Fault detection method for intelligent low-voltage electric equipment

The invention relates to the field of fault detection, in particular to a fault detection method for intelligent low-voltage electric equipment. Comprising the following steps: acquiring a to-be-detected feature vector of target low-voltage electric equipment; inputting the to-be-detected feature vector into the target LSTM model, and generating a corresponding fault probability of the target low-voltage electric equipment in the first future time period; according to the method, when the LSTM is trained, historical power consumption characteristic data and historical environment characteristic data are added into a training sample, and temperature and humidity characteristic data of the environment in a prediction time period (namely a first future time period) are also added. Therefore, the LSTM model can more accurately capture the relationship between the fault and the historical feature data as well as the relationship between the fault and the future environment features. And thus, the probability of fa