Ultrasonic vibration-assisted machining:principle,design and application

Ultrasonic vibration-assisted （UVA） machining is a process which makes use of a micro-scale high frequency vibration applied to a cutting tool to improve the material removal effectiveness. Its principle is to make the tool-workpiece interaction a microscopically non-monotonic process to facilitate chip separation and to reduce machining forces. It can also reduce the deformation zone in a workpiece under machining, thereby improving the surface integrity of a component machined. There are several types of UVA machining processes, differentiated by the directions of the vibrations introduced relative to the cutting direction. Applications of UVA machining to a wide range of workpiece materials have shown that the process can considerably improve machining performance. This paper aims to provide a comprehensive discussion and review about some key aspects of UVA machining such as cutting kinematics and dynamics, effect of workpiece materials and wear of cutting tools, involving a wide range of workpiece materials including metal alloys, ceramics, amorphous and composite materials. Some aspects for further investigation are also outlined at the end.

Theoretical Modeling and Surface Roughness Prediction of Microtextured Surfaces in Ultrasonic Vibration-Assisted Milling

Textured surfaces with certain micro/nano structures have been proven to possess some advanced functions,such as reducing friction,improving wear and increasing wettability.Accurate prediction of micro/nano surface textures is of great significance for the design,fabrication and application of functional textured surfaces.In this paper,based on the kinematic analysis of cutter teeth,the discretization of ultrasonic machining process,transformation method of coordinate systems and the cubic spline data interpolation,an integrated theoretical model was established to characterize the distribution and geometric features of micro textures on the surfaces machined by different types of ultrasonic vibration-assisted milling(UVAM).Based on the theoretical model,the effect of key process parameters(vibration directions,vibration dimensions,cutting parameters and vibration parameters)on tool trajectories and microtextured surface morphology in UVAM is investigated.Besides,the effect of phase difference on the elliptical shape in 2D/3D ultrasonic elliptical vibration-assisted milling(UEVAM)was analyzed.Compared to conventional numerical models,the method of the cubic spline data interpolation is applied to the simulation of microtextured surface morphology in UVAM,which is more suitable for characterizing the morphological features of microtextured surfaces than traditional methods due to the presence of numerous micro textures.The prediction of surface roughness indicates that the magnitude of ultrasonic amplitude in z-direction should be strictly limited in 1D rotary UVAM,2D and 3D UEVAM due to the unfavorable effect of axial ultrasonic vibration on the surface quality.This study can provide theoretical guidance for the design and fabrication of microtextured surfaces in UVAM.

Vibration suppression in multi-tool ultrasonic machining to multi-external and parametric excitations

Ultrasonic machining （USM） is of particular interest for the machining of non-conductive, brittle materials such as engineering ceramics. In this paper, a multi-tool technique is used in USM to reduce the vibration in the tool holder and have reasonable amplitude for the tools. This can be done via dynamic absorbers. The coupling of four nonlinear oscillators of the tool holder and tools representing ultrasonic cutting process are investigated. This leads to a four-degree-of-freedom system subjected to multi-external and multi-parametric excitation forces. The aim of this work is to control the tool holder behavior at simultaneous primary, sub-harmonic and internal resonance condition. Multiple scale perturbation method is used to obtain the solution up to the second order approximations. The different resonance cases are reported and studied numerically. The stability of the system is investigated by using both phase-plane and frequency response techniques. The effects of the different parameters of the tools on the system behavior are studied numerically. Comparison with the available published work is reported.

