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 Rejections - 35 USC § 102
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) 1-5, 7, 9-12, 25-26 is/are rejected under 35 U.S.C. 102(a)(1) & 102(a)(2) as being anticipated by Frommann (US-20110356867).
In regards to claim 1, Frommann teaches a method for monitoring a machine state of a machine system, comprising: (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’)
- providing a time series of measured natural vibration spectra of the machine system, (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- detecting a deformation parameter in at least one monitoring time interval, wherein the deformation parameter is characteristic of a deviation of the measured natural vibration spectra from a reference natural vibration spectrum of at least one reference machine system, (abstract, para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’; fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
- detecting a noise parameter at the at least one monitoring time interval wherein the noise parameter is characteristic of a noise of the measured natural vibration spectra, and (para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’)
- determining the machine state from the deformation parameter and the noise parameter. (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’)
In regards to claim 2, Frommann teaches a method according to claim 1, (see claim rejection 1) wherein
- the deformation parameter comprises a distension of an amplitude-time function of the measured natural vibration spectra in an interval of vibration frequencies with respect to a reference amplitude-time function of a reference natural vibration spectrum of the at least one reference machine system in the interval of vibration frequencies. (para(s) [0115, 0142] fig(s) 5(A-B); fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
In regards to claim 3, Frommann teaches a method according to claim 1, (see claim rejection 1) wherein
- the noise parameter comprises a distension of an amplitude-time function of the measured natural vibration spectra in an interval of vibration frequencies with respect to a smoothed amplitude-time function of the measured natural vibration spectra in the interval of vibration frequencies. (para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’; para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’)
In regards to claim 4, Frommann teaches a method according to claim 1, (see claim rejection 1) wherein –
the detecting of the deformation parameter and the noise parameter and the determining of the machine state are repeated continuously at respective new monitoring time intervals with the providing of each current measured natural vibration spectrum of the time series of measured natural vibration spectra. (para(s) [0008-0013, 0028, 0032])
In regards to claim 5, Frommann teaches a method according to claim 1, (see claim rejection 1) wherein the providing of each natural vibration spectrum of the time series of the measured natural vibration spectra comprises: (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- measuring vibration raw data with a plurality of vibration sensors arranged for vibration measurement on the machine system, (para(s) [0032-0037])
- converting the vibration raw data into vibration spectra of the machine system, the vibration spectra including dynamically excited machine vibrations and natural vibrations of the machine system, and para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’)
- filtering the vibration spectra for eliminating the dynamically excited machine vibrations, whereby the measured natural vibration spectra are obtained. (para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’)
In regards to claim 7, Frommann teaches a method according to claim 1, (see claim rejection 1) wherein the step of providing of each natural vibration spectrum of the time series of the measured natural vibration spectra comprises: (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- measuring vibration raw data with a plurality of vibration sensors arranged for vibration measurement on the machine system while the machine system is in a state without dynamically excited machine vibrations, and (para(s) [0032-0037])
- converting the vibration raw data into vibration spectra of the machine system, the vibration spectra forming the measured natural vibration spectra. (para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’)
In regards to claim 9, Frommann teaches a method according to claim 1, (see claim rejection 1) further including
- determining a multidimensional evaluation parameter from the deformation parameter and the noise parameter, wherein the machine state is determined from the multidimensional evaluation parameter. (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b)) wherein the noise parameter is characteristic of a noise of the measured natural vibration spectra, and (para(s) [0046, 0054, 0080], ‘detects oscillations at various frequencies & applies filtering for unwanted noise.’ )
In regards to claim 10, Frommann teaches a method according to claim 9, (see claim rejection 9) wherein the multidimensional evaluation parameter comprises at least one of: (abstract)
- a position of the deformation parameter and the noise parameter, detected at a common monitoring time interval, in an at least two-dimensional evaluation field, and (para(s) [0115, 0142] fig(s) 5(A-B); fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
- an at least two-dimensional functional of the deformation parameter and the noise parameter, which are detected at a common monitoring time. (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b)) wherein the noise parameter is characteristic of a noise of the measured natural vibration spectra, and (para(s) [0046, 0054, 0080], ‘detects oscillations at various frequencies & applies filtering for unwanted noise.’ )
In regards to claim 11, Frommann teaches a method according to claim 9, (see claim rejection 9) wherein the determining of the machine condition comprises:
- classifying the evaluation parameter by a comparison with predetermined parameter ranges, and (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- outputting the machine state as a function of the result of the classifying. (abstract; para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
In regards to claim 12, Frommann teaches a method according to claim 1, (see claim rejeicon 1) wherein - the machine system comprises a wind power plant. (100, 102 fig(s) 1-2, ‘wind power installation’, ‘tower’)
In regards to claim 25, Frommann teaches a data processing apparatus comprising a computer device configured for carrying out the method according to claim 1. (para(s) [0084-0085], ‘the controller being designed to implement the method according to the disclosure’)
In regards to claim 26, Frommann teaches a computer program product comprising instructions which, when the computer program product is executed by a computer, cause the computer to execute the method according to claim 1. (para(s) [0084-0085], ‘the controller being designed to implement the method according to the disclosure’)
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.
