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 .
This Office Action is in response to Applicant’s amendment and request for continued examination filed 03/05/2026. Claims 1, 3-10, and 12-19 are currently pending in this application.
Claim Rejections - 35 USC § 101
Applicant’s amendment to claim 9 overcomes the previous rejection under 35 U.S.C. 101. The rejection is hereby withdrawn.
Claim Rejections - 35 USC § 112
Applicant’s amendments to claims 3 and 12 overcomes the previous rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. The rejection is hereby withdrawn.
Claim 19 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “high-energy” in claim 19 is a relative term which renders the claim indefinite. The term “high-energy” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For example, Paragraph [0011] of the Applicant’s specification recites that the frequency band should preferably be selected to exclude high-energy content acoustic signals, which refers to excluding frequencies containing a high level of background noise. Additionally, Paragraph [0038] of the Applicant’s specification defines the selection of specific frequency bands, but does not provide a nexus as to the relationship between the selected frequency band and a “high-energy” content.
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 1, 3-10, and 12-19 are rejected under 35 U.S.C. 103 as being unpatentable over Alberto et al. (U.S. 2018/0074112 A1) in view of Schripsema et al. (U.S. 2014/0226242 A1).
Claim 1, Alberto teaches:
A method for detection of electrical abnormalities in association with electrical equipment (Alberto, Paragraph [0025], The system determines potential electrical arcs, i.e. electrical abnormalities, in electrical system 100.), the method comprises:
- registering, by an acoustic sensor device (Alberto, Fig. 1: 102), acoustic signals reflecting sound of the electrical equipment during normal operation thereof (Alberto, Paragraph [0025], The acoustic sensor 102 senses acoustic waves emitted from the forming of an arc. The acoustic energy is generally in specific ranges of frequency bands, e.g. 80-120 kHz or 65-90 kHz (see Alberto, Paragraph [0028]).);
- comparing energy contents of different frequencies of the acoustic signals registered (Alberto, Paragraph [0029], The power or amplitude level, i.e. the energy contents, of the outputted acoustic signal 104 is compared with a threshold. The acoustic energy is correlated with specific frequency bands (see Alberto, Paragraph [0028]).);
- determining at least one frequency band (∆fA, ∆fB) to be monitored during monitoring of the electrical equipment as a frequency band having a relatively low energy content during normal operation, based on the comparison (Alberto, Paragraph [0028], Different frequency bands may be used for monitoring the presence of electrical arcs, wherein periods in which no electrical arcs are detected have relatively low energy content.);
- determining an energy content threshold value (Eth_A, Eth_B) for acoustic signals within the at least one frequency band (∆fA, ∆fB) to be monitored, based on the acoustic signals registered within the at least one frequency band (Alberto, Paragraph [0029], A power or amplitude threshold is used to determine whether a sensed acoustic power or amplitude should be frequency domain analyzed by the processing circuit 110.);
- detecting, among acoustic signals registered by the acoustic sensor device during monitoring of the electrical equipment, an acoustic pulse (P) within the at least one frequency band (∆fA, ∆fB) (Alberto, Paragraphs [0028-0029], The circuit 118 determines that a power or amplitude exceeds a threshold, which is functionally equivalent to an acoustic pulse.), and
- classifying the acoustic pulse (P) as an electrical abnormality associated with the electrical equipment when an energy content of the acoustic pulse (P) exceeds the energy content threshold value (Eth_A, Eth_B) (Alberto, Paragraphs [0028-0029], When the power or amplitude exceeds a threshold, the processing circuit 110 determines whether an arc is present, which would then be classified as an electrical abnormality and generates an alarm to inform a user (see Alberto, Paragraph [0027]).).
Alberto does not specifically teach:
Which sound constitutes background noise during subsequent monitoring of the electrical equipment, and
a calibration process.
