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 .
DETAILED ACTION
This Office Action is in response to Application No. 18/292666 filed on January 26, 2024.
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) 1-3, 6, 8, 10-14, 19, 20, 22, 23, 28, 29, 31, and 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jespersen (WO 2017167389) in view of Elbsat (US 20200356087).
Regarding claim 1, Jespersen teaches a method for predictive maintenance of a system for ventilation, in particular ventilation system or HVAC system, comprising an ultrasonic sensor and/or for predictive maintenance of an ultrasonic flowmeter assembly comprising the ultrasonic sensor configured to be used in the system for ventilation, the ultrasonic sensor comprising: at least one ultrasonic transducer configured to measure ultrasonic signals as a function of time during an operation of the ventilation system and to produce raw electronic signals as a function of time [“according to the invention, a reference digital sample of an initial ultrasonic signal is generated in order to generate data for the reference fingerprint, the initial ultrasonic signal being sent and received by the ultrasonic flow meter (1) and the sent (Tx) and/or the received (Rx) initial ultrasonic signal being digitally sampled by the ultrasonic flow meter (1) so as to obtain a Tx and/or Rx reference digital sample, respectively” (Abstract)], the method comprising the method elements of:
(a) deriving a signal parameter based on the raw electronic signals [“deriving an initial zero crossing pattern from the Tx and/or the Rx reference digital sample and comparing the initial zero crossing pattern to a current zero crossing pattern of a current ultrasonic signal during use of the flow meter” (last paragraph on p.3); and “deriving an initial signal amplitude from the Tx and/or the Rx reference digital sample and comparing the initial signal amplitude to a current signal amplitude of a current ultrasonic signal during the use of the flow meter” 1st paragraph on p.4];
(b) creating a set of data comprising the signal parameter as a function of time [“The reference fingerprint is stored permanently in production stage of the ultrasonic flow meter 1. An alternative embodiment of the ultrasonic flow meter 1 (not shown) comprises a network connection, for example a wireless network connection, for storing the reference fingerprint in are mote data storage, instead.” (spanning paragraph on p.6-7)];
(c) selecting at least one limit parameter [“When the difference between a pair of an initial system parameter and a current system parameter passes a predetermined threshold an alarm is sent by the ultrasonic flow meter 1 via a network connection in order to initiate maintenance upon request.” (last paragraph on p.6)].
Jespersen, however, does not explicitly teach (d) estimating a time limit based on the set of data, wherein the time limit is a time when the signal parameter is predicted to reach the limit parameter.
Elbsat, in analogous art, teaches (d) estimating a time limit based on the set of data, wherein the time limit is a time when the signal parameter is predicted to reach the limit parameter [“the model predictive maintenance process includes predicting a resource consumption of the building equipment over an optimization period as a function of an estimated degradation state of the building equipment.” (¶0010); “One example of a system in which the systems and methods of the present disclosure can be implemented is a variable refrigerant flow (VRF) system that consumes electric power to serve a heating or cooling load. A power consumption model can be used to relate the amount of power consumed by the VRF equipment to the amount of heating or cooling produced by the VRF equipment. An artificial neural network model is trained to predict values of coefficients of the power consumption model as a function of degradation state. To generate training data for the neural network model, both the degradation state and the power consumption can be estimated by the measurements collected from the VRF system. Once the neural network has been trained, the neural network can be used to predict power model coefficients as a function of the current degradation state. The power model coefficients are then used to predict the power consumption of the equipment during operation.” (¶0048); and “In some embodiments, the MPM systems and methods are performed periodically for a building. In some embodiments, the MPM systems and methods can be performed in an event or condition driven manner. For example, various performance indicators (e.g., degradation estimations and/or predictions, fault detection, performance variables, etc.) can be monitored and used to determine if one or more events have occurred or if conditions have been satisfied. In response to the events occurring or the conditions being satisfied, the systems and methods for MPM may be initiated to determine optimal maintenance of building equipment. In some embodiments, the event or condition driven initiation of MPM results in MPM being performed at non-scheduled intervals. In some embodiments, MPM is initiated in response to a user input.” (¶0050)].
