DETAILED ACTION
This office action is in response to application filed on November 23, 2023.
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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/23/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
[0010]: Language “S5, adding the final unknown gas feature Dujto the known gas feature library D … ” should read “S5, adding the final unknown gas feature Duj to the known gas feature library D …” in order to correct for minor informalities (i.e., add space).
[0024]: Language “In S43, the function of the correlationRj between … ” should read “In S43, the function of the correlation Rj between …” in order to correct for minor informalities (i.e., add space).
[0041]: Language “… a squared loss function is constructed according to the known gas featureDi … ” should read “… a squared loss function is constructed according to the known gas feature Di …” in order to correct for minor informalities (i.e., add space).
[0042]: Language “… the final unknown gas feature Dujis obtained … ” should read “… the final unknown gas feature Duj is obtained…” in order to correct for minor informalities (i.e., add space).
[0043]: Language “S5, the final unknown gas feature Dujis added to the known gas feature library D … ” should read “S5, the final unknown gas feature Duj is added to the known gas feature library D …” in order to correct for minor informalities (i.e., add space).
[0057]: Language “… the iteration is stopped and the final unknown gas featureDuj is calculated and obtained … ” should read “… the iteration is stopped and the final unknown gas feature Duj is calculated and obtained …” in order to correct for minor informalities (i.e., add space).
[0062]: Language “In S5, the final unknown gas feature Dujis added to the known gas feature library D … ” should read “In S5, the final unknown gas feature Duj is added to the known gas feature library D …” in order to correct for minor informalities (i.e., add space).
[0082]: Language “… and actual concentrations of the gases the gases and NO are 15% and 15%, respectively” should read “… and actual concentrations of the gases SO2 and NO are 15% and 15%, respectively” in order to correct for minor informalities (i.e., add space).
Appropriate correction is required.
Claim Objections
Claim 1 is objected to because of the following informalities:
Claim language should read:
“A method for measuring a concentration of a gas to be measured by identifying features of an unknown gas, the method comprising the following steps:
S1, injecting standard samples of m known gases into a measuring cell of a gas analyzer, scanning in a standard sample, further obtaining a feature Di of each standard sample D of the m known gases;
S2, injecting a gas mixture into the measurement cell of the gas analyzer, and scanning in the spectral range to obtain [[the]]a feature d of the gas mixture, where the gas mixture includes the m known gases and n unknown gases, and a feature of the unknown gases is defined as Duj;
S3, defining and initializing a known gas weight parameter w and an unknown gas weight parameter wu, and constructing a squared loss function and an objective function according to the Di of each standard sample, the known gas weight parameter w, the Duj of the unknown gases, the unknown gas weight parameter wu, and the d of the gas mixture;
S4, learning and training each parameter in the squared loss function until [[the]]a value of the objective function is less than [[the]]a set value or [[the]]a number of learning times reaches [[the]]a target number, and obtaining [[the]]a final unknown gas feature Duj; and
S5, adding the final unknown gas feature Duj to the D, and obtaining the concentration of [[a]]the gas to be measured in the gas mixture through gas concentration inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 2 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 1, wherein the squared loss function described in S3 is defined as follows:
θ
=
∑
i
=
1
m
w
i
*
D
i
+
∑
j
=
1
n
w
u
i
*
D
u
i
-
d
2
,
and the objective function is defined as min(θ) and constructed according to the squared loss function” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 3 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 2, wherein the Duj of the unknown gases in S2 is defined as follows:
a gas feature function base Φ and a gas feature function space are established, [[the]]an unknown gas parameter Puj is defined and initialized, and the Duj of the unknown gases is constructed according to the gas feature function base Φ and the unknown gas parameter Puj” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 4 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 3, wherein an expression of constructing the Duj of the unknown gases according to the gas feature function base Φ and the unknown gas parameter Puj is as follows: Duj = Puj *Φ” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 5 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 4, wherein Duj described in S4, comprises the following steps:
S41, using an iterative algorithm to learn and train the known gas weight parameter w, the unknown gas weight parameter wu and the unknown gas Puj, and recording an iteration number K;
S42, determining whether [[the]]a remainder of K divided by a given integer N is zero, performing S43 if yes, and performing S44 if not;
S43, constructing a function of a correlation Rj between the Duj of the unknown gases and the D, initializing a correlation coefficient r, and determining whether Rj is greater than r; if yes, re-initializing the unknown gas Puj, and performing S41; if not, performing S44; and