However, the analog circuit 118 and the processing circuit 110 are capable of analyzing power and amplitude, and perform a frequency domain analysis, respectively. Additionally, the system further knows the frequency bands of acoustic waves generated by an electric arc (see Alberto, Paragraph [0047]). Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to have a calibration process for both programming the analog circuit 118 and the processing circuit 110 to perform their respective tasks, as well as assigning the specific frequency domains (see Alberto, Paragraph [0028]) as well as establishing sampling rates (see Alberto, Paragraph [0032]). Such a modification would ensure that the system of Alberto is capable of performing its intended functions.
Schripsema teaches:
Which sound constitutes background noise during subsequent monitoring of the electrical equipment (Schripsema, Paragraphs [0034-0036], Background noise that is sensed by each sensor can be determined during isolated operation of each finger 44, and a baseline value is determined based on the sensed background noise. The process of determining the baseline value is functionally equivalent to a calibration process.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the system in Alberto by integrating the teaching of a noise detection assembly, as taught by Schripsema.
The motivation would be to determine a malfunction of equipment due to an electrical arc (see Schripsema, Paragraph [0044]) in order to reduce or prevent subsequent damage to the equipment (see Schripsema, Paragraph [0003]).
Claim 3, Alberto in view of Schripsema further teaches:
The method of claim 1, wherein each of the at least one frequency band (∆fA, ∆fB) has a bandwidth of at most 50 Hz (Alberto, Paragraph [0028], The frequency ranges cited do not overlap with 100Hz, 75Hz, or 50 Hz, however, Alberto cites that these ranges are examples of ranges in which acoustic energy peaks. Thus, it would have been obvious to one of ordinary skill in the art, at the time of filing, to select lower ranges, as a matter of engineering choice. Such a modification would not change the principal operation of the system, as a whole, and would yield predictable results. Additionally, the terms “preferably” of the claim render the limitations as optional, i.e. preferred values but not required.).
Claim 4, Alberto in view of Schripsema further teaches:
The method of claim 1, further comprising the steps of:
- determining a pulse duration time (∆tp) of the acoustic pulse (P) (Alberto, Paragraphs [0026-0027], The output signal 108 is a time-domain signal, which shows the time variation of the amplitude of the acoustic waves, i.e. the amplitude over time.), and
- classifying the acoustic pulse (P) as an electrical abnormality only when the pulse duration time (∆tp) is below a maximum pulse duration threshold value (Alberto, Paragraphs [0026-0027] and [0032], The analog signal 104 from sensor 102 is a continuous-time signal (see Alberto, Paragraph [0025]). The determination of the presence of an arc is limited based on the sampled digital signals 108, which includes a specified number of samples (see Alberto, Paragraph [0032]). Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to determine the presence of an arc over a time period that is less than the maximum number of samples, which covers a limited time period. For example, 200 samples taken at a rate of 1 per second would yield 200 seconds worth of samples. It would have been obvious to one of ordinary skill in the art, at the time of filing, to set the maximum value at 200 or above, such that the number of samples would be sufficient enough to measure the presence of an arc. This would ensure that the system is able to perform to its intended function.).
Claim 5, Alberto in view of Schripsema further teaches:
The method of claim 1, further comprising the steps of:
- determining a measure indicative of a rate of increase of energy content of the acoustic pulse (P) (Alberto, Paragraph [0029], A measured power or amplitude that is above a threshold value is indicative of a rate of increase of power or amplitude.), and
- classifying the acoustic pulse (P) as an electrical abnormality only when the measure indicative of the rate of increase exceeds a set threshold value (Alberto, Paragraphs [0029] and [0032], A set number p of samples of digital output signal 108 of converter 106 are saved in an FIFO-type memory, which includes the values of acoustic signals leading up to an arc. Therefore, when an arc is determined, the samples p would indicate a rate of increase in acoustic signals greater than 0. It is noted that “the measure of the rate of increase” is interpreted as “the measure indicative of a rate of increase” for consistency.).
