Inkjet Nozzle Defect Detection via Segmented Position Marks
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Solution Overview
Problem
Conventional inkjet printing devices face challenges in reliably detecting and identifying print defects, such as ejection failures or faulty gradations, especially when the end of a test pattern is not recorded, leading to inefficiencies in nozzle identification and potential misinterpretation of dust or foreign matter as position marks.
Innovation Solution
The implementation of an inkjet printing device with an inspection mode that records a test pattern including a print defect detection pattern and a position detection pattern, where the position detection pattern consists of linear patterns extending in the feeding direction, allowing for accurate identification of defective nozzles even when the test pattern end is missing or affected by dust.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional test patterns with reference marks are used for defect detection, then ejection failure detection is possible, but the process becomes complex and time-consuming due to image correlation processing requirements
Solution Approach 1:
The test pattern is segmented into multiple independent position marks, each consisting of a specific number of dots (e.g., 3 dots for first position mark, 5 dots for second position mark). This segmentation allows the system to detect and identify nozzle positions independently for each mark, eliminating the need for complex image correlation processing across the entire pattern, thereby reducing detection time while maintaining accuracy.
Solution Approach 2:
Different position marks are designed with locally distinct characteristics (different numbers of dots) to enable independent identification. The first position mark has a different number of dots than the second position mark, allowing the system to distinguish between them and perform localized defect analysis without processing the entire test pattern as a single unit, thus reducing overall processing time.
2Measurement precision
If rectangular reference marks are used for position detection, then nozzle position identification is achievable, but dust or foreign matter on the recording medium can be mistaken for position marks leading to detection errors
Solution Approach 1:
Position marks are designed with asymmetric characteristics in terms of dot counts (e.g., 3 dots vs. 5 dots) rather than using symmetric rectangular shapes. This asymmetry in the number of dots provides a more distinctive signature that is less likely to be confused with random dust particles or foreign matter, thereby reducing false positive rates while maintaining position detection accuracy.
Solution Approach 2:
The system detects position marks based on the number of dots (a discrete quantitative feature) rather than relying on shape recognition. By using the count of dots as the identifying characteristic, the system creates a more robust detection method that is less susceptible to misinterpretation by dust or foreign matter, as these contaminants typically do not form patterns with specific dot counts.
3Adaptability or versatility
If test patterns extend beyond the recording medium width to include end positions, then complete nozzle coverage is achieved, but the system becomes more complex and requires additional processing
Solution Approach 1:
The test pattern is divided into multiple discrete position marks distributed across the recording medium width. Each position mark is an independent unit with a specific dot configuration. This segmentation allows the system to detect nozzles at all positions including ends, while each mark can be processed independently, reducing the overall processing complexity compared to a single continuous pattern.
Solution Approach 2:
Position marks are pre-configured with distinctive dot patterns during test pattern generation. This preliminary design ensures that even position marks at the ends of the recording medium have identifiable characteristics, allowing complete nozzle coverage without requiring complex post-processing to interpret edge positions.
Data Source
AI summary
The present application discloses an inkjet printing device in which a nozzle that caused a print defect, such as an ejection failure, is reliably identified by a simple process even when an end of a test pattern is not recorded. In a configuration example of the inkjet printing device, a test pattern TPat to be printed for identifying a recording head nozzle that caused a print defect consists of an ejection failure detection pattern DPat and a position detection pattern PPat. The position detection pattern PPat consists of a position mark PM4 and pairs of position marks (PM1 and PM1; PM2 and PM2; and PM3 and PM3) symmetrically arranged with respect to the position mark PM4 in a sheet width direction. Each position mark consists of three linear patterns having the same length and disposed at equal intervals. Moreover, the position detection pattern PPat is configured such that linear pattern length decreases with increasing distance from a center position mark.