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 .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-5, 10-16 and 20 is/are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Bamberg et al. (WO 2022/156873 A1, hereinafter Bam).
Regarding claim 1, Bam discloses a method of inspecting a component for the presence or absence of a defect, comprising:
using a transducer to inspect a subject component comprising a solid metallic material (i.e. component of an aircraft engine) by transmitting a first signal into the subject component and sensing the subject component for a second signal produced as a result of the first signal being transmitted into the subject component, and producing a subject component response signal representative of the second signal (see para. 0009-0011, 0016-0017);
processing the subject component response signal received from the transducer, the processing using a neural network trained on response signal training data from pairs of training components, and the processing including producing a neural network output value (see para. (see para. 0009-0011, 0016-0017); and
producing an indication of a presence or an absence of a defect in the subject component based on the neural network output value (see para. 0013-0014, the system identifies if there’s a defect).
Regarding claim 2, Bam discloses the method of claim 1, wherein the neural network includes a self-attention mechanism (see para. 0085).
Regarding claim 3, Bam discloses the method of claim 2, wherein each said training component is the same type as the subject component (see para. 0009).
Regarding claim 4, Bam discloses the method of claim 3, wherein the response signal training data for each said training component includes a first frequency peak (see para. 0061).
Regarding claim 5, Bam discloses the method of claim 4, wherein each respective pair of training components includes a first training component and a second training component, wherein the first training component, the second training component, and the subject component are all the same type (see para. 0009-0012).
Regarding claim 10, Bam discloses the method of claim 2, further comprising using the neural network to model future subject component response signals of the subject component based on a plurality of historical subject component response signals (see para. 0113).
Regarding claim 11, Bam discloses the method of claim 10, further comprising using the neural network to determine a subject component response signal rate of change (see para. 0098).
Regarding claim 12, Bam discloses the method of claim 10, further comprising using the neural network to predict a future subject component response signal rate of change (see para. 0103).
Regarding claim 13, Bam discloses a component inspection system, comprising:
a signal transmitter (see para. 0024); a signal receiver (see para. 0057); and a controller in communication with the signal transmitter (see para. 0106), the signal receiver, and a non-transitory memory storing instructions, which instructions when executed cause the controller to:
control the signal transmitter to transmit a first ultrasonic signal into a subject component comprising a solid metallic material (see para. 0009-0011, 0016-0017); control the signal receiver to sense the subject component for a second ultrasonic signal and produce a subject component response signal representative of the second ultrasonic signal (see para. 0009-0011, 0016-0017); process the subject component response signal, the processing using a neural network trained on response signal training data from pairs of training components, and the processing including producing a neural network output value (see para. 0009-0011, 0016-0017); and produce an indication of a presence or an absence of a defect in the subject component based on the neural network output value (see para. 0013-0014, the system identifies if there’s a defect).
Regarding claim 14, Bam discloses the system of claim 13, wherein the neural network includes a self-attention mechanism (see para. 0085).
Regarding claim 15, Bam discloses the system of claim 14, wherein each said training component is the same type as the subject component (see para. 0009).
Regarding claim 16, Bam discloses the system of claim 15, wherein the response signal training data for each said training component includes a first frequency peak (see para. 0061).
Regarding claim 20, Bam discloses the system of claim 13, wherein the instructions when executed cause the controller to use the neural network to model future subject component response signals of the subject component based on a plurality of historical subject component response signals (see para. 0113).
Allowable Subject Matter
Claims 6-7 and 17-19 are 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANUEL A RIVERA VARGAS whose telephone number is (571)270-7870. The examiner can normally be reached M-F 9:00-6:00.
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/MANUEL A RIVERA VARGAS/Primary Examiner, Art Unit 2857
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