Claim 6, Alberto in view of Schripsema further teaches:
The method of any of claim 1, further comprising the steps of:
- determining a measure indicative of a rate of decrease of energy content of the acoustic pulse (P) (Alberto, Paragraph [0029], A measured power or amplitude that is not above a threshold value is indicative of a rate of decrease of power or amplitude of a previously measured power or amplitude above the threshold.), and
- classifying the acoustic pulse (P) as an electrical abnormality only when the measure indicative of the rate of decrease exceeds a set threshold value (Alberto, Paragraphs [0029] and [0032], A set number p of samples of digital output signal 108 of converter 106 are saved in an FIFO-type memory, which includes the values of acoustic signals leading up to an arc. It would have been obvious to one of ordinary skill in the art, at the time of filing, for the same FIFO-type memory to be capable of storing samples after a measured arc. Therefore, after an arc is determined, the samples p would indicate a rate of decrease in acoustic signals greater than 0. It is noted that “the measure of the rate of decrease” is interpreted as “the measure indicative of a rate of decrease” for consistency.).
Claim 7, Alberto in view of Schripsema further teaches:
The method of claim 1, further comprising the step of:
- generating an alarm signal and/or automatically switching off the electrical equipment in response to classifying the acoustic pulse (P) as an electrical abnormality (Alberto, Paragraph [0027]).
Claim 8, Alberto in view of Schripsema further teaches:
The method of claim 1, wherein the sound of the electrical equipment is picked up by the acoustic sensor device from a mounting rail for electrical equipment onto which the acoustic sensor device is mounted, an electrical cable onto which the acoustic sensor device is mounted, or an electrical connector into which the acoustic sensor device is integrated (Alberto, Paragraph [0025], The sensor 102 is arranged in physical contact with an electric conductor, which is functionally equivalent to an electrical connector into which the acoustic sensor device is integrated.).
Claim 9, Alberto teaches:
A non-transitory computer-readable storage medium comprising a non-volatile memory configured to store computer-readable instructions which, when executed by at least one processor of a system (Alberto, Paragraph [0027]) for detection of electrical abnormalities in association with electrical equipment (Alberto, Paragraph [0025], The system determines potential electrical arcs, i.e. electrical abnormalities, in electrical system 100.), causes the at least one processor to perform the steps of:
- receiving acoustic signals reflecting sound of the electrical equipment during normal operation thereof, registered by an acoustic sensor device that is operatively coupled to the at least one processor (Alberto, Paragraph [0025], The acoustic sensor 102 senses acoustic waves emitted from the forming of an arc. The acoustic energy is generally in specific ranges of frequency bands, e.g. 80-120 kHz or 65-90 kHz (see Alberto, Paragraph [0028]).);
- comparing energy contents of different frequencies of the acoustic signals registered (Alberto, Paragraph [0029], The power or amplitude level, i.e. the energy contents, of the outputted acoustic signal 104 is compared with a threshold. The acoustic energy is correlated with specific frequency bands (see Alberto, Paragraph [0028]).);
- determining at least one frequency band (∆fA, ∆fB) to be monitored during monitoring of the electrical equipment as a frequency band having a relatively low energy content during normal operation, based on the comparison (Alberto, Paragraph [0028], Different frequency bands may be used for monitoring the presence of electrical arcs, wherein periods in which no electrical arcs are detected have relatively low energy content.);
- determining an energy content threshold value (Eth_A, Eth_B) for acoustic signals within the at least one frequency band (∆fA, ∆fB) to be monitored, based on the acoustic signals registered within the at least one frequency band (∆fA, ∆fB) (Alberto, Paragraph [0029], A power or amplitude threshold is used to determine whether a sensed acoustic power or amplitude should be frequency domain analyzed by the processing circuit 110.);
- detecting, among the acoustic signals registered by the acoustic sensor device during monitoring of the electrical equipment, an acoustic pulse (P) within the at least one frequency band (∆fA, ∆fB) (Alberto, Paragraphs [0028-0029], The circuit 118 determines that a power or amplitude exceeds a threshold, which is functionally equivalent to an acoustic pulse.), and
- classifying the acoustic pulse (P) as an electrical abnormality associated with the electrical equipment when an energy content of the acoustic pulse (P) exceeds the energy content threshold value (Eth_A, Eth_B) (Alberto, Paragraphs [0028-0029], When the power or amplitude exceeds a threshold, the processing circuit 110 determines whether an arc is present, which would then be classified as an electrical abnormality and generates an alarm to inform a user (see Alberto, Paragraph [0027]).).
