Method for predicting remaining life of numerical control machine tool

A method for predicting a remaining life of a tool of a computer numerical control machine, wherein

• a prediction model for the remaining life of the tool is established based on state monitoring, data de-noising, feature extraction and a multi-kernel weighted least squares support vector machine algorithm, and a prediction object for the remaining life of the tool is determined as a milling tool which is a core production element of the CNC machine, and
• the method comprises the following steps:
• step S1:
• collecting a PLC controller signal and an external sensor signal, and monitoring an operation condition and sensor data in a processing process to online monitor wear of the tool and predict the remaining life of the tool, wherein the sensor data comprises vibration signals in three directions of x-axis, y-axis and z-axis and a current signal;
• step S2:
• receiving original signal data and performing pre-processing on the original signal data;
• step S3:
• extracting temporal features of the pre-processed signal obtained in step S2;
• step S4:
• obtaining a data matrix by using a T2 feature map of a principal component analysis PCA based on the temporal features extracted in step S3;
• step S5:
• obtaining a median and a variation of an eigenvector in the data matrix obtained in step S4 in a time period, a first-order difference of the median, and a first-order difference of the variation;
• and
• step S6:
• inputting the matrix eigenvector obtained in step S5 to the multi-kernel weighted least squares support vector machine to obtain a value of the remaining life.