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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/13/2024 was filed and is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 17, 19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chul (KR 102277633 B1, 2021).
Regarding claim 1, Chul teaches A rail inspection device comprising:
a traveling machine (Chul, see nearest image below, “The track inspection device”) that travels along a rail (Chul, see nearest image below, “The track inspection device”. “Track” is being interpreted as involving “rail”) and includes an optical system that acquires an image of an area of the rail being traveled (Chul, translated [0036], sentence 1, reproduced below:
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. “Track shooting camera” is being interpreted as involving “an optical system that acquires an image of an area of the rail being traveled” because of the “downward shooting of the track”); and
a main body having the traveling machine installed on an upper surface (Chul, see nearest image below, “map inspection controller” is being interpreted as involving “a main body” that is installed on an upper surface. Figure 4 shows non-exhaustive examples of this) and including an image analyzer that analyzes the image acquired from the optical system (Chul, [0036], sentence 2-3, reproduced below:
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. “Map inspection controller” that “converts the collected information…into map abnormality point information” is being interpreted as involving image analysis of the optical system data),
wherein the image analyzer:
sets at least one virtual area in the rail area image (Chul, Figure 15, the bounding box is being interpreted as involving at least one virtual area in the rail area image),
extracts an item image of an inspection target item within the virtual area (Chul, Figure 13, shows a non-exhaustive example of item image extraction of an inspection target item, a part of the rail, within the virtual area), and
inspects the inspection target item (Chul, see nearest image above, “map inspection controller” is being interpreted as involving inspection) by comparing the extracted item image with a normal image of the inspection target item (Chul, translated [0084], reproduced below:
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. The machine learning algorithm is being interpreted as involving comparing extracted item with normal image as part of the prediction process.).
Regarding claim 17, Chul teaches The rail inspection device of claim 1, wherein the main body has a built-in battery (Chul, translated [0039]: “generating power for the electric rotation of the picture camera”, which is being interpreted as involving a built-in battery) connected to the traveling machine (Chul, translated [0039]: “generating power…and a driving controller”, which is being interpreted as involving traveling machine), the optical system (Chul, translated [0039]: “generating power for the electric rotation of the picture camera”), and the image analyzer (Chul, translated [0084]: “data analysis unit”, is being interpreted as involving image analysis. PHOSITA would understand that these objects require electricity to run).
Regarding claim 19, Chul teaches A rail inspection method comprising:
providing a rail inspection device (Chul, see nearest image below, “track inspection device”) including:
a traveling machine (Chul, see nearest image below, “The track inspection device”) that travels along a rail (Chul, see nearest image below, “The track inspection device”. “Track” is being interpreted as involving “rail”) and includes an optical system that acquires an image of an area of the rail being traveled (Chul, translated [0036], sentence 1, reproduced below:
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. “Track shooting camera” is being interpreted as involving “an optical system that acquires an image of an area of the rail being traveled” because of the “downward shooting of the track”); and
a main body having the traveling machine installed on an upper surface (Chul, see nearest image below, “map inspection controller” is being interpreted as involving “a main body” that is installed on an upper surface. Figure 4 shows non-exhaustive examples of this) and including an image analyzer that analyzes the image acquired from the optical system (Chul, [0036], sentence 2-3, reproduced below:
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. “Map inspection controller” that “converts the collected information…into map abnormality point information” is being interpreted as involving image analysis of the optical system data),
setting at least one virtual area in the rail area image (Chul, Figure 15, the bounding box is being interpreted as involving at least one virtual area in the rail area image),
extracting an item image of an inspection target item within the virtual area (Chul, Figure 13, shows a non-exhaustive example of item image extraction of an inspection target item, a part of the rail, within the virtual area), and
inspecting the inspection target item (Chul, see nearest image above, “map inspection controller” is being interpreted as involving inspection) by comparing the extracted item image with a normal image of the inspection target item (Chul, translated [0084], reproduced below:
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. The machine learning algorithm is being interpreted as involving comparing extracted item with normal image as part of the prediction process.),
wherein whether a rail is in a normal installation state is inspected by inspecting the presence/absence of an abnormal object (Chul, see nearest image below, “predicts abnormal points”) to inspect an external state of the inspection target item (Chul, translated [0084], sentence 1, reproduced below:
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. “Machine learning algorithm that considers the types and interrelationships of data stored”, is being interpreted as involving “inspect an external state of the inspections target item”) or by inspecting an assembled state of the inspection target item (Chul, translated [0111], sentence 2, reproduced below:
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. Which shows non-exhaustive examples of “track misalignment points”, which is being interpreted as involving “inspecting an assembled state of the inspection target item”).
