waveform capture data is received, the controller 110 evaluates an electrical event illustrated by
the waveform capture data. In one example, the controller 110 may initially determine whether the electrical event is periodic or aperiodic. In response to a determination that the electrical event is aperiodic, the controller 110 proceeds to
make a next determination, and so forth, until the controller 110 arrives at one of the one or more categories discussed above into which to classify the waveform capture”. [0042] Additional or alternate decisions may be executed that deviate from the examples provided herein, and the sequence of decisions leading to
each category, the specific number of each category and the specific contents of each category are not limited to the examples provided herein”),
Bickel”114 is silent on waveform considered an extraneous WFCa redundant WFC, or a provisional WFC.
However, Capote teaches the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 5, combination of Bickel”114 and Capote teaches the method of claim 4,
Bickel”114 further teaches wherein at least one of: the at least one data point in the at least one first cycle of the at least one captured energy-related waveform, and the at least one or more corresponding data points in the at least one second cycle of the at least one captured energy-related waveform or other WFCs (Bickel, Figure 4, Column 404, a typical duration section 404), is at least one of empirically determined and derived by interpolating to ensure the data points are correctly positioned based on their occurrence within the at least one captured energy-related waveform. (Bickel, Figure 4,[0043], “Additional examples of determinations to be executed can include (…) whether the duration of the electrical event is shorter or longer than a selected threshold, whether, if the electrical event is aperiodic, the aperiodic electrical event is a short-duration event,(…) the long-duration electrical event is an interruption, whether, if the electrical event is a long-duration electrical event”. [0046] The received waveform capture information is encoded according to a consistent file format by one or more entities including, for example, software-based entities, hardware-based entities, and so forth. Once a waveform capture has been partially classified as discussed above, information describing the categorization is encoded by the controller 110 for subsequent reference by either the controller 110 or by alternate power quality analysis tool”).
Regarding Claim 6, combination of Bickel”114 and Capote teaches the method of claim 4,
Bickel”114 further teaches wherein sensitivity of the algorithm used to perform the point-by-point comparison can be configured or determined based on at least one of (Bickel, [0046], The received waveform capture information is encoded according to a consistent file format by one or more entities including, for example, software-based entities, hardware-based entities, and so forth. Once Once a waveform capture has been partially classified as discussed above, information describing the categorization is encoded by the controller 110 for subsequent reference by either the controller 110 or by alternate power quality analysis tools”. [0050] FIG. 6 illustrates an analysis view 600 of a software implementation of a graphical user interface in accordance with one embodiment of the invention NOTE: algorithm set up is a design choice programed based on data type, duration, categories or classification):
the data points or cycles being compared the number of data points or cycles used in the comparison, comparison tolerance of the date points or cycle phase angles comparison tolerance of the data point or cycle magnitude, number of consecutive data points being compared, and specific phases being compared. (Figure 4, duration 404), [0040] FIG. 4 illustrates a table 400 of power quality event phenomena categories proposed by a first power quality classification standard. The table 400 includes a categories section 402, a typical duration section 404 and a types
section 406. also see [0026] for different data)
Regarding Claim 7, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 is silent on wherein the at least one captured energy- related waveform is compared to at least one other WFC to determine whether the at least one captured energy-related waveform meets the criteria of being considered an extraneous a redundant WFC, or a provisional WFC.
However, Capote teaches wherein the at least one captured energy- related waveform is compared to at least one other WFC to determine whether the at least one captured energy-related waveform meets the criteria of being considered an extraneous a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 8, combination of Bickel”114 and Capote teaches the method of claim 7,
Bickel”114 further teaches wherein the at least one other WFC is or includes at least one WFC or at least one model of a WFC from a WFC library or repository. (Bickel, [0027] In at least one example, the event data, metadata and IED information are each stored in one or more information libraries. The one or more information libraries may be stored in a memory element (e.g., memory element 114) internal to the controller 110 in some embodiments, while in other embodiments, the information libraries may be externally stored from the controller 110. The controller 110 is operable to access the one or more libraries and update the
stored information according to a schedule (e.g., periodically, a-periodically, automatically, manually, etc.). For example, the controller 110 can poll one or more libraries containing information and data that is relevant to electrical
event diagnoses, including, for example, libraries containing up-to-date power quality classification standards, up-to-date IED information, up-to-date metadata information, historical information describing previous electrical event diagnoses, and so forth”).
