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
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, 2, 12, and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Someda as applied to claim 1 above, and further in view of US 6208268 (herein Scarzello) and Non-Patent Literature titled, “Estimation of vehicle count from the structural response of a bridge” (herein Strain).
Regarding claim 1, Someda teaches A structure evaluation system (detection system, [0032]) comprising:
a plurality of first sensors configured to detect elastic waves generated from the inside of a structure on which a vehicle travels (AE sensor groups 110, 120, [0058]);
one or more second sensors configured to detect passage of the vehicle without depending on damage in the structure (camera 310, [0113]);
a vehicle information estimator configured to estimate vehicle information including at least information of the number of vehicles passing on the structure on the basis of detection results from the one or more second sensors (traffic volume measuring device 300, [0113]); and
an evaluator configured to evaluate a deterioration state of the structure on the basis of the plurality of elastic waves detected by the plurality of first sensors and the vehicle information estimated by the vehicle information estimator (information processing device 400 includes the deterioration detector 410 that detects the state of the bridge structure 10, [0114]).
Additionally regarding claim 1, Someda and Scarzello do not teach, “wherein the one or more second sensors are one or more magnetic sensors configured to detect change in a magnetic flux density.” However, Scarzello teaches it is known in the art to provide magnetic sensors (12, 14, Col., 3, Line 12) to determine magnitude and direction of magnetic forces, which is equivalent to finding magnetic flux density, for motor vehicle surveillance on roadways (Col. 1, Lines 53-56). It would have been obvious to one of ordinary skill in the art before filing to simply substitute ultrasonic sensors found in traffic measuring device 300 of Someda with the magnetic sensors 12, 14, of Scarzello because both measure output curves to detect vehicle traffic volume and flow.
Further regarding claim 1, Someda and Scarzello do not teach, “wherein the vehicle information estimator estimates, as the number of vehicles passing on the structure, the number of peaks of output signals of the one or more second sensors.” However, Strain teaches structural response having peaks (see Fig. 3, each peak associated with a vehicle) to count vehicles travelling across a bridge (Secs. 3-4, p. 752-756).
Regarding claim 2, Someda teaches “wherein the vehicle information estimator estimates the vehicle information on the basis of the change Graham factual inquiries stated in MPEP 2143 B regarding simple substitution of one known element for another to obtain predictable results.
Regarding claim 12, Someda teaches wherein the one or more second sensors are provided in a range which is surrounded by the plurality of first sensors (Fig. 22 teaches AE sensors 121A and 121B surrounded by AE sensors 111A and 111B).
Regarding claim 13, Someda teaches A structure evaluation method comprising:
estimating vehicle information including at least information of the number of vehicles passing on a structure on the basis of a sensing result from one or more second sensors detecting passage of a vehicle without depending on damage in the structure (traffic volume measuring device 300 is installed on, for example, the bridge structure 10, and measures the traffic volume of vehicles V (for example, the number of vehicles V) passing through the bridge structure 10. The traffic volume measuring device 300 includes, for example, a camera 310, [0113]); and
evaluating a deterioration state of the structure on the basis of the plurality of elastic waves detected by a plurality of first sensors detecting elastic waves generated from a structure on which a vehicle travels and the estimated vehicle information (deterioration detector 410 that detects the state of the bridge structure 10, [0114]; detection device 100 is an acoustic emission (AE)-type detection device, installed in the bridge structure 10, which detects an elastic wave generated in the bridge structure 10 The AE-type detection device detects, for example, an elastic wave generated in association with the generation of a fatigue crack in a structure or the development of the fatigue crack, [0057]; [0147] and Fig. 15 teaches eleastic wave detection S11 and use of traffic S16 for output).
Additionally regarding claim 13, Someda does not teach, “wherein the one or more second sensors are one or more magnetic sensors configured to detect change in a magnetic flux density.” However, Scarzello teaches it is known in the art to provide magnetic sensors (12, 14, Col., 3, Line 12) to determine magnitude and direction of magnetic forces, which is equivalent to finding magnetic flux density, for motor vehicle surveillance on roadways (Col. 1, Lines 53-56). It would have been obvious to one of ordinary skill in the art before filing to simply substitute ultrasonic sensors found in traffic measuring device 300 of Someda with the magnetic sensors 12, 14, of Scarzello because both measure output curves to detect vehicle traffic volume and flow.
Further regarding claim 13, Someda and Scarzello do not teach, “wherein the estimating as the number of vehicles passing on the structure number of peaks of output signals of the one or more second sensors.” However, Strain teaches structural response having peaks (see Fig. 3, each peak associated with a vehicle) to count vehicles travelling across a bridge (Secs. 3-4, p. 752-756).
