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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. EP21199471, filed on 09/28/2021.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 05/29/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
[0036] details “Referring back to FIG. 2 , at the step (302), the computing system (104) identifies the one or more cross-sectional regions of each of the blade (102) using the one or more infrared images (103) based on the boundary region. The boundary region is indicative of the transition from the first region with the laminar air flow to the second region with the turbulent air flow.”. Figure 2 details steps 201, 202, 203, and 204, thus it does not detail step 302, and the correct step label should be 202.
Appropriate correction is required.
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.
Claims 1-4 and 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Packer (US20220099067) in view of Lutz (ES2595049), Egedal (US20210048003), and Ito (US20120061966).
In regards to Claims 1 and 6, Packer teaches “at least one processor (104A) (processor – [0014]); and
a memory (104B) communicatively coupled to the at least one processor (104A), wherein the memory (104B) stores instructions for the at least one processor (104A) (“computer processor means, reconstructing an image from the data capture means into a digital image of the wind turbine using the computer processor means, wherein the method is provided with at least one algorithm means to compare and contrast various parts of the digital image, with corresponding parts of a predetermined image of a healthy wind turbine, to identify defects or damage to the wind turbine, and the extent of the defects and damage, so as to ascertain if replacement of the wind turbine blade is necessary” – [0014]; on board computer – [0032]; remote computer – [0033]; portable computer such as laptop, tablet, mobile phone – [0035]), which one execution causes the at least one processor (104A) to:
obtain one or more infrared images (103) of each blade (102) from the plurality of blades (102) of the wind turbine (101) (“the data capture device 1 can be a thermal imaging camera [i.e. infrared image]”…” Alternatively, specialist cameras or data capture devices affixed underneath or on another part of the helicopter, but which are rotatable, have tracking mechanisms, and can maintain a line of sight view of the wind turbine 2 , as the helicopter 3 moves around it, can be used. These would need to be robust enough and should be fitted with anti-vibration dampers or stabilizers to prevent vibrations caused by the helicopter's motion or noise created by the helicopter's rotors (or caused by the turbines that are being inspected) from disrupting the data capture process and affecting the quality of the data that is collected. FIG. 13 shows a top elevation of a data capture device 1 of one aspect of the invention. It has a guide or tracking device 10 which emits a tracking electromagnetic wave such as a laser 13 . The laser 13 is adapted to track the motion of the blade 4 , and “follow” the blade as it rotates, so that a first data capture instrument 11 , such as an optical camera, can take pictures of the section of the blade 4 that is being tracked by the tracking device 10 . In order to do this, the laser 13 must follow the blade 4 as it moves, and the position it points to, and when sufficient image data has been collected, the laser 13 must move along the blade, redirecting the first data capture instrument 11 to collect data from a different section of that same blade, until image data of the whole blade 4 has been collected. This way, the first data capture instrument 11 can obtain image data of the whole “face” of the blade as the laser 13 is pointing and moving along the blade. Once sufficient image data of one blade have been collected, the laser 13 moves to the next blade, and after sufficient image data of that next blade has been collected, to the next (for turbines with 3 blades), until the whole external face of the turbine blades has been captured. Note that ideally this process should take between 20-25 seconds to capture image data of one face of the wind turbine (40 to 50 seconds for the whole turbine), comprising three blades, however the more image data that is collected, the more accurate the reconstructed virtual image will be. Thus, it is possible to collect more image data although this will mean longer data collection time, and may affect the overall cost of the data acquisition phase. When the helicopter 3 moves to a position where it is facing the rear of the turbine ( FIG. 2), the image capture operation is repeated until image data of the whole rear of the turbine has been collected. Thus, the device is provided with object recognition capability to recognize and follow the blade as it rotates and capture image data of the frontal face, rear face and curved sections of each blade. A second data capture instrument 12 is also provided, which is adapted to capture the data of the whole blade 4 , so that feedback is provided to the first data capture instrument 11 and the tracking device 10 . Since the tip of the blade is typically rotating at 100 m/s, this feedback enables the data capture device 1 to know where each blade currently is, and which blade the first data capture instrument 11 should be assessing” – [0062]); and
estimate the energy production (107) for the wind turbine (101) (“Meshing using boundary conditions (domain, physical or periodic) can help determine the torque and output power of a turbine blade, however periodic boundary conditions are used when the physical geometry of interest and the expected pattern of the flow have a periodically repeating nature (see Fluent Inc., 2006; Bazilevs, et al., 2011 incorporated herein by reference).” – [0069]; “The Output power can be calculated by following formula: P=τ×ω where P is power for one blade, τ is torque for one blade ω is angular velocity (rotor angular speed). The torque for a healthy blade within CFX is found from the following formula: torque_y( )@airfoil, and is equal to −1.66774e+006 (N m). Thus, the output power of this model is equal to 1.9512558e+006 (Nm/s) for one blade. Full output power for the wind turbine can be calculated by the following formula: ΔP=P×n where ΔP is the total output power for the whole wind turbine, P is power for one blade and n is the number of the blades. The wind turbine has 3 blades therefore the output power for this wind turbine is equal to 5.8 MW” – [0071]).”
