Implementation of an Add-on Device that Monitors the Sound of a Machine Tool and Automatically Suppresses Chatter

Abstract

The application of the Industrial Internet of Things in a factory to connect machines is a topic that has attracted considerable attention in recent years. After connecting the machines, we can usually obtain the data from the controllers of the machines. However, the controller manufacturers usually do not allow users to remotely change the status of the controllers owing to safety or other reasons, which makes it challenging to enable the machines to adapt to the environment by using sensors. With the acknowledgment of this problem, the objective of this study was to develop an add-on device to provide an alternative solution to control some of the machine behaviors. Our device, based on an embedded system, is equipped with sensors and actuators, including a microphone, a CMOS webcam, stepper motors, and a pneumatic cylinder. After the device is installed on the control panel of a computer numerical control (CNC) machine tool, it can allow users to execute the machining process to cut the materials remotely and monitor the process automatically. Additionally, the device can detect chatter by using the microphone, which is the audio sensor, and suppress chatter automatically by adjusting the spindle speed and feed rate knobs through the mechanism on the device. From the experimental results, the surface roughness of a workpiece can be improved by about 68% after the chatter suppression. The information displayed on the control panel can also be captured by a webcam and processed with optical character recognition (OCR) so that it can be saved as a text file in our device. This information can then be used for the further improvement of the manufacturing process of material cutting.

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.…”