Federated learning (FL) facilitates the collaborative optimization of fault diagnosis models across multiple clients. However. the performance of the global model in the federated center is contingent upon the effectiveness of the local models. Low-quality local models participating in the federation can result in negative transfer within the FL framework. https://www.hacklinkci.com/