S44, determining, as a first condition, whether the iteration number K reaches [[the]]a set maximum K_max or, as a second condition, whether the value of the objective function min(θ) is less than [[the]]a set value ε; when first condition or the second condition is determined to be “yes”, stopping the iterative algorithm and calculating the final unknown gas feature Duj; and when the first condition and the second condition are determined to be “not”, performing S41 and continuing learning and training” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 6 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 5, wherein in S41, the iterative algorithm is a gradient projection method with momentum” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 7 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 6, wherein in S43, the function of the correlation Rj between the Duj of the unknown gases and the D is as follows:
r
e
s
=
D
u
j
*
D
*
D
*
D
-
1
*
D
-
D
u
j
,
R
j
=
1
-
r
e
s
*
r
e
s
D
u
j
*
D
u
j
” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 8 is objected to because of the following informalities:
Claim language should read:
“The method for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gas according to claim 7, wherein in S5, the final unknown gas feature Duj is added to the D, and the concentration of the gas to be measured in the gas mixture is obtained by inversion calculation according to the least square method” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 9 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 1, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 10 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 2, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 11 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 3, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 12 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 4, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 13 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 5, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 14 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 6, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 15 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 7, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
Claim 16 is objected to because of the following informalities:
Claim language should read:
“A system for measuring [[a]]the concentration of [[a]]the gas to be measured by identifying the features of [[an]]the unknown gasthe method of claim 8, the system comprising a light source, [[a]]the measuring cell, a spectrometer, a storage module, a learning and training module, an initialization module, and an inversion module,
wherein the light source is sequentially connected to the measurement cell and the spectrometer, the gas to be measured is injected into the measurement cell, and light emitted by the light source passes through the measurement cell filled with the gas to be measured, is received by the spectrometer and converted into a digital signal and then inputted to the storage module and the learning and training module respectively;
the storage module is configured to store feature data of a variety of known gases;
the learning and training module is configured to construct a squared loss function model between unknown gas features and known gas features and perform learning and training;
the initialization module is connected to the learning and training module, and is configured to initialize [[the]] parameter data in the squared loss function model;
[[the]] final unknown gas feature data obtained by the learning and training is inputted into the storage module;
the inversion module is connected with the storage module and configured to calculate the concentration of the gas to be measured, and [[the]] known gas feature data in the storage module and the final unknown gas feature data acquired by calculation are inputted into the inversion module for inversion calculation” in order to clarify the recited language for compliance under 35 U.S.C. 112.
Appropriate correction is required.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “S1 … scanning in a wide spectral range to obtain an absorption spectrum of each sample … S2 … scanning in a wide spectral range to obtain the feature d of the gas mixture …” which is unclear as to what the scope of ‘wide’ encompasses (e.g., what is considered a wide spectral range? Visible to infrared? Ultraviolet to infrared? Etc.).
The dependent claims do not clarify the recited language and the specification does not provide details as to how this feature should be interpreted (i.e., same language is described in [0006]-[0007], [0039]-[0040], [0069]-[0070] and [0086]-[0087]).
For examination purposes, language is interpreted as indicated in the Claim Objections section.
Claim 5 recites “S44, determining whether the iteration number K reaches the set maximum K_max or whether the value of the objective function min(θ) is less than the set value ε; when at least any one of the above conditions is determined to be “yes”, stopping the iteration and calculating the final unknown gas feature Duj; and when any of the above conditions is determined to be “not”, performing S41 and continuing learning and training” which is unclear as to what should be done when one condition is “yes” (i.e., when at least any one of the above conditions is determined to be “yes”) and the other condition is “not” (i.e., when any of the above conditions is determined to be “not”). Should the iteration stop and the final unknown gas feature be calculated, or should S41 be performed to continue learning and training? Or both?
The dependent claims do not clarify the recited language and the specification does not provide details as to how these statements should be interpreted (i.e., same language is described in [0022] and [0057]).
