The present disclosure discloses a photovoltaic array fault diagnosis method and apparatus based on a random forest algorithm. A strong classifier is constructed with many weak classifiers by integrating a plurality of decision trees, diagnosis results are generated by voting, and even if the diagnosis result of the most votes is wrong, the diagnosis results of the second and third more votes can be taken for reference of maintenance personnel, thereby improving the maintenance efficiency, and shortening the fault time of a system. The method and the apparatus resolve the problems of large data volume, long training time and the like of the conventional neural network algorithm, and can simply and quickly complete a diagnosis task and quickly implement the fault diagnosis of a small photovoltaic array, especially a 3×2 photovoltaic array.
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