Full
Outline
In order to improve the accuracy of photovoltaic array fault diagnosis, an improved artificial neural network (ANN) method for photovoltaic array fault detection is proposed. In ANN, a gated convolutional layer, a flat layer and a fully connected layer are added to replace hidden layer, which solves the problem of gradient disappearance easily in existing ANN. Adaptive Softmax is used as the activation function of the output layer of the model to reduce the computational time incurred due to the large data set size. The simulation model of photovoltaic array was established by using MATLAB to obtain the simulation operation data of different states. Meanwhile, the actual unbalanced operation data set of photovoltaic array was obtained from the literature, and the diagnostic performance of the improved ANN was compared with the six machine learning methods mentioned in the literature, showing the diagnostic performance advantages of the proposed method.
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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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