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针对采用音频法测量球磨机料位时存在特征值随机性强等不确定性因素,引入云理论进行球磨机料位概念表示,并利用云模型实现球磨机料位测量。其过程是对数据进行预处理并提取特征值,然后采用逆向云算法对不同料位下振声信号的特征进行基本料位概念提取,经过概念提升成粗粒度的料位概念表示后,形成不确定性推理的前件云模型;同时依据料位值信息构造推理后件云模型,以此建立云不确定性推理规则集。最后,通过云模型规则推理实现球磨机料位的软测量。多种方法对比实验结果说明了模型的有效性和实用性。
Aiming at the uncertainties such as randomness and strong eigenvalue of the ball mill when using the audio method to measure the material level of the ball mill, a cloud theory is introduced to represent the concept of the ball mill material level, and the cloud model is used to measure the material level of the ball mill. The process is to preprocess the data and extract the eigenvalues. Then, the reverse cloud algorithm is used to extract the concept of basic level of the vibration signal under different levels. After the concept is upgraded to the concept of coarse level of material level, The former cloud model of deterministic inference; meanwhile, construct the cloud model of reasoning afterwards based on the material level information to establish the set of cloud uncertainty inference rules. Finally, soft measurement of ball mill level is achieved by cloud model rule reasoning. A variety of methods to compare the experimental results illustrate the effectiveness of the model and practicality.