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 .
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.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7 December 2022 by the applicant has been considered and is included in the file.
Response to Amendment
Claims 1-9 have been canceled, and new claims 10-29 have been introduced by applicant’s amendments filed 7 December 2022.
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 10-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. An analysis, following the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 RPEG) is included below.
101 Analysis
Step 1:
Claim 10 is directed to a method for determining wind speed components. Therefore, claim 1 is within at least one of the four statutory categories.
Step 2A, Prong I:
Regarding Prong I of Step 2A, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas, per the 2019 Revised Patent Subject Matter Eligibility Guidance:a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 10 includes limitations that are directed to an abstract idea (emphasized below in bold):
A method for determining wind speed components using a LiDAR sensor, the LiDAR sensor being oriented vertically to perform measurements in at least one horizontal measurement plane, each horizontal measurement plane comprising at least two measurement points, the method comprising:
a) acquiring measurement signals from the LiDAR sensor for each measurement point of the at least one horizontal measurement plane;
b) determining an average wind direction and an average wind speed in the at least one horizontal measurement plane by reconstructing wind from the measurement signals;
c) constructing in the at least one horizontal measurement plane a projection line which is perpendicular to the determined average wind direction;
d) determining a time shift between each measurement point of the at least one horizontal measurement plane and the constructed projection line by using the determined average wind speed;
e) for each measurement point of the at least one horizontal measurement plane, determining a corrected measurement signal, the corrected measurement signal corresponding to a measurement signal occurring at a time before acquiring the measurement signals of each measurement point equal to the time shift;
and f) determining the wind speed components in the at least one horizontal measurement plane by use of the corrected measurement signals.
The examiner submits that the emphasized limitation(s) constitute the abstract idea of a mathematical concept and/or mental processes, as the limitations under their broadest reasonable interpretation cover mathematical steps which manipulate velocity data sets to obtain a corrected value, which may additionally be performed as a mental process. Therefore, the claim recites at least one judicial exception.
Step 2A, Prong II:
Regarding Prong II of Step 2A, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. Per the 2019 RPEG, this must include determination of whether any additional elements in the claim (beyond the abstract idea) integrate the exception into a practical application. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
Claim 10 of the current application includes the following additional limitations beyond the abstract idea(s):
the LiDAR sensor being oriented vertically to perform measurements in at least one horizontal measurement plane, each horizontal measurement plane comprising at least two measurement points, the method comprising:
a) acquiring measurement signals from the LiDAR sensor for each measurement point of the at least one horizontal measurement plane.
The identified additional limitations do not integrate the previously noted abstract idea(s) into a practical application for the following reasons:
“Acquiring measurement signals…” and “…each horizontal measurement plane comprising at least two measurement points” are both recited at a high level of generality (i.e. as a general means of gathering LiDAR data for use in the evaluating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
The “LiDAR sensor being oriented vertically…” merely describes how to generally “apply” the otherwise mental processes and/or mathematical concepts of the method of operation and data analysis in a generic or general-purpose LIDAR environment.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, the limitation(s) do not add anything that is not already present when looking at the elements taken individually. For example, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, utilize the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05).
Step 2B:
Regarding step 2B as outlined in the 2019 Guidance and as discussed above, independent claim 10 does not include additional elements that are sufficient to amount to significantly more than the judicial exception, either individually or as an ordered combination, and does not integrate the abstract idea into a practical application. The presented limitations of “Acquiring measurement signals…”, “…each horizontal measurement plane comprising at least two measurement points” and “LiDAR sensor being oriented vertically…” have been determined by the examiner to be insignificant extra-solution activities or general descriptions of how to “apply” the method.
Any conclusion in Step 2A where an additional element(s) is determined to be insignificant extra-solution activity should be re-evaluated in Step 2B to find whether the additional element(s) are more than what is well-known, routine, or conventional activity in the field.
The additional limitations of “Acquiring measurement signals…” and “…each horizontal measurement plane comprising at least two measurement points” are well-understood, routine and conventional activities in the art of LIDAR and LIDAR data analysis because it is well known that data sets such as point clouds of distance and/or velocity data obtained will have more than a single data point for a specific distance from a device. Acquiring of measurement signals is a fundamental part of LiDAR device use, and the specification makes no mention of specific, non-standard collection methods. Additionally, the specification (Background of the Invention, pgs. 2 and 3) indicates that “a LiDAR” can be used to perform the method, and when they are vertically oriented such as the limitation “LiDAR sensor being oriented vertically…” it is known conventionally as “ground-based LiDAR”. The section further notes prior patent applications which describe this method of operation, and does not provide any indication that this component is required to be a specific LiDAR device or requiring it to be anything other than a conventional LiDAR (see MPEP 2106.05(d)(II)).