Analysis of the Rotary Ultrasonic Machining Mechanism

Ultrasonic machining (USM) is considered as an effective method for machining hard and brittle materials such as glass, engineering ceramics, semiconductors, diamonds, metal composites and so on. However, the low material removal rate due to using abrasive slurry limits further application of USM. Rotary ultrasonic machining (rotary USM) superimposes rotational movement on the tool head that vibrates at ultrasonic frequency (20 kHz) simultaneously. The tool is made of mild steel coated or bonded with diamond abrasive. Therefore, abrasive slurry is abandoned and coolant is used to carry debris out of working area. Compared with USM, rotary USM can obtain much higher material removal rate, deep holes, and fine precision, which leads to its further application. Combined with CNC technology, rotary USM can be used to conduct contour machining of hard and brittle materials. In this paper, the movement of abrasive particles in tool tip of rotary ultrasonic machining is analyzed. The impacting and grinding of abrasive in tool tip to machined surface are considered as main factors to material removal rate. The process of crack forming and growing in one loading and unloading cycle can be described as following stages: a) When abrasive particle acts the pressure on work-piece, the macro cracks in periphery of contact area are exerted increasing tensile stress. b) As the tensile stress increase to the critical of material tension, the one of cracks in periphery of contact area begins to propagate around contact area and develop beneath the surface to certain depth. c) Indentation area varies with increasing of load, the circle crack around contact area steadily or dynamical propagates towards inside of work-piece. d) As tensile stress in crack increases to critical of crack steady failure, circle crack suddenly becomes conic crack. e) Further increase load, the crack continues to grow while contact area is surrounded by conic cracks. f) During unloading, conic crack begins to close, some of cracks continue their extension towards the surface and forms a circle groove. The mathematical model for material removal rate shows that the factors affecting on material removal rate are static load, grid and concentration of abrasive, mechanical properties of machined materials, rotational speed of tool and feed speed of work-piece.

Mechanism of ultrasonic-pulse electrochemical compound machining based on particles

The electric double layer with the transmission of particles was presented based on the principle of electrochemistry.In accordance with this theory,the cavitation catalysis removal mechanism of ultrasonic-pulse electrochemical compound machining(UPECM) based on particles was proposed.The removal mechanism was a particular focus and was thus validated by experiments.The principles and experiments of UPECM were introduced,and the removal model of the UPECM based on the principles of UPECM was established.Furthermore,the effects of the material removal rate for the main processing parameters,including the particles size,the ultrasonic vibration amplitude,the pulse voltage and the minimum machining gap between the tool and the workpiece,were also studied through UPECM.The results show that the particles promote ultrasonic-pulse electrochemical compound machining and thus act as the catalyzer of UPECM.The results also indicate that the processing speed,machining accuracy and surface quality can be improved under UPECM compound machining.

Study of Stability and Vibration Reduction in Multi-Tool Ultrasonic Machining under Simultaneous Primary and Internal Resonance

The main object of this paper is the mathematical study of the vibration behavior in ultrasonic machining (USM) described by non-linear differential equations. The ultrasonic machining (USM) consists of the tool holder and the absor-bers representing the tools. This leads to four-degree-of-freedom system subject to multi-external excitation forces. The aim of this project is the reduction of the vibrations in the tool holder and have reasonable amplitudes for the tools represented by the multi-absorbers. Multiple scale perturbation method is applied to obtain the solution up to the second order approximation and to study the stability of the steady state solution near different simultaneous resonance cases. The resulting different resonance cases are reported and studied numerically. The stability of the steady state solution near the selected resonance cases is studied applying both frequency response equations and phase-plane technique. The effects of the different parameters of the system and the absorbers on the system behavior are studied numerically. Optimum working conditions for the tools were obtained. Comparison with the available published work is reported.

Experimental Study on the Machining Technology of ZrO_2 Ceramics Using Diamond Wire Saw with Ultrasonic Vibration

The influence of different technological parameter on material remove rate and surface quality of ZrO2 ceramics is studied using the cutting machining method of electroplate diamond wire saw with ultrasonic vibration.Experimental results show that,compared with the same experiment condition without ultrasonic vibration,this cutting method has the advantages of high material remove rate,good surface quality,little brokenness and so on.

Analysis of Machinable Structures and Their Wettability of Rotary Ultrasonic Texturing Method

Tailored surface textures at the micro- or nanoscale dimensions are widely used to get required functional performances. Rotary ultrasonic texturing （RUT） technique has been proved to be capable of fabricating periodic micro- and nanostructures. In the present study, diamond tools with geometrically defined cutting edges were designed for fabricating different types of tailored surface textures using the RUT method. Surface generation mechanisms and machinable structures of the RUT process are analyzed and simulated with a 3D-CAD program. Textured surfaces generated by using a triangular pyramid cutting tip are constructed. Different textural patterns from several micrometers to several tens of micrometers with few burrs were successfully fabricated, which proved that tools with a proper two-rake-face design are capable of removing cutting chips efficiently along a sinusoidal cutting locus in the RUT process. Technical applications of the textured surfaces are also discussed. Wetting properties of textured aluminum surfaces were evaluated by combining the test of surface roughness features. The results show that the real surface area of the textured aluminum surfaces almost doubled by comparing with that of a flat surface, and anisotropic wetting properties were obtained due to the obvious directional textural features.

