DETAILED ACTION
Claims 1-19 are presented for examination. This office action is response to the submission on 2/29/2024.
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 .
Drawings
The drawings filed on 2/29/2024 are acceptable for examination proceedings.
Claim Objections
Claims 3 and 12 are objected to because of the following informalities:
Claim 3 recites “assessing a usage impact value of gas usage on gas pressure based on gas usage data of upstream and downstream of the target field station” in lines 4-5. Examiner believes this was meant to recite “assessing a usage impact value of gas usage on gas pressure based on gas usage data [[of]] upstream and downstream of the target field station” (Typo). Claim 12 recites a similar limitation in lines 3-4. Appropriate correction is 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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claims 1 and 10:
Claims 1 is drawn to a method and claim 10 is drawn to a system. Therefore claims 1 and 10 fall under one of the four categories of statutory subject matter (process/method, machines/products/apparatus, manufactures, and compositions of matter).
Step 2A: Is the claim directed to a law of nature, a natural phenomenon (product of nature), or an abstract idea?
It is an abstract idea.
Step 2A-Prong 1: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes.
MPEP 2106.04(a) - “Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion).”
claims 1 and 10 are directed to a judicially recognized exception of an abstract idea without significantly more. Each of claims 1 and 10 recites functions below that under the limitation’s broadest reasonable interpretation, enumerates mental concepts. Other than reciting generic computer elements “smart gas pipeline network equipment sensing network”, “gas data center” “smart gas pipeline network equipment object platform”, and “smart gas safety management platform” (as recited in claim 10), nothing in the claims preclude the functions from the mental concept.
The mere nominal recitation of a management platform to perform the mental concept does not take the claim limitations out of the abstract idea (See MPEP 2106.04(a)(2)(III)).
“predict, based on the relevant data, noise enhancement data of the target field station for at least one future time period;” A human can predict noise enhancement data based on relevant data for a future time period (judgment).
“determine, in response to the noise enhancement data satisfying a predetermined condition, a noise reduction control parameter based on the noise enhancement data and the pressure regulation parameter, wherein the noise reduction control parameter includes at least a pressure regulation update parameter of the target field station or the associated field station for the at least one future period;” A human can determine a noise reduction control parameter based on data in response to the data satisfying a condition, that includes a pressure regulation update parameter (judgment).
Step 2A-Prong 2: Does the claim recite additional element that integrate the judicial exception into a practical application?
No.
2106.05(f) Mere Instructions To Apply An Exception
The use of the platforms and data center (as recited in claim 10) are recited at a high level of generality i.e. as generic platforms performing generic functions of obtaining data, predicting noise enhancement data, determining a response to the data, and sending noise reduction control data to another platform. This generic recitation of the platforms and data center is not more than mere instructions to apply the exception using a generic component. The platform that performs the steps merely automates steps which may be done mentally or manually. Thus the additional elements don’t integrate the abstract idea into a practical application as it merely amounts to instructions to apply it. The claim does not set forth improvements to the functioning of a computer or another technological field and uses the generic elements as tools in a conventional way to perform the steps in the claims.
“As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do "‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on "the draftsman’s art").”
2106.05(g) Insignificant Extra-Solution Activity
The term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent. An example of post-solution activity is an element that is not integrated into the claim as a whole, e.g., a printer that is used to output a report of fraudulent transactions, which is recited in a claim to a computer programmed to analyze and manipulate information about credit card transactions in order to detect whether the transactions were fraudulent.
The following is pre-solution activity (mere data gathering):
“obtain relevant data of a target field station, wherein the relevant data includes at least one of operating data of the target field station, noise data of the target field station, and pressure regulation parameter of an associated field station, and the associated field station is a gas field station in a gas pipeline network that jointly regulates pressure with the target field station; “(as recited in claim 10).
The following is post-solution activity:
“the smart gas service platform is configured to send the noise reduction control parameter to the smart gas user platform.” (as recited in claim 10).
The examiner has considered the limitations together as a single abstract idea for Step 2A Prong Two rather than as a plurality of separate ideas to be analyzed individually.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The additional elements amount to implementing generic platforms and a data center towards a field of use and insignificant pre and post-solution activity. The use of the platforms and data center are recited at a high level of generality. This generic recitation of the platforms and data center is not more than mere instructions to apply the exception using a generic component. The platform that performs the steps merely automates steps which may be done mentally or manually. Thus the additional elements don’t integrate the abstract idea into a practical application as it merely amounts to instructions to apply it. The claim does not set forth improvements to the functioning of a computer or another technological field and uses the generic elements as tools in a conventional way to perform the steps in the claims. The insignificant pre and post-solution activity do not integrate the abstract idea into a practical application because they don’t include meaningful limits on practicing the abstract idea.
