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
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.
Claim(s) 1-6, 8-9, 11-12, 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20220276307 (herein Athikessavan) in view of US 5390545 (herein Doan) and US 20220128587 (herein Guettinger).
Regarding claim 1, Athikessavan teaches A method for determining a fault status of a target system (method of detecting a rotor bar fault of an electrical machine, [0008]), the method comprising:
receiving one or more magnetic field signals
processing the one or more magnetic field signals to detect values of one or more parameters indicative of vibration of the target system, wherein the one or more parameters include one or more parameters representing harmonics of the target system and at least one parameter indicative of a speed of the target object (FIG. 5C is a graph 504 presenting the frequency spectrum of summed end-shield leakage fluxes, [0102]; [0082] teaches rotor bar frequency component given using vibration signal and flux signal; mechanical signals may be measured using motion sensors which are capable of measuring velocity, [0013]; overall vibration velocity is computed using the captured vibration signal, [0123]),
wherein the processing includes: obtaining a predetermined number of digital samples of the one or more magnetic field signals (The set of signals is acquired from the electrical machine over a period. The period refers to a time frame over which the set of signals is being acquired to detect the presence of rotor faults, [0066]);
transforming the predetermined number of digital samples of the one or more magnetic field signals into a frequency domain (current, vibration and summed end-shield leakage flux signals are captured for a time window of 10 seconds at a sampling frequency of 10 kHz and then FFT computation is carried out to convert time-domain signals to frequency-domain, [0107]);
detecting, as one of the one or more parameters, a number of the harmonics from the frequency domain transformation (Fig. 5b teaches frequency component Fr, 2Fr, and 3Fr; Note: harmonics is defined in physics as a component frequency of an oscillation or wave);
detecting, as one of the one or more parameters, frequencies of the harmonics from the frequency domain transformation (Fig. 5b teaches measured frequency spectrum, with frequency shown on the x-axis); and
detecting, as one of the one or more parameters, amplitudes of the harmonics from the frequency domain transformation (Fig. 5b teaches measured frequency spectrum, with magnitude shown on the y-axis; Note that magnitude and amplitude both refer to intensity);
calculating deviations between the detected values and corresponding reference values of one or more parameters, parameters, wherein the reference values of one or more parameters are determined using the same predetermined number of digital samples (From the frequency spectrum, the sidebands around the fundamental (supply) frequency components, which correspond to the broken rotor bar fault are extracted for current, vibration and magnetic leakage flux signals, [0107]; During the initial calibration stage, the computed set of load values are a set of baseline load values. During online monitoring, the computed set of load values are a set of online load values, which may be computed during online monitoring over a period, which varies from 1 second to 20 seconds, [0081]; Note that calibration period in [0081] of 1 to 20 seconds equates to the same measurement periods found in [0066]);
determining a fault level of the target system based on the calculated deviations of one or more parameters (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]); and
generating an output signal indicating to the fault level (At step 924, a notification is triggered to indicate the presence of mechanical anomaly, [0131]).
Further regarding claim 1, Athikessavan not teach, “generating pulses responsive to amplitude of the one or more magnetic field signals; and incrementing a counter at a fixed rate between edges of the pulses to detect the speed of the target object.” However, Doan teaches the deficiencies of Athikessavan (timing means 120 counts the number of clock pulses that occur between each "falling edge" of the speed signal. The number of clock pulses represents a value that is proportional to the period of the speed signal, Col. 3, Lines 53-65).
Regarding claim 2, Athikessavan teaches wherein the target system includes a motor system electrical machine may be a motor, [0009]);
Regarding claim 3, Athikessavan teaches wherein the target object includes a rotating shaft having a ring magnet to generate the magnetic field (a permanent magnet rotor, shaft member, [0059]).
Regarding claim 4, Athikessavan and Doan do not teach, “wherein the target object includes a rotating gear having ferromagnetic teeth to generate the magnetic field.” However, Guettinger teaches these deficiencies (wheel 1 that has alternating teeth 2 and notches 3, according to one or more embodiments. In particular, the toothed wheel 1 may be made of a ferromagnetic material (e.g., iron) that attracts magnetic fields, [0038]). It would have been obvious to one of ordinary skill in the art at the time of invention to simply substitute the magnetic field sensing principle of Athikessavan with that of Guettinger because both are used to detect magnetic fields within motors. The above findings satisfies the Graham factual inquiries stated in MPEP 2143 B regarding simple substitution of one known element for another to obtain predictable results.
