Applications of acoustic mapping in electrical discharge machining

The spatial distribution of discharges in electrical discharge machining (EDM) comprises valuable process information, which is not accurately obtained from electrical signals that are utilized extensively for process monitoring and control. This research hence explored the application of acoustic emission (AE) to map the discharges, in consideration of the acoustic time lag. In particular, the work refers to realistic process conditions, wherein AE from successive discharges cause repeated signal interference, which is detrimental to reliable time lag estimation. The applications of this capability for the respective identification of electrode length and workpiece height in fast-hole EDM and wire EDM are presented.     

Process monitoring to assist the workpiece surface quality in machining

The paper reports on research which attempts to correlate the quality of the machined surface after broaching and the output signals obtained from multiple sensors, namely acoustic emission, vibration, and cutting forces. The quality of the machined surface was estimated in terms of geometrical accuracy, burr formation, chatter marks and surface anomalies. Cutting conditions were varied based on an orthogonal array with cutting speed, coolant conditions, and tool settings as factors. Each orthogonal array was repeated at three levels of the tool wear.The results show that the cutting force signals are sensitive enough to detect the geometrical deviation of the machined profile, burr formation and to a lesser extent the chatter marks. The vibration signals were found sensitive to detect the chatter marks while the acoustic emission signal proved to be efficient for the detection of small surface anomalies such as pluckings, laps, and smeared material. However, up to now, no clear distinction between the different types of the surface anomalies could be made using the analysis of the acoustic emission signal.Time and frequency domain analysis of the output signals were carried out in order to develop appropriate techniques for qualitative/quantitative evaluation of the machined surface quality.It was found that each sensory signal is rather limited to a narrow field of application where certain surface features are detectable. The limitations of the employed sensory signals/analysis methodologies used to assess the workpiece surface quality, and their applicability in the industrial machining conditions are also discussed.     

Real-time surface interpolator for 3-D parametric surface machining on 3-axis machine tools

The conventional approaches for surface machining use a sequence of straight lines to approximate the part surface. These straight lines are subsequently translated into linear g-codes by a post processor, and then sent to the CNC system. This process limits the surface machining capability of CNC systems. For example, the CNC machine tool can be controlled only to follow these approximated straight lines since the machine loses the surface information. In contrast, this research utilised a real-time approach for 3-D parametric surface machining on 3-axis CNC machine tools. This real-time approach, called CNC surface interpolator, can read surface g-codes and perform surface machining interpolation. The input to the CNC surface interpolator is the surface g-code, which contains geometric information, such as the coefficients of the parametric surface, as well as cutting conditions. This results in better machining feedrate controls, interpolates more precise machining commands, and requires less machining time compared to that produced by off-line approaches.     

Development of an on-line tool-life monitoring system using acoustic emission signals in gear shaping

Sensing techniques for monitoring machining processes have been one of the focuses of research on process automation. This paper presents the development of on-line tool-life monitoring system for gear shaping that uses acoustic emission (AE). Characteristics of the AE signals are related to the cutting condition, tool material and tool geometry in the cutting of metals. The relationship between AE signal and tool wear was investigated experimentally. Experiments were carried out on the gear shaping of SCM 420 material with a pinion cutter having 44 teeth. Root-mean-square (RMS) AE voltages increase regularly according to tool wear. It is suggested that the maximum value of RMS AE voltage is an effective parameter to monitor tool life. In this study, not only the acquisition method of AE signals for rotating objects but also the signal-processing technique were developed in order to realize the in-process monitoring system for gear shaping. The on-line tool-life monitoring system developed has been successfully applied to gear machining processes.     

Precision manufacturing process monitoring with acoustic emission

Current demands in high-technology industries such as semiconductor, optics, MEMS, etc. have predicated the need for manufacturing processes that can fabricate increasingly smaller features reliably at very high tolerances. In situ monitoring systems that can be used to characterize, control, and improve the fabrication of these smaller features are therefore needed to meet increasing demands in precision and quality. This paper discusses the unique requirements of monitoring of precision manufacturing processes, and the suitability of acoustic emission (AE) as a monitoring technique at the precision scale. Details are then given on the use of AE sensor technology in the monitoring of precision manufacturing processes; grinding, chemical–mechanical planarization (CMP) and ultraprecision diamond turning in particular.     