The system of claim 10 requires platforms and a data center which are recited at a high level of generality. Based on the specification, the invention uses conventional sensors, communication networks, conventional non-transitory computer-readable storage medium, and generic computers and a terminal device in order to implement the platforms and data center recited in claim 10. The functions performed by the generic computer elements are basic functions of a computer including performing mathematical operations and receiving, storing, comparing, and outputting data which have been recognized by the courts as routine and conventional activity.
“Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). On the other hand, courts have held computer-implemented processes to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic.” DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1257-59, 113 USPQ2d 1097, 1105-07 (Fed. Cir. 2014). ”Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display” Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
MPEP 2106.05(d)(II)(i) provides support that receiving or transmitting data over a network is well understood, routine, and conventional.
As such, claims 1 and 10 are not patent eligible.
Dependent Claims 2-9 and 11-19:
Step 1:
Claims 2-9 are drawn to a method, claims 10-18 are drawn to a system, claim 19 is drawn to a non-transitory computer-readable storage medium storing instructions therefore each of claims 2-10 and 12-19 fall under one of four categories of statutory subject matter (process/method, machines/products/apparatus, manufactures, and compositions of matter). Nonetheless, dependent claims 2-9 and 11-19 are also ineligible for the same reasons given with respect to claims 1 and 10.
Steps 2A-2B:
Claims 2-9 and 11-18 recite further mental abstract concepts of determining pressure regulation load data, predicting noise enhancement data, assessing a usage impact value, determining a pre-regulation and target pressure, determining pressure regulation load data, predicting noise enhancement data, determining a pressure regulation adjustment amplitude, determining a candidate parameter, determining noise reduction parameter, determining an adjustment amplitude, determining predicted enhancement data, determining evaluation data, constructing a field station regulation graph, determining a predicted enhancement data, and further defines the field station graph. (See MPEP 2106.04(a)(2)(III)).
Claims 4, 8, 13, 17, and 19 recite further generic computer elements of machine learning models, which are mere tools to predict enhancement data, and are not used in control of functional aspects of real-world processes. The use of machine learning as recited in the claim is merely as a computational technique to generate prediction data. There is no improvement in machine learning techniques recited and no practical application of the predictions generated. The additional element of a non-transitory computer-readable storage medium storing instructions to implement the method of claim 1 is merely a generic computer element and doesn’t integrate the claim as a whole into a practical application. (See MPEP 2106.05(f)).
The additional elements that are in the form of generic computer elements, do not amount to significantly more than an abstract idea because “As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do "‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on "the draftsman’s art").” (MPEP 2106.05(f).
As such, claims 2-9 and 11-19 are not patent eligible.
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.
Claims 1, 5, 10, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ding et al. (CN115978461A) (citations to examiner provided translation) in view of Eberbach et al. (US20170188166A1).
Claim 1:
Ding teaches “A method for noise reduction at a smart gas field station, wherein the method comprises: obtaining relevant data of a target field station, wherein the relevant data comprises at least one of operating data of the target field station, noise data of the target field station, (Ding teaches a method of predicting a leak by monitoring sound i.e. relevant noise data of a target field station at the beginning and end of a gas pipeline in Ding [0066-0069] "In another embodiment of the invention, for further definition and explanation, as shown in FIG3, before sending the changed pressure and the changed time length to the transformer control station, the method further includes: 201. Acquire acoustic signals collected by acoustic detection devices located at the beginning and end of the natural gas pipeline; 202. After filtering the acoustic signal, determine whether there is a leak in the natural gas pipeline by the relationship between the attenuation of the acoustic wave and pressure along the pipeline and the acoustic signal. 203. If leakage is present, the safe pressure threshold range shall be determined based on the acoustic signal."; Ding teaches that the invention provides a control system for natural gas pipelines in Ding [0046] "This invention provides a safety management and control system for natural gas pipelines used in gas-fired power generation. Compared with existing technologies, this invention, upon receiving a natural gas replenishment request from a storage station, sends a data acquisition request to the nearest transformer control station. This allows the transformer control station to provide feedback on the gas supply pressure and pipeline inventory of the natural gas pipeline connected to the storage station. The system acquires the measured pressure of the natural gas pipeline determined by fiber optic equipment, as well as the storage demand of the storage station. Based on the gas supply pressure, pipeline inventory, measured pressure, and storage demand, the system determines the expected change pressure and time duration for the transformer control station to adjust the gas supply. When the changed pressure matches the safe pressure threshold range of the natural