Method and device for monitoring abrasion state of tool based on energy analysis of wavelet packets
A tool wear and energy analysis technology, used in manufacturing tools, measuring/indicating equipment, metal processing machinery parts, etc., can solve problems such as complex mechanical environment and thermal environment, difficult measurement, etc. Effect
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Embodiment 1
[0077] Such as figure 1 As shown, the first embodiment of the present invention provides a tool wear state monitoring method based on wavelet packet energy analysis, which is applied to a server and includes:
[0078] S1: Send a microphone information collection instruction to enable the microphone to collect a first AE signal, and process the first AE signal to generate a second AE signal;
[0079] Specifically, since the first AE signal is a time-varying and weak acoustic signal, the first AE signal needs to be processed, which specifically includes the steps of filtering, amplifying, and converting analog signals to digital signals;
[0080] Preferably, step S1 includes the following steps:
[0081] Amplifying and filtering the first AE signal, and converting the amplified and filtered first AE signal into an analog signal to generate the second AE signal;
[0082] S2: Decompose the second AE signal using a wavelet packet decomposition method to obtain an N-layer wavelet packet, and...
Embodiment 2
[0142] The second embodiment of the present invention provides a tool wear state monitoring device based on wavelet packet energy analysis, including:
[0143] Signal generation module: used to send a microphone information collection instruction so that the microphone collects a first AE signal, and processes the first AE signal to generate a second AE signal;
[0144] Signal processing module: used to decompose the second AE signal using the wavelet packet decomposition method to obtain an N-layer wavelet packet, and reconstruct the N-layer wavelet packet to obtain the frequency domain signal of the N-layer wavelet packet, and Time domain signal of N-layer wavelet packet;
[0145] Feature vector extraction module: used to extract the feature vector of the N-layer wavelet packet based on the time-domain signal of the N-layer wavelet packet and the time-domain signal of the N-layer wavelet packet;
[0146] Neural network building module: establish a BP neural network, input the featur...
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