The existing detection and evaluation technology for composite insulator mainly relies on offline methods, which is difficult to assess the ageing degree of insulators in large-scale operation quickly and conveniently. This article proposes a rapid detection and rating method for surface ageing degree of composite insulators based on hyperspectral technology. At first, the Fourier infrared spectral absorption peaks of Si-O-Si and Si-CH3 between the umbrella skirt and the substrate of aged composite insulator were compared, and then the ageing degree of insulator was rated. At last, the aging degree of insulator was classificated combining hyperspectral data with SVM algorithm models. The results show that the accuracy of the three classifications including slight, moderate, and severe is 71.8%, while the accuracy of the two classifications including sligh and severe is 97.3%. By using intensity threshold segmentation method, it is possible to remove contaminated areas from composite insulator images, and extract ageing areas.
| 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 |