摘要
为了适应小批量、多品种磨削过程的在线监测的要求,本文采用声发射(AE)传感器和功率传感器联合监测磨削过程。通过采用声发射信号归原处理法,可实现对磨削条件多变环境下砂轮钝化进行有效监测,利用该方法可以克服仅靠监测AE信号幅值变化不能监测工件材料、加工要求和磨削参数经常变化环境下砂轮钝化程度的缺陷,同时利用功率传感器对砂轮破碎进行监测;针对磨削条件复杂,难以建立数学模型的难点,本文采用神经网络建立传感器信号与监测信号间的非线性关系。
Returning original processing method of AE signals is pretended to monitoring grinding wheel states under the surroundings of multi - changing grinding conditions in this paper. It can overcome the limitation of the method that only can monitor AE signal amplitude and cannot monitor grinding wheel dullness on condition that grinding parameters, processing requirements and work- piece material are changing frequently. At the same time, power sensor is used to monitor grinding wheel crash. Neural network is used to build the nonlinear relationship between sensor signals and monitoring signals, it is because very difficult to build mathematical model for complex grinding conditions.
出处
《机床与液压》
北大核心
2002年第4期18-19,24,共3页
Machine Tool & Hydraulics
基金
教育部科学技术研究重点资助项目(200032)
山东省自然科学基金资助项目(Q98F02143)
