Prosecution Insights
Last updated: April 19, 2026
Application No. 18/509,077

Method and Rail Vehicle for Detection of a Flaw or Flaws in a Railway Track

Non-Final OA §103
Filed
Nov 14, 2023
Examiner
LIN, CHENG XI
Art Unit
3615
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Technische Universiteit Delft
OA Round
1 (Non-Final)
85%
Grant Probability
Favorable
1-2
OA Rounds
3y 3m
To Grant
99%
With Interview

Examiner Intelligence

Grants 85% — above average
85%
Career Allow Rate
258 granted / 305 resolved
+32.6% vs TC avg
Moderate +14% lift
Without
With
+14.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
26 currently pending
Career history
331
Total Applications
across all art units

Statute-Specific Performance

§101
0.1%
-39.9% vs TC avg
§103
55.4%
+15.4% vs TC avg
§102
23.4%
-16.6% vs TC avg
§112
17.2%
-22.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 305 resolved cases

Office Action

§103
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 is the first non-final office action on the merits. Claims 1-4 are currently pending. Priority Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. FILLIN "Insert series code and serial no. of parent." NL2028399 , filed on FILLIN "Enter the date filing of the parent application." 06/07/2021 . Information Disclosure Statement The information disclosure statement (IDS) submitted on 11/14/2023 has been received and considered by the examiner. Drawings The drawings are accepted. 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 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over FILLIN "Insert the prior art relied upon." \d "[ 2 ]" Furutani et al. (EP 2436574 A1, provided), in view of Li et al. (US 20150291192 A1) and Morita et al. (US 20210078619 A1). Regarding claim 1, Furutani teaches (Fig. 1-4): A rail vehicle (7) comprising: rail wheels accommodated to guide the rail vehicle along a railway track (Fig. 1), wherein each of the wheels is connected to the vehicle by an intermediate axle box (axle box 9) providing a bearing for the wheel (Fig. 1), and at least one accelerometer (acceleration meter 100), a measurement system (defect detection system 20) disposed on or external of the vehicle (Fig. 1), the measurement system (20) comprising a receiving portion (acceleration detector 11) for signals (voltage 21a) from the at least one accelerometer (100)(Fig. 1), and the measurement system (20) comprising a vehicle-railway track interaction model ( threshold storage 10 storing computed threshold values for comparison ) which generates an estimation (threshold alpha) of the expected signals from the at least one accelerometer (threshold alpha computed in advance via a test or analysis; para. 0039), wherein the receiving portion (11) and the vehicle-railway track interaction model (10) connect to a comparator (determination section 90) to compare the measured signals (RMS value amplitude ratio A) and the expected signals (alpha) from the at least one accelerometer (para. 0024; Fig. 4). Furutani does not explicitly teach that the at least one accelerometer is on the axle box. However, Li teaches an alternate flaw detection device for a railway track, wherein (Fig. 1): an axle box (7, 8) comprises at least one accelerometer (para. 0009; Fig. 1) to measure the vibrations on the track (para. 0017). It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, for Furutani to place the accelerometer on the axle box to measure a vibration o f the track, as disclosed by Li, with a reasonable expectation of success because it would provide high-frequency data for early detection of defects for monitoring rail head surface condition. Furutani does not teach the comparator connects to a tuning portion of the measurement system, which tuning portion is arranged to adjust parameters of the vehicle-railway track interaction model so as to provide a closer fit of the estimation of the expected signals from the at least one accelerometer with the measured signals from the at least one accelerometer. However, Morita teaches an alternate railway condition monitoring device, wherein (Fig. 1-3): a tuning portion (model generator 45) is arranged to adjust parameters of a vehicle-railway track interaction model (Learning model M1) so as to provide a closer fit of the estimation of the expected signals (state information acquired in advance) from the at least one accelerometer with the measured signals (state of the track) from the at least one accelerometer (Model generator 45 updat es the learning model M1 based on the measurement data of the state of the track; para. 0084; Claims 8-9; Fig. 3). It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, for Furutani to include a tuning portion to adjust parameters of a vehicle-railway track interaction model to provide a closer fit between the expected signals and the measured signals, as disclosed by Morita, with a reasonable expectation of success because updating the track interaction model over time would ensure “determination accuracy is maintained even if the relationship between the state information and the state of the track changes due to factors such as the season and years of use” (Morita, para. 0084). Regarding the instant claimed steps of method claim 4 note that the operation of the prior structure inherently requires the method steps as claimed (See rejection of claim 1 above) . Allowable Subject Matter Claims 2-3 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 claims . The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 2 , the prior art fails to teach the vehicle-railway track interaction model comprises a model of respective parts of the railway track selected from the group comprising rails, fasteners, rail pads, sleepers, ballast, slabs and substructures . While Furutani teaches (Fig. 1-4): the measurement system (20) comprising a vehicle-railway track interaction model ( threshold storage 10 storing computed threshold values for comparison ) which generates an estimation (threshold alpha) of the expected signals from the at least one accelerometer (threshold alpha computed in advance via a test or analysis; para. 0039); and the secondary reference Morita teaches an alternate railway condition monitoring device, wherein (Fig. 1-3): a tuning portion (model generator 45) is arranged to adjust parameters of a vehicle-railway track interaction model (Learning model M1) , neither reference teaches a vehicle-railway track interaction model of the railway parts including rails, fasteners, rail pads, sleepers, ballast, slabs and substructures . Such a modification would require improper hindsight reasoning and modifications to a modifying reference . Regarding claim 3, the prior art fails to teach the parameters of the vehicle railway track interaction model comprise tuning parameters of respective parts of the railway track selected from the group comprising stiffness, inertia, damping, and geometry irregularities . While Furutani teaches (Fig. 1- 4): the measurement system (20) comprising a vehicle-railway track interaction model (threshold storage 10 storing computed threshold values for comparison) which generates an estimation (threshold alpha) of the expected signals from the at least one accelerometer (threshold alpha computed in advance via a test or analysis; para. 0039); and the secondary reference Morita teaches an alternate railway condition monitoring device, wherein (Fig. 1-3): a tuning portion (model generator 45) is arranged to adjust parameters of a vehicle-railway track interaction model (Learning model M1), neither reference teaches a vehicle-railway track interaction model that is capable of tuning the stiffness, inertia, damping, and geometry irregularities of the track parts . Such a modification w ould require improper hindsight reasoning and modifications to a modifying reference. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure of a railway track flaw detection method using a vehicle-track interaction model : US-20200156676-A1 , US-11879814-B2 , US-11958513-B2 , US-12202531-B2 , JP-2004090848-A , WO-2011019273-A1 , JP-2011245917-A , WO-2015160300-A1 . Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT CHENG XI LIN whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-6102 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Mon. through Fri. 9:00am to 6:00pm EST . Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FILLIN "SPE Name?" \* MERGEFORMAT Samuel (Joe) Morano can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT 5712726684 . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHENG LIN/ Examiner, Art Unit 3615
Read full office action

Prosecution Timeline

Nov 14, 2023
Application Filed
Mar 27, 2026
Non-Final Rejection — §103 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
85%
Grant Probability
99%
With Interview (+14.2%)
3y 3m
Median Time to Grant
Low
PTA Risk
Based on 305 resolved cases by this examiner. Grant probability derived from career allow rate.

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