Decoding physical sensor signals to reveal chip formation and surface deformation: An example in machining nickel-based superalloys

Mypati, Omkar; Robles-Linares, Jose A.; Zan, Shusong; Axinte, Dragos; Liao, Zhirong

Abstract

The current research aims to provide a basic understanding of decoding sensor signals with chip formation and surface integrity during the machining of Ni-based superalloys. Force signal analysis provides cutting energy information, offering insight into chip formation and a limited understanding of surface integrity. Researchers have studied the correlation of acoustic emission (AE) signals with surface quality to address this limitation. However, there remains a fundamental gap in understanding how AE signal variations relate to sub-surface deformation in the machined region. The main complications of understanding the AE signal in milling are due to multiple tooth engagement, where one tooth cuts while others drag material and create flying chips. These actions result in cumulative AE signals, which makes it challenging to understand the fundamental relationship between material deformation and AE signals. To address these limitations, a pendulum-based cutting test methodology is proposed. This approach simplifies the milling process, isolating a single cutting-edge, and chip generation. In addition, the pendulum setup also allows for the analysis of a wide range of cutting speeds within a single test to obtain optimal cutting conditions. Furthermore, the study compares fine-edge and round-edge cutting tools. It reveals that fine-edge tools generate higher amplitude AE signals despite lower cutting forces. This indicates more aggressive cutting action and localised plastic deformation, leading to intense carbide cracking and subsurface damage. Conversely, round-edge tools produce lower amplitude AE signals, suggesting a more distributed stress pattern and reduced carbide cracking.

Citation

Mypati, O., Robles-Linares, J. A., Zan, S., Axinte, D., & Liao, Z. (2025). Decoding physical sensor signals to reveal chip formation and surface deformation: An example in machining nickel-based superalloys. Mechanical Systems and Signal Processing, 225, Article 112297. https://doi.org/10.1016/j.ymssp.2024.112297

• Journal Article Type: Article
• Acceptance Date: Dec 30, 2024
• Online Publication Date: Jan 8, 2025
• Publication Date: Feb 15, 2025
• Deposit Date: Jan 20, 2025
• Publicly Available Date: Jan 22, 2025
• Journal: Mechanical Systems and Signal Processing
• Print ISSN: 0888-3270
• Electronic ISSN: 1096-1216
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 225
• Article Number: 112297
• DOI: https://doi.org/10.1016/j.ymssp.2024.112297
• Keywords: Inconel 718; Acoustic emission; Online monitoring; Chip formation; Surface integrity
• Public URL: https://nottingham-repository.worktribe.com/output/44234055
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0888327024011968?via%3Dihub
• Additional Information: This article is maintained by: Elsevier; Article Title: Decoding physical sensor signals to reveal chip formation and surface deformation: An example in machining nickel-based superalloys; Journal Title: Mechanical Systems and Signal Processing; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.ymssp.2024.112297; Content Type: article; Copyright: © 2025 The Authors. Published by Elsevier Ltd.