Device for testing performance of liquid crystal elastomer material array

Abstract

The invention provides liquid crystal elastomer material array performance testing equipment, which is characterized in that a non-contact optical camera is used for acquiring an image of a tested liquid crystal elastomer array module, and a machine vision learning method is used for learning image parameters of a liquid crystal elastomer array unit in different deformation states; the detection of the deformation performance of the liquid crystal elastomer array unit and the positioning of the abnormal unit are realized according to the image parameters.

Description

technical field [0001] The invention relates to the field of material performance testing, in particular to a testing device for the performance of a liquid crystal elastomer material array. Background technique [0002] Liquid crystal elastomer is a new type of material. It has both the unique positional order and orientation order of liquid crystal materials, and the elastic properties of general polymers. Therefore, it has some unique physical strain properties, such as soft elasticity, shape memory properties, thermotropic properties. Strain characteristics, photo-induced strain characteristics, etc. Just as liquid crystals are sensitive to external stimuli, liquid crystal elastomers are extremely sensitive to external fields such as heat, light, and electricity. Therefore, there is potential in various emerging industries, such as actuators, sensors, artificial muscles, shape memory materials, data storage, tunable lasers, etc. [0003] Because light is clean and poll...

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Problems solved by technology

[0005] In the prior art, artificial visual methods are usually used to judge the deformation of liquid crystal elastomer materials, but due to insufficient accuracy, it has caused obstacles to quantitative research

It is also proposed to use machine vision to detect material deformation, but the image algorithm is complex and the accuracy is low

Moreover, due to the special optical properties of liquid crystal elastomer materials, general material deformation image algorithms cannot accurately detect, and there is no image processing algorithm specifically for liquid crystal elastomer materials.

And most algorithms can only judge whether the deformation of the entire array is normal or abnormal, but cannot accurately locate the abnormal unit position

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