88 citations · 220 across the 10 of their papers we have counts for
10 papers
Pattern Characterization Using Topological Data Analysis: Application to Piezo Vibration Striking Treatment
Max M. Chumley, Melih C. Yesilli, Jisheng Chen +2
Quantifying patterns in visual or tactile textures provides important information about the process or phenomena that generated these patterns. In manufacturing, these patterns can…
Topological Measures for Pattern quantification of Impact Centers in Piezo Vibration Striking Treatment (PVST)
Melih C. Yesilli, Max M. Chumley, Jisheng Chen +2
Surface texture influences wear and tribological properties of manufactured parts, and it plays a critical role in end-user products. Therefore, quantifying the order or structure…
Automated Surface Texture Analysis via Discrete Cosine Transform and Discrete Wavelet Transform
Melih C. Yesilli, Jisheng Chen, Firas A. Khasawneh +1
Surface roughness and texture are critical to the functional performance of engineering components. The ability to analyze roughness and texture effectively and efficiently is much…
Transfer Learning for Autonomous Chatter Detection in Machining
Melih C. Yesilli, Firas A. Khasawneh, Brian Mann
Large-amplitude chatter vibrations are one of the most important phenomena in machining processes. It is often detrimental in cutting operations causing a poor surface finish and d…
Data-driven and Automatic Surface Texture Analysis Using Persistent Homology
Melih C. Yesilli, Firas A. Khasawneh
Surface roughness plays an important role in analyzing engineering surfaces. It quantifies the surface topography and can be used to determine whether the resulting surface finish…
On Transfer Learning of Traditional Frequency and Time Domain Features in Turning
Melih C. Yesilli, Firas A. Khasawneh
There has been an increasing interest in leveraging machine learning tools for chatter prediction and diagnosis in discrete manufacturing processes. Some of the most common feature…
Chatter Diagnosis in Milling Using Supervised Learning and Topological Features Vector
Melih C. Yesilli, Sarah Tymochko, Firas A. Khasawneh +1
Chatter detection has become a prominent subject of interest due to its effect on cutting tool life, surface finish and spindle of machine tool. Most of the existing methods in cha…
Chatter Detection in Turning Using Machine Learning and Similarity Measures of Time Series via Dynamic Time Warping
Melih C. Yesilli, Firas A. Khasawneh, Andreas Otto
Chatter detection from sensor signals has been an active field of research. While some success has been reported using several featurization tools and machine learning algorithms,…
Topological Feature Vectors for Chatter Detection in Turning Processes
Melih C. Yesilli, Firas A. Khasawneh, Andreas Otto
Machining processes are most accurately described using complex dynamical systems that include nonlinearities, time delays, and stochastic effects. Due to the nature of these model…
On Transfer Learning For Chatter Detection in Turning Using Wavelet Packet Transform and Empirical Mode Decomposition
Melih C. Yesilli, Firas A. Khasawneh, Andreas Otto
The increasing availability of sensor data at machine tools makes automatic chatter detection algorithms a trending topic in metal cutting. Two prominent and advanced methods for f…