Elijah Kannatey-Asibu

Quantitative Relationships for Acoustic Emission from Orthogonal Metal Cutting

Theoretical relationships have been drawn between acoustic emission (AE) and the metal cutting process parameters by relating the energy content of the AE signal to the plastic work of deformation which generates the emission signals. The RMS value of the emission signal is expressed in terms of the basic cutting parameters. Results are presented for 6061-T6 aluminum and SAE 1018 steel over the range of speeds 25.2 to 372 sfm (0.128 to 1.9 m/s) and rake angles 10 to 40 deg. Good correlation has been found between predicted and experimental signal energy levels. In addition, AE generation from chip contact along the tool face is studied and the AE energy level reflects the existence of chip sticking and sliding on the tool face, and indicates the feasibility of utilizing AE in tool wear sensing.

Hidden Markov Model-based Tool Wear Monitoring in Turning

This paper presents a new modeling framework for tool wear monitoring in machining processes using hidden Markov models (HMMs). Feature vectors are extracted from vibration signals measured during turning. A codebook is designed and used for vector quantization to convert the feature vectors into a symbol sequence for the hidden Markov model. A series of experiments are conducted to evaluate the effectiveness of the approach for different lengths of training data and observation sequence. Experimental results show that successful tool state detection rates as high as 97% can be achieved by using this approach.

A study of tool wear using statistical analysis of metal-cutting acoustic emission

Abstract Many aspects of the interactions between cutting tools, workpiece material and the chips formed during machining that affect the wear and failure of the tool are not fully understood. The analysis of acoustic emission signals generated during machining has been proposed as a technique for studying both the fundamentals of the cutting process and tool wear and as a methodology for detecting tool wear and failure on line. A brief review of the theory of acoustic emission is presented. Acoustic emission data from reduced contact length machining experiments and tool flank wear tests are analyzed using distribution moments. The analysis shows that the skew and kurtosis of an assumed β distribution for the r.m.s. acoustic emission signal are sensitive to both the stick-slip transition for chip contact along the tool rake face and progressive tool wear on the flank of the cutting tool.

Modelling and analysis of metal transfer in gas metal arc welding

A numerical model combining the methods of enthalpy, effective-viscosity and volume-of-fluid is developed to simulate the metal transfer process in gas metal arc welding. The model describes not only the influence on droplet profile and transfer frequency of electromagnetic force, surface tension, and gravity, but it can also model the nonisothermal phenomena such as heat transfer and phase change. The model has been used to study the shape of the melting interface on the welding wire, the droplet oscillation at wire tip, the characteristics of relevant physical variables and their roles in metal transfer. We find that the taper formation in spray transfer is closely related to the heat input on the unmelted portion of the welding wire, and the taper formation affects the globular–spray transition by decelerating the transfer process. The formation of satellite drops during the metal transfer process is also considered. High-speed photography, laser-shadow imaging, and metallographic analysis validate the numerical model, and recommendations are made on the topics that require further consideration for a more accurate metal transfer model.

Acoustic emission during orthogonal metal cutting

Abstract The theory of acoustic emission and the analysis of emission signals is reviewed as it applies to generation of acoustic emission in metal cutting. Based upon the mechanics of the orthogonal cutting operation a relationship is developed between the root mean square (RMS) voltage of the acoustic emission and fundamental cutting parameters. The validity of this relationship is evaluated by a series of tests varying cutting speed, feed and rake angle for orthogonal machining. Strong dependence of the RMS voltage of the emission on both strain rate and cutting velocity was observed. The sources of acoustic emission in metal cutting are discussed and areas of additional work in the study of acoustic emission from metal cutting are identified.

Sensor systems for real-time monitoring of laser weld quality

On-line process monitoring is beneficial for maintaining high quality products at high production rates and low cost. Off-line traditional testing of welds can be costly in terms of time, material, and productivity. Real-time nondestructive testing, however, can be just as accurate as off-line testing; yet faster, cheaper, and increase productivity, when perfected for high volume repetitive applications. In the field of real-time monitoring, various sensors have shown promise in detecting weld states. These include acoustic emission, audible sound, infrared detectors, ultraviolet detectors, electromagnetic acoustic transducers, and polyvinylidene fluoride. Nevertheless, previous work indicates that no single sensor can reliably detect the full spectrum of weld states. As a result, sensor fusion has been investigated for integrating the advantages of individual sensors. This article presents a survey of technical information that is currently available in the literature, commercial systems, and patents, fo...

Analysis of Sound Signal Generation Due to Flank Wear in Turning

A new concept is introduced to model the main effect of tool wear on system dynamics during stable cutting. Audible sound generated from the cutting process is analyzed as a source for monitoring tool wear during turning, assuming adhesive wear as the predominant wear mechanism. The analysis incorporates the dynamics of the cutting process. In modeling the interaction on the flank surface, the asperities on the surfaces are represented as a trapezoidal series function with normal distribution. The effect of changing asperity height, size, spacing, and the stiffness of the asperity interaction is investigated and compared with experimental data.

Monitoring of laser weld penetration using sensor fusion

Depth of penetration is a critical parameter in laser welding. In many applications, full penetration is desired, but difficult to detect in real time. A sensor fusion system using infrared, ultraviolet, audible sound, and acoustic emission has been implemented for real time monitoring of CO2 laser lap welds in both laboratory and industrial production settings. Signals from the welds were analyzed by: (1) singular value decomposition with data fusion, (2) class mean scatter with decision fusion, (3) class mean scatter with feature fusion, and (4) singular value decomposition with decision fusion using minimum distance and quadratic classification. A classification rate of 100% was obtained for detection of full penetration for both laboratory and production settings.

Acoustic emission and force sensor fusion for monitoring the cutting process

Abstract An acoustic emission and force-based sensor fusion system involving pattern recognition analysis has been used to detect tool breakage, chip form and a threshold level of tool flank wear in turning. When normalized with the resultant force, the force components in the cutting, radial and feed directions were found to be highly sensitive to variables such as feedrate, material hardness, tool coating and tool wear, depth of cut, and speed in fractional factorial experiments. A three-dimensional analytical force model was extended to include the effect of flank wear in order to interpret the experimental findings. Subsequently, using an empirical bilinear relationship between the machining variables and forces, a filter was designed to eliminate the variable effects such that pattern recognition of tool failure under varying conditions was feasible. Results of the sensor fusion approach involving testing the system with the same data used in designing it when using AE and force signals indicate a 94% accuracy for sensing tool wear alone, whereas using only AE for detecting chip form and tool breakage indicate a 99 and 96% accuracy respectively.

Acoustic emission from plastic deformation of a pure single crystal

Acoustic emission (AE) during plastic deformation is analyzed for a pure single crystal neglecting the effects of grain boundaries, impurities, and second‐phase particles. Acceleration of a moving dislocation is considered to be the principal AE source. There are two major mechanisms of dislocation motion related to acceleration, initial, and continuous oscillatory motion. Initial motion induced by the creation of mobile dislocations is modeled as a step function of velocity. Continuous oscillatory motion produced by interactions with neighboring dislocations is modeled as a harmonic function. These mechanisms vary with strain and strain rate due to dislocation multiplication. AE can thus be described in terms of strain and strain rate. Annihilation at a free surface is also regarded as an AE source in addition to the initial and oscillatory motions. The kinetic and strain energies stored around a moving dislocation are dissipated during annihilation, and can be related to AE. The frequency spectrum of AE...