Laser recovery of machining damage under curved silicon surface

Nano-second pulsed laser irradiation was used to recover machining-induced damage under curved surfaces of single-crystal silicon. Microstructural changes of silicon due to laser irradiation were characterized by cross-sectional transmission electron microscopy and laser micro-Raman spectroscopy. The recoverable damage depth was predicted by finite element modeling of laser-induced temperature change in the workpiece material. Slanted irradiation experiments were performed and the critical surface inclination angle for complete recovery was experimentally obtained. The results demonstrate that atomic-level subsurface integrity and nanometric surface roughness can be achieved on large-curvature silicon surfaces, such as the surfaces of toroidally shaped wafer edges.     

A brief review: acoustic emission method for tool wear monitoring during turning

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process monitoring. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing processes. This paper reviews briefly the research on AE sensing of tool wear condition in turning. The main contents included are:

1. The AE generation in metal cutting processes, AE signal classification, and AE signal correction.

2. AE signal processing with various methodologies, including time series analysis, FFT, wavelet transform, etc.

3. Estimation of tool wear condition, including pattern classification, GMDH methodology, fuzzy classifier, neural network, and sensor and data fusion.

A review of AE-based tool wear monitoring in turning is an important step for improving and developing new tool wear monitoring methodology.     

A quick method for evaluating the thresholds of workpiece surface damage in machining

This paper proposes a Pendulum-Based Cutting Test (PBCT) methodology which allows quick cutting tests for surface integrity evaluation along with providing cutting energies associated with particular level of workpiece surface damage, this is backed by an unified cutting energy model that links damage level of machined surface with energy partition in the cutting area. PBCT method could rapidly define the energy transferred to the workpiece that incurs particular magnitude of surface damage without using conventional machine tools and monitor the cutting process while only limited amount of materials is required. A demonstration of the proposed method is presented for Inconel718.     

Inspection of power plant headers utilizing acoustic emission monitoring

Fossil power plant high energy, high temperature steam headers have been found to be susceptible to thermal fatigue assisted creep degradation. These mechanisms initiate and grow cracks in chrome molybdenum headers, from the bore hole edges and stub tube-to-header welds. Linking up of multiple cracks can lead to explosive expulsion of tubes and severe shorting of the header life. In order to extend the header life and operate safely, a better understanding of crack growth that may occur during specific plant operating conditions is needed. With that understanding, harsh operating conditions that may be causing excessive crack propagation and header damage can be curtailed. Acoustic emission monitoring of headers was performed to assist in identifying operating conditions that lead to header damage. This Electric Power Research Institute (EPRI) sponsored program found acoustic emission activity levels correlated to identified crack growth and analytically calculated stresses. Utilizing these results, draft EPRI guidelines have been developed to aid electric utilities in performing acoustic emission monitoring on superheater headers.     

The application of acoustic emission for precision drilling process monitoring

Precision drilling is a process where a close tolerance hole can be produced with a special drill bit without subsequent reaming. Producing a hole without reaming results in less overall processing time during hole preparation. Precision drilling is best accomplished by a robot with a computer controlled drilling end effector due to the high degree of process control required. Some aspects of the process, such as spindle speed, feed rate, and peck cycles, can easily be controlled by a computer controlled end effector. Other variables, such as drill bit wear, chipping, and point geometry variation, cannot be controlled with the end effector. These variables affect the diameter of the hole but cannot be detected unless the hole or the drill bit is manually inspected. It is not practical to stop the process and check the diameter after every hole. Therefore, a means to perform real time drilling process monitoring is required to detect if an oversized hole is being drilled. The primary objective of this research was to correlate the diameter of a hole drilled in steel with any acoustic emission (AE) signal measurement parameter. The secondary objective was to correlate drill bit lip height variation, which has a significant influence on the diameter of a hole, with any AE signal measurement parameter. The results of this study showed that acoustic emission could only be correlated to hole diameter variations if those variations were related to the lip height variations. However, AE energy and RMS were correlated to lip height variations under a wide variety of conditions.     