gas pipeline, and the changed pressure is less than or equal to the maximum pressure value of the pipeline, the changed pressure and the changed time length are sent to the pressure control station so that the pressure control station can increase the gas supply based on the changed pressure and the changed time length. The safe pressure threshold range includes the maximum and minimum supply pressure values determined when there is a leak in the natural gas pipeline."; Ding teaches determining a pressure using the sound data in Ding [0101] "Furthermore, the acoustic signal includes a head end acoustic signal and an end acoustic signal. The determining module is specifically used to determine the difference between the head end acoustic signal and the end acoustic signal, and to determine whether the difference is within the abnormal range of the acoustic signal along the pipeline by using the pipeline friction attenuation relationship. If the difference is within the abnormal range of the acoustic signal along the pipeline, the head end acoustic signal and the end acoustic signal are processed by signal conversion to obtain the pipeline head end pressure and the pipeline end pressure. By determining whether the friction attenuation pressure value calculated by determining the pipeline length, the pipeline head end pressure, and the pipeline end pressure is equal to a preset friction attenuation threshold, it is determined whether there is a leak in the natural gas pipeline."), and
“and determining, in response to the noise enhancement data satisfying a predetermined condition, a noise reduction control parameter based on the noise enhancement data and the pressure regulation parameter, wherein the noise reduction control parameter comprises at least a pressure regulation update parameter of the target field station (Ding teaches that if a leak is determined to be present i.e. the noise data satisfies a predetermined condition, it adjusts the safe pressure threshold range e.g. for a future period based on the acoustic signal i.e. noise data in Ding [0066-0069] "In another embodiment of the invention, for further definition and explanation, as shown in FIG3, before sending the changed pressure and the changed time length to the transformer control station, the method further includes: 201. Acquire acoustic signals collected by acoustic detection devices located at the beginning and end of the natural gas pipeline; 202. After filtering the acoustic signal, determine whether there is a leak in the natural gas pipeline by the relationship between the attenuation of the acoustic wave and pressure along the pipeline and the acoustic signal. 203. If leakage is present, the safe pressure threshold range shall be determined based on the acoustic signal.”).
Ding does not appear to explicitly teach “predicting, based on the relevant data, noise enhancement data of the target field station for at least one future period;” However, Eberbach does teach this claim limitation (Eberbach teaches predicting loudness in a future time period and implementing corrective actions which may include transmitting a control signal to equipment e.g. the pressure threshold may be adjusted in response to a predicted sound exceeding a threshold in Eberbach [0076-0077] "In block 260, the hearing protection system may determine whether the SPL exposure is above a predetermined safety threshold value. If the worker's predicted or actual exposure is determined to be over the safety threshold value, the hearing protection system may signal that adjustments may be required to the noise zone and/or worker schedule. In block 270, the hearing protection system 190 may implement corrective actions to reduce risk, which may include reducing the noise level or modifying the worker's task schedule. The hearing protection system 190 may transmit a control signal to machinery and/or equipment to slow down or turn off for a predetermined period of time to reduce the SPLs in the particular noise zone, signal the worker to take an alternate transit path to a location in the facility, alter the workers scheduled tasks to avoid the SPLs in the particular noise zone, or a combination thereof").
Ding and Eberbach are analogous art because they are from the same field of endeavor of industrial controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Ding and Eberbach before him/her, to modify the teachings of A gas-fired power generation natural gas pipeline safety management and control system of Ding to include the prediction of future noise of Eberbach because adding the Predicting harmful noise events and implementing corrective actions prior to noise induced hearing loss of Eberbach would allow for a reduction in noise induced hearing loss as described in Eberbach [0005] “Workers may routinely be instructed to wear personal protective equipment that includes hearing protection, but such routine instructions are typically not predictive and do not usually customize the level of hearing protection for the actual worker and the actual environment. Workers may ignore such routine instructions, and even if followed may provide under or over protection. It would, therefore, be beneficial to provide a way of reducing noise induced hearing loss.” And in Eberbach [0077] “In block 270, the hearing protection system 190 may implement corrective actions to reduce risk, which may include reducing the noise level or modifying the worker's task schedule. The hearing protection system 190 may transmit a control signal to machinery and/or equipment to slow down or turn off for a predetermined period of time to reduce the SPLs in the particular noise zone, signal the worker to take an alternate transit path to a location in the facility, alter the workers scheduled tasks to avoid the SPLs in the particular noise zone, or a combination thereof. The hearing protection system 190 may also change the prescribed PPE for the worker to increase NRR, or allocate additional hearing protection to the worker.”
