2results about How to "Solve the island problem" patented technology

This invention relates to the field of photovoltaic power generation fault diagnosis technology, and in particular to a photovoltaic array fault diagnosis system and method based on artificial intelligence. By encrypting and preprocessing multi-source data, a multimodal dataset is constructed, providing a comprehensive and collaborative data foundation for subsequent analysis. The collaborative diagnosis model can analyze the battery and inverter status in parallel. By combining circuit equivalent models, spatial adjacency relationships, and theoretical power models for calculation, the diagnosis results have physical interpretability. A physical consistency verification rule based on power flow analysis is introduced to cross-validate and logically fuse the preliminary diagnosis results, generating reliable comprehensive fault diagnosis results. This approach solves the technical problem in existing technologies that focus on independent analysis of single components such as photovoltaic cells or inverters, lacking effective fusion and collaborative utilization of multi-source heterogeneous data, which limits the accuracy of diagnosis results.

A product quality prediction system based on federated learning includes a server and clients set up on multiple production lines. The server sends an initial product quality prediction model and fused model parameters to the clients. The fused model parameters are obtained by fusing the model parameters sent by each client. The clients include: multiple sensors for collecting product manufacturing process data; a training set construction module for acquiring sensor data and performing feature extraction to construct a local training set; a model training module for training the acquired product quality prediction model using a forward propagation federated training method based on the local training set; encrypting and sending the model parameters during training to the server and updating the local product quality prediction model according to the fused parameters; stopping training when training requirements are met to obtain a trained product quality prediction model; and a product quality prediction module for performing quality prediction based on the trained product quality prediction model.