Jespersen, on the one hand, teaches acquisition and storage of ultrasonic time‑series parameters (e.g., amplitude, envelope, zero‑crossing patterns) and thresholded alarms when current parameters deviate from stored reference fingerprints. Elbsat, on the other hand, teaches a model‑predictive maintenance framework that predicts future degradation/performance trajectories, compares predicted values to thresholds, and schedules maintenance over an optimization horizon.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to apply Elbsat’s predictive maintenance methods to Jespersen’s stored ultrasonic parameters because Elbsat explicitly contemplates use with building/HVAC equipment and requires time‑varying performance indicators of the exact type Jespersen provides. The application of the MPM prediction/scheduling technique to Jespersen’s time‑series data would yield the predictable result of an estimated time‑to‑threshold and a scheduled maintenance action.
Regarding claim 2, Jespersen/Elbsat teach the method of claim 1, wherein in step (a) the deriving the signal parameter comprises extracting the signal parameter from the raw electronic signals or from electronic signals processed therefrom, in particular amplified and/or filtered electronic signals; in particular wherein at least one of the raw electronic signals is obtained as an average over a plurality of measurements, or at least one of the raw electronic signals is obtained by signal processing in the processing unit [“Preferably, the initial ultrasonic signal is sampled in one or more series of digital samples, each series having a sampling frequency … multiple series of digital samples are combined to digitally reconstruct properties of the initial ultrasonic signal which shall be stored in the reference fingerprint.” (last paragraph on p.2 on Jespersen)].
Regarding claim 3, Jespersen/Elbsat teach the method of claim 1, wherein the ultrasonic signals are emitted by a first ultrasonic transducer and/or by a second ultrasonic transducer, and wherein the ultrasonic signals are reflected at least once before being measured by the ultrasonic transducer(s) [“Preferably, the ultrasonic flow meter comprises a first ultrasonic transducer and a second ultrasonic transducer, the initial ultrasonic signal being sent between the first ultrasonic transducer and the second ultrasonic transducer” (last paragraph on p.2 on Jespersen), “the sent (Tx) and/or the received (Rx) initial ultrasonic signal being digitally sampled” (1st paragraph on p.2 on Jespersen), and “so as to obtain a Tx and/or the Rx reference digital sample” (abstract on Jespersen)].
Regarding claim 6, Jespersen/Elbsat teach the method of claim 1, wherein the signal parameter an amplitude of the raw electronic signal [“It is preferred that the reference fingerprint includes one or more of measurement clock calibration data, temperature measurement circuit calibration data, time measurement circuit calibration data, measurement statistics, an initial ultrasonic signal amplitude, or initial zero crossing patterns as initial system parameters.” (1st paragraph on p.3 on Jespersen)].
Regarding claim 8, Jespersen/Elbsat teach the method of claim 1, wherein the ultrasonic sensor comprises a signal processing unit configured to process the raw electronic signals and/or to amplify the raw electronic signals by applying the gain factor to produce the amplified electronic signals as a function of time, in particular wherein the ultrasonic sensor is an ultrasonic sensor for measuring a flow and/or temperature of a fluid through a channel [“Preferably, the analog-to-digital converter for obtaining the reference digital sample is part of a microcontroller of the ultrasonic flow meter.” (3rd paragraph on p.3 on Jespersen)].