Regarding claims 1, 2, 12, and 13, it would have been obvious to one of ordinary skill in the art to simply substitute the signal processing of Scarzello with the peak detection means of Strain because both would provide predictable results for detecting vehicle traffic volume. 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.
Claim(s) 4-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Someda, Scarzello and Strain as applied to claim 1 above, and further in view of US 20220187253 (herein Takamine).
Regarding claim 4, Someda does not teach, “a position locator configured to locate positions of sources of a plurality of elastic waves on the basis of the plurality of elastic waves detected by the plurality of first sensors; a distribution generator configured to generate an elastic wave source density distribution indicating a density distribution of positions of sources of the plurality of elastic waves on the basis of a location result from the position locator; and a corrector configured to correct the elastic wave source density distribution generated by the distribution generator on the basis of the vehicle information estimated by the vehicle information estimator, wherein the evaluator evaluates the deterioration state of the structure using the elastic wave source density distribution.” However, Takamine teaches the deficiencies of Someda (position locator 423 performs position locating of an elastic wave source on the basis of sensor position information, [0066]; distribution generator 424 generates an elastic wave source density distribution using the elastic wave source distribution, [0069]; corrector 425 corrects information based on position locating performed by the position locator 423).
Regarding claim 5, Takamine further teaches the deficiencies of Someda, specifically: “wherein the corrector calculates a density in a predetermined range by dividing the number of elastic wave sources of which positions have been located in the predetermined range by an area of the predetermined range and corrects the elastic wave source density distribution by dividing the calculated density by the number of vehicles included in the vehicle information” (evaluator 426 sets a plurality of areas of a predetermined range on the elastic wave source density distribution AD after correction. In accordance with this, the evaluator 426 divides each area on the elastic wave source density distribution AD after correction. The evaluator 426 performs comparison with the threshold 15 for each divided area (hereinafter referred to as a “divided area”). For example, the evaluator 426 compares the density of the inside of the divided area with the threshold 15, [0159]; [0090]-[0093] further teach corresponding correction calculation).
Regarding claim 6, Someda does not teach, “a position locator configured to locate positions of sources of a plurality of elastic waves on the basis of the plurality of elastic waves detected by the plurality of first sensors; and a distribution generator configured to generate an elastic wave source density distribution indicating a density distribution of the positions of the sources of the plurality of elastic waves obtained on the basis of the vehicle information estimated by the vehicle information estimator and a location result from the position locator, wherein the evaluator evaluates the deterioration state of the structure using the elastic wave source density distribution.” However, Takamine teaches the deficiencies of Someda (position locator 423 performs position locating of an elastic wave source on the basis of sensor position information, [0066]; distribution generator 424 generates an elastic wave source density distribution using the elastic wave source distribution, [0069]; evaluator 426 evaluates a deterioration state of the structure 50 using the elastic wave source density distribution AD after correction output from the corrector 425, [0094]).
Regarding claim 7, Takamine further teaches the deficiencies of Someda, specifically: “a signal processor configured to extract a feature of the plurality of elastic waves by performing signal processing on the plurality of elastic waves output from the plurality of first sensors, wherein the vehicle information estimator further estimates one of a vehicle type, a vehicle length, a vehicle weight, a traveling lane, and a vehicle speed of the vehicle as the vehicle information on the basis of output signals of the one or more second sensors and outputs the estimation result to the signal processor, wherein the signal processor identifies the extracted feature of the plurality of elastic waves on the basis of the estimation result output from the vehicle information estimator and outputs the identified feature of the plurality of elastic waves, and wherein the evaluator evaluates the deterioration state of the structure on the basis of the feature of the plurality of elastic waves output from the signal processor and the vehicle information estimated by the vehicle information estimator” (a configuration in which a plurality of sensors 20-1 to 20-n are connected to one signal processor 30, [0143]; acquirer 421 obtains… traffic volume information of the vehicle 10 is information representing how many vehicles 10 of a certain vehicle type have passed through the structure 50 in a predetermined period, [0063]; evaluator 426 evaluates a deterioration state of the structure 50, [0094]).