Claim 5:
Ding in view of Eberbach teaches “The method of claim 1, wherein the determining, in response to the noise enhancement data satisfying a predetermined condition, a noise reduction control parameter based on the noise enhancement data and the pressure regulation parameter comprises: determining an adjustment amplitude of the pressure regulation parameter based on the noise enhancement data; determining a candidate parameter by adjusting the pressure regulation parameter based on the adjustment amplitude;” (Ding teaches that if a leak is determined to be present i.e. the noise data satisfies a predetermined condition, it adjusts the safe pressure threshold range e.g. the pressure amplitude may be adjusted based on the threshold range changing based on the acoustic signal i.e. noise data in Ding [0066-0069] "In another embodiment of the invention, for further definition and explanation, as shown in FIG3, before sending the changed pressure and the changed time length to the transformer control station, the method further includes: 201. Acquire acoustic signals collected by acoustic detection devices located at the beginning and end of the natural gas pipeline; 202. After filtering the acoustic signal, determine whether there is a leak in the natural gas pipeline by the relationship between the attenuation of the acoustic wave and pressure along the pipeline and the acoustic signal. 203. If leakage is present, the safe pressure threshold range shall be determined based on the acoustic signal."), and
“determining the noise reduction control parameter through an iteration based on evaluation data of the candidate parameter.” (Ding teaches that the safe pressure range is compared with the changed pressure to determine whether the pressure change can be carried out i.e. it evaluates the adjustment in Ding [0070] "In this embodiment of the invention, in order to determine whether there is a leak in the natural gas pipeline, the safe pressure threshold range determined based on the leak is compared with the changed pressure to determine whether pressure change gas supply can still be carried out in the case of pipeline leakage. First, the acoustic signals collected by the acoustic detection equipment at the beginning and end of the natural gas pipeline are obtained, and the presence of pipeline leakage is determined based on the acoustic signals... If a leak is present, this embodiment of the invention determines a safe pressure threshold range based on the acoustic signal, and compares this safe pressure threshold range with the changed pressure.").
Claim 10:
Ding teaches “An Internet of Things (IoT) system for noise reduction at a smart gas field station, wherein the system comprises a smart gas user platform, a smart gas service platform, a smart gas safety management platform, a smart gas pipeline network equipment sensing network platform, and a smart gas pipeline network equipment object platform;” (Ding teaches a processor, communication interface, memory, and communication bus in Ding [0109-0115] "As shown in Figure 5, the terminal may include: a processor 502, a communication interface 504, a memory 506, and a communication bus 508.The processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508. Communication interface 504 is used to communicate with other network elements such as clients or other servers. The processor 502 is used to execute program 510, which can specifically execute the relevant steps in the above-described embodiment of the safety management method for gas-fired power generation and natural gas pipelines. Specifically, program 510 may include program code that includes computer operation instructions. The processor 502 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The terminal includes one or more processors, which can be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs. Memory 506 is used to store program 510. The memory 506 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device."),
“the smart gas safety management platform includes a smart gas pipeline network safety management sub-platform and a smart gas data center; the smart gas pipeline network equipment sensing network platform is configured to interact with the smart gas data center and the smart gas pipeline network equipment object platform;” (Ding teaches a program which determines gas supply based on threshold ranges i.e. it is a safety management platform and data center and that the measured pressure is acquired and used to determine the expected change pressure i.e. the sensing platform interacts with the smart gas data center in Ding [0116-0119] "Specifically, program 510 can be used to cause processor 502 to perform the following operations: When a natural gas storage increase request is received from a storage station, a data acquisition request is sent to the nearest transformer control station so that the transformer control station can provide feedback on the gas supply pressure and pipeline storage of the natural gas pipeline connected to the storage station. The system acquires the measured pressure of the natural gas pipeline determined by the fiber optic device, as well as the storage demand of the storage station, and determines the expected change pressure and change time of the gas supply to the transformer control station based on the gas supply pressure, the pipeline storage, the measured pressure, and the storage demand. When the changed pressure matches the safe pressure threshold range of the natural gas pipeline, and the changed pressure is less than or equal to the maximum pressure value of the pipeline, the changed pressure and the changed time length are sent to the pressure control station so that the pressure control station can increase the gas supply based on the changed pressure and the changed time length. The safe pressure threshold range includes the maximum and minimum supply pressure values determined when there is a leak in the natural gas pipeline."),
“the smart gas safety management platform is configured to: obtain relevant data of a target field station, wherein the relevant data includes at least one of operating data of the target field station, noise data of the target field station, and pressure regulation parameter of an associated field station, and the associated field station is a gas field station in a gas pipeline network that jointly regulates pressure with the target field station;” (Ding teaches a method of predicting a leak by monitoring sound i.e. relevant noise data of a target field station at the beginning and end of a gas pipeline in Ding [0066-0069] "In another embodiment of the invention, for further definition and explanation, as shown in FIG3, before sending the changed pressure and the changed time length to the transformer control station, the method further includes: 201. Acquire acoustic signals collected by acoustic detection devices located at the beginning and end of the natural gas pipeline; 202. After filtering the acoustic signal, determine whether there is a leak in the natural gas pipeline by the relationship between the attenuation of the acoustic wave and pressure along the pipeline and the acoustic signal. 