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 .
Claim Objections
Claim 16 is objected to because of the following informalities: Claim 16 claims “The apparatus of claim 1” is understood as “The method of claim 10”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 3-8, 10, 12-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Telefus et al., US20200366078 (hereinafter referred to as Telefus), in view of Handy et al., US20190011492 (hereinafter referred to as Handy), and in further view of Wang et al., “A DC Series Arc Fault Detection Method Based on a Lightweight Convolutional Neural Network Used in Photovoltaic System” (hereinafter referred to as Wang).
In regards to claim 1, Telefus teaches an apparatus (apparatus of Fig. 2A), comprising: a first terminal (Line Hot 111; [Fig. 2A]); a second terminal (Load Hot 121; [Fig. 2A]) distal from the first terminal (implicit; [Fig. 2A]); a solid state circuit breaker (Electromechanical AC Switch 202; [Fig. 2A]) having a third terminal (left input node of 202; [Fig. 2A]) coupled to the first terminal (implicit; [Fig. 2A]), and a fourth terminal (right output node of 202; [Fig. 2A]) coupled to the second terminal (implicit; [Fig. 2A]), the solid state circuit breaker selectively configured as a closed switch or an open switch (switched-closed state, & “open” circuit; [0072-0073]) and a current sensor (current sensor 204; [Fig. 2A]) coupled to a current path (path from line hot 111 to load hot 121; [Fig. 2A]) coupling the first terminal and the second terminal (implicit; [Fig. 2A]) and configured to sense an electrical current (magnitude of current; [0077]) flowing on the current path while the solid state circuit breaker is configured as the closed switch (It is inherent that the circuit breaker would be closed in order for current to flow, otherwise the current sensor would measure 0 current), and configured to process data (current sense signal; [0010]) representative of the electrical current.
Telefus does not teach a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach, the student CNN model coupled to the solid state circuit breaker and the current sensor and the data being processed cyclically with a period defined by an arc fault detection cycle, wherein, in response to the student CNN model detecting, in association with the electrical current, an arc fault lasting a predetermined number of consecutive arc fault detection cycles, the solid state circuit breaker is reconfigured as the open switch.
Handy teaches data (current sense signal, Telefus) being processed cyclically (logging; [0035]) with a period (event; [0035]) defined by an arc fault detection cycle, wherein, in response to the student CNN model detecting, in association with the electrical current, an arc fault lasting a predetermined number of consecutive arc fault detection cycles (five arc fault events; [0035]), the solid state circuit breaker is reconfigured as the open switch (trip the breaker, Telefus; [0217-0218]).
Handy does not teach a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach, the student CNN model coupled to the solid state circuit breaker and the current sensor and configured to process data representative of the electrical current.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate data being processed cyclically with a period defined by an arc fault detection cycle, wherein, in response to the student CNN model detecting, in association with the electrical current, an arc fault lasting a predetermined number of consecutive arc fault detection cycles, the solid state circuit breaker is reconfigured as the open switch as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
Wang teaches a student convolutional neural network (CNN) (Lightweight Convolutional Neural Network; [Title]) model that was pretrained using a knowledge distillation-based teacher-student approach, the student CNN model coupled to the solid state circuit breaker (Examiner’s Note: The artificial intelligence taught by Telefus resides within the processor and the Processor 220 is coupled to the circuit breaker’s control input.) and the current sensor (Examiner’s Note: The Processor 220 is coupled to the sense line of the Current Sensor 204 as taught by Telefus.) and configured to process data (Processor 220, Telefus) representative of the electrical current.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus & Handy in order to incorporate a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach, the student CNN model coupled to the solid state circuit breaker and the current sensor and configured to process data representative of the electrical current as taught by Wang. The motivation for doing so would be to provide an improved artificial intelligence model to replace the artificial intelligence as taught by Telefus.
In regards to claim 3, Telefus teaches wherein in an unbiased state (disconnect the utility power source to the branch circuit; [0011]), the solid state circuit breaker presents a high impedance (implicit of a switched-open state; [0011]) between the third terminal and the fourth terminal, providing a failsafe open-switch-state (switched-open state; [0011]) at the solid state circuit breaker.
In regards to claim 4, Telefus does not teach wherein the predetermined number is configurable.
Handy teaches wherein the predetermined number is configurable (predetermined number of arc fault events, for example, after five; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the predetermined number is configurable as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 5, Telefus does not teach wherein a reliability of arc fault detections increases as the predetermined number increases.
Handy teaches wherein a reliability (build confidence; [0035]) of arc fault detections increases as the predetermined number increases (repeatedly determining; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein a reliability of arc fault detections increases as the predetermined number increases as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 6, Telefus does not teach wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive.
Handy teaches wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive (for example, after five arc fault events; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive, as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 7, Telefus does not teach wherein the detecting of the arc fault is continuous during the predetermined number of consecutive arc fault detection cycles.