Design of Five-Axis Ultrasonic Assistant Compound Machine Tool

A compound machine tool was designed, which combined rotary ultrasonic assisted grinding, electrical discharge machining(EDM) and multi-axis milling. Experimental results indicated that its positioning accuracy was less than 5.6 μm and its repetitive positioning accuracy was less than 1.8 μm; the vibration amplitude of ultrasonic grinding system was uniform and stable, and the EDM system worked well and stably.A smooth surface of K9 optical glass component was achieved by the grinding method.

Study on flaw identification of ultrasonic signal for large shafts based on optimal support vector machine

Automatic identification of flaws is very important for ultrasonic nondestructive testing and evaluation of large shaft.A novel automatic defect identification system is presented.Wavelet packet analysis(WPA)was applied to feature extraction of ultrasonic signal,and optimal Support vector machine(SVM)was used to perform the identification task.Meanwhile,comparative study on convergent velocity and classified effect was done among SVM and several improved BP network models.To validate the method,some experiments were performed and the results show that the proposed system has very high identification performance for large shafts and the optimal SVM processes better classification performance and spreading potential than BP manual neural network under small study sample condition.

Ultrasonic prediction of crack density using machine learning:A numerical investigation

Cracks are accounted as the most destructive discontinuity in rock, soil, and concrete. Enhancing our knowledge from their properties such as crack distribution, density, and/or aspect ratio is crucial in geo-systems. The most well-known mechanical parameter for such an evaluation is wave velocity through which one can qualitatively or quantitatively characterize the porous media. In small scales, such information is obtained using the ultrasonic pulse velocity(UPV) technique as a non-destructive test. In large-scale geo-systems, however, it is inverted from seismic data. In this paper, we take advantage of the recent advancements in machine learning(ML) for analyzing wave signals and predict rock properties such as crack density(CD) – the number of cracks per unit volume. To this end, we designed numerical models with different CDs and, using the rotated staggered finite-difference grid(RSG) technique, simulated wave propagation. Two ML networks, namely Convolutional Neural Networks(CNN) and Long Short-Term Memory(LSTM), are then used to predict CD values. Results show that, by selecting an optimum value for wavelength to crack length ratio, the accuracy of predictions of test data can reach R2> 96% with mean square error(MSE) < 25e-4(normalized values). Overall, we found that:(i) performance of both CNN and LSTM is highly promising,(ii) accuracy of the transmitted signals is slightly higher than the reflected signals,(iii) accuracy of 2D signals is marginally higher than 1D signals,(iv)accuracy of horizontal and vertical component signals are comparable,(v) accuracy of coda signals is less when the whole signals are used. Our results, thus, reveal that the ML methods can provide rapid solutions and estimations for crack density, without the necessity of further modeling.

Improving Ultrasonic Testing by Using Machine Learning Framework Based on Model Interpretation Strategy

Ultrasonic testing(UT)is increasingly combined with machine learning(ML)techniques for intelligently identifying damage.Extracting signifcant features from UT data is essential for efcient defect characterization.Moreover,the hidden physics behind ML is unexplained,reducing the generalization capability and versatility of ML methods in UT.In this paper,a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efciency of UT.Firstly,multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space.Subsequently,a feature selection method based on model interpretable strategy(FS-MIS)is innovatively developed by integrating Shapley additive explanation(SHAP),flter method,embedded method and wrapper method.The most efective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively.The proposed framework is validated by identifying and locating side-drilled holes(SDHs)with 0.5λcentral distance and different depths.An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments.The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival(ToAs)of the scattered waves emitted by adjacent SDHs.The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67%with an average error of 0.25%,signifcantly improving the time resolution of UT signals.On this basis,the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets.The imaging resolution is enhanced to 0.5λby implementing the total focusing method(TFM).The relative errors of hole depths and central distance are no more than 0.51%and 3.57%,respectively.Finally,the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.

