This Office action is in response to application filed on 04/24/2024.
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 .
Preliminary Amendment
Preliminary Amendments filed 4/24/2024 to the specification, abstract, and claims are entered. In this amendment,
Claims 1-14 are canceled.
Claims 15-27 have been added.
Abstract Objection
The Abstract of the disclosure filed on 4/24/2024 is objected to because of the following informalities:
The abstract must be as concise as the disclosure permits. The language should be clear and concise and should not repeat information given in the title or in the claims body. See MPEP § 608.01(b) and 37 C.F.R. 1.438. The purpose of the abstract is to enable the Office and the public generally to determine quickly from a cursory inspection the nature and gist of the technical disclosure. See MPEP § 608.01(b) and 37 C.F.R. 1.72.
Appropriate correction is required.
Note: The abstract should be labeled with “CURRENT AMENDMENT” if it’s amended.
References Listed in Specification
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, applications, or other information submitted for consideration by the Office, and MPEP § 609.04(a), subsection I. states, "the list may not be incorporated into the specification but must be submitted in a separate paper. (See specification pages 2-4). Therefore, unless the references have been listed on form PTO-892 or have been cited by the examiner on form PTO-892, they have not been considered.
Claim Objections
Claims 15, 18, and 27 are objected to because of the following informalities:
Claims 15 and 18 recite “a drive/reception”, should write “a drive or reception”.
and “the basis of” should read “a basis of”.
Claim 18 recites “the vibratable unit” should read “the mechanically vibratable unit”. Further, “the sensor unit (3)” should it read “a sensor unit”?
Claim 27 recites “the basis of” should read “a basis of”.
Appropriate correction required.
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.
Claims 15-27 are rejected under 35 U.S.C. 101 as 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.
Regarding claims 15 and 27, the examiner submits that under Step 1 of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (see also 2019 Revised Patent Subject Matter Eligibility Guidance) for evaluating claims for eligibility under 35 U.S.C. 101, the claims are to a method and apparatus which are the statutory categories of invention.
Regarding claim 15, continuing with the analysis, under Step 2A - Prong One of the test, the limitations (see Italic font below) of:
“providing the vibronic sensor, including: a mechanically vibratable unit; and a drive/reception unit designed to excite, via an excitation signal, the mechanically vibratable unit to vibrate mechanically and to receive mechanical vibrations of the mechanically vibratable unit and to convert the mechanical vibrations into a reception signal; recording at least one spectrum of the vibronic sensor as input data, providing the input data to a neural network that is designed to determine a statement about the state of the vibronic sensor on the basis of the input data; and outputting the statement about the state of the vibronic sensor” fall into the groupings of mathematical concepts and mental processes. Therefore, the claim recites a judicial exception under Step 2A - Prong One of the test.
Regarding claim 27, continuing with the analysis, under Step 2A - Prong One of the test, the limitations (see Italic font below) of:
“an electronic system of a vibronic sensor or a separate computing unit, wherein the data process device is embodied to: record at least one spectrum of the vibronic sensor as input data, provide the input data to a neural network that is designed to determine a statement about a state of the vibronic sensor on the basis of the input data, and output the statement about the state of the vibronic sensor” fall into the groupings of mathematical concepts and mental processes. Therefore, the claim recites a judicial exception under Step 2A - Prong One of the test.
Furthermore, under Step 2A - Prong Two of the test, this judicial exception is not integrated into a practical application. In particular, the additional elements recited in the claims (see below limitations in non-Italic font):
Regarding claim 15, “A computer-implemented method for monitoring a state of a vibronic sensor, comprising: providing the vibronic sensor, including: a mechanically vibratable unit; and a drive/reception unit designed to excite, via an excitation signal, the mechanically vibratable unit to vibrate mechanically and to receive mechanical vibrations of the mechanically vibratable unit and to convert the mechanical vibrations into a reception signal; recording at least one spectrum of the vibronic sensor as input data, providing the input data to a neural network that is designed to determine a statement about the state of the vibronic sensor on the basis of the input data; and outputting the statement about the state of the vibronic sensor” generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), add extra-solution activities (i.e., receiving, recording, outputting data) using elements recited at a high level of generality (i.e., vibronic sensor, mechanically vibratable unit) (see MPEP 2106.05(g)), and/or add the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f));
Regarding claim 27: “A data processing device comprising an electronic system of a vibronic sensor or a separate computing unit, wherein the data process device is embodied to: record at least one spectrum of the vibronic sensor as input data, provide the input data to a neural network that is designed to determine a statement about a state of the vibronic sensor on the basis of the input data, and output the statement about the state of the vibronic sensor” generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), add extra-solution activities (i.e., recording, providing data as input, outputting data) using elements recited at a high level of generality (i.e., vibronic sensor) (see MPEP 2106.05(g)), and/or add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).
