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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Honda (US 2023/0366382 A1; related search report).
Regarding claim 1, Honda discloses state detection apparatus comprising:
an analyzer configured to detect a state of a detection target [[0002] abnormal states of a wind power generation device may be classified into wear states caused by wear of a sliding part such as a shaft, a speed-up gear, a generator, a yaw controller, or a pitch controller, and sudden states caused by a lightning strike or the like; [abstract] an analysis step (step S2) of performing a spectrogram analysis on the acoustic data recorded in the measurement step, on a frequency axis and in a temporal axis space as a temporal change in a frequency characteristic by using the short-time Fourier transform or the wavelet transform;], wherein
the analyzer is configured to
acquire, as acoustic information, a result of measuring sound generated at the detection target [[abstract] abnormality determination method for a wind power generation device includes: a measurement step (step Sl) of measuring sound emitted by the wind power generation device and recording acoustic data],
detect a state of the detection target based on a pattern included in an image representing a time variation of a frequency component of the acoustic information [[abstract] detection step (step S3) of detecting, from the analysis result in the analysis step, a signal component emitted from an abnormal portion of the wind power generation device in a time corresponding to rotation of the wind power generation device; [0018] abnormality is determined by measuring sound emitted by the wind power generation device, performing spectrogram analysis on the corresponding acoustic data on a frequency axis and in a temporal axis space as a temporal change in a frequency characteristic], and
output a result of detecting the state of the detection target [[abstract] a determination step (step SS) of determining that the wind power generation device is abnormal when the signal component detected in the detection step is greater than or equal to a certain threshold value.].
Regarding claim 2, Honda discloses the state detection apparatus according to claim 1, wherein the analyzer is configured to analyze a site of the detection target at which a sound represented by the pattern is generated [[0051] the determination result is displayed by the display device of the remote monitoring device 7, and is used for monitoring at a remote site or the like.].
Regarding claim 3, Honda teaches the state detection apparatus according to claim 2, wherein the analyzer is configured to output that a state of the site at which the sound represented by the pattern is generated is abnormal in a case in which a numerical value representing a difference between the pattern and a normal pattern is equal to or greater than a difference threshold [[abstract] determining that the wind power generation device is abnormal when the signal component detected in the detection step is greater than or equal to a certain threshold value.; [0017]; [0022]; [0023]].
Regarding claim 4, Honda teaches the state detection apparatus according to claim 3, wherein the analyzer is configured to detect the state of the detection target based on a database that associates the pattern with the state of the detection target, and generate the normal pattern based on acoustic information for which the state of the detection target is normal and register the normal pattern in the database [[0050] blade 3 of the wind power generation device 2 exhibits a difference between the wind noise in a normal operation state and the wind noise in an abnormal state as a result of damage due to deterioration, a lightning strike, a flying object, or the like. It is preferable that acoustic data is acquired for wind noise in an abnormal state, and that the threshold value of the signal component of a characteristic sound when a blade 3 is damaged is configured based on the acquired data and the knowledge and so forth of an expert engaged in performing maintenance work on the wind power generation device 2; [0057] first, the measurement unit 10 measures sound emitted by the wind power generation device 2 (step Sl). The measured sound is converted into a digital signal, and acoustic data is recorded in the recording unit 21.].
Regarding claim 5, Honda teaches a state detection system comprising: the state detection apparatus according to claim 1; and a sound collection apparatus configured to measure sound generated at a detection target and output a result of measurement to the state detection apparatus as acoustic information [[0037] an abnormality determination system 1 is a system that determines an abnormal state of the wind power generation device 2 based on the sound generated by the wind power generation device 2, and is equipped with a microphone 5 that measures the sound generated by the wind power generation device 2, and an abnormality determination device 6 that acquires the sound measured by the microphone 5 and determines the abnormal state of the wind power generation device 2].
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.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Honda (US 2023/0366382 A1) as applied to claim 5 above, and further in view of Nguyen (WO 2010/061255 A2).
Regarding claim 6, Honda does not explicitly teach and yet Nguyen teaches the state detection system according to claim 5, wherein the sound collection apparatus comprises a plurality of microphones, and is configured to generate acoustic information representing a component of sound arriving at the sound collection apparatus from a predetermined direction based on sound detected by each of the microphones [[pg. 5:1-10] patent the method employs image and acoustic monitoring inside a turbine, nacelle, tower, or hub, and processes the information to detect faults or anomalies during turbine operations. While the present invention employs noise measurements, Wobben's method only detect faults, it does not reduce noise; [pg. 9:5-25] pitch limits are used to prevent blade loads exceeding their fatigue limits. These limits depend on the properties of the blades and are determined analytically and experimentally. Noise sensor microphones or blade mounted pressure sensors have an output, which represents noise signals 147. The microphones 160, 161, 162, 163 are located on the ground 104 and/or microphones 164,165, 166, 167 are attached to the tower 102. The microphones should surround the tower to triangulate blade noise source and to also account for the changing yaw position of the turbine in response to changes in wind direction. A yaw angle sensor 124 is provided to generate a yaw angle 143.].
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention with a reasonable expectation of success, to substitute the microphone as taught by Honda with the microphone array as taught by Nguyen for detecting sounds from a running wind turbine blade so direction of the noise source may be determined by triangulation (Nguyen) [[pg. 9:10-20]].
Regarding claim 7, Honda does not explicitly teach and yet Nguyen teaches the state detection system according to claim 6, wherein the analyzer of the state detection apparatus is configured to acquire a plurality of pieces of acoustic information representing a component of sound arriving at the sound collection apparatus from each direction in a plurality of directions and detect the state of the detection target based on the plurality of pieces of acoustic information [[pg. 5:1-10] [pg. 9:5-25]].
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention with a reasonable expectation of success, to substitute the microphone as taught by Honda with the microphone array as taught by Nguyen for detecting sounds from a running wind turbine blade so direction of the noise source may be determined by triangulation (Nguyen) [[pg. 9:10-20]].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN D ARMSTRONG whose telephone number is (571)270-7339. The examiner can normally be reached M - F 9am-5pm.
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/JONATHAN D ARMSTRONG/ Examiner, Art Unit 3645
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