For examination purposes, language is interpreted as indicated in the Claim Objections section.
Examiner’s Note
Claims 1-16 were evaluated for patent eligibility under 35 U.S.C. 101 using the SUBJECT MATTER ELIGIBILITY TEST FOR PRODUCTS AND PROCESSES described in the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (see also 2019 Revised Patent Subject Matter Eligibility Guidance) to determine patent eligibility under 35 U.S.C. 101.
Regarding claim 1, the examiner submits that under Step 1 of the test for evaluating claims for eligibility under 35 U.S.C. 101, the claim is to a process, which is one of the statutory categories of invention.
Continuing with the analysis, under Step 2A - Prong One of the test:
the limitation “S3, defining and initializing a known gas weight parameter w and an unknown gas weight parameter wu, and constructing a squared loss function and an objective function according to the known gas feature Di, the known gas weight parameter w, the unknown gas feature Duj, the unknown gas weight parameter wu, and the gas mixture featured d” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mental processes and/or mathematical concepts (e.g., defining variables for setting a mathematical function, see specification at [0011]-[0012]; see also claim 2). Except for the recitation of the extra-solution activities (i.e., source/type of data being evaluated) and/or the field of use, the limitation in the context of this claim mainly refers to performing mental evaluations and/or applying mathematical concepts to set variables for a mathematical equation.
the limitation “S4, learning and training each parameter in the squared loss function until the value of the objective function is less than the set value or the number of learning times reaches the target number, and obtaining the final unknown gas feature Duj” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mental processes and/or mathematical concepts (e.g., , see specification at [0018]-[0026]; see also claims 5 and 7) to obtain additional information (i.e., the final unknown gas feature Duj). Except for the recitation of the extra-solution activities (i.e., source/type of data being evaluated) and/or the field of use, the limitation in the context of this claim mainly refers to performing mental evaluations and/or applying mathematical concepts to manipulate data and obtain a result.
Therefore, the claim recites a judicial exception under Step 2A - Prong One of the test.
Furthermore, under Step 2A - Prong Two of the test, the claim recites:
“A method for measuring a concentration of a gas to be measured by identifying features of an unknown gas” which generally links the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h));
“S1, injecting standard samples of m known gases into a measuring cell of a gas analyzer, scanning in a wide spectral range to obtain an absorption spectrum of each sample, further obtaining a feature Di of each sample gas, and establishing a feature library D of the known gases” which adds extra-solution activities (e.g., mere data gathering, source/type of data to be manipulated) using elements recited at a high level of generality (i.e., a measuring cell of a gas analyzer) (see MPEP 2106.05(g)), as well as generic computer functions (e.g., store data) (see MPEP 2106.05(f));
“S2, injecting a gas mixture into the measurement cell of the gas analyzer, and scanning in a wide spectral range to obtain the feature d of the gas mixture, where the gas mixture includes m known gases and n unknown gases, and features of the unknown gases are defined as Duj” which adds extra-solution activities (e.g., mere data gathering, source/type of data to be manipulated) using elements recited at a high level of generality (i.e., the measurement cell of the gas analyzer) (see MPEP 2106.05(g)); and
“S5, adding the final unknown gas feature Duj to the known gas feature library D, and obtaining the concentration of a gas to be measured in the gas mixture through gas concentration inversion calculation” which, besides adding generic computer functions (e.g., store data) (see MPEP 2106.05(f)), integrates the judicial exception into a practical application, when considering the claim as a whole, by reflecting an improvement to other technology or technical field (i.e., obtaining the concentration of a gas to be measured in the gas mixture, see specification at [0004], [0044], [0100]) (see MPEP 2106.05(a)).
Therefore, these additional elements, when considered individually and in combination, integrate the judicial exception into a practical application. The claim, when considered as a whole, is eligible at Prong Two of the Revised Step 2A (see 2019 Revised Patent Subject Matter Eligibility Guidance – Revised Step 2A, see also MPEP 2106.04(d)).
Regarding the dependent claims 2-16, they were also found to be patent eligible under 35 U.S.C. 101 by incorporating the eligible subject matter of their corresponding independent claim.
