A detection method for raw silk cleaning defects

Abstract

The invention discloses a method for detecting raw silk cleaning defects. The existing method for detecting raw silk by using equipment is still not very high in coincidence rate of cleaning indexes. The method is characterized in that the raw silk cleaning defects are detected by using a combination of a capacitance sensor and a photoelectric sensor; the method comprises the steps of enabling raw silk to be detected to pass through the photoelectric sensor and the capacitance sensor; when the capacitance sensor detects a new defect, respectively recording the starting point, terminal point and diameter variation rate of the detected defect; when the photoelectric sensor detects a new defect, respectively recording the starting point, terminal point and diameter variation rate of the detected defect; when the capacitance sensor and the photoelectric sensor defect a defect at the same position, using an absolute value of a large value in the difference between the starting point and the terminal point of the defect to represent the length of the detected defect, and taking an absolute value of a large value in the change rate of the defect diameter to represent the diameter change rate of the detected defect. Compared with the traditional detection data, when being used for detecting the raw silk, the method provided by the invention enables the coincidence rate of the cleaning indexes to reach 95% or above.

Description

technical field [0001] The invention relates to the inspection of raw silk quality, in particular to a method for detecting cleaning defects of raw silk. Background technique [0002] The current national standards for raw silk still use the traditional blackboard test to evaluate the main quality indicators—raw silk evenness, cleanliness, and cleanliness. The blackboard inspection method is that the inspector inspects both sides of the blackboard piece by piece at a place 0.5 meters in front of the blackboard (2.1 meters for evenness inspection), and compares the cleaning sample photo, clean sample photo, and evenness sample photo to distinguish the types and quantities of various defects. Then according to the classification regulations of various defects, the cleanliness, cleanliness and evenness of raw silk are scored. The inspection principle is: in a specific lighting inspection room, use the area covered by the silk strip on the blackboard and the light transmission ...

AI Technical Summary

Problems solved by technology

[0003] The problems of the above inspection methods are: first, the blackboard inspection is a sensory inspection method, which is affected to a certain extent by factors such as the eyesight, quality, experience and emotion of the inspectors; second, there is a "minimum discrimination" phenomenon in the sensory inspection. For silk strips with similar evenness and cleanliness, it is often difficult to distinguish the difference; third, the degree of evenness change is affected by the Mach band effect of human vision, and it is easy to judge distortion, so that the reliability and reproducibility of raw silk grade evaluation are reduced.

[0007] The current detection method using equipment to detect raw silk, the compliance rate of the cleaning index is still not very high