Regarding claim 10, Jespersen/Elbsat teach the method of claim 1, further comprising in step (b) a step of selecting an initial signal parameter corresponding to a specified or a predetermined value of the raw electronic signal; and/or comprising in step (b) a step of selecting an initial gain factor corresponding to a specified or a predetermined value of the amplified electronic signal [“It is preferred that the method comprises the steps of deriving an initial zero crossing pattern … and comparing …; deriving an initial signal amplitude … and comparing …; measuring clock calibration data …; deriving an initial envelope function …; deriving initial frequency content …; … The steps … are included in the reference fingerprint of the ultrasonic flow meter in a fifth step of the inventive method.” (1st paragraph on p.3 on Jespersen)].
Regarding claim 11, Jespersen/Elbsat teach the method of claim 10, wherein the initial signal parameter and/or the initial gain factor is determined during a calibration or start-up procedure; and/or the set of data comprises at least two data pairs [“Preferably, the reference fingerprint is generated during production and/or calibration of the ultrasonic flow meter.” (1st paragraph on p.5 on Jespersen)].
Regarding claim 12, Jespersen/Elbsat teach the method of claim 1, the method further comprising a step of creating a signal parameter time curve using the set of data [“Monitoring of the complete temperature measurement can be done by comparing the transit time as calculated from temperature, flow meter geometry and a known relation … Monitoring … thus allows indirect monitoring of … changes over time.” (spanning paragraph p.3-4 on Jespersen)].
Regarding claim 13, Jespersen/Elbsat teach the method of claim 12, wherein the signal parameter time curve is obtained by a step of interpolating the set of data [“multiple series of digital samples are combined to digitally reconstruct properties of the initial ultrasonic signal which shall be stored in the reference fingerprint.” (last paragraph of p.2 on Jespersen); while Jespersen doesn’t explicitly discloses interpolating, a person of ordinary skill in the art would understand that interpolating is a known technique used for data reconstruction].
Regarding claim 14, Jespersen/Elbsat teach the method of claim 12, comprising a step of extrapolating the signal parameter time curve and determining the time limit from an intersection between the extrapolated signal parameter time curve and a limit parameter threshold value [“…the one or more performance indicators include … a predicted future degradation of the building equipment … the operations further include comparing the estimated current degradation, the predicted future degradation, or the performance variable of the building equipment to a corresponding threshold.” (¶0005 on Elbsat) and “… predicting a resource consumption … over an optimization period … and … optimizing an objective function … to determine the maintenance schedule.” (¶0010 on Elbsat) — Elbsat discloses predicting future trajectories and using predictions to schedule maintenance (i.e., determining when thresholds will be crossed).].
Regarding claim 19, Jespersen/Elbsat explicitly teach all the claim limitations except for the method of claim 12, wherein the signal parameter time curve and/or the interpolation and/or the extrapolation is linear or stepwise linear.
Jespersen, however, teaches an ultrasonic flow meter that collects and stores time‑series measurement statistics (including SNR and amplitude) and compares current values to stored references, initiating action when predetermined thresholds are crossed. Linear extrapolation is a well‑known mathematical forecasting technique that operates on time‑series data to estimate short‑term future values.
Therefore, 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 Jespersen’s monitoring system to apply linear extrapolation to the stored/current measurement statistics to predict when a monitored parameter will reach the stored threshold. The modification uses a known technique (linear extrapolation) applied to a known device/method (Jespersen’s fingerprint/monitoring system) to achieve the predictable result of estimating time‑to‑threshold and enabling earlier maintenance scheduling.
Regarding claim 20, Jespersen/Elbsat teach the method of claim 1, wherein measurement time intervals are selected in a range from one month to several years [Elbsat discloses periodic/event‑driven MPM and optimization periods such as “30 weeks, 52 weeks, 10 years, 30 years” as example optimization horizons (¶0115, 0156, 0370)].
Regarding claim 22, Jespersen/Elbsat teach the method of claim 1, the method further comprising a step of raising an alarm when the signal parameter reaches the limit parameter [“When the difference between a pair of an initial system parameter and a current system parameter passes a predetermined threshold an alarm is sent by the ultrasonic flow meter 1 via a network connection in order to initiate maintenance upon request.” (last paragraph on p.6 on Jespersen)].
