研究目的
Solving the problem of yarn color fault detection in yarn production by designing a special photoelectric sensor.
研究成果
The experimental results show that the design of photoelectric sensor can effectively detect yarn of different color faults. The method proposed in this paper to detect yarn fault is both valid and efficient.
研究不足
The experiment only tests the system's static performance due to the limitation of experimental conditions.
1:Experimental Design and Method Selection:
The paper designs a photoelectric sensor module consisting of a light source, reflective beam receiver, and through beam receiver to detect yarn color faults. The light path and driver circuit are designed to meet the requirements of the photoelectric sensor.
2:Sample Selection and Data Sources:
The experiment uses two different diameters of uniform white yarn production as yarn gauge, dyed with green, yellow, black, and orange to simulate different yarn color faults.
3:List of Experimental Equipment and Materials:
High brightness white LED as light source, photoelectric diode (model 2cu2e) as photoelectric receiver, Kohler lens for collimation light path, and condenser lens for photoelectric diode.
4:Experimental Procedures and Operational Workflow:
The yarn fault detection system collects data of 25KHz square wave using NI's PCI-6251 high precision data acquisition board, with data saved to .xcl file after the experiment.
5:Data Analysis Methods:
Data is de-noised using Matlab, and the system's static performance is tested.
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Precision Low Noise Op-Amp
AD8616
AD company
Used in the transresistance amplifier circuit
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White LED
Light source for the photoelectric sensor
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Photoelectric Diode
2cu2e
Beijing's north optoelectronic co., LTD
Photoelectric receiver for the photoelectric sensor
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Kohler Lens
Collimation light path for the photoelectric sensor
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Condenser Lens
Condenser light path for the photoelectric diode
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Operational Amplifier
OPA350
TI company
Used in the constant current driver circuit
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Data Acquisition Board
PCI-6251
NI company
Used for signal acquisition and processing based on virtual instrument
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