Evaluation of fatigue damage in reinforced concrete slab by acoustic emission

The applicability of acoustic emission (AE) technique for evaluation of fatigue damage in reinforced concrete (RC) slabs under cyclic loadings in both laboratory and as a structure in service is studied. The fundamental test performed in laboratory shows that the cracking process can be practically monitored by the measurement of AE signals. Analysis of the relationship between loading phase and AE activity indicates that the final stages of the fracture process can be evaluated by detecting AE signals generated near the minimum loading phase. Comparison of the results from the structure and that from the laboratory specimen demonstrates that AE energy can be an effective parameter for the evaluation of fatigue damage in RC slabs in service.     

Post-impact damage characterisation on natural fibre reinforced composites using acoustic emission

The present study aims to characterise damage due to low velocity impact on jute fibre reinforced polyester composites. To attain this goal, a number of post-impact mechanical tests have been carried out, including tensile tests, three-point bending and indentation, using either a staircase or a continuous loading programme. On all these tests acoustic emission activity (AE) was monitored. The results, compared with damage observed under an optical microscope, show that AE is able to perform a reliable measurement of the level of damage also, on a natural fibre reinforced laminate. The main limitations of this study are owing to the rather low ultimate stress of the material and to the need to apply a loading to evaluate the damage produced by the impact event.     

Characterization of the grinding process by acoustic emission

The properties of a ground surface can be estimated on-line during manufacturing based on the analysis of acoustic signals emitted by the grinding process. This possibility is demonstrated using an experimental system comprising an external grinding machine, a data acquisition unit and an artificial neural network. In the initial phase of system application, an empirical model of the grinding process is formed in the memory of the neural network by self-organized learning driven by empirical data consisting of the acoustic emission spectrum and a surface roughness correlation function. After learning, the system applies the model to estimate the correlation function of the surface profile from the input acoustic emission spectrum. For this purpose, non-parametric regression, based on the conditional average estimator, is utilized. Experiments were done on the grinding of hardened steel workpieces by a corundum wheel. During formation of the model, the surface profile and its correlation function were determined off-line, while in testing system performance the surface correlation function was estimated on-line from the acoustic emission spectrum. With respect to the estimation error, three characteristic periods of the process were observed corresponding to grinding with a newly dressed, slightly worn, and worn out wheel. The best estimation is obtained during grinding by a slightly worn wheel.     

SCC damage evolution on martensitic stainless steel by using acoustic emission technique

Abstract

In the present work, acoustic emission testing (AE) technique was successfully applied to identify damage phenomena occurred during stress corrosion cracking (SCC) in chloride-containing environment of a precipitation hardening martensitic stainless steel. Through the use of multi-variable statistical analysis [by coupling principal component analysis (PCA) and self-organising map (SOM)], the different stages of SCC mechanisms (i.e. activation, growth and propagation of cracks) have been identified and analysed. In particular each mechanism was related to specific and significant AE patterns allowing its univocal recognition.     

An integrated monitoring method to supervise waterjet machining

The paper reports on development, calibration and exploitation of an integrated energy-based monitoring method for waterjet machining. The main advantage of the method resides in its ability to simultaneously monitor the level of output (at nozzle), active (cutting through) and passive (not cutting) waterjet energy thus enabling its budgeting. Relying on multiple acoustic emission sensors, the monitoring solution was implemented on the harsh waterjet environment to detect process malfunctions (e.g. jet penetration, nozzle clogging) and by adjust cutting conditions (e.g. feed speed) to result in improved accuracy and quality of machined surfaces.     

Efficient machining of complex-shaped seal slots for turbomachinery

Complex sealing arrangement in turbomachinery can increase turbine efficiency by reducing leakage of high-pressure cooling flows into the hot gas path. While die-sinking EDM is widely used to machine straight seal slots, electrode preparation and wear make it less efficient for complex shapes. This paper presents research on optimisation of a variant of EDM milling using process control and fluid dynamics simulation to exploit optimal machining conditions. The analysis demonstrates a stable process to machine complex shaped slots by focusing on the key requirements for large-scale turbomachinery component manufacture, namely productivity, surface integrity and process monitoring.     

