Abstract: The condition monitoring and early warning system for electrical equipment ensures the safety and stable operation of the equipment through real-time monitoring and early warning mechanisms. This paper proposes a design for an electrical equipment condition monitoring and early warning system based on deep learning. The system utilizes convolutional neural networks and recurrent neural networks to analyze and process the operation data of electrical equipment, achieving a complete process solution from data collection, data transmission, data preprocessing to model construction and real-time monitoring and early warning. The design of this system aims to improve the accuracy and timeliness of electrical equipment fault detection, ensuring the efficient operation and maintenance of the equipment.