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) 2-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chul, in view of Choe (KR 102332917 B1, 2020).
Regarding claim 2, Chul teaches The rail inspection device of claim 1, wherein the rail area image includes:
a plurality of rails that appear to have narrow intervals in a first direction toward a vanishing point (Chul, Figure 15(a), which shows a non-exhaustive example of a plurality of rails on the bottom of the image. These rails then extend into the distance, or in the first direction, toward a vanishing point. PHOSITA and common human knowledge would know this happens when you look at human made parallel objects that go into the distance, such as with train tracks),
a plurality of yokes installed on the plurality of rails at intervals in a second direction toward the vanishing point (Chul, Figure 15(a), which shows a non-exhaustive example of a plurality of yokes on the top of the image and creates a U-shape down towards the rails, the grid like pattern is being interpreted as supporting the rail system),
a plurality of turn buckles (Chul, Figure 15(a), which shows a non-exhaustive example of a plurality of turn buckles which keep the rails straight on the bottom) installed on the plurality of rails at equal intervals (Chul, Figure 15(a), which shows a non-exhaustive example of a plurality of turn buckles which keep the rails straight on the bottom at equal intervals) along the second direction (Chul, Figure 15(a), which shows a non-exhaustive example of a plurality of turn buckles which keep the rails straight on the bottom along the second direction) with the yoke interposed therebetween (Chul, Figure 15(a), the yoke goes along the right side then appears to be interposed between the turn buckles) and appearing to be disposed on both sides of the plurality of yokes in the first direction (Chul, Figure 15(a), the yoke goes along the right side and left side and appears to be disposed on both sides of the plurality of yokes in the first direction), and
However, Chul does not appear to explicitly teach Litz wire supports and a ceiling support connected to upper portions of the plurality of turn buckles.
Pertaining to the same field of endeavor, Choe teaches
a plurality of Litz wire supports installed at intervals in the first direction between the plurality of rails (Choe, Figure 1, the pink shaded items are being interpreted as involving “Litz wire supports” as it looks similar to the instant application’s Litz wire support 12 in Figure 8, which are also installed at intervals in the first direction between the plurality of rails),
a ceiling support (Choe, Figure 1, the item the translucent and flat item on top near the ceiling is being interpreted as “a ceiling support”) connected to upper portions of the plurality of turn buckles (Choe, Figure 1, which shows the supports on both sides of the translucent item at the turn are being interpreted as “turn buckles”).
Chul and Choe are considered to be analogous art because they are directed to rail transport inspection systems and algorithms. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for rail transport inspection systems and algorithms (as taught by Chul) to include Litz wire supports and a ceiling support connected to upper portions of the plurality of turn buckles (as taught by Choe) because the combination provides improvement to real-time inspection productivity and efficiency (Choe, Abstract). Further, PHOSITA and the field of mechanical engineering would know that rails need support, otherwise they will buckle. It would be obvious to try to provide support to prevent rails for twisting and turning with the obvious result of either buckling or not buckling.
Regarding claim 3, Chul teaches The rail inspection device of claim 2, wherein the virtual area includes a rectangular box shape (Chul, Figure 15(a), which shows a non-exhaustive example of a rectangular box shape, which is being interpreted as involving the virtual area) elongated in the first direction in a lower area (Chul, Figure 15(a), which shows the bounding box elongated in the first direction in a lower area) along a third direction perpendicular (Chul, Figure 15(a), which shows the bounding box elongated in the first direction in a lower area along a third direction perpendicular) to the first direction and the second direction of the rail area image (Chul, Figure 15(a), which shows the bounding box elongated in the first direction in a lower area along a third direction perpendicular to the first direction and the second direction of the rail area image),
However, Chul does not appear to explicitly teach Litz wire supports.
Pertaining to the same field of endeavor, Choe teaches
and reveals information on the plurality of rails (Choe, [0008]: “At this time, inspection items regarding the installation status of the OHT rail include the rail step, width, clearance, and installation location of the guide rail.” “Inspection” is being interpreted as involving “reveals information”) and the plurality of Litz wire supports (Choe, Figure 1, the pink shaded items are being interpreted as involving “Litz wire supports” as it looks similar to the instant application’s Litz wire support 12 in Figure 8, which are also installed at intervals in the first direction between the plurality of rails).
Chul and Choe are considered to be analogous art because they are directed to rail transport inspection systems and algorithms. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for rail transport inspection systems and algorithms (as taught by Chul) to include Litz wire supports (as taught by Choe) because the combination provides improvement to real-time inspection productivity and efficiency (Choe, Abstract). Further, PHOSITA and the field of mechanical engineering (as a non-exhaustive example) would know that rails need support, otherwise they will buckle. It would be obvious to try to provide support to prevent rails for twisting and turning with the obvious result of either buckling or not buckling. Additionally, the Litz wire supports are part of the rail system. PHOSITA would want to inspect them as part of the system.
