State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel). 2012 Sep 25;12(10):12964-87. doi: 10.3390/s121012964.
The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools.
刀具的可靠性对加工精度和生产效率至关重要。传统的基于统计的可靠性评估方法旨在为给定和固定条件下的大量相同单位提供可靠性的一般和总体估计。然而，它在描述刀具的运行特性方面效果有限。为了克服这一局限性，本文提出了一种评估刀具运行可靠性的方法。引入比例协变量模型来构建运行可靠性与状态监测信息之间的关系。利用小波包变换和改进的距离评估技术从振动信号中提取敏感特征，并基于比例协变量模型构建协变量函数。最终，使用从历史数据的小样本中获得的基线协变量函数计算评估刀具的故障率函数。实验结果和比较研究表明，该方法可有效评估刀具的运行可靠性。
