How can i know the frequency of acoustic emission in a machning ?

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Marc Schmieger Popular answer

It seems that 25kHz comes from the machine with it`s first harmonic at 50kHz. Just change the machine`s operating point [(rotational) speed, force, ...] to check if the peaks move in your FFT.

And it`s not clear what you mean with denoising: just filtering your sound waves or active noise control / reduction?

Patrice Simard

Hello Xiaolu Wang

I am not sure you can actually decide right now. Your signal has clearly 2 levels of information. The highpass exhibits events do look like EA bursts. Perhaps you could explain the low pass one with informations about the machining.

Marc Schmieger

Xiaolu Wang

@ Patrice Simard. Sorry, i don't get what you mean. The highpass is used for removing the signal of 25khz and 50 khz which i consider as noise signal. But i am not sure it's noise signal.

And what i want to know is how to get pure signal from machining. How to recognize the noise signal and where they come from and then how to reduce them?

The present way i used are wavelet analysis to reduce white noise signal from DAQ system and highpass to reduce low frequency noise.

Thank you for your answer.

@Marc Schmieger. You mean that the 25 khz and 50 khz are all noise signal from the vibration from mechine movement like rotation of spindle. And the 25khz is the first harmonic. Your advice will make a good validation of that.

When i have recognized the noise frequency spectrem, i can use the filter to reduce the noise. This is what i want to do. So i use highpass to reduce the low frequency noise signal.And i use wavelet analysis to reduce the white noise, but the high frequency useful signal will be reduced. This is not what i want.

So my question is how to recognize the noise frequency？ and where it come from?, the way to reduce it from the AE signal in meching.

Thank you for your answer which will make a great help for me.

U. Dreher

"acoustic" emission and 25/50 kHz ? This is not exactly 'acoustic' - this is ultrasound!

I do not even get what you want to achieve. So, if you want to give us a bit of information on the application and what your target is, we might be able to do more than guess :)

Regards

Hi U.Dreher

The acoustic emission signal is ultrasound. And my appliaction is used AE sensor to detect the operation of grinding.

What i want to do is denosing the raw signal to achieve the pure signal from the grinding. But i don't make sure the two highest peak in 25khz,50khz in the frequency domain are useful signal. I think they are noise come from the vabration of mechine in the grinding operation.

So, another i want to know is how to denoising if the noise signal is distributed in the all frequency domain?

Thank you!

To distinguish signals coming from the machine itself without workpiece (motor rotation, converter, inverter...) and sound coming from the process of grinding with workpiece you just might perform two tests: One without a workpiece but running the machine and then grinding a workpiece. The observed signals should give you more impression how to separate your different sound signals and how to proceed with calculations/filtering.

As I already know that even a bunch of keys creates a certain amount of ultrasound when shaken, I would not bet on the 25/50 kHz not coming from the process. But it could be overlaid by noises from the machine. maybe you will have to subtract a certain "noise floor" from your signal prior further processing.

Wish you success.

@Marc Schmieger

Yes. It's a good way to distinguish the noise and the useful signal. But it just works at the frequency preformance between them is different.

My acoustic emission sensor is located near the rotary diamond roller which have serious effection on the signal. Now the difference of my signal is not obvious as i can sure the dressing CBN grinding wheel is happened because i hear the the voice of the event. So, i can't explain this phenomenon.Is attentuation of the signal from the dressing grinding wheel so serious? Or some other reasons?

Thanks a lot!