Regarding claim 23, Jespersen/Elbsat teach the method of claim 1, the method further comprising the step of setting an alarm threshold for the signal parameter smaller or larger than the limit parameter and raising an alarm when the signal parameter reaches the alarm threshold [“When the difference between a pair of an initial system parameter and a current system parameter passes a predetermined threshold an alarm is sent by the ultrasonic flow meter 1 via a network connection in order to initiate maintenance upon request.” (last paragraph on p.6 on Jespersen)].
Regarding claim 28, Jespersen/Elbsat teach the method of claim 1, wherein the method serves for detecting malfunctioning of the ultrasonic sensor, in particular signal fading due to accumulation of dust or debris on the ultrasonic transducer and/or on at least one reflection point or reflection surface of the conduit [“In order to detect changes which affect K, At, and c which may require recalibration or maintenance of the ultrasonic flow meter, it is known to use fingerprinting for the ultrasonic flow meter. … Thus, a change in ultrasonic flow meter geometry and thus K may give rise to recalibration or repair of the ultrasonic flow meter.” (1st paragraph on p.2 of Jespersen)].
Regarding claim 29, Jespersen/Elbsat teach the method of claim 1, wherein the ultrasonic signals from the ultrasonic transducers providing reduced raw sensor signals or requiring increased gain factors compared to other ultrasonic transducers are used with less weight or are neglected, e.g. when determining the flow and/or temperature of the fluid through the channel [“The method according to the invention allows to generate the reference fingerprint and to compare … the measurement circuits already included … without using any external devices.” (3rd paragraph on p.2 of Jespersen)].
Regarding claim 30, Jespersen/Elbsat teach the method of claim 1, wherein the ultrasonic sensor comprises at least two ultrasonic transducers that are fixed to a channel section and are arranged at a distance from each other along the channel section, in particular wherein the channel section comprises at least one reflector for providing a reflection path for one or between two of the ultrasonic transducers [“Preferably, the ultrasonic flow meter comprises a first ultrasonic transducer and a second ultrasonic transducer … Furthermore, the present invention relates to the ultrasonic flow meter adapted to perform the method for monitoring the ultrasonic flow meter.” (abstract and 2nd paragraph on p.1 of Jespersen)].
Regarding claim 31, Jespersen/Elbsat teach a sensor comprising:
an ultrasonic transducer configured to measure ultrasonic signals as a function of time and to produce a raw electronic signals as a function of time [“Preferably, the ultrasonic flow meter comprises a first ultrasonic transducer and a second ultrasonic transducer … Furthermore, the present invention relates to the ultrasonic flow meter adapted to perform the method for monitoring the ultrasonic flow meter.” (abstract and 2nd paragraph on p.1 of Jespersen)]; and a signal processing unit configured to process the raw electronic signals and/or to amplify the electronic signals by applying a gain factor to produce amplified electronic signals as a function of time, wherein the sensor is configured to perform the method for predictive maintenance of claim 1 [“according to the invention, a reference digital sample of an initial ultrasonic signal is generated in order to generate data for the reference fingerprint, the initial ultrasonic signal being sent and received by the ultrasonic flow meter (1) and the sent (Tx) and/or the received (Rx) initial ultrasonic signal being digitally sampled by the ultrasonic flow meter (1) so as to obtain a Tx and/or Rx reference digital sample, respectively” (Abstract)].
Regarding claims 33 and 34, these claim(s) limitations are significantly similar to those of claim(s) 9; and, thus, are rejected on the same grounds.
Regarding claim 32, these claim(s) limitations are significantly similar to those of claim(s) 1; and, thus, are rejected on the same grounds.
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jespersen (WO 2017167389) in view of Elbsat (US 20200356087); and further in view of Hokkanen (WO 2018116071)
Regarding claim 4, Jespersen/Elbsat explicitly teach all the claim limitations except for the method of claim 3, wherein the ultrasonic signals are transferred via at least two different reflection paths, and the method elements (a)-(d) are performed separately for each of the reflection paths.