Subject Matter Not Rejected Over Prior Art
Claims 1-16 are distinguished over the prior art of record for the following reasons:
Regarding claim 1.
Zhou (CN 108287141 A, IDS reference, see translation) discloses/teaches:
A method for measuring a concentration of a gas to be measured (abstract, p. 2: a multi-component gas concentration method based on spectroscopy analysis and least square method is presented), comprising the following steps:
S1, injecting standard samples of m known gases into a measuring cell of a gas analyzer, scanning in a wide spectral range to obtain an absorption spectrum of each sample, further obtaining a feature Di of each sample gas, and establishing a feature library D of the known gases (p. 2, S2: standard sample absorption response (feature) is obtained using an spectrum analyzer (see p. 3 regarding using a standard infrared spectrum library for peak comparison));
S2, injecting a gas mixture into the measurement cell of the gas analyzer, and scanning in a wide spectral range to obtain the feature d of the gas mixture, where the gas mixture includes m known gases and n unknown gases, and features of the unknown gases are defined as Duj (p. 2, S1-S3: absorption response of mixed gas, which implies a gas mixture having different known and unknown gases, is obtained by measuring background absorption response and standard sample absorption response).
Zhang (CN 113916810 A, IDS reference, see translation) discloses:
“The invention claims a multi-component gas concentration analysis method, comprising the following steps: (A1) for the possible gas component, establishing the function relation Ai=S (C) between the absorption spectrum and the concentration, i is the spectrum pixel point number, C is the concentration, A represents the absorbance; obtaining absorption spectrum database Aij=S (Cj), j is gas component sequence number; (A2) obtaining the absorption spectrum A’i of the sample gas, using the matching algorithm to obtain the main gas component in the sample gas, the component sequence number is j= 1: K; so as to obtain the sample gas in each gas component of the estimated concentration C’j and light absorption spectrum A’ij; (A3) constructing combined absorption spectrum L is iteration times, λ is the spectrum pixel wavelength; (A4) combining the loss function to construct a target function; (A5) using an iterative algorithm to adjust the estimated concentration C’j and a1, so as to iteratively optimize the target function, when the target function is the minimum estimated concentration C’j as the concentration of each gas component in the sample gas” (Abstract: a multi-component gas concentration method based on absorption vs. concentration relationship obtains the absorption spectrum of a sample gas and matches it with information in a database, adjusting the concentration information based on the measured absorption spectrum).
Zhu (CN 102435567 A, IDS reference, see translation) discloses:
“This invention relates to an inversion calculation method for measuring the gas component concentration. The inversion calculation method for measuring the gas component concentration based on the differential absorption spectrum establishes a mathematical model, using the least square method to solve, it is capable of real time recording the content of all kinds of pollutants in the smoke gas, and the gas is unknown” (Abstract: an inversion calculation method for measuring gas component concentration based on differential absorption spectrum technology and least square fit (see p. 4)).
The closest prior art of record, taken individually or in combination, fail to teach or suggest (see italic text):
“A method for measuring a concentration of a gas to be measured by identifying features of an unknown gas, comprising the following steps:
S3, defining and initializing a known gas weight parameter w and an unknown gas weight parameter wu, and constructing a squared loss function and an objective function according to the known gas feature Di, the known gas weight parameter w, the unknown gas feature Duj, the unknown gas weight parameter wu, and the gas mixture featured d;
S4, learning and training each parameter in the squared loss function until the value of the objective function is less than the set value or the number of learning times reaches the target number, and obtaining the final unknown gas feature Duj; and
S5, adding the final unknown gas feature Duj to the known gas feature library D, and obtaining the concentration of a gas to be measured in the gas mixture through gas concentration inversion calculation”
in combination with all other limitations within the claim, as claimed and defined by the applicant.
Regarding claims 2-16.
They are also distinguished over the prior art of record due for their dependency.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
ZHOU, SHENG et al., CN 110146455 A, Laser spectrum gas concentration measuring method based on deep learning
Reference discloses a laser spectrum gas concentration measuring method based on deep learning.
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/LINA CORDERO/Primary Examiner, Art Unit 2857