Regarding claim 8, Takamine further teaches the deficiencies of Someda, specifically: “wherein the vehicle information estimator classifies one of a vehicle type, a vehicle length, a vehicle weight, a traveling lane, and a vehicle speed of the vehicle into a plurality of classes using a trained model for classifying one of a vehicle type, a vehicle length, a vehicle weight, a traveling lane, and a vehicle speed of the vehicle into a plurality of classes with one or more of amplitude, sustainment time, envelope area, gravity center frequency, and maximum frequency out of features acquired from output signals of the one or more second sensors as an input” (acquirer 421 obtains… traffic volume information of the vehicle 10 is information representing how many vehicles 10 of a certain vehicle type have passed through the structure 50 in a predetermined period, [0063]; [0084] teaches tread width may differentiate types of vehicles, using running part position).
Regarding claim 9, Takamine further teaches the deficiencies of Someda, specifically: “a signal processor configured to extract a feature of the plurality of elastic waves by performing signal processing on the plurality of elastic waves output from the plurality of first sensors, wherein the vehicle information estimator further estimates one of a vehicle type, a vehicle length, a vehicle weight, a traveling lane, and a vehicle speed of the vehicle as the vehicle information on the basis of output signals of the one or more second sensors and outputs the estimation result to the signal processor, wherein the signal processor adds the estimation result to the extracted feature of the plurality of elastic waves on the basis of the estimation result output from the vehicle information estimator and outputs the added feature, and wherein the distribution generator generates the elastic wave source density distribution for each class on the basis of the feature of the plurality of elastic waves output from the signal processor, the estimation result, and the vehicle information estimated by the vehicle information estimator” (signal processor 30, [0143]; elastic wave propagation speed v may be obtained, [0065]; acquirer 421 obtains… traffic volume information of the vehicle 10 is information representing how many vehicles 10 of a certain vehicle type have passed through the structure 50 in a predetermined period, [0063]; [0084] teaches tread width may differentiate types of vehicles, using running part position).
Regarding claim 10, Takamine further teaches the deficiencies of Someda, specifically: “a class selector configured to select a specific class in accordance with an instruction input from the outside, wherein the class selector displays the elastic wave source density distribution corresponding to the selected class on a display” (acquirer 421 may obtain the vehicle information--such as certain vehicle type--in accordance with an input of a user, [0063]; display 44 generates a video signal for displaying an evaluation result, [0073]).
Regarding claim 11, Takamine teaches the deficiencies of Someda, specifically: “wherein the one or more second sensors are a plurality of second sensors, wherein the plurality of second sensors are arranged in a vehicle traveling axis direction” (second AE sensor group 120 includes a plurality of AE sensors 121 (for example, four AE sensors 121A, 121B, 121C, and 121D), [0067], see Fig. 6). It would have been have been obvious to one of ordinary skill in the art before the time of filing to incorporate the positions of sensors taught by Takamine into the detection system of Someda. Such is a mere rearrangement of parts and an obvious design choice and, according to MPEP § 2144.04 VI. C, may be held unpatentable because the rearrangement would not affect the operation of the device. See In re Japikse, 181 F.2d 1019, 86 USPQ 70 (CCPA 1950). Note that according to MPEP § 2144, “Office personnel may invoke legal precedent as a source of supporting rationale when warranted and appropriately supported.”
Additionally regarding claim 11, Someda does not teach, “wherein the vehicle information estimator estimates a vehicle speed of the vehicle on the basis of a time difference between times at which passage of the vehicle has been detected by the plurality of second sensors.” However, Scarzello teaches this method of determining speed is known in the art (Vehicle speed is determined by a time-distance relationship using at least one of the first and second time intervals and the known distance. Vehicle length is determined by a time-speed relationship using the third time interval and the determined vehicle speed, Col. 2, Lines 25-29). It would have been obvious to one of ordinary skill in the art before the time of filing to incorporate the speed calculation of Scarzello into the combined detection system of Someda, Scarzello, and Takamine. One would be motivated to do so for at least the purpose of providing greater sensitivity to detect motor vehicles (Col. 1, Line 50).
For the above claims 4-11, it would have been obvious to one of ordinary skill in the art before the time of filing to incorporate the elements noted above of Takamine into the detection system of the combination of Someda, Scarzello and Strain. One would be motivated to do so for at least the purpose of correcting structure evaluation information to accommodate for position locating ([0017]).
Response to Arguments
Applicant’s arguments filed 6/12/2025 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. Someda and Scarzello remain relevant as presented above and in the previous Office Action. However, the Office introduces Strain to show that it is common to process peaks of structure responses to detect and count vehicles crossing the structure.
Conclusion
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/WALTER L LINDSAY JR/Supervisory Patent Examiner, Art Unit 2852
/PHILIP T FADUL/Examiner, Art Unit 2852
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