203. If leakage is present, the safe pressure threshold range shall be determined based on the acoustic signal."; Ding teaches that the invention provides a control system for natural gas pipelines in Ding [0046] "This invention provides a safety management and control system for natural gas pipelines used in gas-fired power generation. Compared with existing technologies, this invention, upon receiving a natural gas replenishment request from a storage station, sends a data acquisition request to the nearest transformer control station. This allows the transformer control station to provide feedback on the gas supply pressure and pipeline inventory of the natural gas pipeline connected to the storage station. The system acquires the measured pressure of the natural gas pipeline determined by fiber optic equipment, as well as the storage demand of the storage station. Based on the gas supply pressure, pipeline inventory, measured pressure, and storage demand, the system determines the expected change pressure and time duration for the transformer control station to adjust the gas supply. When the changed pressure matches the safe pressure threshold range of the natural gas pipeline, and the changed pressure is less than or equal to the maximum pressure value of the pipeline, the changed pressure and the changed time length are sent to the pressure control station so that the pressure control station can increase the gas supply based on the changed pressure and the changed time length. The safe pressure threshold range includes the maximum and minimum supply pressure values determined when there is a leak in the natural gas pipeline."; Ding teaches determining a pressure using the sound data in Ding [0101] "Furthermore, the acoustic signal includes a head end acoustic signal and an end acoustic signal. The determining module is specifically used to determine the difference between the head end acoustic signal and the end acoustic signal, and to determine whether the difference is within the abnormal range of the acoustic signal along the pipeline by using the pipeline friction attenuation relationship. If the difference is within the abnormal range of the acoustic signal along the pipeline, the head end acoustic signal and the end acoustic signal are processed by signal conversion to obtain the pipeline head end pressure and the pipeline end pressure. By determining whether the friction attenuation pressure value calculated by determining the pipeline length, the pipeline head end pressure, and the pipeline end pressure is equal to a preset friction attenuation threshold, it is determined whether there is a leak in the natural gas pipeline."), and
“determine, in response to the noise enhancement data satisfying a predetermined condition, a noise reduction control parameter based on the noise enhancement data and the pressure regulation parameter, wherein the noise reduction control parameter includes at least a pressure regulation update parameter of the target field station (Ding teaches that if a leak is determined to be present i.e. the noise data satisfies a predetermined condition, it adjusts the safe pressure threshold range e.g. for a future period based on the acoustic signal i.e. noise data in Ding [0066-0069] "In another embodiment of the invention, for further definition and explanation, as shown in FIG3, before sending the changed pressure and the changed time length to the transformer control station, the method further includes: 201. Acquire acoustic signals collected by acoustic detection devices located at the beginning and end of the natural gas pipeline; 202. After filtering the acoustic signal, determine whether there is a leak in the natural gas pipeline by the relationship between the attenuation of the acoustic wave and pressure along the pipeline and the acoustic signal. 203. If leakage is present, the safe pressure threshold range shall be determined based on the acoustic signal.”).
Ding does not appear to explicitly teach “predict, based on the relevant data, noise enhancement data of the target field station for at least one future time period;” However, Eberbach does teach this claim limitation (Eberbach teaches predicting loudness in a future time period and implementing corrective actions which may include transmitting a control signal to equipment e.g. the pressure threshold may be adjusted in response to a predicted sound exceeding a threshold in Eberbach [0076-0077] "In block 260, the hearing protection system may determine whether the SPL exposure is above a predetermined safety threshold value. If the worker's predicted or actual exposure is determined to be over the safety threshold value, the hearing protection system may signal that adjustments may be required to the noise zone and/or worker schedule. In block 270, the hearing protection system 190 may implement corrective actions to reduce risk, which may include reducing the noise level or modifying the worker's task schedule. The hearing protection system 190 may transmit a control signal to machinery and/or equipment to slow down or turn off for a predetermined period of time to reduce the SPLs in the particular noise zone, signal the worker to take an alternate transit path to a location in the facility, alter the workers scheduled tasks to avoid the SPLs in the particular noise zone, or a combination thereof").
Ding and Eberbach are analogous art because they are from the same field of endeavor of industrial controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Ding and Eberbach before him/her, to modify the teachings of A gas-fired power generation natural gas pipeline safety management and control system of Ding to include the prediction of future noise of Eberbach because adding the Predicting harmful noise events and implementing corrective actions prior to noise induced hearing loss of Eberbach would allow for a reduction in noise induced hearing loss as described in Eberbach [0005] “Workers may routinely be instructed to wear personal protective equipment that includes hearing protection, but such routine instructions are typically not predictive and do not usually customize the level of hearing protection for the actual worker and the actual environment. Workers may ignore such routine instructions, and even if followed may provide under or over protection. It would, therefore, be beneficial to provide a way of reducing noise induced hearing loss.” And in Eberbach [0077] “In block 270, the hearing protection system 190 may implement corrective actions to reduce risk, which may include reducing the noise level or modifying the worker's task schedule. The hearing protection system 190 may transmit a control signal to machinery and/or equipment to slow down or turn off for a predetermined period of time to reduce the SPLs in the particular noise zone, signal the worker to take an alternate transit path to a location in the facility, alter the workers scheduled tasks to avoid the SPLs in the particular noise zone, or a combination thereof. The hearing protection system 190 may also change the prescribed PPE for the worker to increase NRR, or allocate additional hearing protection to the worker.”
