Abstract:The realtime working conditions of the ball mill during the grinding process are complicated. It is difficult to accurately obtain the internal load status of the ball mill. In this study, the energy difference between the original cylinder vibration signal and the intrinsic mode function is utilized as the evaluation parameter of the adaptive variational mode decomposition (VMD) layer number. In this way, a new autocorrelation function is formulated. The intrinsic mode function is processed by introducing the RifeVincent selfconvolution window and the energy centrobaric method. A feature extraction method for ball mill load based on the adaptive VMD and the improved power spectrum estimation is proposed. The ball mill load identification system based on LabVIEW is developed. The number of layers of intrinsic mode function can be adaptively determined. The algorithm's abilities to resist modal aliasing and false components are enhanced. The accuracy of ball mill load detection is improved. Measurement results show that internal load features of ball mill during grinding process are effectively extracted, and the mill load status is accurately identified. This method provides accurate and reliable basis for the optimization control and efficiency improvement of the grinding. .txt