Process Optimization of Ultrasonic Extraction of Puerarin Based on Support Vector Machine

In ultrasonic extraction technology, optimization of technical parameters often considers extraction medium only, without including ultrasonic parameters. This paper focuses on controlling the ultrasonic extraction process of puerarin, investigating the influence of ultrasonic parameters on extraction rate, and empirically analyzing the main components of Pueraria, i.e., isoflavone compounds. A method is presented combining orthogonal experi- mental design with a support vector machine and a predictive model is established for optimization of technical parameters. From the analysis with the predictive model, appropriate process parameters are achieved for higher extraction rate. With these parameters in the ultrasonic extraction of puerarin, the experimental result is satisfactory. This method is of significance to the study of extracfing root-stock plant medicines.

An Effective Machine-Learning Based Feature Extraction/Recognition Model for Fetal Heart Defect Detection from 2D Ultrasonic Imageries

Congenital heart defect,accounting for about 30%of congenital defects,is the most common one.Data shows that congenital heart defects have seriously affected the birth rate of healthy newborns.In Fetal andNeonatal Cardiology,medical imaging technology(2D ultrasonic,MRI)has been proved to be helpful to detect congenital defects of the fetal heart and assists sonographers in prenatal diagnosis.It is a highly complex task to recognize 2D fetal heart ultrasonic standard plane(FHUSP)manually.Compared withmanual identification,automatic identification through artificial intelligence can save a lot of time,ensure the efficiency of diagnosis,and improve the accuracy of diagnosis.In this study,a feature extraction method based on texture features(Local Binary Pattern LBP and Histogram of Oriented Gradient HOG)and combined with Bag of Words(BOW)model is carried out,and then feature fusion is performed.Finally,it adopts Support VectorMachine(SVM)to realize automatic recognition and classification of FHUSP.The data includes 788 standard plane data sets and 448 normal and abnormal plane data sets.Compared with some other methods and the single method model,the classification accuracy of our model has been obviously improved,with the highest accuracy reaching 87.35%.Similarly,we also verify the performance of the model in normal and abnormal planes,and the average accuracy in classifying abnormal and normal planes is 84.92%.The experimental results show that thismethod can effectively classify and predict different FHUSP and can provide certain assistance for sonographers to diagnose fetal congenital heart disease.

TP-Series Ultrasonic Cleaning Machines

In the patents pavilion of the Fifth Asia-Pacific Fair, the attention of numerous visitors was riveted by an onthe-spot demonstration. Standing before them was a machine with a stainless steel casing partly in a container of clear water. The operator pressed a button and ripples appeared on the surface of the water. The operator took watch chain s and jewellery from the visitors and put them in

Ultrasonic vibration-assisted cutting of titanium alloys:A state-of-the-art review

The remarkable ability of titanium alloys to preserve their superior physical and chemical characteristics when subjected to extreme conditions significantly enhances their importance in the aerospace,military,and medical sectors.However,conventional machining of titanium alloys leads to elevated tool wear,development of surface defects,and reduced machining efficiency due to their low heat conductivity,and chemical affinity.These issues can be somewhat counteracted by integrating ultrasonic vibration in the conventional machining of titanium alloys and also enhance sustainability.This review article offers a holistic evaluation of the influence of ultrasonic vibration-assisted milling and turning on cutting forces,temperature,tool wear,and surface integrity,encompassing surface morphology,surface roughness,surface residual stress,surface hardness,and surface tribological properties during titanium alloys machining.Furthermore,it investigates the sustainability aspect that has not been previously examined.Studies on the performance of ultrasonic-assisted cutting revealed several advantages,including decreased cutting forces and cutting temperature,improved tool life,and a better-machined surface during machining.Consequently,the sustainability factor is improved due to minimized energy consumption and residual waste.In conclusion,the key challenges and future prospects in the ultrasonic-assisted cutting of titanium alloys are also discussed.This review article provides beneficial knowledge for manufactur-ers and researchers regarding ultrasonic vibration-assisted cutting of titanium alloy and will play an important role in achieving sustainability in the industry.