Regarding claim 5, Athikessavan teaches wherein the determining of the fault level of the target system includes: comparing the calculated deviations of one or more parameters to corresponding predetermined threshold values (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]).
Regarding claim 6, Athikessavan teaches wherein the determining of the fault level of the target system further includes: determining the fault level of the target system to be a first fault level if none of the calculated deviations is greater than or equal to a corresponding predetermined threshold value; and determining the fault level of the target system to be a second fault level if at least one of the calculated deviations is greater than or equal to the corresponding predetermined threshold value (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]).
Regarding claim 8, Athikessavan teaches auto-calibrating the reference values of one or more parameters (during initial calibration, a set of Baseline Load Values (BLVs) are measured and stored in a database for various loading conditions, [0085]-[0086]).
Regarding claim 9, Athikessavan teaches wherein the auto-calibrating of the reference values is responsive to a first startup of the sensor (method may further comprise a calibration step e.g. an initial calibration, prior to the step of acquiring the set of online signals from the electrical machine, [0068]; Fig. 3 and [0080] teach calibration 304 occurs after energizing motor).
Regarding claim 11, Athikessavan teaches wherein the auto-calibrating the reference values of one or more parameters includes: processing the one or more magnetic field signals to detect the reference values of one or more parameters; and storing the reference values to non-volatile memory of the sensor (At step 304, a set of signals/data is acquired from the electrical machine. The set of signals/data may be a set of baseline signals/data acquired from the electrical machine during calibration e.g. initial calibration. The set of signals/data may also be a set of online signals/data acquired from the electrical machine during online monitoring over a period, [0080]; During calibration, a set of Baseline Load Values (BLVs) may be measured and stored in a database, [0068]).
Regarding claim 12, Athikessavan and Doan do not teach, “receiving a signal responsive to a temperature of the sensor, wherein storing the reference values to non-volatile memory of the sensor is responsive to a determination that the temperature of the sensor is between a predetermined range of temperatures.” However, Guettinger teaches these deficiencies (sensor device, as described herein, may be a temperature sensor, [0027]; the switching thresholds 15 and 16, stored in memory, [0064]; the signal tracking processing circuit 23 may generate the event signal 38 (e.g., an event pulse 38) each time sensor signal 31 crosses one or both of the switching thresholds 15 and/or 16 in a particular rising or falling direction, [0071]). It would have been obvious to one of ordinary skill in the art at the time of invention to incorporate the temperature sensor of Guettinger into the fault detector of Athikessavan. One would be motivated to do so for at least the purpose of preventing sensor deadlock and improve sensor sensitivity ([0003]).
Regarding claim 17, Athikessavan teaches wherein the one or more parameters include a parameter indicative of an amplitude of the one or more magnetic field signals (the fundamental components, f.sub.s of line-current and summed end-shield leakage fluxes are characterized by the highest magnitudes in the frequency spectrum, [0103]).
Regarding claim 23, Athikessavan teaches superimposing another output signal that carries information about the repetitive motion of the target object onto the output signal indicating the fault level is a second output signal (Figs. 6A-C and [0104]-0105] teach examples of superimposed signals that indicate fault), wherein the superimposed signal is provided at a common output terminal of the sensor ([0176] teaches output of sensor to devices such as display 1308).
For the above claims 1-6, 8-9, 11-12, 17 and 23, it would have been obvious to one of ordinary skill in the art before the time of filing to simply substitute the velocity calculation of Athikessavan with speed detection of Doan because the substitution would provide predictable results for measuring speed/velocity from a vibration signal. The above findings satisfies the Graham factual inquiries stated in MPEP 2143 B regarding simple substitution of one known element for another to obtain predictable results.