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.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frommann (US-20110356867), in view of, Hameed et al., (‘Condition monitoring and fault detection of wind turbines and related algorithms: A review’ (2009))
In regards to claim 6, Frommann teaches a method according to claim 5, (see claim rejection 5)
Frommann teaches the use of filters to apply to unwanted noise in higher frequencies or lower frequencies (para [0047, 0139]), however, does not specifically disclose the use of a Kalman filter.
Frommann does not teach:
wherein
- the filtering of the vibration spectra comprises applying a Kalman filter to the vibration spectra.
Hameed teaches:
wherein
- the filtering of the vibration spectra comprises applying a Kalman filter to the vibration spectra. (pg 23 (ii); fig. 34 b)
It would have been obvious before the effective filing date of the invention for Fromman to provide the device & method for Monitoring a Machine State of a Machine System such as a wind power plant and the like to indicate malfunctions in the equipment.
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.
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.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frommann (US-20110356867), in view of, Hameed et al., (‘Condition monitoring and fault detection of wind turbines and related algorithms: A review’ (2009))
Frommann teaches:
In regards to claim 8, Frommann teaches a method according to claim 7, (see claim rejection 7)
Frommann teaches the use of filters to apply to unwanted noise in higher frequencies or lower frequencies (para [0047, 0139]), however, does not specifically disclose the use of a Kalman filter.
Frommann does not teach:
further including
- filtering the vibration spectra, which comprises applying a Kalman filter to the vibration spectra.
Hameed teaches:
further including
- filtering the vibration spectra, which comprises applying a Kalman filter to the vibration spectra. (pg 23 (ii); fig. 34 b)
It would have been obvious before the effective filing date of the invention for Fromman to provide the device & method for Monitoring a Machine State of a Machine System such as a wind power plant and the like to indicate malfunctions in the equipment.
Claim Rejections - 35 USC § 102
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) 13-17, 19, 21-24 is/are rejected under 35 U.S.C. 102(a)(1) & 102(a)(2) as being anticipated by Frommann (US-20110356867).
In regards to claim 13, Frommann teaches a monitoring apparatus, which is configured for monitoring a machine state of a machine system, comprising: (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’)
- a measuring device, which is configured for providing a time series of measured natural vibration spectra of the machine system, (para [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b); fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
- an analyzing device, which is configured for detecting a deformation parameter, which is characteristic of a deviation of the measured natural vibration spectra from at least one reference natural vibration spectrum of at least one reference machine system, in at least one monitoring time interval and for detecting a noise parameter, which is characteristic of a noise of the measured natural vibration spectra, in the at least one monitoring time interval, and (abstract, para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’; fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’; para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b); para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’)
- an evaluation device configured for determining the machine state from the deformation parameter and the noise parameter. (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’; para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’; fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
In regards to claim 14, Frommann teaches a monitoring apparatus according to claim 13, wherein (see claim rejection 13)
- the analyzing device is configured to detect, as the deformation parameter, (para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’) a distension of an amplitude-time function of the measured natural vibration spectra in an interval of vibration frequencies with respect to a reference amplitude-time function of the reference natural vibration spectra of the at least one reference machine system in the interval of vibration frequencies. (para(s) [0115, 0142] fig(s) 5(A-B); fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
In regards to claim 15, Frommann teaches a monitoring apparatus according to claim 13, wherein (see claim rejection 13)
- the analyzing device is configured to detect, as the noise parameter, a distension of an amplitude-time function of the measured natural vibration spectra in an interval of vibration frequencies from a smoothed amplitude-time function of the measured natural vibration spectra in the interval of vibration frequencies. (para(s) [0115, 0142] fig(s) 5(A-B); fig(s) 4-5, ‘correlations of oscillations an ambient parameters’; 520, 530, 550 fig. 5b, ‘unusual oscillation’, ‘threshold’, ‘extremal values’)
In regards to claim 16, Frommann teaches a monitoring apparatus according to claim 13, wherein (see claim rejection 13)
- the analyzing device is configured to repeat the detecting of the deformation parameter and the noise parameter and the determining of the machine state continuously at respective new monitoring time intervals with the providing of each current measured natural vibration spectrum of the time series of measured natural vibration spectra. (para(s) [0008-0013, 0028, 0032, 0079]; fig(s) 5(a-b))
In regards to claim 17, Frommann teaches a monitoring apparatus according to claim 13, further comprising: (see claim rejection 13)
- a plurality of vibration sensors of the measuring device arranged to measure vibration raw data on the machine system, (para(s) [0032-0037])
- a conversion device configured for converting the vibration raw data into a vibration spectrum of the machine system, wherein the vibration spectrum contains dynamically excited machine vibrations and natural vibrations of the machine system, and (para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’; para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- a filter device configured for filtering the vibration spectrum for eliminating the dynamically excited machine vibrations, wherein the measured natural vibration spectrum is obtained. . (para [0139], ‘To eliminate wind-excited oscillations, there can preferably be high-pass filtering with a cut-off frequency of approximately 0.05 Hz, for example.’)