Accordingly, the above additional limitations in claims 15 and 27, when considered individually and in combination, do not integrate the judicial exception into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considering the claims as a whole. The claims are directed to a judicial exception under Step 2A of the test.
Additionally, under Step 2B of the test, claims 15 and 27 do not include additional elements that, when considered individually and in combination, are sufficient to amount to significantly more than the judicial exception because the additional elements:
recite extra-solution activity (i.e., mere data gathering) using elements recited at a high level of generality, see MPEP 2106.05(g).
generally link the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h), i.e., an implemented method for monitoring a state of a vibronic sensor.
add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claims, when considered as a whole, do not provide significantly more
under Step 2B of the test. Based on the analysis, the claims are not patent eligible.
Dependent claims 16-26 that are also directed to the non-statutory subject matter because:
they just extend the abstract idea of the independent claims by additional limitations that under the broadest interpretation in light of the specification, cover performance of the limitations using mathematical concepts and mental processes.
the additional elements recited in the dependent claims, when considered individually and in combination, refers to extra-solution activities recited at a high level of generality, i.e., recording (claim 25), and use computer implementation (i.e., machine learning) to facilitate the application of the abstract idea (claims 16-24 and 26), which as indicated in the Office's guidance does not integrate the judicial exception into a practical application (Step 2A -Prong Two) and/or does not provide significantly more (Step 2B).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 18 and 25 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 18 recites “an environment of the sensor” lacks antecedent basis. It is unclear whether “the sensor” refers to “the vibronic sensor” or “the sensor unit”?
Claim 25 recites “the state of the sensor” lacks antecedent basis. It is unclear whether it refers to “the state of the vibronic sensor”?
For purpose of examination to claims 18 and 25, is interpreted “the vibronic sensor”.
Claim Rejections - 35 USC § 103
The following is a quotation under AIA of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action.
A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
Claims 15-17, 19-22, and 26-27 are rejected under AIA 35 U.S.C. 103 as being obvious over US 2018/0372534 of D’Angelico in view of US 2021/0342691 of Lui et al., hereinafter Lui.
As per Claim 15, D’Angelico teaches a computer-implemented method for monitoring a state of a vibronic sensor, comprising:
providing the vibronic sensor, including: a mechanically vibratable unit (see [0013] );
a drive/reception unit designed to excite, via an excitation signal (an excitation/ reception unit is a drive/reception unit, see [0044] ), the mechanically vibratable unit to vibrate mechanically and to receive mechanical vibrations of the mechanically vibratable unit (see Abstract, [0014], [0055] ) and to convert the mechanical vibrations into a reception signal (transform mechanical vibrations into electrical receiving signal, see [0005] );
recording at least one spectrum of the vibronic sensor as input data (a complete spectrum of vibration system contains all information considered “recorded spectrum”, see [0015], [0019] ), providing the input data that is designed to determine a statement about the state of the vibronic sensor on the basis of the input data (the vibration “amplitude” of tuning fork at frequency filter considered “input data”. It is noted vibronic sensor contains a tuning fork, see [0055], the vibrations received to determine two different malfunctions F1, F2, see [0044]-[0045] ); and
outputting the statement about the state of the vibronic sensor ( the frequency function results as a function of the configuration of the vibronic sensor considered “a derived output statement described sensor’s oscillation frequency changes, see [0016]).
D’Angelico does not explicitly teach input data to a neural network
Lui teaches inputting data to a neural network (data input to preprocessing neural network, i.e. data is first filtered “noise”, see [0008], [0061], [0124], Fig 1).
It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teaching of D’Angelico having inputting data to preprocessing neural network as taught by Lui that would input data to filter as preprocessing neural network to eliminate signal noise (Lui, Abstract).
As per Claim 16, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico teaches wherein the at least one spectrum is a frequency spectrum ( the range of the amplitude and/or the phase spectrum considered signal’s frequency spectrum, see [0016], Fig 3: amplitude spectrum ).
As per Claim 17, D’Angelico in view of Lui teaches the method according to claim 16, D’Angelico teaches wherein the frequency spectrum includes an amplitude or a phase of the reception signal as a function of a frequency of the excitation signal (excitation amplitude in Figs 2a-2b, frequency function results, see [0016], [0024]).
As per Claim 19, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico does not teach wherein the neural network is a deep neural network. Lui teaches the neural network is a deep neural network (see [0052], [0033], also convolutional neural network CNN considered deep learning, see [0056] ). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teaching of D’Angelico having deep learning or convolutional neural network as taught by Lui that would retrain and maintain their models fairly frequently to maintain performance and greatly reduce such work repetition by automatically and learned by a neural network (Lui, [0140]).
As per Claim 20, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico further teaches comprising: supplying the input data to a data preprocessing module having at least one filter for filtering the input data with respect to at least one piece of information (the variable frequency filter as the frequency to be filtered “preprocessing”, see [0026] ). D’Angelico does not teach providing the filtered input data to the neural network. Lui teaches providing the filtered input data to the neural network (Abstract). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teaching of D’Angelico having filtered input data to neural network as taught by Lui that would input data to filter as preprocessing neural network to eliminate signal noise (Lui, Abstract).