Hokkanen, in analogous art, teaches wherein the ultrasonic signals are transferred via at least two different reflection paths, and the method elements (a)-(d) are performed separately for each of the reflection paths [“The parameters related to receiving can be optimized e.g. in such a way that in calibration the transmission signal is measured for longer than the duration of the transmission signal and the reception signal received is divided into time ranges, which are analyzed in more detail. From the phase-difference behavior of two receivers, cyclically occurring ranges in which the measurement gives an accurate and repeatable result can be distinguished. The temporal starting point for the receiving time window can, based on this calibration, be set for each sensor for the point detected as optimal in its installation position.” (spanning paragraph on p.5-6)].
Jespersen/Elbsat, on the one hand, teaches an ultrasonic flow meter that digitally samples transmit/receive waveforms, derives and stores time‑series signal parameters (amplitude, envelope, zero‑crossings, measurement statistics) as a reference fingerprint for monitoring and thresholded alarm (self‑monitoring of Tx/Rx parameters); wherein a model‑predictive maintenance (MPM) framework that consumes time‑varying performance indicators (estimated current degradation, predicted future degradation, performance variables), predicts future trajectories, and schedules maintenance when predicted values cross thresholds. Hokkanen, on the other hand, teaches duct‑mounted ultrasonic sensing with multiple receivers/reflector paths and calibration that divides received signals into time windows (separable reflection paths) and selects parameters per path.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to apply Elbsat’s known MPM forecasting and scheduling methods to Jespersen’s time‑series ultrasonic parameters measured in the multi‑path duct configurations taught by Hokkanen: the inputs (time‑series amplitude/phase/envelope data) directly match Elbsat’s required performance indicators, the target devices (ultrasonic HVAC/duct sensors and flowmeters) operate in the same technical field, and the expected benefit (predicting time‑to‑threshold per path and scheduling maintenance) is the same kind of improvement Elbsat achieves for other building equipment. Applying Elbsat’s prediction/extrapolation and scheduling to Jespersen/Hokkanen sensor outputs is a routine engineering application of a known technique to closely related devices and thus yields a predictable result (time‑to‑limit estimates and maintenance schedules per reflection path) without introducing new, non‑obvious technical effects.
Claim(s) 7 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jespersen (WO 2017167389) in view of Elbsat (US 20200356087); and further in view of Hokkanen (WO 2018116071); and still further in view of Gaugler (DE 10118934).
Regarding claim 7, Jespersen/Elbsat explicitly teach all the claim limitations except for the method of claim 1, comprising the step of amplifying the raw electronic signals by applying a gain factor to produce amplified electronic signals as a function of time, wherein the gain factor is adapted to provide an amplification of the raw electronic signals such that the amplified electronic signals exceed a given minimum threshold value, and wherein the signal parameter is or corresponds to the gain factor and the limit parameter is or corresponds to a gain factor limit.
Gaugler, in analogous art, comprising the step of amplifying the raw electronic signals by applying a gain factor to produce amplified electronic signals as a function of time, wherein the gain factor is adapted to provide an amplification of the raw electronic signals such that the amplified electronic signals exceed a given minimum threshold value, and wherein the signal parameter is or corresponds to the gain factor and the limit parameter is or corresponds to a gain factor limit [“…the control device of a reception amplifier of an ultrasonic measuring device can be a very simple amplifier Carry out regulation, in which always via an adjustable amplifier an optimal received voltage amplitude can be provided. To this Purpose can be provided, for example, that directly from the monitoring a control signal for an adjustable transmission frequency of the measurement device is delivered.”, “an inventive Monitoring device with an optical or acousticsignal device Issue of a warning signal when the value falls below a specified comparison to provide voltage.”, and “it is therefore provided that the emp capture signals of the ultrasonictransducers to be monitored in a comparator a switching offset from the zero crossing by an offset voltagethreshold to be converted into rectangular digital signals and their key ratio is determined” (paragraphs 5-7 on p.2)].
