智能统计工序质量控制的体系研究

针对统计工序质量控制的要求，提出了智能控制体系的基本框架，论述了控制图模式的分类及其表达。对智能统计工序质量控制的控制图模式识别、控制图异常模式的参数估计和诊断分析专家系统3个主要方面进行了分析，并提出了解决方案和系统模型。在模型构造中，采用小波概率神经网络进行控制图的模式识别和控制图异常模式的参数估计。模拟仿真和实际应用结果表明：该方法结构简单、收敛速度快、识别准确率高，能够满足控制图在线检测和分析的需要。

Intelligent statistical process control system

Aiming at the problem of statistical process control,basic framework of intelligence control system was presented.Patterns and expression of the control chart were discussed.Three major fields of intelligent statistical process control including control chart patterns identification,abnormal patterns parameters estimation,and the diagnose expert system were introduced and analyzed.The solution scheme and system model were also presented.In the modeling of the structure,the wavelet probabilistic neural network was used to recognize the control chart patterns and estimate the abnormal patterns parameters.Simulation and application results showed that the performance of the proposed method had many advantages such as simple structure,fast convergence,high identification rate,and it could be used in on-line detection and analysis of control chart.