Observations on chip formation and acoustic emission in machining Ti–6Al–4V alloy

Orthogonal cutting tests were undertaken to investigate the mechanisms of chip formation for a Ti–6Al–4V alloy and to assess the influences of such on acoustic emission (AE). Within the range of conditions employed (cutting speed, v_c=0.25–3.0 m/s, feed, f=20–100 μm), saw-tooth chips were produced. A transition from aperiodic to periodic saw-tooth chip formation occurring with increases in cutting speed and/or feed. Examination of chips formed shortly after the instant of tool engagement, where the undeformed chip thickness is slightly greater than the minimum undeformed chip thickness, revealed a continuous chip characterised by the presence of fine lamellae on its free surface. In agreement with the consensus that shear localisation in machining Ti and its alloys is due to the occurrence of a thermo-plastic instability, the underside of saw-tooth segments formed at relatively high cutting speeds, exhibiting evidence of ductile fracture. Chips formed at lower cutting speeds suggest that cleavage is the mechanism of catastrophic failure, at least within the upper region of the primary shear zone. An additional characteristic of machining Ti–6Al–4V alloy at high cutting speeds is the occurrence of welding between the chip and the tool. Fracture of such welds appears to be the dominant source of AE. The results are discussed with reference to the machining of hardened steels, another class of materials from which saw-tooth chips are produced.     

Surface integrity in finish hard turning of case-hardened steels

Highly stressed steel components, e.g., gears and bearing parts, are appropriate applications for hard turning. Therefore, the process effects on significant engineering properties of work materials have to be carefully analyzed. Roughness, residual stresses, and white layers as parts of surface integrity, are functions of the machining parameters and of the cuttability of the cutting edge, i.e. of the tool wear.The aim of this work was to study the influence of feed rate, cutting speed, and tool wear on the effects induced by hard turning on case-hardened 27MnCr5 gear conebrakes and to point out the technical limitations in mass production.     

Dry machining of Inconel 718, workpiece surface integrity

In the machining of Inconel 718, nickel based heat resistant superalloy and classified difficult-to-cut material, the consumption of cooling lubricant is very important. To reduce the costs of production and to make the processes environmentally safe, the goal is to move toward dry cutting by eliminating cutting fluids. This goal can be achieved by using coated carbide tool and by increasing cutting speed.The present paper firstly reviews the main works on surface integrity and especially residual stresses when machining Inconel 718 superalloy. It focuses then on the effect of dry machining on surface integrity. Wet and dry turning tests were performed at various cutting speeds, with semi-finishing conditions (0.5 mm depth of cut and 0.1 mm/rev feed rate) and using a coated carbide tool. For each cutting test, cutting force was measured, machined surface was observed, and residual stress profiles were determined. An optimal cutting speed of 60 m/min was determined, and additional measurements and observations were performed. Microhardness increment and the microstructure alteration beneath the machined surface were analysed. It is demonstrated that dry machining with a coated carbide tool leads to potentially acceptable surface quality with residual stresses and microhardness values in the machining affected zone of the same order than those obtained in wet conditions when using the optimised cutting speed value; in addition, no severe microstructure alteration was depicted.     

A review of surface roughness generation in ultra-precision machining

Ultra-precision machining (UPM) is capable of manufacturing a high quality surface at a nanometric surface roughness. For such high quality surface in a UPM process, due to the machining complexity any variable would be possible to deteriorate surface quality, consequently receiving much attention and interest. The general factors are summarized as machine tool, cutting conditions, tool geometry, environmental conditions, material property, chip formation, tool wear, vibration etc. This paper aims to review the current state of the art in studying the surface roughness formation and the factors influencing surface roughness in UPM. Firstly, the surface roughness characteristics in UPM is introduced. Then in UPM, a wide variety of factors for surface roughness are then reviewed in detail and the mechanism of surface roughness formation is concluded thoroughly. Finally, the challenges and opportunities faced by industry and academia are discussed and several principle conclusions are drawn.