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 § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4 and 6-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Peter et al. (BE 1026844) in view of Thomas (DE 102011077363).
Regarding to claims 1, 6-7:
Peter et al. discloses a method for determining the service life of a switching device (FIG. 3, element 1000), the method comprising the steps of:
providing a neural network having at least two input variables and an output variable (FIG. 6 shows a neural network with inputs and outputs), wherein the inputs include a continuous variable and a discrete variable (FIG. 6: The neural network takes the continuous current ISpulse as an input. Beside, the neural network also takes into account the usage history of the switching device or the number of switching cycles that have already been carried out (page 3, paragraphs 1-5). This usage history or the number of switching cycles is considered as a discrete variable);
determining at least a current variable, which represents a current flowing through the switching device, and a switching device state variable (FIG. 6 shows at least the ISpule that reads on the claimed current variable because it is the measured current flowing through the switch 1000. The usage history or the number of switching cycles that have already been carried out of the switching device indicates the state variable of the switching device);
inputting the current variable as an input variable into the neural network (FIG. 6: At least the current ISpulse is inputted to the neural network. The neural network also takes into account the usage history of the switching device or the number of switching cycles (page 3, paragraphs 1-5). This usage history or the number of switching cycles is considered as a discrete variable); and
determining a remaining service life of the switching device by means of the neural network (page 9, 3rd-4th paragraphs: One of possible output portions of the artificial neural network is the expected remaining life of the switch).
Peter et al. however is silent wherein the usage history or the number of switching cycles of the switching device state variable represents sticking or jammed or fused switching device.
Thomas teaches that for a contactor switch, due to the aging history and the switching cycles have been carried out, the contacts may get the local melting and thereby stick (page 4, 7th paragraph).
Therefore, it would have been obvious for one having ordinary skill in the art at the time of the filing date to modify Peter’s determination the remaining service life to also be based on the switch condition such as sticking due to long-term aging of the contacts as taught by Thomas.
Peter also discloses the following claims:
Regarding to claim 2: wherein the current variable is a continuous variable, and the switching device state variable is a discrete variable (FIG. 6: The ISpule is the current flowing through the switch while the switch is in the contact state; as a result, the ISpule is continuous. Furthermore, the current state of the switch corresponds to the number of the switching cycles; for example, 1,000 switching cycles, 10,000 switching cycles, and 40,000 switching cycles (page 3), so they are discrete variables).
Regarding to claim 3: wherein the neural network is trained by means of monitored learning (page 2, lines 25-32: The artificial neural network is operated based on training data used in a learning process).
Regarding to claim 4: wherein at least the method steps are carried out in a cloud-based device (It is well-known that training a machine learning model or a neural network is performed on a cloud-based service provided by major technology companies. Please see Mohassel et al. (US 2021/0209247), paragraph [0002]).
Regarding to claims 8, 10-11: wherein the discrete variable is representative of two states: an open state or a closed state (FIG. 6: The neural network takes the contact voltage (UKontakt) as an input, wherein the high/low voltage of the contact voltage corresponds to the ON/OFF of the switch).
Regarding to claim 9: further comprising: i) inputting a service life variable as an input variable into the neural network, and ii) comparing the service life variable with the output variable prior to determining the remaining service life of the switching device by means of the neural network (FIG. 6 and page 9, paragraphs 1-9: The neural network determines the remaining service life of the switching device based on the aging history and the number of switching cycles that have already been carried out (service life variable) in comparison to the data in the training phase of the neural network).
Response to Arguments
Applicant's arguments filed 2/3/26 have been fully considered but they are not persuasive. Please see the rejection above for newly citations and explanations.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAM S NGUYEN whose telephone number is (571)272-2151.
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/LAM S NGUYEN/ Primary Examiner, Art Unit 2853
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