Fuzzy Reliability Estimation for Cutting Tools
Fuzzy Reliability Estimation for Cutting Tools
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DOI：
10.1016/j.procir.2014.06.057
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Shujie Liu;Hongchao Zhang;Chao Li;Huitian Lu;Yawei Hu
中科院分区：
文献类型：
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作者：
Shujie Liu;Hongchao Zhang;Chao Li;Huitian Lu;Yawei Hu
刀具是机床的重要组成部分，其可靠性直接影响机床的整体加工效率和稳定性。介绍了状态空间模型在刀具可靠性评估中的应用。针对单一评价阈值不易确定的问题，提出了模糊阈值的概念。我们使用性能或替代变量来模糊化系统的状态和成功/失败事件被视为模糊集。在试验中测量声发射信号，并从声发射信号中提取小波包（WP）能量来估计刀具状态。将系统的退化看作是一个连续退化的随机动态过程。通过卡尔曼滤波算法预测劣化趋势，并根据预测的劣化状态和预先设定的模糊阈值计算相应的模糊可靠度。根据该决策模型可以得到刀具更换的最佳时间。
A cutting tool is an important part of machine tools and its reliability influences the total manufacturing effectiveness and stability of machine tools. The paper presents the application of state space model in the cutting tool reliability assessment. As the single evaluation threshold is not easy to determine, the paper puts forward the concept of fuzzy threshold to solve this problem. We use the performance or substitute variable to fuzzify the states of the system and the success/failure events are treated as fuzzy sets. The acoustic emission signal is measured in the test, and wavelet packet (WP) energy extracted from the acoustic emission signal is used to estimate the tool state. The deterioration of the system is seen as a stochastic dynamic process with continuous degrading. The deterioration tendency is predicted by the Kalman filter algorithm, and the corresponding fuzzy reliability is calculated based on the forecasted deterioration state and a pre-set fuzzy threshold. The best time of when the tool should be replaced can be obtained from the decision making model.