Handy teaches wherein the detecting of the arc fault is continuous (repeatedly determining; [0035]) during the predetermined number of consecutive arc fault detection cycles.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the detecting of the arc fault is continuous during the predetermined number of consecutive arc fault detection cycles as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 8, Telefus teaches wherein after the solid state circuit breaker is reconfigured as the open switch, the solid state circuit breaker (electromagnetic switch 302; [0084]) (Electromechanical AC Switch 202, Telefus) is maintained as the open switch (manually open; [0084]) (Examiner’s Note: Telefus teaches opening and closing the electromagnetic switch manually or automatically, so it would be engineering design choice for how to trip or reset the electromagnetic switch.) until a user (user; [0084]) authorizes again reconfiguring the solid state circuit breaker as the closed switch (manually… close the air-gap electromagnetic switch 302; [0084]).
In regards to claim 10, Telefus teaches a method (method of Fig. 2A), comprising: configuring at least a portion of one or more processors (Processor 220; [Fig. 2A]); configuring a solid state circuit breaker (Electromechanical AC Switch 202; [Fig. 2A]) as a closed switch (switched-closed state; [0072]); processing data representative (current sense signal; [0010]) of an electrical current (magnitude of current; [0077]) flowing through the closed switch of the solid state circuit breaker (It is inherent that the circuit breaker would be closed in order for current to flow, otherwise the current sensor would measure 0 current).
Telefus does not teach configuring at least a portion of one or more processors as a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach; configuring a solid state circuit breaker controlled by the student CNN model as a closed switch; processing data representative of an electrical current flowing through the closed switch of the solid state circuit breaker utilizing the student CNN model, the data being processed cyclically with a period defined by an arc fault detection cycle; and reconfiguring the solid state circuit breaker as an open switch in response to the student CNN model detecting, in association with the electrical current, an arc fault lasting a predetermined number of consecutive arc fault detection cycles.
Handy teaches the data (current sense signal, Telefus) being processed cyclically (logging; [0035]) with a period (event; [0035]) defined by an arc fault detection cycle; and reconfiguring the solid state circuit breaker as an open switch (trip the breaker, Telefus; [0217-0218]), in association with the electrical current, an arc fault (arc fault; [0035]) lasting a predetermined number of consecutive arc fault detection cycles (five arc fault events; [0035]).
Handy does not teach configuring at least a portion of one or more processors as a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach; configuring a solid state circuit breaker controlled by the student CNN model as a closed switch; processing data representative of an electrical current flowing through the closed switch of the solid state circuit breaker utilizing the student CNN model, and reconfiguring the solid state circuit breaker as an open switch in response to the student CNN model detecting.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate the data being processed cyclically with a period defined by an arc fault detection cycle; and reconfiguring the solid state circuit breaker as an open switch, in association with the electrical current, an arc fault lasting a predetermined number of consecutive arc fault detection cycles as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
Wang teaches configuring at least a portion of one or more processors (Processor 220, Telefus) as a student convolutional neural network (CNN) model (Lightweight Convolutional Neural Network; [Title]) that was pretrained using a knowledge distillation-based teacher-student approach; configuring a solid state circuit breaker controlled by the student CNN model as a closed switch (Examiner’s Note: The artificial intelligence taught by Telefus resides within the processor and the Processor 220 is coupled to the circuit breaker’s control input.); processing data representative of an electrical current (Examiner’s Note: The Processor 220 is coupled to the sense line of the Current Sensor 204 as taught by Telefus.) flowing through the closed switch of the solid state circuit breaker utilizing the student CNN model, and reconfiguring the solid state circuit breaker as an open switch in response to the student CNN model detecting.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus & Handy in order to incorporate configuring at least a portion of one or more processors as a student convolutional neural network (CNN) model that was pretrained using a knowledge distillation-based teacher-student approach; configuring a solid state circuit breaker controlled by the student CNN model as a closed switch; processing data representative of an electrical current flowing through the closed switch of the solid state circuit breaker utilizing the student CNN model, and reconfiguring the solid state circuit breaker as an open switch in response to the student CNN model detecting as taught by Wang. The motivation for doing so would be to provide an improved artificial intelligence model to replace the artificial intelligence as taught by Telefus.
In regards to claim 12, Telefus teaches wherein in an unbiased state (disconnect the utility power source to the branch circuit; [0011]), the solid state circuit breaker presents a high impedance (implicit of a switched-open state; [0011]) between the third terminal and the fourth terminal, providing a failsafe open-switch-state (switched-open state; [0011]) at the solid state circuit breaker.
In regards to claim 13, Telefus does not teach wherein the predetermined number is configurable.
Handy teaches wherein the predetermined number is configurable (predetermined number of arc fault events, for example, after five; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the predetermined number is configurable as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 14, Telefus does not teach wherein a reliability of arc fault detections increases as the predetermined number increases.
Handy teaches wherein a reliability (build confidence; [0035]) of arc fault detections increases as the predetermined number increases (repeatedly determining; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein a reliability of arc fault detections increases as the predetermined number increases as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 15, Telefus does not teach wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive.
