Investigation of Milling Stability under Cutting Fluid Supply by Microphone Signal Analysis

Abstract

Force and acceleration are the most well-known signals for the monitoring of milling vibration. However, the noncontact and low-cost microphone is also a potential choice for cutting vibration measurement. The superior detection sensitivity of the microphone against milling dynamics was preliminarily verified. However, the limitations of microphones to record milling vibration have also been reported over the past two decades, such as the vibration identification accuracy under the influence of environmental noise. In this work, the microphone signal beyond 5 kHz is employed in the milling stability analysis to diminish the effect of low-frequency environmental noise. In addition, almost all current studies for cutting noise analyses are conducted without cutting fluid (dry cutting). This is far from most practical manufacturing processes. The cutting fluid is used in this work and a waterproof device is particularly designed to ensure the microphone operation against the cutting fluid. The microphone signal is analyzed on the basis of the scatter diagram of time domain (SDTD) to discuss the variation trend due to the milling stability. In addition, both the fast Fourier transform (FFT) and short-time Fourier transform (STFT) were employed to clarify the signal characteristics in the frequency domain. Finally, the finished workpiece surface was examined with the stability lobe diagram (SLD) to verify the acoustic analysis results.

Improved Estimation of End-Milling Parameters from Acoustic Emission Signals Using a Microphone Array Assisted by AI Modelling

“…In this context, techniques based on the sensing of acoustic emission (AE) phenomena have gained increasing interest during the last few years due to their simplicity of use and the ability to monitor a wide variety of features, such as teeth breakage [ 7 , 8 ], runout [ 9 , 10 ] and chattering [ 11 , 12 ]. In particular, those techniques based on the use of noncontact sensors in the range of audible sound, such as different types of microphones [ 13 , 14 ], are particularly attractive due to the reduced intrusiveness, so they have been used for detecting the chattering phenomenon [ 15 , 16 , 17 ] and tool condition monitoring in conventional machining [ 18 , 19 ], high-speed machining [ 20 ] and abrasion processes [ 21 ].…”

Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission

“…In the event of a tool with broken or blunt teeth, acoustic emission technologies can automatically detect their presence with the use of relatively simple setups [9][10][11][12][13]. Even if the tool is in good working condition, phenomena like runout [14,15] or chatter [16][17][18][19] are common problems that modern industry has to face, but due to the change in the acoustic emission generated by each of those phenomena they can be readily detected and solved.…”

Hazards That Can Affect CNC Machine Tools during Operation—An AHP Approach

“…The stability of the machining process using data collected by microphone signal analysis was presented in [6]. Tool wear is also considered as a major source of hazard when CNC machining is considered.…”