Claim 14:
The limitations of claim 14 are substantially the same as claim 5 and it is rejected for the same reasons.
Claim 19:
Ding in view of Eberbach teaches “A non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements the method of claim 1.” (Ding teaches a memory storing a program that is executed by a processor in Ding [0109-0115] "As shown in Figure 5, the terminal may include: a processor 502, a communication interface 504, a memory 506, and a communication bus 508.The processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508. Communication interface 504 is used to communicate with other network elements such as clients or other servers. The processor 502 is used to execute program 510, which can specifically execute the relevant steps in the above-described embodiment of the safety management method for gas-fired power generation and natural gas pipelines. Specifically, program 510 may include program code that includes computer operation instructions. The processor 502 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The terminal includes one or more processors, which can be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs. Memory 506 is used to store program 510. The memory 506 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.").
Claims 2-3 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Ding et al. (CN115978461A) (citations to examiner provided translation) in view of Eberbach et al. (US20170188166A1), further in view of Lander et al. (US20180320828A1).
Claim 2:
Ding in view of Eberbach teaches “The method of claim 1, wherein the predicting, based on the relevant data, noise enhancement data of the target field station for at least one future period comprises: determining, based on the pressure regulation parameter, pressure regulation load data of the target field station for the at least one future period;” (Ding teaches that the pressure will be maintained in the threshold i.e. the threshold determines a future pressure load in Ding [0064] "In this embodiment of the invention, after determining the change pressure, the change pressure is compared with the safe pressure threshold range of the natural gas pipeline, and the change pressure is also compared with the maximum pressure value of the pipeline. Therefore, when the change pressure matches the safe pressure threshold range of the natural gas pipeline and the change pressure is less than or equal to the maximum pressure value of the pipeline, the current execution terminal sends the change pressure and change time length to the transformer control station. The safe pressure threshold range includes the maximum and minimum pressure values determined when there is a leak in the natural gas pipeline. This ensures that when the pressure change matches this safe pressure threshold range, it indicates that even if there is a leak in the natural gas pipeline, safe pressure can still be supplied when supplying gas based on the pressure change.").
Ding and Eberbach do not appear to explicitly teach “and predicting, based on the relevant data and the pressure regulation load data, the noise enhancement data.” However, Lander does teach this claim limitation (Lander teaches that pressure is typically proportional to pipe sounds i.e. the measured pressure may be used to determine the noise data in Lander [0045] "Combining these two measures (i.e., time-varying and time-invariant pressure signals) can be advantageous. For example, it is beneficial to record pipe sounds when the fluidic pressure is greatest because the amplitude of the pipe sounds is typically proportional to fluidic pressure and because the fluid flow rate, which is a source of noise, is typically inversely proportional to fluidic pressure. The absolute level of fluidic pressure, and its diurnal variations, may provide useful information about the strain experienced by the pipeline network, with high levels or variations in fluidic pressure being a source of stress, and hence reduced life expectancy, for pipe assets.").
Ding, Eberbach, and Lander are analogous art because they are from the same field of endeavor of industrial controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Ding, Eberbach, and Lander before him/her, to modify the teachings of A gas-fired power generation natural gas pipeline safety management and control system of Ding modified to include the prediction of future noise of Eberbach to include the relationship of pressure and noise of Lander because adding the Integrity assessment of a pipeline network of Lander would allow for providing useful information of strain experienced by the pipeline network as described in Lander [0045] “Combining these two measures (i.e., time-varying and time-invariant pressure signals) can be advantageous. For example, it is beneficial to record pipe sounds when the fluidic pressure is greatest because the amplitude of the pipe sounds is typically proportional to fluidic pressure and because the fluid flow rate, which is a source of noise, is typically inversely proportional to fluidic pressure. The absolute level of fluidic pressure, and its diurnal variations, may provide useful information about the strain experienced by the pipeline network, with high levels or variations in fluidic pressure being a source of stress, and hence reduced life expectancy, for pipe assets."
