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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/16/2025 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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, 5, 11, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Feldman et al. (US 2015/0226683; “Feldman”) in view of Pulice (USPN 5,485,083; of record).
Regarding claim 1, Feldman discloses a method for sensing a property of a fluid (¶ [0017]), comprising: a) generating an AC voltage signal at a frequency (¶ [0061]) b) exciting a driving element of a sensing unit (17) by the voltage signal (¶ [0059]) c) bringing a sensor head (7) comprising a sensing element (7a) provided as a probe extending from the sensor head (7) into contact with the fluid (¶ [0019]; “[t]he first sensor unit may be configured and operable for measuring the first physical parameter of the liquid while interacting with a flow of the liquid (i.e. while being in contact with/immersed in the examined liquid”, ¶ [0060]; “the sensor unit 7a may be configured as a small inductive probe (e.g., an epoxy resin-coated inductive probe)”), and sensing a complex impedance of the fluid using the sensing element (7a) (¶¶ [0034], [0038-[0039, [0063]), wherein the sensing element (7a) comprises one or more resistance temperature detectors (7c) and one or more inductive coils (11c, 12c), and wherein sensing the complex impedance of the fluid comprises sensing the inductive impedance of the fluid with the one or more resistance temperature detectors (7c) and the one or more inductive coils (11c, 12c) (¶¶ [0034], [0063], [0104]), d) receiving a sensed signal from the sensing element (7a) (¶ [0052]), e) performing signal processing on the sensed signal (¶¶ [0051], [0105]) and f) repeating steps a-e across a range of frequencies to obtain a fingerprint of the fluid (¶¶ [0019], [0091]).
While Feldman’s sensing system is embodied as a submersible probe, Feldman does not explicitly disclose the inductance coil being disposed around a fluid pipeline.
However, disposing an inductance coil around a fluid pipeline is well-known in the art of submersible type probes. For example Pulice teaches in figure 1 an inductance probe (100) in which the inductance coil (160) is disposed around a fluid pipeline (110) (col. 3, lines 13-41; Examiner notes as is typical in the art, the “pipeline” is formed from a hollowed-out portion of the probe body onto which the coil is disposed).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to engineer Feldman’s probe in such a manner that the inductance coil is disposed around a fluid pipeline (e.g. formed by a hollow portion of the probe body) for the purpose of better stabilizing the components and having a structure on which to mount wiring.
Regarding claim 2, Feldman discloses the range of frequencies comprises 10 Hz to 100 kHz (¶¶ [0034], [0062]) but fails to disclose 0.04 Hz.
However, Feldman teaches the need for low-frequency impedance measurements (¶ [0026]; “proper selection of the frequency range of said relatively low-frequency field facilitates determination of the electrical conductivity of the examined liquid”) thus establishing frequency as a result-effective variable. Furthermore, the claimed range and the disclosed range are sufficiently close that a prima facie case of obviousness exists. See MPEP §2144.05 (“[i]n the case where the claimed ranges "overlap or lie inside ranges disclosed by the prior art" a prima facie case of obviousness exists. In re Wertheim, 541 F.2d 257, 191 USPQ 90 (CCPA 1976); In re Woodruff, 919 F.2d 1575, 16 USPQ2d 1934 (Fed. Cir. 1990)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to optimize the low-frequency range to extend to the claimed frequency range as appropriate for the fluid under test in order to effectively minimizes a dielectric losses component of the complex dielectric permittivity of the liquid and thus ensure that the electrical (voltage) response of the liquid mainly characterizes the electric conductivity of the liquid (¶ [0026]).
Regarding claim 3, Feldman discloses storing the fingerprint in a database (¶ [0107]).
Regarding claim 5, Feldman discloses the fingerprint is one or more of an electrochemical fingerprint and an electromagnetic induction fingerprint (¶¶ [0091], [0107]).
Regarding claim 11, Feldman discloses the sensing element (7a) includes one inductive coil (13) and an amplifier (34a), and wherein sensing the complex impedance of the fluid comprises obtaining an inductive coil signal from the one inductive coil (13) and amplifying the inductive coil signal with the amplifier (34a) (see figures 2F & 2G ¶ [0094]).