In regards to claim 19, Frommann teaches a monitoring apparatus according to claim 13, further comprising: (see claim rejection 13)
- a plurality of vibration sensors arranged to measure vibration raw data on the machine system while the machine system is in a state without dynamically excited machine vibrations, and para(s) [0032-0037])
- a conversion device configured for converting the vibration raw data into a vibration spectrum of the machine system, the vibration spectrum forming the measured natural vibration spectrum. (para(s) [0008, 0010, 0014, 0032, 0099-0101]; ‘unusual oscillation results & ambient parameter comparisons to measured values’)
In regards to claim 21, Frommann teaches a monitoring apparatus according to claim 13, further comprising: (see claim rejection 13)
- an evaluation device configured for determining a multi-dimensional evaluation parameter from the deformation parameter and the noise parameter and for determining the machine state from the evaluation parameter. , (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b)) wherein the noise parameter is characteristic of a noise of the measured natural vibration spectra, and (para(s) [0046, 0054, 0080], ‘detects oscillations at various frequencies & applies filtering for unwanted noise.’ )
In regards to claim 22, Frommann teaches a monitoring apparatus according to claim 21, further comprising: (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’)
- a classification device configured for classifying the evaluation parameter by a comparison with predetermined parameter ranges, and (para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
- an output device configured for outputting the machine state depending on the result of the classifying. (abstract; para(s) [0008, 0030, 0051, 0057, 0077, 0079]; fig(s) 5(a-b))
In regards to claim 23, Frommann teaches a monitoring apparatus according to claim 13, further comprising at least one of:
- memory-programmable logic controllers, (para(s) [0084-0085], ‘the controller being designed to implement the method according to the disclosure’)
- programmable logic controllers, and - an FGPA unit. (para(s) [0084-0085], ‘the controller being designed to implement the method according to the disclosure’)
In regards to claim 24, Frommann teaches a monitoring apparatus according to claim 13, wherein (see claim rejection 13)
- the monitoring apparatus is configured for monitoring a machine state of a wind power plant. (abstract; para [0008]; fig(s) 1-2, ‘wind power installation’)
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.
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.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frommann (US-20110356867), in view of, Hameed et al., (‘Condition monitoring and fault detection of wind turbines and related algorithms: A review’ (2009))
In regards to claim 18, Frommann teaches a method according to claim 17, (see claim rejection 17)
Frommann teaches the use of filters to apply to unwanted noise in higher frequencies or lower frequencies (para [0047, 0139]), however, does not specifically disclose the use of a Kalman filter.
Frommann does not teach:
wherein
- the filtering of the vibration spectra comprises applying a Kalman filter to the vibration spectra.
Hameed teaches:
wherein
- the filtering of the vibration spectra comprises applying a Kalman filter to the vibration spectra. (pg 23 (ii); fig. 34 b)
It would have been obvious before the effective filing date of the invention for Fromman to provide the device & method for Monitoring a Machine State of a Machine System such as a wind power plant and the like to indicate malfunctions in the equipment.
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.
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.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frommann (US-20110356867), in view of, Hameed et al., (‘Condition monitoring and fault detection of wind turbines and related algorithms: A review’ (2009))
Frommann teaches:
In regards to claim 20, Frommann teaches a method according to claim 19, (see claim rejection 7)
Frommann teaches the use of filters to apply to unwanted noise in higher frequencies or lower frequencies (para [0047, 0139]), however, does not specifically disclose the use of a Kalman filter
Frommann does not teach:
further including
- filtering the vibration spectra, which comprises applying a Kalman filter to the vibration spectra.
Hameed teaches:
further including
- filtering the vibration spectra, which comprises applying a Kalman filter to the vibration spectra. (pg 23 (ii); fig. 34 b)
It would have been obvious before the effective filing date of the invention for Fromman to provide the device & method for Monitoring a Machine State of a Machine System such as a wind power plant and the like to indicate malfunctions in the equipment.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The references cited Zhang (CN-119782780), He (CN-118585851), Leigh (US-11543325) and Theratil (US 2020/0040914) references further describe a method & device for monitoring a machine state as described by the claims.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN C BUTLER whose telephone number is (571)270-3973. The examiner can normally be reached 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephanie E Bloss can be reached at (571)272-3555. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.C.B/Examiner, Art Unit 2852
/STEPHANIE E BLOSS/Supervisory Primary Examiner, Art Unit 2852
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