Independent claim 10 is not patent eligible as it does not amount to significantly more than the judicial exception.
Dependent claims 11-29 do not recite further limitations which may cause the claim(s) to be determined to be patent eligible. The limitations of the dependent claims are directed towards additional aspects of the judicial exception and/or are well understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application because the limitations within the dependent claims can be further classified as abstract ideas. For example, dependent claim 11 includes the limitation “wherein the projection line is constructed as a straight line perpendicular to the wind direction passing through a barycenter of the measurement points of the at least one measurement plane or passing through a measurement point”, which only moves where a projection line is created, and thus can be classified as a mathematical concept and/or a mental process because determining a point to place a line may be done without substantial, specialized processing. Other dependent claims, such as 16- 19, determine a mathematical formula for the time shift, where the equation is solely based on a 2-Dimensional version of a rotated velocity vector and a kinematic equation. Thus, dependent claims 11-29 are not patent eligible under the same rationale as was discussed regarding the rejection of independent claim 10.
Therefore, claims 10-29 is/are rejected under 35 USC § 101.
Claim Rejections - 35 USC § 103
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) 10-12, and 26-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300) in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1).
Regarding claim 10, Suomi teaches a method for determining wind speed components using a LiDAR sensor, the LiDAR sensor being oriented vertically to perform measurements in at least one horizontal measurement plane, each horizontal measurement plane comprising at least two measurement points (pg. 13, FIg. 4, where LIDAR is aimed upwards and measurement planes include at least two points), the method comprising:
a) acquiring measurement signals from the LiDAR sensor for each measurement point of the at least one horizontal measurement plane (pgs. 12-13, where LIDAR collect data for multiple data points which include distance, coordinates, and wind velocity vectors)
b) determining an average wind direction and an average wind speed in the at least one horizontal measurement plane by reconstructing wind from the measurement signals (pg. 14, where a moving-average of horizontal wind speed is calculated based on LIDAR data);
d) determining a time shift between each measurement point of the at least one horizontal measurement plane and the constructed projection line by using the determined average wind speed (pg. 16, where a time shift between two points, utilizing wind speed, can be determined from the kinematic equation x=Ut).
e) for each measurement point of the at least one horizontal measurement plane, determining a corrected measurement signal, the corrected measurement signal corresponding to a measurement signal occurring at a time before acquiring the measurement signals of each measurement point equal to the time shift (pg. 14, where a correction to each point may be implemented to correct for bias in data)
and f) determining the wind speed components in the at least one horizontal measurement plane by use of the corrected measurement signals (pg. 14, where a correction to each data point may be implemented to correct for bias in data to determine updated velocity data).
Suomi is silent on setting a projection line perpendicular to the wind’s velocity vector.
Tsadka teaches a system for monitoring wind characteristics utilizing LIDAR, where a perpendicular is set to the direction of the wind vector in a plane ([0061], [0070]).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to modify Suomi to incorporate the teachings of Tsadka to set a reference or projection plane perpendicular to the direction of average wind velocity with a reasonable expectation of success. As Tsadka notes, this plane is generally set because it is the preferred orientation of a wind turbine, which allows for maximizing the amount of electricity which may be generated ([0061]). Using this perpendicular as the offset for data correction would have a predictable result of determining a mathematical difference between an optimal orientation of a turbine, and the current average wind velocity in a plane.
Regarding claim 11, Suomi as modified above teaches a method as claimed in claim 10, wherein
the projection line is constructed as a straight line perpendicular to the wind direction passing through a barycenter of the measurement points of the at least one measurement plane or passing through a measurement point of the at least one measurement plane (pg. 13, Fig. 4, where Doppler lidar measures multiple points within a plane (in this example, 5 points) and average wind direction u-vector is focused on a measurement point within a plane.)
Regarding claim 12, Suomi as modified above teaches a method as claimed in claim 11, wherein
the projection line is constructed by a line perpendicular to the wind direction passing through the measurement point of the at least one measurement plane which was most recently measured (pg. 13 - pg. 14, where lidar scanning techniques include frequently updating scans of area separated by known durations, where data analysis is routinely updated by newest data set).
Regarding claim 26, Suomi as modified above teaches a method as claimed in claim 10, wherein
the average wind direction and the average wind speed (v-) are determined for a fixed duration time window or a sliding time window, with the fixed duration time window ranging between 1 min and 1 h (Pg. 15, Fig. 6, where sample windows were taken of LIDAR Doppler data in 10-minute intervals).
