PATENT CLAIM ANALYSIS

Application Number: 16070985
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-01
Patent Classification: ["156", "351000"]

Abstract:
A corrugated board sheet defect detecting device detects a defect in a single-faced cardboard sheet guided by a guide member with corrugated core paper facing outwards. The device includes a radiating device, an image capturing device, an image processing device, and an assessing device. The radiating device is configured to radiate light toward the core paper at a radiation angle relative to the single-faced cardboard sheet. The image capturing device is configured to capture an image of a portion of the core paper irradiated with the light. The image processing device is configured to a light portion and a dark portion in a direction in which the single-faced cardboard sheet is transported based on the captured image. The assessing device is configured to assess a quality by comparing a length of the light portion and a length of the dark portion.

Claim (Index 14):
The corrugated board sheet defect detecting device according to  claim 13 ,\n wherein the assessment value is a ratio between a total value of the lengths of the plurality of the light portions, on which quality assessment is already completed, and a total value of the lengths of the plurality of the dark portions, on which quality assessment is already completed.

Metadata:
- Claim Count in Document: 12.0
- Percentile: 95.0
- Lexical Diversity: 2.58621
- Patent Class: 156.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15564462', '12676990', '13389853', '14047253', '15742838']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.907738056727325
- 35 USC 102 Novelty (BERT): 0.5222702174621667
- Combined Prediction Score: 0.8691912728008091
- Mean Citation Score: 239.60249
- Max Citation Score: 276.15726
- Similarity Product: 144.6706659968734

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test