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To improve the robustness of traditional brake disc surface defeet detection, an automatic detection instrument based on machine vision is designed. The defect features of brake discs are extracted using the Improved Gaussian Difference algorithm and Hough Transform algorithm (IGD-IHT). An identification method for brake disc surface defects is designed based on the Perception-based Image Quality Evaluator and Dempster rule-improved Bayes particle swarm optimization-Nonlinear echo state network to better identify defects. The experimental results show that accuracy of this method is more than 97%, the false alarm rate is less than 1.5%, and the missing alarm rate is less than 1.5%. The method described in this article is superior to traditional methods and improves the accuracy of brake disc surface defect recognition. Factory testing shows that this method can accurately identify almost all defects, and there are relatively few false positives or false negatives, and has high reliability and stability.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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