Regarding claim 18, Feldman discloses exciting the driving element of the sensing unit (7a) by the voltage signal comprises: with a sine wave generator clocked by a microcontroller (8), exciting the fluid by a sequence of sine wave voltage signals, each of the sine wave voltage signals having a known frequency (see figure 2H, ¶¶ [0091], [0095]).
Claims 4, 6, 7, 8 are rejected under 35 U.S.C. 103 as being unpatentable over Feldman and Pulice, and further in view of Ballantine et al. (US 2019/0317152; “Ballantine”).
Regarding claim 4, Feldman as modified by Pulice disclose all the limitations of claim 3 on which this claim depends.
Feldman discloses storing a fluid’s impedance spectrum in a database but is silent to training an artificial intelligence model.
In the same field of endeavor, Ballantine teaches creating fingerprints for a sample using impedance spectroscopy and then storing the impedance plots in a database (¶ [0030]). Ballantine also generally teaches training an artificial intelligence model based on stored impedance spectra in a database ([i]n an embodiment, correlations of impedance responses of various types of batteries to charge state and/or various failure modes may be discovered by collecting in data sets the impedance responses (i.e., EIS data) of various batteries along with other indications of charge state and/or failure modes, and then using such data sets to train a learning algorithm (e.g., an artificial intelligence (AI) or neural network model) to create a learned database (i.e., an EIS database) that can be used by an Electrochemical Impedance Spectroscopy Analyzer (EISA) [0030]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Feldman to train an AI model based on comparison of stored impedance data to continuously or periodically refine the learned databases over time and/or to discover failure mode (“[a] learned database may be created for each of a variety of battery types. Further, the process of collecting information on impedance responses of batteries to and charge state and/or failure modes for various types of batteries using such data sets to train a learning algorithm may be performed continuously or periodically so as to refine the learned databases over time. The collection of battery impedance responses (i.e., EIS data), charge state and failure mode and the creation and refinement of learned databases may be performed in a centralized service, such as an EISA network, which may make the learned EISA databases available to EIS systems via a network (e.g., the Internet). In some embodiments, such an EISA network may be cloud-based” ¶ [0030], Ballantine).
Regarding claim 6, Feldman as modified by Pulice disclose all the limitations of claim 5 on which this claim depends.
Feldman discloses creating a fingerprint of the fluid based on the impendence spectrum (¶ [0011]).
Feldman and Pulice are silent to training an artificial intelligence model based on the fingerprint.
However, in the same field of endeavor, Ballantine generally teaches training an artificial intelligence model based on stored impedance spectra in a database ([i]n an embodiment, correlations of impedance responses of various types of batteries to charge state and/or various failure modes may be discovered by collecting in data sets the impedance responses (i.e., EIS data) of various batteries along with other indications of charge state and/or failure modes, and then using such data sets to train a learning algorithm (e.g., an artificial intelligence (AI) or neural network model) to create a learned database (i.e., an EIS database) that can be used by an Electrochemical Impedance Spectroscopy Analyzer (EISA)”, ¶[0030]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Feldman and Pulice, to train an AI model based on comparison of stored impedance data to continuously or periodically refine the learned databases over time and/or to discover failure mode (“[a] learned database may be created for each of a variety of battery types. Further, the process of collecting information on impedance responses of batteries to and charge state and/or failure modes for various types of batteries using such data sets to train a learning algorithm may be performed continuously or periodically so as to refine the learned databases over time. The collection of battery impedance responses (i.e., EIS data), charge state and failure mode and the creation and refinement of learned databases may be performed in a centralized service, such as an EISA network, which may make the learned EISA databases available to EIS systems via a network (e.g., the Internet). In some embodiments, such an EISA network may be cloud-based” ¶ [0030], Ballantine).
Regarding claim 7, Feldman as modified by Pulice and Ballantine disclose all the limitations of claim 6 on which this claim depends.
