Theoretical and experimental study of a new defrost control strategy based on gray scale graph theory

Abstract

Frosting of the evaporators is inevitable during system operation. As such, defrosting must be conducted periodically to ensure stable and efficient operation of the system. However, the current control methods often cause ``mal-defrosting'' due to the complexity and randomness of frosting. To improve the defrosting accuracy of the system a new detection method for the amount of frost was proposed based on the image processing gray scale image theory. Further, the theory of combining the frosting characteristic parameter St with gray contrast C of the frosting image to forecast the critical defrosting time t of the system was established. Through experiments, the best defrosting times (tbest1 and tbest2) of the system were determined, compared with t. Additionally, a frosting error factor (FEF) was identified, compared with the St value of times(tbest1,tbest2 and t). The results show that there was a defrost lag in the defrost time determined by the existing defrost control method,the average time error TEF was by 177.25 s and 321 s. Finally, in view of the illumination effect, the influence of illumination intensity on the accuracy of the proposed method was explored. After changing the illumination intensity,new defrost control method still offers high control accuracy, TEF was by 64 s and 324 s. Overall, from the perspective of engineering applications, the proposed method can reduce the influence of illumination intensity on frosting image recognition, allowing the system to accurately judge the defrosting start point, thereby realising accurate defrosting.