DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claim 9 objected to because of the following informalities: in the recited “a annular mist flow the state of the fluid is” it is unclear as to what is being referred to here as the state of the fluid is? Appropriate correction is required.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8, & 10-16 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Frisby [PG. Pub. No.: US 2013/0068035 A1].
With regards to claims 1 & 17, Frisby discloses an estimation apparatus comprising: an acquisition unit that acquires state data including intensity data of at least one frequency band (frequency band, ¶0022) related to a detection signal detected (¶0029) by a vortex flow meter for a fluid (vortex shedding flow meter, ¶0039); a state determination estimation unit that estimates a state of the fluid based on the state data acquired by the acquisition unit (a flow velocity calculation unit 32 for calculating (or estimating), ¶0039); a fluid quality estimation unit that estimates, from the intensity data, at least either of a liquid amount or dryness related to the fluid according to the state of the fluid estimated by the state determination estimation unit (phase composition/dryness determination unit, ¶0029-0030); and an output unit that outputs at least either of the liquid amount or the dryness estimated by the fluid quality estimation unit (an outputting unit for outputting the phase composition and/or dryness parameter. The outputting unit may comprise a display for displaying the phase composition and/or dryness parameter and/or a transmitter for transmitting the phase composition and/or dryness parameter and database 46 would contain a "three-dimensional" look-up table correlating flow velocity, energy parameter and temperature with dryness parameters, ¶0024 & ¶0051).
With regards to claim 2, Frisby discloses wherein the acquisition unit acquires a digital signal representing the intensity data of at least one frequency band from the vortex flow meter (¶0039).
With regards to claim 3, Frisby discloses wherein the acquisition unit acquires the state data including at least one of a flow speed (flow velocity), a temperature (temperature), a pressure (pressure), a viscosity, concentration, or density measured for the fluid, and the fluid quality estimation unit estimates, from the intensity data acquired by the acquisition unit, and the state data including at least one of the flow speed (flow velocity), the temperature, the pressure, the viscosity, the concentration, or the density measured for the fluid, at least either of the liquid amount or dryness related to the fluid, according to a state of the fluid estimated by the state determination estimation unit (¶0051).
With regards to claim 4, Frisby discloses wherein the vortex flow meter outputs, to a computing apparatus, a pulse signal representing a vortex frequency of the detection signal generated based on the intensity data of at least one frequency band, and the acquisition unit acquires the state data including at least one of the pressure, the flow speed, a volumetric flow rate, the density, or a mass flow rate of the fluid calculated based on the pulse signal by the computing apparatus (¶0051).
With regards to claim 5, Frisby discloses wherein the acquisition unit acquires the state data including intensity data of a plurality of frequency bands related to a detection signal of the fluid detected by the vortex flow meter, and the fluid quality estimation unit estimates at least either of the liquid amount or dryness related to the fluid from the intensity data of the plurality of frequency bands (a range of frequencies, ¶0045).
With regards to claim 6, Frisby discloses wherein the fluid quality estimation unit estimates, from a maximum value among the intensity data of the plurality of frequency bands or a combined value of intensity data of the plurality of frequency bands, at least either of the liquid amount or dryness related to the fluid (a range of frequencies, ¶0045).
With regards to claim 7, Frisby discloses wherein the acquisition unit acquires the intensity data that is normalized, and the fluid quality estimation unit estimates, from the intensity data that is normalized, at least either of the liquid amount or dryness related to the fluid (¶0045).
With regards to claim 8, Frisby discloses further comprising: a selection unit that selects, from a plurality of computations, a computation corresponding to the state of the fluid estimated by the state determination estimation unit, wherein the fluid quality estimation unit estimates, from the intensity data acquired by acquisition unit, at least either of the liquid amount or dryness related to the fluid through the computation selected by the selection unit (¶0045-0046).
With regards to claim 10, Frisby discloses wherein the state determination estimation unit: determines whether the state of the fluid is wet vapor based on the state data acquired by the acquisition unit (Fig. 1, ¶0038); and estimates which of a stratified flow, a stratified wavy flow, or an annular mist flow the state of the fluid is based on the state data acquired by the acquisition unit (0039), when the state of the fluid is determined to be wet vapor (wet steam, ¶0042).
With regards to claim 11, Frisby discloses wherein the state determination estimation unit estimates (¶0047), based on the state data acquired by the acquisition unit, the state of the fluid by using a first model for estimating the state of the fluid from the state data (46, database takes two values, ¶0047).
