Steel Plate Defect Classification Based on the Fractional Sliding Model Observer
Source abstract
Abstract
Aiming at the problem of steel plate defect classification, a new approach based on the fractional sliding model observer is proposed. Firstly, the sliding model observer is used to construct the defect detecting model of the steel plate. Then, the sliding model observer parameters are estimated using the detected data sequences and the fractional transform method which is inserted into the constructed model to transform the data sequences. By analyzing the constructed fractional sliding surface data, the digital defect features are extracted, which are used to implement the classification of steel plate defects. Finally, experiments demonstrate availability of the proposed method.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Industrial Vision Systems and Defect Detection · Structural Health Monitoring Techniques · Optical measurement and interference techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
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