Packer is silent with regards to the language of “identify one or more cross-sectional regions (302) of each of the blade (102) using the one or more infrared images (103) based on a boundary region (301)”
Lutz teaches “identify one or more cross-sectional regions (302) of each of the blade (102) using the one or more infrared images (103) based on a boundary region (301) (Infrared thermography takes advantage of the fact that all objects at a temperature above absolute zero emit radiation in the infrared region, which is characteristic of the corresponding temperature. Therefore, for temperatures between 0 °C and 1000 °C, the maximum intensity is emitted at wavelengths between 3μm and 10μm. This radiation can be detected using special infrared cameras, resulting in an image of the surface temperature of the objects measured. - [0011]; Thermographic imaging is used particularly advantageously to determine the surface quality of the rotor blade. - [0022]; Figures 1-3 show thermographic images of the rotor blade with different angles of attack with Figure 4 being a thermogram of a rotor blade, with the Figures show the surface and areas – [0025]-[0026])”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer to incorporate the teaching of Lutz to utilize infrared thermography to determine regions of a rotor blade. By utilizing infrared thermography this is an improvement that yields predictable results in the inspection of rotor blades of wind turbines.
Packer in view of Lutz is silent with regards to the language of “identify one or more cross-sectional regions (302) of each of the blade (102) based on a boundary region (301), wherein the boundary region (301) is indicative of a transition from a first region with laminar air flow to a second region with a turbulent air flow; determine a plurality of polar values indicative of an aerodynamic profile for each of the one or more cross-sectional regions (302) based on one or more panel method based techniques and the boundary region (301)”
Egedal teaches “identify one or more cross-sectional regions (302) of each of the blade (102) based on a boundary region (301), wherein the boundary region (301) is indicative of a transition from a first region with laminar air flow to a second region with a turbulent air flow (“deriving the air flow characteristic based on the at least two temperature values” – [0023]; “the air flow characteristic is further based on a geometry of the surface of the blade” – [0025]; “the different positions at which the temperature values are measured have a substantially same radial position but different circumferential positions, in particular close to a leading edge of the blade and/or around an expected laminar to turbulent transition region” – [0028]; “Depending on the geometry of the surface of the rotor blade, the expected laminar to turbulent transition region may be located between for example 0% and 80% of a circumferential extent of the surface of the blade at the suction side and/or the pressure side. Thereby, providing temperature measurements in this expected transition region may enable to accurately determine the actual transition region or transition point which may of course depend on the radial position” – [0030]);
determine a plurality of polar values indicative of an aerodynamic profile for each of the one or more cross-sectional regions (302) based on one or more panel method based techniques and the boundary region (301) (“The determination of the location of the stagnation point and/or the determination of the stagnation temperature may be useful for estimating one or more parameters of the air flow characteristics, in particular the angle of attack and the free flow speed” – [0015]; “According to an embodiment of the present invention, the air flow characteristic comprises at least one of: direction of the air flow, in particular direction of the free air flow (i.e. not affected by the airfoil), in particular angle of attack, laminar to turbulent transition point of the (air foil affected) air flow, speed of the air flow, in particular speed the free air flow” – [0016]; “According to an embodiment of the present invention, the method comprises determining a location of a maximum difference between one of the measured temperature values and a temperature value of the ambient air; deriving a value of a direction of the air flow, in particular angle of attack as measured between the direction of the air flow and a chord line of the blade, based on the location and in particular at least on a geometry of the surface of the blade” – [0031]);”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer in view of Lutz to incorporate the teaching of Edegal to determine the region transition from laminar to turbulent air flow based on thermal data. By utilizing infrared thermography this is an improvement that yields predictable results in the inspection of rotor blades of wind turbines. By using the thermal data to determine the angel of attack with the laminar to turbulent transition point of a blade, this is an improvement that yields predictable results in the evaluation of the air flow over blades in a wind turbine.