As per Claim 21, D’Angelico in view of Lui teaches the method according to claim 20, D’Angelico does not teach wherein the data preprocessing module includes a neural network for data preprocessing. Lui teaches the data preprocessing module includes a neural network for data preprocessing (see Abstract). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teaching of D’Angelico having data preprocessing includes a neural network as taught by Lui that would facilitate inputting data to filter as preprocessing neural network to eliminate signal noise (Lui, Abstract).
As per Claim 22, D’Angelico in view of Lui teaches the method according to claim 21, D’Angelico teaches wherein the data preprocessing module is designed to determine at least one resonance peak (the received vibration, i.e., the excitation of resonance frequency, see [0005], [0009]. It is noted regulate the frequency of the excitation voltage and rectifier, considered keeping voltage stable, while using peak rectifier to determine the two different malfunctions, see [0016], [0047] ), a number of resonance peaks within a spectrum, or a background signal of the spectrum.
As per Claim 26, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico teaches a predeterminable fill level of a medium in a container (see [0001], [0004], [0014] ), D’Angelico does not teach the neural network is designed to determine on the basis of the input data. Lui teaches the neural network is designed to determine on the basis of the input data (determine a preprocessing weight parameter “input data”, see Claim 2 lines 2-3, [0123] ). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teaching of D’Angelico using neural network to determine the input data as taught by Lui that would facilitate outputting of another neural network with parameter that changes dynamically depending on the input (Lui, [0123]).
Claim 27 is rejected for the same rationale as in claim 1.
Claim 18 is rejected under AIA 35 U.S.C. 103 as being obvious over D’Angelico in view of Lui and US patent 7260977 of Griessbaum et al., hereinafter Griessbaum.
As per Claim 18, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico teaches wherein the statement about the state of the vibronic sensor is a statement about the state of the sensor unit (3) including a build-up or corrosion in a region of the sensor unit (mechanically-vibratable unit may be deposits, corrosion, and/or abrasion, see [0031]-[0032] ), a degree of coverage, a damping, or a sensitivity of the vibratable unit (the range of amplitude and/or phase spectrum sensitive relevant malfunctions [0015], different malfunctions of a vibronic sensor [0012]), a statement about the drive/reception unit, a statement about vibrations in an environment of the sensor, or a statement about an electrical contact in the region of the sensor (see [0003]).
D’Angelico and Lui do not teach a statement about at least one environmental parameter or a change of the at least one environmental parameter.
Griessbaum teaches a statement about at least one environmental parameter or a change of the at least one environmental parameter (col 3 lines 60-64, col 8 lines 50-58). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teachings of D’Angelico and Lui having environment of the electromechanical transducer as taught by Griessbaum that would facilitate for identifying switching functions of transduce (Griessbaum, col 4 line 63 to col 4 line 3).
Claims 23-25 are rejected under AIA 35 U.S.C. 103 as being obvious over D’Angelico in view of Lui and US patent 5682317 of Keeler et al., hereinafter Keeler.
As per Claim 23, D’Angelico in view of Lui teaches the method according to claim 15, D’Angelico teaches (vibronic sensor [0003] ), but does not teach wherein the neural network is designed to carry out predictive maintenance of the sensor at least on the basis of the input data. Keeler teaches the neural network is designed to carry out predictive maintenance of the sensor at least on the basis of the input data (Fig 1a: each of sensors 27, 31, 33, 35 has an output connected to input of virtual sensor 18 which is periodically checking to determine if anyone of those sensors faulty, see col 4 lines 40-43 and 58 to col 5 line 6). It would have been obvious to one ordinary skill in the art at the time before the effective filing date of claimed invention to modify the teachings of D’Angelico and Lui having sensors periodically to check for faulty as taught by Keeler that would facilitate predicting the sensor condition, i.e., to replace the invalid sensors with predicted sensor value (Keeler, col 11 lines 37-43).
As per Claim 24, D’Angelico in view of Lui and Keeler teaches the method according to claim 23, D’Angelico teaches wherein the neural network is a recurrent neural network (see [0033], [0036] ).
As per Claim 25, D’Angelico in view of Lui and Keeler teaches the method according to claim 24, D’Angelico teaches further comprising: recording as a function of time at least one piece of information from the spectrum and/or the statement about the state of the sensor (see [0025], [0055] ).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 2020/0116545 of Vogt (Monitoring the condition of a vibronic sensor).
WO 2018/114281A1 of Monse et al (Vibronic sensor with interference compensation).
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to LYNDA DINH whose telephone number is (571) 270-
7150. The examiner can normally be reached on M-F 10 AM - 6 PM ET.
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/LYNDA DINH/Examiner, Art Unit 2857
/LINA CORDERO/Primary Examiner, Art Unit 2857
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