Regarding claim 27, Suomi as modified above teaches a method as claimed in claim 26, wherein
the time window ranges between 5 min and 30 min (Pg. 15, Fig. 6, where sample windows were taken of LIDAR Doppler data in 10-minute intervals).
Claim(s) 13-15, 25 and 28-29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300), in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1) and further in view of Bayon et al. (hereinafter Bayon, US 20150145253 A1).
Regarding claim 13, Suomi as modified above teaches the method as claimed in claim 10.
Suomi is silent on the use of a wind uniformity hypothesis in the data analysis.
Bayon teaches a method for wind turbine monitoring, where an estimator of the wind speed at the rotor uses wind reconstruction which is based on a hypothesis of wind uniformity in the at least one measurement plane ([0080] - [0082], where unitary coherence hypothesis is used to assign uniform wind vectors on a measurement plane)
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of Bayon to utilize a wind uniformity hypothesis within the method of wind velocity measurement with a reasonable expectation of success. Use of wind uniformity models as noted by Bayon allow for simplification in mathematical analysis of velocity datasets by setting specific values equal to known values (such as an average or zero in a given direction) ([0078] – [0083]) and these approximations would lead to a predictable result in reducing mathematical efforts required to analyze the velocity data collected.
Claim 14 is similarly rejected to claim 13.
Claim 15 is similarly rejected to claim 13.
Regarding claim 25, Suomi as modified above teaches the method as claimed in claim 10.
Suomi is silent on the wind speed component equation.
Bayon teaches a method for wind turbine monitoring, where an estimator of the wind speed at the rotor is constructed by use of vector and matrix representation, where
w
x
(
t
)
w
y
(
t
)
w
z
(
t
)
=
L
1
N
+
m
1
(
t
-
δ
t
1
)
m
2
(
t
-
δ
t
2
)
m
N
(
t
-
δ
t
N
)
with
w
x
,
w
y
,
w
z
being wind speed components,
m
1
,
m
2
,
…
,
m
N
being measurement signals of measurement points 1 to N, δt being a time shift of measurement points 1 to N, and
L
1
N
+
being a geometric reconstruction matrix of the wind speed components ([0104] - [0118]; where the reconstruction of wind velocity vectors at time t is related to measurement values before delay and a reconstruction matrix).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of Bayon to utilize transformation matrix which utilizes the time shift between two points in two reference frames within the method of wind velocity measurement with a reasonable expectation of success. Use of matrices to reconstruct, or apply correction values to vectors (such as a wind velocity vector) is a well-known mathematical process of matrix and vector math.
Regarding claim 28, Suomi as modified above teaches the method as claimed in claim 10.
Suomi is silent on the use of a frozen turbulence hypothesis in the data analysis.
Bayon teaches a method for wind turbine monitoring, where an estimator of the wind speed at the rotor is constructed by use of a frozen turbulence hypothesis with a vertical component of the speed being considered zero ([0077] - [0082], where frozen turbulence hypothesis is utilized).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of Bayon to utilize a frozen turbulence hypothesis within the method of wind velocity measurement with a reasonable expectation of success. Use of frozen turbulence models and unitary coherence hypothesis as noted by Bayon, allow for simplification in mathematical analysis of velocity datasets by setting specific values equal to known values (such as an average or zero in a given direction) ([0078] – [0083]) and these approximations would lead to a predictable result in reducing mathematical efforts required to analyze the velocity data collected.
Claim 29 is similarly rejected to claim 28.
Claim(s) 16-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300) in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1), and further in view of “Rotation of velocity vectors in Cartesian Coordinates” on Mathematics Stack Exchange (hereinafter “MSE”, Mathematics Stack Exchange via Wayback Machine, snapshot 20150921).
Regarding claim 16, Suomi as modified above teaches a method as claimed in claim 10.
Suomi is silent on the mathematical nature of the time shift associated between the original wind vector and the projection reference frame.