Packer in view of Lutz and Edegal is silent with regards to the language of “estimate the energy production (107) for the wind turbine (101) based on one or more blade (102)-element momentum (BEM) based techniques using the plurality of polar values”
Ito teaches “estimate the energy production (107) for the wind turbine (101) based on one or more blade (102)-element momentum (BEM) based techniques using the plurality of polar values (power generation output of a wind power generator acquired in accordance with the blade element momentum theory – [0033]; variables and steps related to the equation detailed in [0035]-[0063], with [0056] detailing the inclusion of the attack angle)”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer in view of Lutz and Edegal to incorporate the teaching of Ito to utilize blade element momentum theory to evaluate the wind turbine. By utilizing blade element momentum theory, this is an improvement that yields predictable results in the evaluation of the output of wind turbines based on the parameters associated with the blades.
In regards to Claims 2 and 7, Packer in view of Lutz, Egegal, and Ito discloses the claimed invention as detailed above. Packer is silent with regards to the language of “wherein identifying one or more cross-sectional regions (302) comprises: determining the boundary region (301) of the blade (102) in the one or more infrared images (103) using one or more image processing techniques; and
segregating the blade (102) in the one or more infrared images (103) into the one or more cross-sectional regions (302) based on the boundary region (301) and pixel values associated with the one or more infrared images (103).”
Lutz further teaches “wherein identifying one or more cross-sectional regions (302) comprises: determining the boundary region (301) of the blade (102) in the one or more infrared images (103) using one or more image processing techniques (Figures 1-3 show thermographic images of the rotor blade with different angles of attack with Figure 4 being a thermogram of a rotor blade, with the Figures show the surface and areas – [0025]-[0026]);
segregating the blade (102) in the one or more infrared images (103) into the one or more cross-sectional regions (302) based on the boundary region (301) and pixel values associated with the one or more infrared images (103) (By precisely superimposing the pixels of both thermograms in their respective wavelength ranges, advantageous possibilities arise for identifying thermal differences both in the surface layer of the rotor blade and also in the interface between the surface layer and a base body. By taking measurements in both wavelength ranges, the absolute temperature of the respective rotor blade can be measured independently of emission coefficients, and it is also possible to cancel out the influence of changes in solar radiation - [0018]; Figures 1-3 show the regions in the thermographic image).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer in view of Lutz, Egegal, and Ito to incorporate the further teaching of Lutz to utilize infrared thermography to determine regions of a rotor blade. By utilizing infrared thermography this is an improvement that yields predictable results in the inspection of rotor blades of wind turbines.
In regards to Claims 3 and 8, Packer in view of Lutz, Egegal, and Ito discloses the claimed invention as detailed above. Packer further teaches “wherein determining the plurality of polar values comprises: providing each of the one or more cross-sectional regions (302), the boundary region (301), and one or more sectional co-ordinates as an input to the one or more panel method based techniques (“In analysing the data that is gathered by the data capture phase, the image data has to be imported into a software system that undertakes the reconstruction of the virtual image. This can be done on a computing system aboard the helicopter, or remotely during the data capture phase (using a conventional data transfer link that transfers the data from the helicopter to a remote location for analysis). Alternatively it can be done after the data capture phase, whereby the data is fed into a computing system for analysis. There are many data processing software packages on the market that can undertake such an exercise. Such software includes modularization, aero-hydro-servo-elastic tools, and other aerodynamics multi-physics engineering software and generally software simulation tools. One such software package is ANSYS CFX, a high-performance computational fluid dynamics (CFD) software package that can be employed to create virtual images of turbines, from hundreds of files of image data. In order to demonstrate the accuracy of these software packages, in as far as calculating values for a blade that are comparable or equal to the manufacturer specified values (within an acceptable error margin), one method uses meshing, whereby an IGES file created by a CAD program such as SolidWorks can be imported into ANSYS MESHING CFD grid generation system to generate the computational grids required for the CFD analyses. FIG. 3 shows a 3-D blade geometry model of an NREL 5 Mega Watts (MVV) offshore baseline wind turbine blade 4 generated by ANSYS CFD simulation software from a CAD drawing, showing airfoils cross sections 7 . As a form of background, the NREL 5 MW offshore baseline wind turbine blade properties are based on the values given in the report titled “Aeroelastic Modelling of the LMH64-5 Blade” by C. Lindenburg” – [0068]).”
Packer is silent with regards to the language of “determining the plurality of polar values for each of the one or more cross- sectional regions (302) based on an output of the one or more panel method based techniques.”