Regarding Claim 12, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches comprising: in response to determining the at least one captured energy-related waveform does not meet the criteria of being considered ([0040]” FIG. 4 illustrates a table 400 of power quality event phenomena categories proposed by a first power quality classification standard, and types section 406”. a typical duration section 404 404, [0042] NOTE: electrical events are categorized based on standard classified events. However, additional or alternate possible categories of electrical events determination is possible. see [0042], [0049] (fig 5, step 510) [0049]). an extraneous WFC a redundant WFC, or a provisional WFC, determining whether the at least one captured energy-related waveform meets the criteria of being considered a redundant WFC or another WFC classification. (Bickel”114, Figure 2, [0026] “Event data includes data descriptive of the electrical event. For example, the event data can include recurrence and repetition information (e.g., whether or not the event is repetitive, how often the event recurs, etc.”. one of the detected event is a “redundant event” categorized based on repetitive event data).
Regarding Claim 13, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches comprising: determining whether each WFC of the at least one captured waveform to be analyzed was captured using same or similar WFC characteristics; and in response to determining each WFC of the at least one captured waveform to be analyzed was not captured using same or similar WFC characteristics, determining whether one or more of the WFCs need to be reconstructed to make the WFCs suitable for comparisons or other meaningful analysis.(Bickel”114, Figure 2, [0044] The controller 110 is further operable to refine the discussed diagnostic processes by executing a Wave Shape Learning procedure on waveform captures that have known electrical event causes. By analyzing the characteristics of a
waveform produced by an electrical event with known causes. [0045] Figure 3-4, For example, with reference to the electrical event 302, the controller 110 may identify a wave shape or wave shapes with characteristics that are substantially identical to previously-learned wave shapes, and can ascribe the stored, known cause of the previously-learned wave shape(s) to the electrical event 302”)
Regarding Claim 14, combination of Bickel”114 and Capote teaches the method of claim 13,
Bickel”114 further teaches, wherein the WFC characteristics include at least one of: sample rate, resampling algorithms, down sampling algorithms, and other waveform capture constraints. (Bickel”114, Figures 1- 2, [0032] At act 210, the controller 110 evaluates the partial classification determined at act 208 against metadata, IED
information and the additional event data to further refine the partial classification. For example, the controller 110 may evaluate the sampling rate of the IED that provided the waveform capture to the controller 110 to ensure that the IED is capable of accurately representing the original event signal”).
Regarding Claim 15, combination of Bickel”114 and Capote teaches the method of claim 13,
Bickel”114 further teaches, wherein in response to determining one or more of the WFCs need to be reconstructed to make the WFCs suitable for comparisons or other meaningful analysis, the one or more of the WFCs are reconstructed based on or using one or more techniques. (Bickel”114, [0006] the controller is further configured to request additional information from the at least one intelligent electronic device. In one embodiment, the controller is further configured to modify a diagnosis based in part on the additional information. [0033] “the controller 110 can diagnose a cause of an electrical event (e.g., a three-phase capacitor switching event) by comparing the classification information discussed above (i.e., the partial classification [ e.g., as an oscillatory transient], the additional event data [ e.g., voltage data, current data, event synchronicity information, event polarity information, etc.], the IED information [ e.g., IED sampling rate information l and the meta data re. g., date and time information, hierarchy information, etc.]) against a lookup table or other data storage entity”)
Regarding Claim 16, combination of Bickel”114 and Capote teaches the method of claim 15,
Bickel”114 further teaches wherein the one or more techniques include at least one of: resampling, upsampling, downsampling, decimating, normalizing, and adding a range of acceptability. (Bickel”114, Figures 1- 2, [0032] the controller 110 may evaluate the sampling rate of the IED that provided the waveform capture to the controller 110 to ensure that the IED is capable of accurately representing the original event signal”).
Regarding Claim 17, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further teaches identifying events based is/are based, at least in part, on at least one of: load type(s), load mix, process(es), application(s) and customer type(s)). (Bickel”114, [0025] Metadata includes data indicative of the context in which the waveform capture data was acquired. For example, the metadata can include load type information, load characteristic information”)
Bickel”114 is silent on identifying events as an extraneous WFC, a redundant WFC, or a provisional WFC .
However, Capote teaches an extraneous WFC, a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 18, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further wherein the at least one waveform capture device includes at least one Intelligent Electronic Device (IED). (Bickel”114, Figure 1, [0019] FIG. 1 “The power monitoring system 100 includes one or more IEDs 102”).
