Research on Temperature Adaptive Control Method of Auxiliary Dialysis Equipment Based on RBF Neural Network

Aiming at the difficulties of slow heating rate, slow temperature response, easy to be affected by ambient temperature and low precision in the heating process of manual peritoneal dialysis auxiliary equipment, this paper deeply analyzes the heating control process of the equipment, designs a temperature adaptive control method of auxiliary dialysis equipment based on RBF neural network, and explores the efficient heating control system of auxiliary dialysis equipment. On the basis of collecting a large number of actual data in the heating process, the intelligent data processing algorithm is introduced. The RBF neural network algorithm is used to adaptively compensate the dialysate temperature, and the temperature detection value without compensation is compared. The temperature adaptive control method of auxiliary dialysis equipment based on RBF neural network can adjust the control parameters in real time and accurately, solve the problems of slow heating speed and low temperature accuracy caused by easy environmental impact and uneven heating in the heating process, and realize real-time accurate monitoring of dialysate temperature. The treatment accuracy reaches $\pm \mathbf{1}\ {{}^{\circ}\mathbf{C}}$, with high stability and heating efficiency. The temperature control effect is significantly improved, ensuring the safety and comfort of the product. It has significant application value for clinical treatment of peritoneal dialysis.