Ballantine teaches analyzing a fingerprint of a second sample by the trained artificial intelligence model ([i]n an embodiment, correlations of impedance responses of various types of batteries to charge state and/or various failure modes may be discovered by collecting in data sets the impedance responses (i.e., EIS data) of various batteries along with other indications of charge state and/or failure modes, and then using such data sets to train a learning algorithm (e.g., an artificial intelligence (AI) or neural network model) to create a learned database (i.e., an EIS database) that can be used by an Electrochemical Impedance Spectroscopy Analyzer (EISA) ¶ [0030]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Feldman as taught by Ballantine, to analyze fingerprint of different fluids using an AI model for rapid and efficient detection of fluid quality and/or degradation status (“[b]y comparing the impedance response of the battery being measured to known signatures of impedance responses of batteries with known characteristics, the characteristics of the measured battery may be identified. Characteristics of the battery that may be determined based at least in part on the impedance response include charge conditions (e.g., state of charge), anode conditions, and cathode conditions. Based on the determined characteristics of the battery, a setting of the electrochemical device may be adjusted. Additionally, determined characteristics of the battery may be compared to a failure threshold, and when the characteristics exceed the failure threshold, a failure mode of the battery may be indicated, such as buildup of non-conductive compounds on the anode or cathode, dendritic breakdown of the electrolyte, etc.” ¶ [0029], Ballantine).
Regarding claim 8, Feldman as modified by Pulice and Ballantine disclose all the limitations of claim 6 on which this claim depends.
Feldman discloses that impedance of a fluid is dependent on composition and temperature (¶¶ [0054], [0113]-[0115]).
Therefore, when considering the combined teachings of Feldman, Pulice and Ballantine, one having ordinary skill in the art would readily appreciate and infer that training an artificial model using impedance spectra of fluid would depend on parameters such as temperature and composition.
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to train the model taught by Ballantine using parameters such as composition and temperature which are known to be impedance dependent for the purpose of allowing a user to confidently differentiate fluids based solely on their impedance spectra.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman and Pulice and further in view of Helm et al. (EP 0371261; “Helm”, of record).
Regarding claim 12, Feldman and Pulice disclose all the limitations of claim 1 on which this claim depends.
Feldman discloses the sensing element includes at least two inductive coils (11c, 12c), the at least two inductive coils (11c, 12c) including one sensing coil (12c) and one or more driving coils (11c) (¶ [0061]).
Feldman and Pulice are silent to combining an output of the one sensing coil and the one or more driving coils with at least one of: an analogue multiplier and a mixer.
Helm discloses two inductive coils including one sensing coil and one or more driving coils (Figure 5 is a block diagram with a driver coil and two sensor coils, one of which is a reference coil, for inductively derived generation of the reference voltage, Figure 6 shows a multi-coil sensor with a plurality of driver coils and sensor coils, p.8; sensing the complex impedance (The change in sensor voltage with respect to the same follows the equation: [Image Omitted] where M₁₂ the mutual inductance between the driver coil and the sensor coil, M₁₃ the mutual inductance between the driver coil and the approaching object, M₂₃ the mutual inductance between the sensor coil and the approaching object, the complex impedance Z₃ and ω mean the frequency of the driver coil current i T, p.3); combining an output of the one sensing coil and the one or more driving coils with at least one of: an analogue multiplier and a mixer (FIG. 10 shows a proximity sensor for detecting the amount and the phase of the sensor voltage by means of an all-pass filter 46, with which an adjustable phase shift can be achieved. In this case the driver coil voltage U T and the amplified sensor coil voltage U S2 are passed to a multiplier 55 after passing the all-pass 46, p.10).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Feldman to sense the complex impedance of the fluid by combining output of the one sensing coil and the driving coils with an analogue multiplier as taught by Helm to reduce the temperature and/or frequency drift as known in the art (“[a] major advantage of this circuit is that the input current i S of the measuring amplifier 8 is almost zero, since it has a very high input impedance and therefore measures the voltage U S of the sensor coil 3 in idle mode. This means that there is practically no temperature drift in such a system”, p.9, Helm).