Claim 3:
Ding in view of Eberbach, further in view of Lander teaches “The method of claim 2, wherein the determining, based on the pressure regulation parameter, pressure regulation load data of the target field station for the at least one future period comprises: assessing a usage impact value of gas usage on gas pressure based on gas usage data of upstream and downstream of the target field station;” (Ding teaches that the safe pressure range is compared with the changed pressure to determine whether the pressure change can be carried out i.e. a leak may be present downstream and upstream of the station, affecting the usage in Ding [0070] "In this embodiment of the invention, in order to determine whether there is a leak in the natural gas pipeline, the safe pressure threshold range determined based on the leak is compared with the changed pressure to determine whether pressure change gas supply can still be carried out in the case of pipeline leakage. First, the acoustic signals collected by the acoustic detection equipment at the beginning and end of the natural gas pipeline are obtained, and the presence of pipeline leakage is determined based on the acoustic signals... If a leak is present, this embodiment of the invention determines a safe pressure threshold range based on the acoustic signal, and compares this safe pressure threshold range with the changed pressure."),
“determining a pre-regulation pressure and a target pressure of the target field station based on the usage impact value and the pressure regulation parameter;” (Ding teaches that the safe pressure range is compared with the changed pressure to determine whether the pressure change can be carried out i.e. the usage and regulation pressures may determine the target pressure in Ding [0070] "In this embodiment of the invention, in order to determine whether there is a leak in the natural gas pipeline, the safe pressure threshold range determined based on the leak is compared with the changed pressure to determine whether pressure change gas supply can still be carried out in the case of pipeline leakage. First, the acoustic signals collected by the acoustic detection equipment at the beginning and end of the natural gas pipeline are obtained, and the presence of pipeline leakage is determined based on the acoustic signals... If a leak is present, this embodiment of the invention determines a safe pressure threshold range based on the acoustic signal, and compares this safe pressure threshold range with the changed pressure."), and
“and determining the pressure regulation load data based on the pre-regulation pressure and the target pressure.” (Ding teaches that the safe pressure range is compared with the changed pressure to determine whether the pressure change can be carried out i.e. the pressure difference before and after the new threshold is compared in Ding [0070] "In this embodiment of the invention, in order to determine whether there is a leak in the natural gas pipeline, the safe pressure threshold range determined based on the leak is compared with the changed pressure to determine whether pressure change gas supply can still be carried out in the case of pipeline leakage. First, the acoustic signals collected by the acoustic detection equipment at the beginning and end of the natural gas pipeline are obtained, and the presence of pipeline leakage is determined based on the acoustic signals... If a leak is present, this embodiment of the invention determines a safe pressure threshold range based on the acoustic signal, and compares this safe pressure threshold range with the changed pressure.").
Claim 11:
The limitations of claim 11 are substantially the same as claim 2 and it is rejected for the same reasons.
Claim 12:
The limitations of claim 12 are substantially the same as claim 3 and it is rejected for the same reasons.
Claims 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Ding et al. (CN115978461A) (citations to examiner provided translation) in view of Eberbach et al. (US20170188166A1), further in view of Lander et al. (US20180320828A1), further in view of Rostamzadeh et al. (US20200388166A1).
Claim 4:
Ding in view of Eberbach, further in view of Lander teaches “The method of claim 2” as described above. Ding, Eberbach, and Lander do not appear to explicitly teach “wherein the method further comprises: predicting the noise enhancement data by a first prediction model based on a field station sub-graph of the target field station, the first prediction model being a machine learning model.” However, Rostamzadeh does teach this claim limitation (Rostamzadeh teaches a machine learning module that is trained using historical information in Rostamzadeh [0103] "FIG. 8 shows an example machine learning module 800 according to some examples of the present disclosure. Machine learning module 800 utilizes a training module 810 and a prediction module 820. Training module 810 inputs historical information 830 into feature determination module 850A. The historical information 830 may be labeled. As described above, historical information may include historical measurements of dynamic feature information for a plurality of geographical regions. The dynamic feature information may be collected over a plurality of historical time periods (training time periods), which are also indicated in the historical information 830, at least in some embodiments. Static feature information for the geographical regions is also used in training of the model."; Rostamzadeh teaches the machine learning algorithm producing a model in Rostamzadeh [0107] "The machine learning algorithm 870 produces a model 806 (e.g. equivalent to trained model 314 in some aspects) based upon the features 860 and the label."; Rostamzadeh teaches using the model by inputting current information e.g. a field station sub-graph to predict loudness in Rostamzadeh [0109] "Feature determination module 850B may determine the same set of features or a different set of features from the current information 890 as feature determination module 850A determined from historical information 830. In some examples, feature determination module 850A and 850B are the same module. Feature determination module 850B produces a feature vector 815, which is input into the model 806 to generate a loudness prediction 895 for the geographic region. The loudness prediction 895 includes predictions for multiple frequencies. In one example embodiment, the training module 810 may operate in an offline manner to train the model 806. The prediction module 820, however, may be designed to operate in an online manner. It should be noted that the model 806 may be periodically updated via additional training and/or user feedback.").
