Abstract
The multi-information data acquisition system of tool wear condition of CNC lathe is built by acquiring the acoustic emission and vibration acceleration signals. The data of acoustic emission and vibration acceleration signals during the process of CNC machine tool processing under the conditions of different tool wear degrees and different cutting conditions are acquired and analyzed using the orthogonal experimental method. The optimum characteristic frequency band of acoustic emission and vibration acceleration signals was extracted by the wavelet envelope decomposition method so as to recognize tool wear condition as the characteristic parameters. The characteristic information of acoustic emission and vibration acceleration signals during the process of CNC machine tool processing was fused. In addition, the intelligent recognition of tool wear condition during the process of machine tool processing was researched.
Highlights
Tool wear and breakage will occur in the process of CNC machine tool cutting, which will directly affect the machining accuracy and surface quality of the workpiece
18 groups of P2 and P4 band energy value of the vibration signal and P4 band energy value of the acoustic emission signal which are not the training samples are selected from the test characteristic data, and the corresponding spindle speed is selected as the test samples together. ese test samples are input into the BP neural network to verify the intelligent recognition method of tool wear state
The pattern recognition method of support vector machine is used to recognize the tool wear state based on single sensor information. en, BP neural network technology is used to identify the tool wear state by fusing the vibration signal, acoustic emission signal, and spindle speed feature information
Summary
Tool wear and breakage will occur in the process of CNC machine tool cutting, which will directly affect the machining accuracy and surface quality of the workpiece. In order to ensure the accuracy of machining, it is necessary to replace the tool before the tool is severely worn, so it is necessary to replace the tool frequently, but the frequent replacement of the tool reduces the efficiency of production and improves the cost of machining. By monitoring and identifying the tool wear status, the tool can be replaced at the right time. Monitoring, identifying the tool wear status, and timely replacing the tool can ensure the machining accuracy and can improve the tool utilization and reduce the production cost. Replacing the cutting tool at the right time can avoid the scrapping of the workpiece and the failure of the machine tool caused by the failure of the cutting tool
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