With regards to claim 12, Frisby discloses wherein the selection unit selects (42, vibration signal analysis unit, ¶0047), from a plurality of second models for estimating, from intensity data of at least one frequency band related to a detection signal of the fluid, at least either of a liquid amount or dryness related to the fluid (determining unit 44 determines the steam dryness value from the data in the look-up table and displays this dryness value, ¶0047), a second model corresponding to the state of the fluid estimated by the state determination estimation unit according to the state of the fluid, and the fluid quality estimation unit estimates, from the intensity data, at least either of the liquid amount or dryness related to the fluid by using the second model selected by the selection unit (database 46 contains a look-up table that contains reference or calibration data that correlates a range of flow velocities and energy parameters with steam dryness values, ¶0047).
With regards to claim 13, Frisby discloses further comprising: a learning processing unit that generates the second model for each state of the fluid (¶0049).
With regards to claim 14, Frisby discloses a learning apparatus comprising; a learning processing unit that generates, from intensity data of at least one frequency band related to a detection signal detected by a vortex flow meter for a fluid (¶0045), a second model for estimating at least either of a liquid amount or dryness related to the fluid for each state of the fluid (¶0047-0049).
With regards to claim 15, Frisby discloses a method comprising: acquiring, by a computer (determining unit 44, ¶0047), state data including intensity data of at least one frequency band related to a detection signal detected by a vortex flow meter for a fluid (determines the steam dryness value from the data in the look-up table and displays this dryness value, ¶0047); estimating, by the computer, a state of the fluid based on the state data acquired ((phase composition/dryness determination unit, ¶0029-0030); estimating, by the computer from the intensity data, at least either of a liquid amount or dryness related to the fluid according to the state of the fluid estimated(phase composition/dryness determination unit, ¶0029-0030); and outputting, by the computer, at least either of the liquid amount or the dryness estimated (¶0047).
With regards to claim 16, Frisby discloses a learning method comprising: generating, by a computer (determining unit 44, ¶0047) from intensity data of at least one frequency band (frequency band, ¶0022) related to a detection signal (¶0029) detected by a vortex flow meter for a fluid (vortex shedding flow meter, ¶0039), a second model for estimating at least either of a liquid amount or dryness related to the fluid for each state of the fluid (an outputting unit for outputting the phase composition and/or dryness parameter. The outputting unit may comprise a display for displaying the phase composition and/or dryness parameter and/or a transmitter for transmitting the phase composition and/or dryness parameter and database 46 would contain a "three-dimensional" look-up table correlating flow velocity, energy parameter and temperature with dryness parameters, ¶0024 & ¶0051).
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.
Claim(s) 17 & 18 is/are rejected under 35 U.S.C. 102(a)(1)) as anticipated by Frisby [PG. Pub. No.: US 2013/0068035 A1] or, in the alternative, under 35 U.S.C. 103 as obvious over Sun NPL: IOP Publishing, Measurement Science and Technology, 23 November 2007,
With regards to claims 17 & 18, Frisby discloses (44, determination unit functioning as a processor/microprocessor which includes programs for a computer to function and operate as its intended use, ¶0047) an acquisition unit that acquires state data including intensity data of at least one frequency band (frequency band, ¶0022) related to a detection signal detected (0029) by a vortex flow meter for a fluid (vortex shedding flow meter, ¶0039); a state determination estimation unit that estimates a state of the fluid based on the state data acquired by the acquisition unit (a flow velocity calculation unit 32 for calculating (or estimating), ¶0039); a fluid quality estimation unit that estimates, from the intensity data, at least either of a liquid amount or dryness related to the fluid according to the state of the fluid estimated by the state determination estimation unit (phase composition/dryness determination unit, ¶0029-0030); and an output unit that outputs at least either of the liquid amount or the dryness estimated by the fluid quality estimation unit (an outputting unit for outputting the phase composition and/or dryness parameter. The output unit may comprise a display for displaying the phase composition and/or dryness parameter and/or a transmitter for transmitting the phase composition and/or dryness parameter and database 46 would contain a "three-dimensional" look-up table correlating flow velocity, energy parameter and temperature with dryness parameters, ¶0024 & ¶0051). However, it is silent on non-transitory computer readable medium having recorded thereon a program that causes a computer to function as.
Sun teaches of gas-liquid two – phase flow pattern based on frequency domain analysis of vortex flowmeter signals having a Neural networks (program as a non-transitory computer readable medium) in approximating the percentage of energy the signal has in a given frequency band (page 4-7).
At the time of the invention, it would have been obvious to one ordinary skilled art to provide a neural network as a non-transitory computer readable medium based upon the teachings of Sun. When modifying Frisby one would have readily concluded to provide the neural network to predict flow patterns, adopt inputs successfully, (ABSTRACT, page 1).
Conclusion
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/FRANCIS C GRAY/ Primary Examiner, Art Unit 2852
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