关键词: 模糊聚类, 软测量, 能耗, 径向基函数, 染纱

Abstract: Aiming at the measurement problem of energy consumption in dyeing process, a multiple neural network soft sensing modeling of dyeing energy consumption based on self-adaptive Fuzzy C-Means（FCM）clustering was proposed. The method adopted FCM to separate a whole real-time training data set into several clusters with different centers, and the clustering centers were modified by a self-adaptive fuzzy clustering algorithm. Each sub-set was trained by Radial Base Function Networks (RBFN), and then the outputs of sub-models were combined to obtain the final result. This method was simulated by a soft sensing modeling of energy consumption in dyeing process and a practical case study. The results demonstrated that the method made significant improvement in model prediction accuracy and robustness with a good online measurement capability with manufacturing executive system.

Key words: fuzzy clustering, soft sensing, energy consumption, radial base fuction, dyeing