Alberto does not specifically teach:
Which sound constitutes background noise during subsequent monitoring of the electrical equipment, and
a calibration process.
However, the analog circuit 118 and the processing circuit 110 are capable of analyzing power and amplitude, and perform a frequency domain analysis, respectively. Additionally, the system further knows the frequency bands of acoustic waves generated by an electric arc (see Alberto, Paragraph [0047]). Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to have a calibration process for both programming the analog circuit 118 and the processing circuit 110 to perform their respective tasks, as well as assigning the specific frequency domains (see Alberto, Paragraph [0028]) as well as establishing sampling rates (see Alberto, Paragraph [0032]). Such a modification would ensure that the system of Alberto is capable of performing its intended functions.
Schripsema teaches:
Which sound constitutes background noise during subsequent monitoring of the electrical equipment (Schripsema, Paragraphs [0034-0036], Background noise that is sensed by each sensor can be determined during isolated operation of each finger 44, and a baseline value is determined based on the sensed background noise. The process of determining the baseline value is functionally equivalent to a calibration process.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the system in Alberto by integrating the teaching of a noise detection assembly, as taught by Schripsema.
The motivation would be to determine a malfunction of equipment due to an electrical arc (see Schripsema, Paragraph [0044]) in order to reduce or prevent subsequent damage to the equipment (see Schripsema, Paragraph [0003]).
Claim 10, Alberto teaches:
A system for detection of electrical abnormalities in association with electrical equipment, the system comprises an acoustic sensor device for registering acoustic signals reflecting sound of the electrical equipment (Alberto, Paragraph [0025], The system determines potential electrical arcs, i.e. electrical abnormalities, in electrical system 100.), and at least one processor operatively coupled to the acoustic sensor device (Alberto, Paragraph [0027]) and configured to:
- receive acoustic signals registered by the acoustic sensor device (Alberto, Paragraph [0025], The acoustic sensor 102 senses acoustic waves emitted from the forming of an arc. The acoustic energy is generally in specific ranges of frequency bands, e.g. 80-120 kHz or 65-90 kHz (see Alberto, Paragraph [0028]).);
- compare energy contents of different frequencies of the acoustic signals registered by the acoustic sensor device (Alberto, Paragraph [0029], The power or amplitude level, i.e. the energy contents, of the outputted acoustic signal 104 is compared with a threshold. The acoustic energy is correlated with specific frequency bands (see Alberto, Paragraph [0028]).);
- determine at least one frequency band (∆fA, ∆fB) to be monitored during monitoring of the electrical equipment as a frequency band having a relatively low energy content during normal operation, based on the comparison (Alberto, Paragraph [0028], Different frequency bands may be used for monitoring the presence of electrical arcs, wherein periods in which no electrical arcs are detected have relatively low energy content.);
- determine an energy content threshold value (Eth_A, Eth_B) for acoustic signals within the at least one frequency band (∆fA, ∆fB) to be monitored, based on the acoustic signals registered within the at least one frequency band (Alberto, Paragraph [0029], A power or amplitude threshold is used to determine whether a sensed acoustic power or amplitude should be frequency domain analyzed by the processing circuit 110.);
- detect, among the acoustic signals registered by the acoustic sensor device during monitoring of the electrical equipment, an acoustic pulse (P) within the at least one frequency band (∆fA, ∆fB) (Alberto, Paragraphs [0028-0029], The circuit 118 determines that a power or amplitude exceeds a threshold, which is functionally equivalent to an acoustic pulse.), and
- classify the acoustic pulse (P) as an electrical abnormality associated with the electrical equipment {100} when an energy content of the acoustic pulse (P) exceeds the energy content threshold value (Eth_A, Eth_B) (Alberto, Paragraphs [0028-0029], When the power or amplitude exceeds a threshold, the processing circuit 110 determines whether an arc is present, which would then be classified as an electrical abnormality and generates an alarm to inform a user (see Alberto, Paragraph [0027]).).