Additionally for the above claims 1-6, 8-9, 11-12, 17, and 23, Athikessavan does not teach, “sensed by a plurality of magnetic field sensing elements”, “the sensor being provided within a single integrated circuit (IC) package located about the target object.” However, Guettinger teaches it is known in the art to incorporate magnetic field elements H1 and H2 ([0041] and Fig. 1C) within a single magnetic field sensor module 6, and further arrange a plurality of magnetic field sensors and a sensor circuitry accommodated (i.e. integrated) in the same chip ([0029]) proximal to a subject (see Fig. 1C). As such, it would have been obvious to the ordinary artisan to package magnetic flux sensor 214 into a package taught by Guettinger. One would be motivated to do so for at least the purpose of providing a differential measurement signal generated by two sensor elements for robustness to homogenous external stray magnetic fields ([0030]).
Regarding claim 18, Athikessavan teaches A sensor comprising:
one or more magnetic field sensing elements (magnetic flux sensors 214, 216, 218, 220, [0074]; Note: magnetic flux is the magnetic field through an area);
a circuit configured to: receive one or more magnetic field signals sensed by the one or more magnetic field sensing elements, the one or more magnetic field signals responsive to a magnetic field generated by a target object of a target system (a set of p flux signals may be acquired and summed to obtain a total flux signal. The set of p flux signals may be acquired from p flux sensor e.g. 214, [0073]; functional operations that operate on data within a computer memory or an electronic circuit, [0163]), the target object having repetitive motion (electrical machine may be a motor, [0009]);
process the one or more magnetic field signals to detect values of one or more parameters indicative of vibration of the target system, wherein the one or more parameters include one or more parameters representing harmonics of the target system and at least one parameter indicative of a speed of the target object (FIG. 5C is a graph 504 presenting the frequency spectrum of summed end-shield leakage fluxes, [0102]; [0082] teaches rotor bar frequency component given using vibration signal and flux signal; mechanical signals may be measured using motion sensors which are capable of measuring velocity, [0013]; overall vibration velocity is computed using the captured vibration signal, [0123]),
wherein the processing includes: obtaining a predetermined number of digital samples of the one or more magnetic field signals (The set of signals is acquired from the electrical machine over a period. The period refers to a time frame over which the set of signals is being acquired to detect the presence of rotor faults, [0066]);
transforming the one or more magnetic field signals into a frequency domain (At step 306, the acquired time-domain signals from step 304 are then converted to frequency-domain by Fast Fourier Transform (FFT) or Discrete Fourier Transform, [0081]);
detecting, as one of the one or more parameters, a number of the harmonics from the frequency domain transformation (Fig. 5b teaches frequency component Fr, 2Fr, and 3Fr; Note: harmonics is defined in physics as a component frequency of an oscillation or wave);
detecting, as one of the one or more parameters, frequencies of the harmonics from the frequency domain transformation (Fig. 5b teaches measured frequency spectrum, with frequency shown on the x-axis); and
detecting, as one of the one or more parameters, amplitudes of the harmonics from the frequency domain transformation (Fig. 5b teaches measured frequency spectrum, with magnitude shown on the y-axis; Note that magnitude and amplitude both refer to intensity);
calculate deviations between the detected values and corresponding reference values of one or more parameters, wherein the reference values of one or more parameters are determined using the same predetermined number of digital samples (From the frequency spectrum, the sidebands around the fundamental (supply) frequency components, which correspond to the broken rotor bar fault are extracted for current, vibration and magnetic leakage flux signals, [0107]);
determine a fault level of the target system based on the calculated deviations of one or more parameters (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]);
and generate an output signal indicating to the fault level (At step 924, a notification is triggered to indicate the presence of mechanical anomaly, [0131]).
Further regarding claim 18, Athikessavan not teach, “generating pulses responsive to amplitude of the one or more magnetic field signals; and incrementing a counter at a fixed rate between edges of the pulses to detect the speed of the target object.” However, Doan teaches the deficiencies of Athikessavan (timing means 120 counts the number of clock pulses that occur between each "falling edge" of the speed signal. The number of clock pulses represents a value that is proportional to the period of the speed signal, Col. 3, Lines 53-65).
Regarding claim 19, Athikessavan teaches wherein the determining of the fault level of the target system includes: comparing the calculated deviations of one or more parameters to corresponding predetermined threshold values (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]).