Jespersen/Elbsat, on the one hand, discloses an ultrasonic flow meter that digitally samples Tx/Rx waveforms, derives and stores time‑series signal parameters (amplitude, envelope, zero‑crossings, measurement statistics) as a reference fingerprint, and compares current parameters to stored references to detect degradation and trigger alarms (calibration/production fingerprinting, ADC + microcontroller processing); wherein a model‑predictive maintenance (MPM) framework that consumes time‑varying performance indicators (estimated current degradation, predicted future degradation, performance variables), predicts future trajectories, and schedules maintenance when predicted values cross thresholds.
Gaugler, on the other hand, discloses monitoring amplitude/duty‑cycle with a comparator and an adjustable reception amplifier (i.e., gain control) and issuing warnings when the received amplitude falls below a set comparison voltage (i.e., detecting contamination/aging and regulating gain to maintain signal quality).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to apply Elbsat’s MPM prediction/scheduling to the ultrasonic‑signal time‑series and fingerprint data taught by Jespersen, and to monitor/drive the amplifier and comparator signals using Gaugler’s contamination‑sensitive amplitude/duty‑cycle measures. The inputs (time‑series amplitude, envelope, comparator duty ratio, gain setting) directly match Elbsat’s required performance indicators; the devices operate in the same technical field (ultrasonic sensing/flow or HVAC instrumentation); and the improvement sought (predicting time‑to‑threshold and planning maintenance) is the same kind of system‑level benefit Elbsat achieves for building equipment. Applying Elbsat’s forecasting and scheduling methods to Jespersen’s sensor outputs together with Gaugler’s gain/threshold monitoring is therefore a routine engineering adaptation of a known technique to closely related devices to obtain a predictable result: per‑sensor (or per‑path) time‑to‑limit estimates, adaptive gain actions, and scheduled maintenance or alarms before signal quality falls below the contamination/operational thresholds.
Regarding claim 24, Jespersen/Elbsat explicitly teach all the claim limitations except for the method of claim 1, wherein the limit parameter and/or the alarm threshold is determined such that a threshold amplitude of the raw electronic signals, which is indicative of a maximal allowable dirt accumulation in the system for ventilation, is not underrun; and/or wherein the gain factor limit and/or the alarm threshold is determined such that a threshold amplitude of the amplified electronic signals, which is indicative of a maximal allowable dirt accumulation in the system of ventilation, is not underrun.
Gaugler, in analogous art, wherein the limit parameter and/or the alarm threshold is determined such that a threshold amplitude of the raw electronic signals, which is indicative of a maximal allowable dirt accumulation in the system for ventilation, is not underrun; and/or wherein the gain factor limit and/or the alarm threshold is determined such that a threshold amplitude of the amplified electronic signals, which is indicative of a maximal allowable dirt accumulation in the system of ventilation, is not underrun [“With increasing pollution, which is caused, for example, by lime, rust and magnetite, is reduced the receiving voltage and thus the quality of the flow measurement worse until it is finally no longer possible.” (3rd paragraph on p.1), and “Finally, it is also within the scope of the invention, an inventive Monitoring device with an optical or acoustic signal device Issue of a warning signal when the value falls below a specified comparison to provide voltage. Such a warning signal can make a recommendation for an exchange of the deteriorating ultrasound transducer is given, before the device fails completely.” (7th paragraph on p.2)].
Jespersen/Elbsat, on the one hand, discloses an ultrasonic flow meter that digitally samples Tx/Rx waveforms, derives and stores time‑series signal parameters (amplitude, envelope, zero‑crossings, measurement statistics) as a reference fingerprint, and compares current parameters to stored references to detect degradation and trigger alarms (calibration/production fingerprinting, ADC + microcontroller processing); wherein a model‑predictive maintenance (MPM) framework that consumes time‑varying performance indicators (estimated current degradation, predicted future degradation, performance variables), predicts future trajectories, and schedules maintenance when predicted values cross thresholds.
