Label Stop Sensor Gap Detection Using FFT Signal Processing
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Solution Overview
Problem
Conventional label stop sensors (LSSs) often fail to accurately detect gaps between labels on continuous media, leading to material waste and incorrect detection of label characteristics as gaps.
Innovation Solution
The implementation of a label stop sensing device that uses a photoelectric sensor combined with a Fast Fourier Transform (FFT) module to accurately detect gaps by converting time domain signals to frequency domain signals, filtering out false detections, and utilizing stored tables to predict gap locations and distinguish between label boundaries and background noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional label stop sensors are used to detect gaps between labels, then the device complexity is reduced, but the measurement precision deteriorates leading to missed gap detections and false positives
Solution Approach 1:
The sensor signal processing is segmented into distinct stages: raw signal acquisition, FFT transformation, threshold comparison, and gap confirmation. This segmentation allows each stage to perform a specific function, improving overall detection accuracy while keeping the system manageable. The segmentation of detection into multiple processing steps enables the system to distinguish between genuine gaps and false signals more effectively.
Solution Approach 2:
The Fast Fourier Transform (FFT) module acts as an intermediary between the photoelectric sensor and the gap detection logic. It transforms the time-domain sensor signals into frequency-domain representations, providing an intermediate processing layer that enhances the ability to identify genuine gap patterns while filtering out noise and false detections from pre-printed label content.
2Reliability
If simpler sensor systems are used, then the device complexity is reduced, but the reliability deteriorates causing material waste
Solution Approach 1:
The system incorporates feedback mechanisms where the FFT-processed signal is continuously compared against stored threshold values and gap patterns. This feedback loop allows the system to learn from previous detections and adjust its sensitivity, reducing false positives and missed detections. The feedback from the gap detection results also feeds back into the media feeding control to ensure accurate label positioning.
Solution Approach 2:
The system performs preliminary actions by pre-processing the sensor signal through FFT transformation and pre-establishing threshold values and gap patterns in memory before actual gap detection occurs. This preliminary preparation enables the system to quickly and reliably identify genuine gaps when they occur, improving detection reliability without requiring complex real-time processing during the critical detection moment.
3Productivity
If traditional gap detection methods are used, then the manufacturing precision is maintained, but the productivity decreases due to material waste from false detections
Solution Approach 1:
The system changes the parameter domain from time-domain signal processing to frequency-domain processing using FFT. This parameter transformation enables more effective differentiation between genuine gap patterns and false signals from pre-printed content. By operating in the frequency domain, the system can identify periodicities and patterns that are characteristic of actual gaps while filtering out spurious signals, thereby reducing false detections and associated media waste.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution minimizes missed gap detection and false positives, ensuring precise feeding and printing within label boundaries, thereby reducing material waste and improving printing accuracy.
Implementation Method 1
A photoelectric sensor combined with a Fast Fourier Transform (FFT) module is used to detect gaps between labels on continuous media
Data Source
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AI summary
A printing device comprises: a media feeding mechanism configured to feed print media through a print area of the printing device, the print media including a plurality of labels separated by a plurality of gaps; a printing mechanism configured to print on the labels of the print media; and a label stop sensing device configured to sense the gaps between the labels on the print media, the label stop sensing device further configured to provide a control signal for controlling the media feeding mechanism and the printing mechanism; wherein the label stop sensing device comprises a gap detection module configured to receive a time domain signal and perform a transform to obtain a frequency domain signal to predict the locations of the gaps.