Regarding claim 20, Athikessavan teaches wherein the determining of the fault level of the target system further includes: determining the fault level of the target system to be a first fault level if none of the calculated deviations is greater than or equal to a corresponding predetermined threshold value; and determining the fault level of the target system to be a second fault level if at least one of the calculated deviations is greater than or equal to the corresponding predetermined threshold value (At step 922, the online anomaly indicator value is compared with the baseline anomaly indicator value of the corresponding loading condition. A decision is determined whether the online anomaly indicator value is greater than (BAIV?AIT), i.e. whether the online anomaly indicator value is greater than the BAIV by a threshold, [0131]; During the initial calibration stage, the computed set of load values are a set of baseline load values. During online monitoring, the computed set of load values are a set of online load values, which may be computed during online monitoring over a period, which varies from 1 second to 20 seconds, [0081]; Note that calibration period 1 to 20 seconds equates to the periods found in [0066]).
Regarding claim 24, Athikessavan teaches a common output terminal (system bus 1328, [0180]), wherein the circuit is configured to superimpose another output signal that carries information about the repetitive motion of the target object onto the output signal indicating the fault level is a second output signal (Figs. 6A-C and [0104]-0105] teach examples of superimposed signals that indicate fault), wherein the superimposed signal is provided at the common output terminal ([0180] teaches output of sensor to system bus 1328).
For the above claims 18-20 and 24, it would have been obvious to one of ordinary skill in the art before the time of filing to simply substitute the velocity calculation of Athikessavan with speed detection of Doan because the substitution would provide predictable results for measuring speed/velocity from a vibration signal. The above findings satisfies the Graham factual inquiries stated in MPEP 2143 B regarding simple substitution of one known element for another to obtain predictable results.
Additionally for the above claims 18-20 and 24, Athikessavan does not teach, “a plurality of magnetic field sensing elements”, “the sensor is provided within a single integrated circuit (IC) package located about the target object.” However, Guettinger teaches it is known in the art to incorporate magnetic field elements H1 and H2 ([0041] and Fig. 1C) within a single magnetic field sensor module 6, and further arrange a plurality of magnetic field sensors and a sensor circuitry accommodated (i.e. integrated) in the same chip ([0029]) proximal to a subject (see Fig. 1C). As such, it would have been obvious to the ordinary artisan to package magnetic flux sensor 214 into a package taught by Guettinger. One would be motivated to do so for at least the purpose of providing a differential measurement signal generated by two sensor elements for robustness to homogenous external stray magnetic fields ([0030]).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Athikessavan, Doan, and Guettinger as applied to claim 5 above, and further in view of Zhang.
Regarding claim 7, Athikessavan and Doan do not teach, “wherein at least one of the parameters has two or more corresponding predetermined threshold values, wherein the determining of the fault level of the target system further includes: determining the fault level of the target system to be a first fault level if the calculated deviation of the at least one of the parameters is less than a first corresponding predetermined threshold value; determining the fault level of the target system to be a second fault level if the calculated deviation of the at least one of the parameters is greater than or equal to the first corresponding predetermined threshold value and less than a second corresponding predetermined threshold value; and determining the fault level of the target system to be a third fault level if the calculated deviation of the at least one of the parameters is greater than or equal to the second corresponding predetermined threshold value.” However, Zhang teaches these deficiencies (p. 5 teaches first, second and third thresholds, with each teaching varying level of fault and response). It would have been obvious to one of ordinary skill in the art at the time of invention to incorporate the calculation of phase difference of Zhang into the fault detection of Athikessavan. One would have been motivated to do so for at least the purpose of improving fault detection to estimate torque, for following degradation (p. 11).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable Athikessavan, Doan, and Guettinger as applied to claim 8 above, and further in view of US 20220373402 (herein Wyatt).
Regarding claim 10, Athikessavan and Doan do not teach, “wherein the auto-calibrating of the reference values is responsive to a user command.” However, Wyatt teaches it is known in the art that calibration can occur based on user selection ([0028]). It would have been obvious to one of ordinary skill in the art at the time of invention to allow user selection (taught by Wyatt) for initializing the self-calibration of Athikessavan. One would have been motivated to combine the inventions as an obvious design choice to have an additional level of control of calibration.
Claim(s) 14 and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Athikessavan, Doan, and Guettinger as applied to claim 1 above, and further in view of Zhang.