Regarding Claim 19, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 further wherein the at least one waveform capture device is associated with an Electrical Power Monitor System (EPMS) responsible for monitoring or controlling one or more aspects of the electrical system. (Bickel”114, Figure 1, [0019] FIG. 1 “The power monitoring system 100 “)
Regarding Claim 20, Bickel”114 teaches,
A system (Bickel”114, Figure 1, [0019] “The power monitoring system 100 “)
for automatically identifying, analyzing and reducing extraneous waveform captures (WFCs), comprising:
at least one processor (Bickel”114, Figure 8, 806-processor);
at least one memory device coupled to the at least one processor, the at least one processor and the at least one memory device (Bickel”114, Figure 8, 810-memory);
configured to:
capturing at least one energy-related waveform (Bickel”114, Figure 2, Step 204, Receive waveform data) in an electrical system using at least one waveform capture device (Bickel”114, Figure 2, “the method comprising receiving, by a controller from an intelligent electronic device. [0019] FIG. 1 illustrates a power monitoring system 100 for monitoring voltage, current, frequency, power, energy and/or other related values measured by one or more IEDs”).
comparing the at least one captured energy-related waveform to a previously captured enerqy-related waveform to determine whether the at least one captured enerqy-related waveform meets the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC; and
comparing the at least one captured energy-related waveform to a previously captured energy-related waveform to determine whether the at least one captured energy-related waveform(Bickel”114, Figure 2, Step 212, [0032], At act 212, the controller 110 compares the evaluated symptoms (e.g., represented by a partial classification, additional event data, metadata and IED information) to a lookup table including previously-stored electrical event symptoms and a diagnosed cause of the electrical event. the controller 110 may compare the evaluated symptoms to a waveform library in lieu of, or in addition to, the lookup table to diagnose a cause of an electrical event”) (Bickel, Figure 2, At act 214, the controller 110 diagnoses at least one potential electrical event responsible for causing the observed waveform symptoms” [0040]” FIG. 4 illustrates a table 400 of power quality event phenomena categories proposed by a first power quality classification standard, and types section 406”. a typical duration section 404 404, [0042] NOTE: electrical events are categorized based on standard classified events. However, additional or alternate possible categories of electrical events determination is possible. see [0042], [0049] (fig 5, step 510) [0049]).
Bickel”114 is silent on identifying events as an extraneous WFC, a redundant WFC, or a provisional WFC
However, Capote teaches the criteria of being considered an extraneous WFC, a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 21, combination of Bickel”114 and Capote teaches the system of claim 20,
Bickel”114 further wherein the at least one waveform capture device is associated with an Electrical Power Monitor System (EPMS) responsible for monitoring or controlling one or more aspects of the electrical system. (Bickel”114, Figure 1, [0019] FIG. 1 “The power monitoring system 100 “)
Regarding Claim 22, combination of Bickel”114 and Capote teaches the system of claim 21,
Bickel”114 further teaches wherein the EPMS is responsible for monitoring electrical signals, data derived from electrical signals, or controlling one or more aspects of the electrical system. (Bickel”114, Figure 1, [0019] “FIG. 1 illustrates a power monitoring system 100 for monitoring voltage, current, frequency, power, energy and/or other related values measured by one or more IEDs”).
Regarding Claim 23, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 is silent on wherein the at least one captured energy- related waveform is compared to at least one other WFC to determine whether the at least one captured energy-related waveform meets the criteria of being considered an extraneous a redundant WFC, or a provisional WFC.
However, Capote teaches wherein the at least one captured energy- related waveform is compared to at least one other WFC to determine whether the at least one captured energy-related waveform meets the criteria of being considered an extraneous a redundant WFC, or a provisional WFC (Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Regarding Claim 24, combination of Bickel”114 and Capote teaches the method of claim 1,
Bickel”114 is silent wherein the extraneous WFC does not contain relevant information for a real event that occurred on the electrical system
However, Capote teaches wherein the extraneous WFC does not contain relevant information for a real event that occurred on the electrical system(Capote, [0027] “Identifying events that are determined to be associated with one another allows excluding other events from further processing. In an example, processing of received indications of events is able to determine which events are associated with a particular event and create a presentation that only includes indications of events that are determined to be related to an that particular event. By including only events that are related to a particular event, unrelated events, which may be considered as extraneous information or "noise" in evaluating and analyzing events that affect the operations of an electrical distribution system, are able to be specially marked or excluded from further processing in some examples” NOTE: identifies unrelated events or extraneous events).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 event identification method in view of Capote method to identify unrelated extraneous events and further process to reduce WFC data with the benefits of providing accurate event identification for a power distribution network.(Capote, [0019]-[0020]) Moreover, the aggregating groups of data and using a processor to categorize and analyze data is well-known technique applied within the art and would yield the expected results yet with higher accuracy (KSR).
