Textural coarseness quantitative evaluation method based on signal detection theory

Abstract

The invention discloses a textural coarseness quantitative evaluation method based on a signal detection theory. The textural coarseness quantitative evaluation method comprises the steps that a textural coarseness perception experiment is carried out, the identifying results of perceiving different texture samples of a tester are recorded, the identifying results are contrasted with a normal distribution table to obtain the probability of texture false reporting after perception and the probability of correct texture answering after perception, and the coarseness discriminability index is calculated by combining the objective texture parameters of different texture samples; according to the correlation, the objective texture parameters serve as input, the quantized value of the texture coarseness based on the signal detection theory serve as output, a textural coarseness perception evaluation model is established, and the weight of the objective texture parameter in the model is acquired through nonlinear least squares fitting; and the objective texture parameters to be evaluated are substituted into the model and then output to obtain the corresponding textural coarseness quantized value. According to the textural coarseness quantitative evaluation method based on the signal detection theory, the stability of subjective perception results under the condition of limited experimental subjects is effectively improved, the accuracy of evaluation is improved, and the method can be widely applied to predicting of textural coarseness perception of mechanical arms.

Description

technical field [0001] The invention relates to a quantitative evaluation method of texture roughness based on signal detection theory, and belongs to the technical field of texture force tactile modeling and expression. Background technique [0002] Texture is the key factor for the human body to obtain the perceptual information of the surface of an object. The tactile perception mechanism of the human body to texture is complex. By quantifying subjective perception and establishing a subjective perception evaluation model, it can guide the prediction of perception results under different objective attributes, and is used to establish virtual Validation of textures. [0003] In traditional research, there are two main evaluation methods for tactile perception: objective evaluation method and subjective evaluation method. Zhang Jiankai used the finite element model to establish a perception model between the objective properties and roughness of the object when the finger ...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, provide a texture roughness quantitative evaluation method based on signal detection theory, and solve the existing texture roughness evaluation by establishing an evaluati

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