Regarding claim 4, Chul teaches The rail inspection device of claim 3, wherein the image analyzer (Chul, see nearest image below, “data analysis” is being interpreted to be used on images) includes a plurality of algorithms (Chul, see nearest image below, “machine learning algorithm” is being interpreted as involving ”plurality of algorithms”) through which the normal image of the inspection target item is trained (Chul, translated [0084], sentence 1, reproduced below:
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. “predicts abnormal points” is being interpreted as involving “normal image of the inspection target item is trained”. PHOSITA would know abnormal indicates “normal” exists),
the inspection target item includes the plurality of rails (Chul, translated [0036], sentence 1:
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”track shooting camera” is being interpreted as involving “the inspection target item includes the plurality of rails”), and
the item image of the plurality of rails (Chul, see nearest image below, “railway rail inspection”) is acquired in real time (Chul, see nearest image below, “in real time”) through the optical system (Chul, see nearest image below, “image-based data” which shows optical system is involved) to inspect the presence/absence of abnormal objects (Chul, translated [0081], reproduced below:
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. When combined with [0036], the railway rail inspection inspects the presence/absence of abnormal objects. The BRI for presence/absence is “OR”) including scratches, damage, or particles on the plurality of rails (Chul, translated [0111], sentence 2, reproduced below:
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. Which shows non-exhaustive examples of “damage”. Examiner notes this is an “OR” phrase, so only one item needs to be considered).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chul, as modified by Choe, in view of Prasongpongchai (“A vision-based method for the detection of missing rail fasteners”, 2017).
Regarding claim 5, Chul teaches The rail inspection device of claim 4, wherein the…, and
is trained in at least one of the plurality of algorithms (Chul, see nearest image below, “machine learning algorithm” is being interpreted as involving “plurality of algorithms”) to inspect whether the image matches the abnormal object found on the plurality of rails (Chul, translated [0084], reproduced below:
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. “Predicts abnormal points for each tunnel section” is being interpreted as involving abnormal object image matching found on the plurality of rails).
However, Chul and Choe does not appear to explicitly teach an image of the rail accessory or the hand tool.
Pertaining to the same field of endeavor, Prasongpongchai teaches
abnormal object further includes a rail accessory (Prasongpongchai, Figure 1 and text, which shows “missing rail fasteners”, which are being interpreted as a non-exhaustive example of the rail accessory) or a hand tool…
an image of the rail accessory (Prasongpongchai, Figure 1 and text, which shows “missing rail fasteners”, which are being interpreted as a non-exhaustive example of the rail accessory) or the hand tool…
Chul, Choe, and Prasongpongchai are considered to be analogous art because they are directed to rail transport inspection systems and algorithms. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for rail transport inspection systems and algorithms (as taught by Chul and Choe) to include image of the rail accessory or the hand tool (as taught by Prasongpongchai) because the combination reduces inspection time and human error (Prasongpongchai, Abstract). Further, PHOSITA would know humans may forget or leave tools or accessories around as part of a project; as this may affect the functioning of the rail transport system, it would be obvious to try to detect these abnormalities.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chul, in view of Yang (“Fine-Grained Visual Prompting”, 2023).
Regarding claim 16, Chul teaches The rail inspection device of claim 1, wherein the setting of the at least one virtual area in the rail area image divides the rail area image into the virtual area (Chul, Figure 15, which shows the bounding box that is being interpreted as dividing the rail area image into the virtual area)
However, Chul does not appear to explicitly teach blurs the remaining area.
Pertaining to the same field of endeavor, Yang teaches
and the remaining area, and blurs the remaining area (Yang, Abstract, “Consequently, our investigation reveals that a straightforward application of blur outside the target mask, referred to as the Blur Reverse Mask, exhibits exceptional effectiveness.” Figure 1 also shows everything outside the virtual area [the remaining area], mask, is blurred; look at the last row and column, for an example).
Chul and Yang are considered to be analogous art because they are directed to image analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for rail transport inspection systems and algorithms (as taught by Chul) to include blurs the remaining area (as taught by Yang) because the combination provides and improvement to visual perception using visual prompts (Yang, Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Zhakov et al (“Automatic Fault Detection in Rails of Overhead Transport Systems for Semiconductor Fabs”, 2019) discloses rail inspection method using machine learning of overhead hoist transport systems.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY B DUONG whose telephone number is (571)272-1358. The examiner can normally be reached Monday - Thursday 10a-9p (ET).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.B.D./Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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