Allowable Subject Matter
Claims 9, 13-17 and 19-21 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.
Regarding claim 9, none of the prior art either alone or in combination discloses or renders obvious a method as claimed wherein a second sensing element comprises one or more resistance temperature detectors and one or more pairs of electrodes comprising a driving electrode and a sensing electrode; and wherein sensing the complex impedance of the fluid comprises sensing the capacitive impedance of the fluid with the one or more resistance temperature detectors and the one or more pairs of electrodes in combination with the remaining claim limitations.
It is noted that Feldman, the closest prior art to Applicant’s claimed invention, teaches away from this configuration (see ¶[0096]; “[t]he inductive sensor configuration exemplified in FIGS. 2A-E overcomes problems associated with regular contact electrodes when used in complex liquids (e.g., milk). For example, contact electrodes can become clogged with fatty deposits, degrading the level of the signal and requiring frequent cleaning, usually using aggressive materials. Another problem associated with contact electrodes typically occur when the level of salt is significant in the liquid flow, which may cause ions accumulation along the electrode interface such that the electric field between the electrodes falls mainly on the thin layer close to the electrodes where the ions have accumulated”).
Regarding claim 13, none of the prior art either alone or in combination discloses or renders obvious a method as claimed wherein the sensing element comprises at least three inductive coils, the three inductive coils including two sensing coils and one or more driving coils, and wherein sensing the complex impedance of the fluid comprises converting coil signals with at least one instrumentation amplifier, subtracting converted coil signals from each other, and then gaining a resulting difference between signals in combination with the remaining claim limitations.
Claims 14-16 would be allowable based on their dependence on claim 13.
Regarding claim 17, none of the prior art either alone or in combination discloses or renders obvious a method as claimed wherein sensing the complex impedance of the fluid comprises one of: performing current-voltage measurement by measuring current through a reference resistor wired in series with electrodes of a second sensing element; and performing auto-balancing bridge measurement by using an inverting op-amp to cancel current flowing through a test impedance by establishing a virtual ground point in combination with the remaining claim limitations.
Regarding claim 19, none of the prior art either alone or in combination discloses or renders obvious a method as claimed wherein receiving the sensed signal from the sensing element comprises: periodically measuring a voltage of the sensed signal and collecting a plurality of sample tuples comprising pairings of sample times and sample voltages; redefining the sample times as integral values and applying a signal frequency transform to the sample times; and identifying a best fit sine wave for the sample set using a least-squares derivation in combination with the remaining claim limitations.
Claim 20 would be allowable based on its dependence on claim 19.
Regarding claim 21, none of the prior art either alone or in combination discloses or renders obvious a method as claimed wherein the sensor head further comprises a manifold that surrounds and protects the sensing element and which is configured to reduce electromagnetic interference and noise; wherein the one or more inductive coils are surrounded by the driving element and the driving element is further surrounded by a magnetic shield; wherein step c) further comprises bringing a second sensing element into contact with the fluid, wherein sensing the complex impedance of the fluid is further based on the second sensing element, and wherein the second sensing element comprises one or more pairs of electrodes formed as pins having a plurality of concentric plates or rings disposed thereon; and wherein step d) further comprises receiving a second sensed signal from the second sensing element in combination with the remaining claim limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2017/0248572 discloses an in-line impedance spectroscopy sensor comprising an inductive coil.
US 2019/0156600 discloses an in-line impedance spectroscopy sensor comprising an inductive coil.
US 2024/0197230 (of record) contains many aspects of the claimed invention however it is not available as prior art under 102(a)(1) or 102(a)(2).
USPN 8,522,604, USPN 7,956,601, US 2011/0068807, and USPN 5,811,664 (all of record) all discuss monitoring properties of a fluid using impedance/inductance measurements of a fluid flowing through a pipe with a coil wound around it. However, these references all use the resonant frequency of the associated tank circuit as a marker for fluid properties rather than a spectral fingerprint as disclosed in the instant application.
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/NATALIE HULS/Primary Examiner, Art Unit 2863