A Method of Judgment of Turning Tool Wear Based on Adversarial Neural Network
A neural network and judgment method technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as insufficient number of samples, unsatisfactory diagnosis results, and difficulty in developing deep learning models, so as to avoid rejection rates. The effect of increasing and improving reliability
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[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0029] Such as Figure 1-Figure 3 As shown, a method for judging the wear of a turning tool based on an adversarial neural network includes the following steps:
[0030] S1: Collect the current signal data of the spindle in the CNC machine tool. The collected current signal data of the spindle in the CNC machine tool includes collecting the current signal of the spindle idling and the current signal of the spindle load when the tool is working from the beginning to the wear.
[0031] S2: Perform data preprocessing on the collected spindle current signal data in the CNC machine tool, use wavelet packet transform analysis to obtain a time-frequency diagram, and convert the time-frequency diagram into a 64*64*3 image. The moving average signal is extracted, analyzed using wavelet packet transform, and the obtained image is transformed.
[0032] S3: Usin...
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