Claims 1-4, 6-24 are rejected under 35 U.S.C. 103 as being unpatentable over Bickel”114 and in view of Capote and in further view of Menzel et al. (CA 3093991 A 1, hereinafter Menzel”991, previously cited).
Regarding Claim 9, combination of Bickel”114 and Capote teaches the method of claim 8,
Bickel Bickel”114 is silent on wherein the WFC library or repository is a cloud- based WFC library or repository.
However, Manzel”991 teaches wherein the WFC library or repository is a cloud- based WFC library or repository. (Manzel”991, [0024] “to store the power event profiles in a digital repository (e.g., library) in accordance with an exemplary embodiment of the present disclosure”. [0040] For clarity, some or
all calculations may be performed within the software application, cloud-based
application, gateway and/or other location/device/system remote from the IED extracting said energy-related signal(s)”)
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 external storage (library/ storage) of computing system with a cloud based application as taught by Manzel”991 with the benefit of real-time centralized better and improved event monitoring for a power distribution network.(Manzel”991,[0093]) Moreover, using a cloud-based computing system for data processing and storage and maintaining network systems is well-known technique applied within the art and would yield the expected results yet with higher accuracy and faster implication(KSR).
Regarding Claim 10, combination of Bickel”114 and Capote teaches the method of claim 7,
Bickel”114 teaches, wherein the at least one captured energy-related waveform is compared to at least one other WFC using one or more data analysis techniques (Bickel”114, [0046] The received waveform capture information is encoded according to a consistent file format by one or more entities including, for example, software-based entities, hardware-based entities, and so forth. Once a waveform
capture has been partially classified as discussed above, information describing the categorization is encoded by the controller 110 for subsequent reference by either the controller 110 or by alternate power quality analysis tools”).
Bickel”114 is silent on the one or more data analysis techniques including at least one of: expert- based algorithms, rules-based algorithms, statistics-based algorithms, visual comparison(s), curve fitting algorithms, signal processing algorithms, and unsupervised, semi-supervised and supervised learning techniques and algorithms.
However, Manzel”991 teaches the one or more data analysis techniques including at least one of: expert- based algorithms, rules-based algorithms, statistics-based algorithms, visual comparison(s), curve fitting algorithms, signal processing algorithms, and unsupervised, semi-supervised and supervised learning techniques and algorithms. ( Menzel”991, [0051] “The analysis on each waveform is something that may optionally be localized. For example, analysis, interpretation, and/or models that are implemented at a system level may be communicated to the IED to implement locally”. NOTE: models are expert based algorithm)
It would have been obvious to a person of ordinary skill before the effective filing date to modify Bickel”114 analysis tools of computing system with statistical analysis tool/ model/algorithm application as taught by Manzel”991 with the benefit of analysis/ diagnosis of events better and improved event monitoring for a power distribution network.(Manzel”991,[0034]-[0036], and [0051]) Moreover, using a statistical analysis/ models/ algorithm software with computing system for data processing for maintaining network systems is well-known technique applied within the art and would yield the expected results yet with higher accuracy and faster implication(KSR).
Conclusion
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
MO et al. (CN 113361573 A) describes “The invention provides a method for identifying the correlation type of a power quality disturbance event, which relates to the technical field of power system analysis and comprises the following steps: firstly, acquiring characteristic information of any two power quality disturbance events on the same target monitoring point; then processing the characteristic information of any two power quality disturbance events to obtain the associated characteristic information between any two power quality disturbance events; and finally, inputting the correlation characteristic information into a correlation type classification recognition model for recognition to obtain a correlation type recognition result between any two power quality disturbance events. According to the invention” (abstract).
Ding et al. (CN 105786903 B) The invention recites “ the method that the present invention proposes a kind of pair of electrical energy power quality disturbance event category, SVM classifier based on stochastic gradient descent algorithm is applied in the Classification and dentification of electrical energy power quality disturbance event by the present invention, can effectively solve the wired sample of electric power big data, non-linear and high dimensional pattern classification problem. The present invention approaches χ using Linear SVM2Core SVM so that classifier has the Computationally efficient of linear kernel simultaneously, and has both the high- class accuracy rate of Non-linear Kernel function. The present invention need to can only be classified using the symbol of data after projection, therefore when data preservation, need to only be stored the symbol of data after pretreatment, be alleviated nowadays growing electric network data amount significantly and bring challenges to storage. The present invention is accurate, analysis electric power big data provides possibility in real time”).
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/DILARA SULTANA/Examiner, Art Unit 2858
/EMAN A ALKAFAWI/Supervisory Patent Examiner, Art Unit 2858
4/3/2026
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