Machining process monitoring using an infrared sensor

Abstract

Machining is a crucial process for the manufacturing of precision aerospace, automotive, and biomedical parts. Issues such as tool wear, chatter, and workpiece deformation affect the machined parts' quality. Early detection of these issues is required to achieve the desired quality of precision machined parts. Traditionally, these process anomalies are monitored using commercial sensors like lasers, dynamometers, accelerometers, etc. This article presents monitoring of the machining process based on a low-cost infrared sensor. The signal processing of infrared sensor data is performed in the time and frequency domain to estimate tool wear, chatter, and workpiece deflection. Validation of the results is accomplished by using commercial sensors through established methods. Results of validation experiments corroborate the strength of the proposed approach in estimating the tool wear, chatter, and workpiece deformation. Compared to the state-of-the-art sensors, which are engineered to monitor specific attributes of the machining process, the employed sensor can monitor multiple aspects.