Alberto does not specifically teach:
Said acoustic signals constituting background noise during subsequent monitoring of the electrical equipment, and
a calibration process.
However, the analog circuit 118 and the processing circuit 110 are capable of analyzing power and amplitude, and perform a frequency domain analysis, respectively. Additionally, the system further knows the frequency bands of acoustic waves generated by an electric arc (see Alberto, Paragraph [0047]). Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to have a calibration process for both programming the analog circuit 118 and the processing circuit 110 to perform their respective tasks, as well as assigning the specific frequency domains (see Alberto, Paragraph [0028]) as well as establishing sampling rates (see Alberto, Paragraph [0032]). Such a modification would ensure that the system of Alberto is capable of performing its intended functions.
Schripsema teaches:
Said acoustic signals constituting background noise during subsequent monitoring of the electrical equipment (Schripsema, Paragraphs [0034-0036], Background noise that is sensed by each sensor can be determined during isolated operation of each finger 44, and a baseline value is determined based on the sensed background noise. The process of determining the baseline value is functionally equivalent to a calibration process.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the system in Alberto by integrating the teaching of a noise detection assembly, as taught by Schripsema.
The motivation would be to determine a malfunction of equipment due to an electrical arc (see Schripsema, Paragraph [0044]) in order to reduce or prevent subsequent damage to the equipment (see Schripsema, Paragraph [0003]).
Claim 12, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein each of the at least one frequency band (∆fA, ∆fB) has a bandwidth of at most 50 Hz (Alberto, Paragraph [0028], The frequency ranges cited do not overlap with 100Hz, 75Hz, or 50 Hz, however, Alberto cites that these ranges are examples of ranges in which acoustic energy peaks. Thus, it would have been obvious to one of ordinary skill in the art, at the time of filing, to select lower ranges, as a matter of engineering choice. Such a modification would not change the principal operation of the system, as a whole, and would yield predictable results. Additionally, the terms “preferably” of the claim render the limitations as optional, i.e. preferred values but not required.).
Claim 13, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein the at least one processor is configured to:
- determining a pulse duration time (∆tp) of the acoustic pulse (P) (Alberto, Paragraphs [0026-0027], The output signal 108 is a time-domain signal, which shows the time variation of the amplitude of the acoustic waves, i.e. the amplitude over time.), and
- classify the acoustic pulse (P) as an electrical abnormality only when the pulse duration time (∆tp) is below a maximum pulse duration threshold value (Alberto, Paragraphs [0026-0027] and [0032], The analog signal 104 from sensor 102 is a continuous-time signal (see Alberto, Paragraph [0025]). The determination of the presence of an arc is limited based on the sampled digital signals 108, which includes a specified number of samples (see Alberto, Paragraph [0032]). Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to determine the presence of an arc over a time period that is less than the maximum number of samples, which covers a limited time period. For example, 200 samples taken at a rate of 1 per second would yield 200 seconds worth of samples. It would have been obvious to one of ordinary skill in the art, at the time of filing, to set the maximum value at 200 or above, such that the number of samples would be sufficient enough to measure the presence of an arc. This would ensure that the system is able to perform to its intended function.).