Handy teaches wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive (for example, after five arc fault events; [0035]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the predetermined number is a number between 2 and 10, inclusive, or more specifically between 4 and 7, inclusive, as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 16, Telefus does not teach wherein the detecting of the arc fault is continuous during the predetermined number of consecutive arc fault detection cycles.
Handy teaches wherein the detecting of the arc fault is continuous (repeatedly determining; [0035]) during the predetermined number of consecutive arc fault detection cycles.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus in order to incorporate wherein the detecting of the arc fault is continuous during the predetermined number of consecutive arc fault detection cycles as taught by Handy. The motivation for doing so would be to prevent false arc fault tripping (Handy, [0035]).
In regards to claim 17, Telefus teaches the method of claim 10, further comprising: maintaining the reconfiguration of the solid state circuit breaker (electromagnetic switch 302; [0084]) (Electromechanical AC Switch 202, Telefus) as the open switch (manually open; [0084]) (Examiner’s Note: Telefus teaches opening and closing the electromagnetic switch manually or automatically, so it would be engineering design choice for how to trip or reset the electromagnetic switch.) until receipt of a user authorization (user; [0084]) to again configure the solid state circuit breaker as the closed switch (manually… close the air-gap electromagnetic switch 302; [0084]).
Claim(s) 2 & 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Telefus et al., US20200366078 (hereinafter referred to as Telefus), in view of Handy et al., US20190011492 (hereinafter referred to as Handy), in further view of Wang et al., “A DC Series Arc Fault Detection Method Based on a Lightweight Convolutional Neural Network Used in Photovoltaic System” (hereinafter referred to as Wang), and in further view of Lumanog et al., US20240186790 (hereinafter referred to as Lumanog).
In regards to claim 2, Telefus, Handy, & Wang do not teach wherein the solid state circuit breaker comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) configured as a single pole single throw switch.
Lumanog teaches wherein the solid state circuit breaker (electromechanical AC switch, Telefus) comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) (MOSFET 152; [0109]) configured as a single pole single throw switch (Telefus [Fig. 2A] & Lumanog [Fig. 6] teach a SPST switch because both are on one power bus and operate as an open/closed switch).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus, Handy, & Wang in order to incorporate wherein the solid state circuit breaker comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) configured as a single pole single throw switch as taught by Lumanog. The motivation for doing so would be an engineering design choice to apply a known substitute for electromechanical circuit breakers.
In regards to claim 11, Telefus, Handy, & Wang do not teach wherein the solid state circuit breaker comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) configured as a single pole single throw switch.
Lumanog teaches wherein the solid state circuit breaker (electromechanical AC switch, Telefus) comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) (MOSFET 152; [0109]) configured as a single pole single throw switch (Telefus [Fig. 2A] & Lumanog [Fig. 6] teach a SPST switch because both are on one power bus and operate as an open/closed switch).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Telefus, Handy, & Wang in order to incorporate wherein the solid state circuit breaker comprises a metal- oxide-semiconductor field-effect transistor (MOSFET) configured as a single pole single throw switch as taught by Lumanog. The motivation for doing so would be an engineering design choice to apply a known substitute for electromechanical circuit breakers.
Allowable Subject Matter
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Claim 9 is indicated containing allowable subject matter because prior art fails to teach or suggest, either alone or in combination all of the limitations of claim 1 & 9, especially “where the student CNN model is implemented as a plurality of building blocks, respective building blocks being implemented as: a one-dimensional pointwise convolution with one-half of all filters at a first sub- layer, wherein each of the one-half of all filters at the first sub-layer is a 1x1 matrix; a one-dimensional depthwise convolution with one-half of all filters at a second sub-layer, wherein each of the one-half of all filters at the second sub-layer is 5x1 matrix; a max pooling at a third sub-layer with a filter size of 2x1; and a one-dimensional convolution with a stride of two with all filters at a fourth sub- layer, wherein each of the all filters at the fourth sub-layer is a 2x1 matrix.”
Claim 18 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Claim 9 is indicated containing allowable subject matter because prior art fails to teach or suggest, either alone or in combination all of the limitations of claim 10 & 18, especially “implementing the student CNN model as a plurality of building blocks, each building block of the plurality of building blocks implemented as: a one-dimensional pointwise convolution with one-half of all filters as a first sub-layer, wherein each of the one-half of all filters at the first sub-layer is a 1x1 matrix; a one-dimensional depthwise convolution with one-half of all filters at a second sub-layer, wherein each of the one-half of all filters at the second sub-layer is 5x1 matrix; a max pooling at a third sub-layer with a filter size of 2x1; and a one-dimensional convolution with a stride of two with all filters at a fourth sub-layer, wherein each of the all filters at the fourth sub-layer is a 2x1 matrix.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Xia et al., “An Arc Fault Detection System for the Household Photovoltaic Inverter according to the DC Bus Currents” is relevant for a photovoltaic system with a circuit breaker. Liu et al., CN114998202A, is relevant for another prior art discussing a student convolutional neural network.
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SAMANTHA LYNETTE FAUBERT
Examiner
Art Unit 2836
/CRYSTAL L HAMMOND/Supervisory Primary Examiner, Art Unit 2838
Prosecution Insights