Ding, Eberbach, Lander, and Rostamzadeh are analogous art because they are from the same field of endeavor of industrial controls and noise prediction. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Ding, Eberbach, Lander, and Rostamzadeh before him/her, to modify the teachings of A gas-fired power generation natural gas pipeline safety management and control system of Ding modified to include the prediction of future noise of Eberbach, further modified to include the relationship of pressure and noise of Lander to include the prediction of noise using a machine learning model of Rostamzadeh because adding the Time varying loudness prediction system of Rostamzadeh would allow for determination of when louder operations are acceptable as described in Rostamzadeh [0099] “In particular, the noise map data can provide the predicted loudness at various times of the day and, thus, allow for flight time schedules to be generated to maintain an acceptable level of loudness. By way of example, the noise map data can help determine at which time in the morning and/or night flights should commence and/or end for the day, and/or what intermediate times may be better to have a lower aggregate nose level (e.g., when school is ending for the day).”
Claim 13:
The limitations of claim 13 are substantially the same as claim 4 and it is rejected for the same reasons.
Allowable Subject Matter
Claims 6-9 and 15-18 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claim 6:
Rostamzadeh teaches a loudness predictive model based on weather in Rostamzadeh [0089], a weighting factor accounting for population density with respect to time varying loudness in Rostamzadeh [0039], and using the predicted loudness to determine acceptable loudness in areas in Rostamzadeh [0098]. None of the previously cited art or cited art in the conclusion teaches specifically “determining the adjustment amplitude based on a noise tolerance and associated enhancement data of the associated field station” (in combination with the other elements of the claim) having all the claimed features of the applicant’s instant invention.
Claim 7:
Ding teaches adjusting an acceptable pressure range based on noise data satisfying a condition and comparing the pressure range to the pressure in Ding [0066-0070], however it does not teach doing so based on data from both its station and an associated station. None of the previously cited art or cited art in the conclusion teaches specifically “determining predicted enhancement data of the target field station and the associated field station based on the candidate parameter; and determining the evaluation data of the candidate parameter based on the predicted enhancement data.” (in combination with the other elements of the claim) having all the claimed features of the applicant’s instant invention.
Claims 8-9:
Claims 8-9 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims based on their dependency on claim 7.
Claims 15-18:
The limitations of Claims 15-18 are substantially the same as those of claims 6-9 and would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims for the same reasons listed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Rostamzadeh et al. (US20200388166A1) additionally teaches a loudness predictive model based on weather in Rostamzadeh [0089] "The measurement devices discussed above have the capability to measure Cambridge based time varying loudness at least every second. Data collected from several locations is used by the disclosed embodiments for a training set. The training set is used to build a loudness predictive model. The loudness predictive model predicts a noise magnitude at any instant in the day based on other inputs including weather, traffic volume, traffic speed, and distance from a road (e.g. highway)."; Rostamzadeh teaches a weighting factor accounting for population density with respect to time varying loudness (TVL) in Rostamzadeh [0039] "For any given location and hour, TVL is integrated, in some embodiments, into equivalent loudness for that hour. As additional aircraft operations and flight routes are performed within a region, a TVL at these times and locations will change based on the perceived loudness of air operations relative to an existing soundscape. The disclosed embodiments capture this by measuring the delta in TVL between ambient sound and ambient sound after aircraft operations are introduced. Some embodiments perform these determinations for each spectral region. Some embodiments also include a weighting factor to account for population density in a particular region and at a particular time of day, as below: weighted impact(l,h)=ΔTVL(l,h)*P(l,h)"; Rostamzadeh teaches using the predicted loudness to determine acceptable loudness in areas in Rostamzadeh [0098] "As further described herein, the noise map data can be utilized for various purposes associated with an aerial vehicle. For example, in some implementations, the noise map data can be utilized for aerial vehicle routing and/or sky lane optimization. For example, aerial vehicle routes can be generated based on the noise map data to create routes that would maintain an acceptable level of loudness for the locations along the route in the geographic area. The acceptable level of loudness may be a threshold (e.g., in decibels or other unit) under which a total noise level (e.g., predicted loudness plus aerial vehicle generated loudness/noise) is to remain below. The threshold may be set by a regulatory body or other authority, a service entity managing an aerial fleet, or the like. The routes and/or sky lanes can be created such that the aerial vehicles are routed in a manner not to exceed the acceptable level of loudness at any point along the route. Moreover, a sky lane for a route (e.g., a volume around a route in which the aerial vehicle is to stay within) can be generated to ensure that the aerial vehicle stays within a threshold distance along a route to maintain an acceptable noise level."
Nielsen (US20130209220A1) teaches adjustment of windmill parameters if expected noise is over a threshold which changes over time in Nielsen [0020-0022].
Dufour et al. (US20210285605A1) teaches prediction of consumption over a distribution network according to time and weather data and predicts a change in pressure in Dufour [0166-0167].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Zachary A Cain whose telephone number is (571)272-4503. The examiner can normally be reached Mon-Fri 7:00-3:30 CST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth M Lo can be reached at (571) 272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Z.A.C./ Examiner, Art Unit 2116
/KENNETH M LO/ Supervisory Patent Examiner, Art Unit 2116
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