Claim 14, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein the at least one processor is configured to:
- determine a measure indicative of a rate of increase of energy content of the acoustic pulse (P) (Alberto, Paragraph [0029], A measured power or amplitude that is above a threshold value is indicative of a rate of increase of power or amplitude.), and
- classify the acoustic pulse (P) as an electrical abnormality only when the measure indicative of the rate of increase exceeds a set threshold value (Alberto, Paragraphs [0029] and [0032], A set number p of samples of digital output signal 108 of converter 106 are saved in an FIFO-type memory, which includes the values of acoustic signals leading up to an arc. Therefore, when an arc is determined, the samples p would indicate a rate of increase in acoustic signals greater than 0. It is noted that “the measure of the rate of increase” is interpreted as “the measure indicative of a rate of increase” for consistency.).
Claim 15, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein the at least one processor is configured to:
- determine a measure indicative of a rate of decrease of energy content of the acoustic pulse (P) (Alberto, Paragraph [0029], A measured power or amplitude that is not above a threshold value is indicative of a rate of decrease of power or amplitude of a previously measured power or amplitude above the threshold.), and
- classify the acoustic pulse (P) as an electrical abnormality only when the measure indicative of the rate of decrease exceeds a set threshold value (Alberto, Paragraph [0032], A set number p of samples of digital output signal 108 of converter 106 are saved in an FIFO-type memory, which includes the values of acoustic signals leading up to an arc. It would have been obvious to one of ordinary skill in the art, at the time of filing, for the same FIFO-type memory to be capable of storing samples after a measured arc. Therefore, after an arc is determined, the samples p would indicate a rate of decrease in acoustic signals greater than 0. It is noted that “the measure of the rate of decrease” is interpreted as “the measure indicative of a rate of decrease” for consistency.).
Claim 16, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein the at least one processor is configured to generate an alarm signal and/or to automatically switch off the electrical equipment in response to classifying the acoustic signal (P) as an electrical abnormality (Alberto, Paragraph [0027]).
Claim 17, Alberto in view of Schripsema further teaches:
The system of claim 10, wherein the acoustic sensor device is configured to pick up the sound of the electrical equipment from a mounting rail for electrical equipment onto which the acoustic sensor device is mounted, an electrical cable onto which the acoustic sensor device is mounted, or an electrical connector onto or into which the acoustic sensor device is mounted or integrated (Alberto, Paragraph [0025], The sensor 102 is arranged in physical contact with an electric conductor, which is functionally equivalent to an electrical connector into which the acoustic sensor device is integrated.).
Claim 18, Alberto in view of Schripsema further teaches:
The method of claim 1, wherein the energy content threshold value (Eth_A, Eth_B) is set to a value above an energy content of said background noise (Alberto, Paragraph [0029], In the combination of Alberto in view of Schripsema, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the threshold to be set based on the incorporated background noise. Such a modification would ensure the combination, as a whole, would operate for its intended function and yield predictable results.).
Claim 19, Alberto in view of Schripsema further teaches:
The method of claim 1, wherein the at least one frequency band to be monitored is selected to exclude high-energy content of said background noise (Schripsema, Paragraph [0044], The signal from the noise detection assembly is compared to a threshold, wherein the value compared to the threshold is based on an average. It would have been obvious to one of ordinary skill in the art, at the time of filing, for the averaging of the detected noise to effectively exclude high-energy content of the background noise, because the microprocessor only compares average sensed values instead of potentially “high” values.).
Response to Arguments
Applicant's arguments filed 03/05/2026 have been fully considered but they are moot in view of the new grounds of rejection, necessitated by the Applicant’s amendment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES J YANG whose telephone number is (571)270-5170. The examiner can normally be reached 9:30am-6:00p M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, BRIAN ZIMMERMAN can be reached at (571) 272-3059. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JAMES J YANG/ Primary Examiner, Art Unit 2686