Tool wear online monitoring method based on wavelet packet analysis and rbf neural network
A technology of neural network and tool wear, applied in manufacturing tools, measuring/indicating equipment, metal processing equipment, etc., can solve problems such as low resolution
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[0032] Reference attached Figure 1-6 Taking the milling process of general aviation material titanium alloy as an example, the specific implementation of the present invention will be described.
[0033] The present invention proposes a tool wear online monitoring method based on wavelet packet analysis and RBF neural network. Figure 1-2 Indicates the process and feature extraction process of the tool wear online monitoring method, which mainly includes 6 steps:
[0034] Step 1: Under a certain working condition, use constant cutting parameters to process the part. The tool mills the side of the titanium alloy workpiece with a radial distance of 1mm and an axial depth of 2mm for 58 times. The tool changes from initial wear to Blunt wear, measure the flank wear of the tool after each machining, and extract 50 sets of tool wear measurements as the output value of the neural network for training. At the same time, the Kistler 9123C rotary dynamometer is used to measure the cutting f...
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