MSE teaches a time shift δt of each measurement point i may be determined with the formula:
δ
t
i
=
x
i
cos
Ψ
-
y
i
sin
Ψ
v
-
with
x
i
and
y
i
being the coordinates of the measurement point i in a frame associated with the at least one measurement plane,
v
-
being the determined average wind speed, and Ψ being an angle formed between a y axis of the at least one measurement plane and the projection line (Where a time between two points with a known velocity, in two dimensions in Cartesian space which has been rotated by an angle Psi will maintain the form of the vector version of a kinematic equation
t
=
r
→
v
-
).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of MSE to utilize vector representations of the kinematic equations, with reference frame rotation between a velocity in Cartesian coordinates and a reference frame (in this instance perpendicular to the wind velocity) matrix which with a reasonable expectation of success. Use of two- and three-dimensional vector notation, kinematic equation, and changing of reference frames is a well-known mathematical process of matrix and vector math which is utilized in physics via the kinematic equations, and use here would have a predicable result of representing wind velocity and changes in reference frames in more than a single dimension.
Claim 17 is similarly rejected to claim 16.
Claim 18 is similarly rejected to claim 16.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300), in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1) and Bayon et al. (hereinafter Bayon, US 20150145253 A1), and further in view of “Rotation of velocity vectors in Cartesian Coordinates” on Mathematics Stack Exchange (hereinafter “MSE”, Mathematics Stack Exchange via Wayback Machine, snapshot 20150921).
Regarding claim 19, Suomi as modified above teaches a method as claimed in claim 13.
Suomi is silent on the mathematical nature of the time shift associated between the original wind vector and the projection reference frame.
MSE teaches a time shift δt of each measurement point i may be determined with the formula:
δ
t
i
=
x
i
cos
Ψ
-
y
i
sin
Ψ
v
-
with
x
i
and
y
i
being the coordinates of the measurement point i in a frame associated with the at least one measurement plane,
v
-
being the determined average wind speed, and Ψ being an angle formed between a y axis of the at least one measurement plane and the projection line (Where a time between two points with a known velocity, in two dimensions in Cartesian space which has been rotated by an angle Psi will maintain the form of the vector version of a kinematic equation
t
=
r
→
v
-
).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of MSE to utilize vector representations of the kinematic equations, with reference frame rotation between a velocity in Cartesian coordinates and a reference frame (in this instance perpendicular to the wind velocity) matrix with a reasonable expectation of success. Use of two- and three-dimensional vector notation, kinematic equation, and changing of reference frames is a well-known mathematical process of matrix and vector math which is utilized in physics via the kinematic equations, and use here would have a predicable result of representing wind velocity and changes in reference frames in more than a single dimension.
Claim(s) 20-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300) in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1) and further in view of Krumm (US 20060047472 A1).
Regarding claim 20, Suomi as modified above teaches a method as claimed in claim 10.
Suomi is silent on the use of interpolation in the dataset analysis.
Krumm teaches a method for measuring position and movement of objects, where an interpolation of prior and subsequent measurement signals of a measurement point being considered ([0052] - [0053]; where linear interpolation between a prior and later data set may be utilized to approximate a missing data point).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of Krumm to utilize interpolation within the data analysis of wind velocities with a reasonable expectation of success. As Krumm notes ([0006] - [0009]) interpolation in camera and LIDAR distance information reduces calculation time and difficulty in situations where data points may be missed, and therefore reduces resources necessary for the calculations present.
Claim 21 is similarly rejected to claim 20.
Claim 22 is similarly rejected to claim 20.
Claim(s) 23-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suomi et al. (hereinafter Suomi, “Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities”, MDPI Sensors 2018, 18, 1300), in view of Tsadka et al. (hereinafter Tsadka, US 20110106324 A1) and Bayon et al. (hereinafter Bayon, US 20150145253 A1), and further in view of Krumm (US 20060047472 A1).
Regarding claim 23, Suomi as modified above teaches a method as claimed in claim 13.
Suomi is silent on the use of interpolation in the dataset analysis.
Krumm teaches a method for measuring position and movement of objects, where an interpolation of prior and subsequent measurement signals of a measurement point being considered ([0052] - [0053]; where linear interpolation between a prior and later data set may be utilized to approximate a missing data point).
Therefore, to one of ordinary skill in the art before the effective filing date of the claimed invention, it would have been obvious prima facie to further modify Suomi to incorporate the teachings of Krumm to utilize interpolation within the data analysis of wind velocities with a reasonable expectation of success. As Krumm notes ([0006] - [0009]) interpolation in camera and LIDAR distance information reduces calculation time and difficulty in situations where data points may be missed, and therefore reduces resources necessary for the calculations present.
Claim 24 is similarly rejected to claim 23.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kara Richter whose telephone number is (571)272-2763. The examiner can normally be reached Monday - Thursday, 8A-5P EST, Fridays are variable.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Hodge can be reached at (571) 272-2097. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.M.R./Examiner, Art Unit 3645
/ROBERT W HODGE/Supervisory Patent Examiner, Art Unit 3645