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Reliability Assessment of CNC Machining Center Based on Weibull Neural Network

机译:基于威布尔神经网络的数控加工中心可靠性评估

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摘要

CNC machining centers, as the key device in modern manufacturing industry, are complicated electrohydraulic products. The reliability is the most important index of CNC machining centers. However, simple life distributions hardly reflect the true law of complex system reliability with many kinds of failure mechanisms. Due to Weibull model's versatility and relative simplicity and artificial neural networks' (ANNs) high capability of approximating, they are widely used in reliability engineering and elsewhere. Considering the advantages of these two models, this paper defined a novel model: Weibull neural network (WNN). WNN inherits the hierarchical structure from ANNs which include three layers, namely, input layer, hidden layer, and output layer. Based on more than 3000 h field test data of CNC machining centers, WNN has been successfully applied in comprehensive operation data analysis. The results show that WNN has good approximation ability and generalization performance in reliability assessment of CNC machining centers.
机译:CNC加工中心是现代制造业中的关键设备,是复杂的电动液压产品。可靠性是CNC加工中心最重要的指标。但是,简单的寿命分布很难反映出具有多种故障机制的复杂系统可靠性的真实规律。由于Weibull模型的通用性和相对简单性以及人工神经网络(ANN)的高逼近能力,它们被广泛用于可靠性工程和其他领域。考虑到这两个模型的优点,本文定义了一个新颖的模型:威布尔神经网络(WNN)。 WNN从ANN继承了层次结构,该ANN包括三层,即输入层,隐藏层和输出层。基于数控加工中心3000多个小时的现场测试数据,WNN已成功应用于综合运行数据分析。结果表明,WNN在数控加工中心可靠性评估中具有良好的逼近能力和泛化性能。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第23期|292197.1-292197.8|共8页
  • 作者单位

    Jilin Univ, Sch Mech Sci & Engn, Changchun 130025, Peoples R China;

    Jilin Univ, Sch Mech Sci & Engn, Changchun 130025, Peoples R China;

    Jilin Univ, Sch Mech Sci & Engn, Changchun 130025, Peoples R China;

    Jilin Univ, Sch Mech Sci & Engn, Changchun 130025, Peoples R China;

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