摘要
出于对提高明胶生产自动化程度、保证出胶质量的考虑,通过现场数据的采集,建立明胶骨素p H值的检测和浸泡液p H值的控制模型;结合C均值聚类和混合算法对F N N的检测和控制模型进行结构和参数辨识,在matlab环境下进行仿真,仿真结果表明,检测模型具有很好的学习能力和泛化能力,其误差可控制在[-0.1,0.1],控制模型使得浸泡液的pH值保持在4.0,与传统人工定时加酸相比,使得中和整个工序提前了5小时。
For the combination of C-means clustering and hybrid algorithm to improve the gelatin production automation to ensure that the adhesive quality considerations, through the collection of field data, the establishment of gelatin the osteoprotegerin pH value of the detection and soaking the pH of the control model;FNN detection and control of the model structure and parameter identification, simulation in matlab environment, simulation results show that the detection model of good learning and generalization ability, its error can be controlled in the [-0.1,0.1], the control model makes the immersion maintain the pH at 4.0, compared with the traditional artificial timing acid, making the whole process in advance by five hours.
出处
《自动化与仪器仪表》
2012年第5期187-188,共2页
Automation & Instrumentation
关键词
模糊神经
明胶骨素中和
C均值聚类
Fuzzy neural
Gelatin osteoprotegerin
C-means clustering