Gaugler, on the other hand, discloses monitoring amplitude/duty‑cycle with a comparator and an adjustable reception amplifier (i.e., gain control) and issuing warnings when the received amplitude falls below a set comparison voltage (i.e., detecting contamination/aging and regulating gain to maintain signal quality).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to apply Elbsat’s MPM prediction/scheduling to the ultrasonic‑signal time‑series and fingerprint data taught by Jespersen, and to monitor/drive the amplifier and comparator signals using Gaugler’s contamination‑sensitive amplitude/duty‑cycle measures. The inputs (time‑series amplitude, envelope, comparator duty ratio, gain setting) directly match Elbsat’s required performance indicators; the devices operate in the same technical field (ultrasonic sensing/flow or HVAC instrumentation); and the improvement sought (predicting time‑to‑threshold and planning maintenance) is the same kind of system‑level benefit Elbsat achieves for building equipment. Applying Elbsat’s forecasting and scheduling methods to Jespersen’s sensor outputs together with Gaugler’s gain/threshold monitoring is therefore a routine engineering adaptation of a known technique to closely related devices to obtain a predictable result: per‑sensor (or per‑path) time‑to‑limit estimates, adaptive gain actions, and scheduled maintenance or alarms before signal quality falls below the contamination/operational thresholds.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jespersen (WO 2017167389) in view of Elbsat (US 20200356087); and further in view of Hokkanen (WO 2018116071); and still further in view of Gysling (US 20110226063)
Regarding claim 9, Jespersen/Elbsat explicitly teach all the claim limitations except for the method of claim 1, wherein the limit parameter is determined such that a required minimum signal to noise ratio of the raw electronic signals is not underrun; and/or wherein the gain factor limit is determined such that a required minimum signal to noise ratio of the amplified electronic signal is not underrun.
Gysling, in analogous art, wherein the limit parameter is determined such that a required minimum signal to noise ratio of the raw electronic signals is not underrun [“The ratio of the fluid borne signal component (considered the ‘signal’ …) to the structural borne signal component (considered ‘noise’ …) of the arrived signal is a measure of the signal‑to‑noise for a flow meter application. In general, increasing the magnitude of the fluid borne signal component relative to the structural borne signal component (i.e., improving the signal‑to‑noise ratio) improves the operability and performance of ultrasonic flow meters.” (¶0006–0007), and “To increase the fluid borne signal component of the received signal, the transmitted signal is transmitted … at a frequency that is coincident with a resonant frequency of the pipe wall.” (¶0028)]; and/or wherein the gain factor limit is determined such that a required minimum signal to noise ratio of the amplified electronic signal is not underrun.
Jespersen discloses monitoring “signal to noise ratio” as a fingerprint statistic and signaling an “alarm” upon crossing a “predetermined threshold,” while Elbsat discloses general threshold‑triggered maintenance initiation by “comparing … to a corresponding threshold” and acting when the “trigger condition has been satisfied.” Gysling defines SNR for ultrasonic flow meters and further discloses increasing/maintaining it (e.g., resonance matching), thereby motivating minimum‑SNR limits for acceptable operation.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to determine and enforce SNR‑based limits on both raw and amplified ultrasonic measurement signals by combining Jespersen with Elbsat, and Gysling, because this merely applies known thresholding and gain‑control techniques to similar ultrasonic sensing devices to achieve a predictable improvement in signal quality monitoring and maintenance scheduling.
Allowable Subject Matter
Claims 15-18, 25 and 26 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.
Conclusion
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/Ramon A. Mercado/ Supervisory Patent Examiner, Art Unit 3658