Regarding claim 14, Athikessavan and Doan do not teach, “wherein the receiving of the one or more magnetic field signals sensed by the plurality of magnetic field sensing elements of the sensor includes receiving a first magnetic field signal sensed by a first magnetic field sensing element and receiving a second magnetic field signal sensed by a second magnetic field sensing element, wherein the one or more parameters include a parameter indicative of a phase difference between the first and second magnetic field signals, wherein the processing of the one or more magnetic field signals to detect the values of the one or more parameters includes: generating a first phase signal responsive to a phase of the first magnetic field signal; generating a second phase signal responsive to a phase of the second magnetic field signal; and calculating the phase difference between the first and second magnetic field signals based on a comparison of the first and second phase signals.” However, Zhang teaches these deficiencies (three current sensors 127, p. 11; Note; p. 9 teaches and it is known in the art that magnetic flux is proportional to voltage or current and may be sensed using current; Specifically, in the first combination, the current ia of a and b phase and ib and rotor position theta r combination; in the second combination, b and c-phase current ib and ic and rotor position theta r combination; and in the third combination, a and c-phase current ia and ic and rotor position theta r combination, p. 11). It would have been obvious to one of ordinary skill in the art at the time of invention to incorporate the calculation of phase difference of Zhang into the fault detection of Athikessavan. One would have been motivated to do so for at least the purpose of improving fault detection to estimate torque, for following degradation (p. 11).
Regarding claim 25, Guettinger teaches “wherein the phase difference depends on a placement and orientation of the plurality of magnetic field sensing elements provided within the single IC package” (two Hall sensor elements H1 and H2 may generate sensor signals Sx1 and Sx2, respectively, that are phase-shifted with respect to each other with the phase-shift being proportional to the lateral distance, [0045]). To reiterate the previously-stated motivation, one would be motivated to combine Guettinger with Athikessavan for at least the purpose of providing a differential measurement signal generated by two sensor elements for robustness to homogenous external stray magnetic fields ([0030]).
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Athikessavan, Doan, and Guettinger as applied to claim 8 above, and further in view of US 6598195 (herein Adibhatla).
Regarding claim 22, Athikessavan teaches “wherein the auto-calibrating the reference values of one or more parameters includes: processing the one or more magnetic field signals to detect the reference values of one or more parameters”(During the initial calibration stage, the computed set of load values are a set of baseline load values, [0081]). Athikessavan does not appear to teach, “in response to determining that the detected reference values deviate from previous reference values by more than to a threshold value: disregarding the detected reference values, and providing an output indicating a failure of the auto-calibrating.” However, Adibhatla teaches such a calibration operation is known in the art. Adibhatla teaches a difference between the actual sensor value and the modeled sensor value is then computed and compared to a predetermined threshold. A sensor fault is detected if the difference is greater than the predetermined threshold. Once a sensor fault is detected, it is isolated (Abstract). Isolation would equate to disregarding of the present invention. It would have been obvious to one of ordinary skill in the art before the time of filing to incorporate the operations taught by Adibhatla into the calibration of Athikessavan. One would be motivated to do so for at least the purpose of reduce false negatives and false positives (Col. 1, Lines 44-51).
Response to Arguments
Applicant's arguments filed 11/19/2025 have been fully considered but they are not persuasive.
Applicant states “modifying Athikessavan to use a single sensor pack would entirely change the principle of operation of that reference.” However, the Office is not implying to place sensors 214, 216, in a single package. Rather, the Office states that design of a single magnetic sensor (such as 214) is known in the art to utilize multiple elements—i.e. sensor 214 is composed of more than one magnetic sensor ‘element.’ Guettinger teaches a common example of a single sensor module “package” 6 integrated together, including sensor elements H1 and H2, and corresponding circuitry. One of ordinary skill in the art would understand sensors 214, 216 of Athikessavan may be constructed similar to the module package 6 of Guettinger.
Applicant states Athikessavan relies on multiple sensor devices. The Office disagrees--Athikessavan may still function with only one vibration flux signal ([0019]), with multiple flux sensors included in other embodiments. This magnetic flux measurement using a single package would work equivalently to Guettinger’s sensor, with elements spaced apart radially.
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.
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/WALTER L LINDSAY JR/Supervisory Patent Examiner, Art Unit 2852
/PHILIP T FADUL/Examiner, Art Unit 2852