Egegal further teaches “determining the plurality of polar values for each of the one or more cross- sectional regions (302) based on an output of the one or more panel method based techniques (“The determination of the location of the stagnation point and/or the determination of the stagnation temperature may be useful for estimating one or more parameters of the air flow characteristics, in particular the angle of attack and the free flow speed” – [0015]; “According to an embodiment of the present invention, the air flow characteristic comprises at least one of: direction of the air flow, in particular direction of the free air flow (i.e. not affected by the airfoil), in particular angle of attack, laminar to turbulent transition point of the (air foil affected) air flow, speed of the air flow, in particular speed the free air flow” – [0016]; “According to an embodiment of the present invention, the method comprises determining a location of a maximum difference between one of the measured temperature values and a temperature value of the ambient air; deriving a value of a direction of the air flow, in particular angle of attack as measured between the direction of the air flow and a chord line of the blade, based on the location and in particular at least on a geometry of the surface of the blade” – [0031])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer in view of Lutz, Egegal, and Ito to incorporate the further teaching of Edegal to determine the region transition from laminar to turbulent air flow based on thermal data. By utilizing infrared thermography this is an improvement that yields predictable results in the inspection of rotor blades of wind turbines. By using the thermal data to determine the angel of attack with the laminar to turbulent transition point of a blade, this is an improvement that yields predictable results in the evaluation of the air flow over blades in a wind turbine.
In regards to Claims 4 and 9, Packer in view of Lutz, Egegal, and Ito discloses the claimed invention as detailed above. Packer is silent with regards to the language of “wherein estimating the energy production (107) comprises: providing the plurality of polar values associated with each of the one or more cross-sectional regions (302), a blade (102) geometry data, a wind turbine (101) operational data as an input to the one or more BEM based techniques; and estimating the energy production (107) for the wind turbine (101) based on an output of the one or more BEM based techniques.”
Ito further teaches “wherein estimating the energy production (107) comprises: providing the plurality of polar values associated with each of the one or more cross-sectional regions (302), a blade (102) geometry data, a wind turbine (101) operational data as an input to the one or more BEM based techniques; and estimating the energy production (107) for the wind turbine (101) based on an output of the one or more BEM based techniques (power generation output of a wind power generator acquired in accordance with the blade element momentum theory – [0033]; variables and steps related to the equation detailed in [0035]-[0063], [0038] details projected area of rotor, [0039] details radius of rotor, [0043] number of blades, [0046], distance of blade, [0040] power coefficient, with [0056] detailing the inclusion of the attack angle).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Packer in view of Lutz, Egegal, and Ito to incorporate the further teaching of Ito to utilize blade element momentum theory to evaluate the wind turbine. By utilizing blade element momentum theory, this is an improvement that yields predictable results in the evaluation of the output of wind turbines based on the parameters associated with the blades.
Allowable Subject Matter
Claims 5 and 10 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
In regards to Claims 5 and 10, Packer in view of Lutz, Egegal, and Ito discloses the claimed invention as detailed above. Packer further teaches “determining at least one of a damage area (106) of the blade (102), a type of the damage (105) on the blade (102) using an Artificial Intelligence (AI) model (“The computer processor means is adapted to run the algorithm means to compare and contrast various parts of the digital image, with corresponding parts of a predetermined image of a healthy wind turbine” – [0038]; “The computer processing means is adapted to identify defects or damage to the wind turbine blades, and the extent of the defect and damage” – [0039]; “The algorithm means may be adapted to interface with an Artificial Intelligence (AI) engine” - [0041];
Packer in view of Lutz, Egegal, and Ito are silent with regards to the language of “determining a deviation between the energy production (107) estimated for the wind turbine (101) and a pre-defined threshold value;
computing a reduction in the energy production (107) of the wind turbine (101) based on the deviation;
determining a financial loss (108) from the wind turbine (101) due to the reduction in the energy production (107);
determining one or more factors of the blade (102) in the wind turbine (101) affected by the damage, wherein the one or more factors comprises a load distribution associated with each of the blade (102) in the wind turbine (101), asymmetric load distributions between each of the blade (102) in the wind turbine (101), a noise emission value associated with the wind turbine (101), and a need for a control change in the wind turbine (101); and
identifying at least one of a type of a maintenance activity and a time duration for performing the maintenance activity for the damage area (106) of the blade (102) in the wind turbine (101) based on the financial loss (108) and the one or more factors.”
Conclusion
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/YOSSEF KORANG-BEHESHTI/Examiner, Art Unit 2857
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