Milling Characteristics and Damage Assessment of Ultrasonic Vibration-Assisted End Milling C_(f)/SiC Composites

C_(f)/SiC composites are characterized as anisotropic,heterogeneous,brittle,and hard materials.The process of manufacturing C_(f)/SiC composites using traditional machining techniques is prone to edge chipping damage and tool wear,which makes it difficult to meet the machining quality and machining accuracy.The purpose of this paper is to investigate the milling characteristics and damage assessment during ultrasonic vibration-assisted end milling(UVAEM)of C_(f)/SiC composites.Firstly,UVAEM experiments on C_(f)/SiC composites were carried out at different ultrasonic amplitudes and comparative experiments with conventional milling(CM).In addition,tool wear,surface roughness,surface micromorphology,milling force and subsurface damage(SSD)were measured and analysed.Finally,the SSD factors of C_(f)/SiC composites were established to quantify machining damage,and analyzed the effect of ultrasonic amplitude on SSD.Furthermore,the formation mechanism of SSD was investigated and discussed.The findings indicate that appropriate ultrasonic amplitude improves the surface quality by UVAEM,while excessive amplitude deteriorates the surface quality.During the UVAEM,micro/macro brittle fracture of the fibers on the surface occurs,leading to machining defects such as fiber breakage,fiber-interface debonding and pits.The milling force gradually decreases with the increase of ultrasonic amplitude.On the other hand,the forms of SSD in CM and UVAEM are mainly fiber pullout,subsurface crack,crack extension and machining pits.Matrix cracking and fiber pullout in SSD were affected by fiber orientation.Moreover,the introduction of ultrasonic vibration plays a significant contribution in the inhibition of the SSD in C_(f)/SiC composites.

Surface integrity characterization of thirdgeneration nickel-based single crystal blade tenons after ultrasonic vibration-assisted grinding

Machined surface integrity of workpieces in harsh environments has a remarkable influence on their performance.However,the complexity of the new type of machining hinders a comprehensive understanding of machined surface integrity and its formation mechanism,thereby limiting the study of component performance.With increasing demands for high-quality machined workpieces in aerospace industry applications,researchers from academia and industry are increasingly focusing on post-machining surface characterization.The profile grinding test was conducted on a novel single-crystal superalloy to simulate the formation of blade tenons,and the obtained tenons were characterized for surface integrity elements under various operating conditions.Results revealed that ultrasonic vibration-assisted grinding(UVAG)led to multiple superpositions of abrasive grain trajectories,causing reduced surface roughness(an average reduction of approximately29.6%)compared with conventional grinding.After examining the subsurface layer of UVAG using transmission electron microscopy,the results revealed that the single-crystal tenon grinding subsurface layer exhibited a gradient evolution from the near-surface to the substrate.This evolution was characterized by an equiaxed nanocrystalline layer measuring 0.34μm,followed by a submicrocrystalline grain-forming zone spanning 0.6μm and finally,a constituent phase-twisted dis-torted deformation zone over 0.62μm.Under normal grinding conditions,the tenon exhibited low surface hardening(not exceeding 15%),and residual compressive stresses were observed on its surface.In cases where grinding burns occurred,a white layer appeared on the tenon's surface,which demonstrated varying thicknesses along the teeth from top to root due to thermal-force-structural coupling effects.Additionally,these burns introduced residual tensile stresses on the tenon's surface,potentially substantially affecting its fatigue life.This paper enhances our understanding of UVAG processes and establishes a foundation for their application in manufacturing singlecrystal turbine blades for next-generation aero-turbine engines.

Research on Cutting Force of Ultrasonic Diamond Wire Saw

Based on impulse and vibration machining theories,a mathematical model of cutting force for the electroplated diamond ultrasonic wire saw was established using superposition principle.The differences between the cutting forces with and without ultrasonic effect were analyzed theoretically and experimentally.The results indicate that the cutting force of diamond wire increases along with the spindle speed decrease and the lateral pressure increase.The force in ultrasonic vibration cutting is about 20% to 30% less than that in conventional cutting.Also,the cutting trajectory of single diamond grit in sawing process is simulated,and the reason that the ultrasonic vibration can reduce the cutting force is explained further.

Surface effects of hybrid vibration-assisted femtosecond laser system for micro-hole drilling of copper substrate

The ultrafast laser based hybrid machining system was studied and a novel approach was demonstrated to improve laser machining quality on metals by vibrating the optical objective lens with a low frequency (500 Hz) and various displacements (0-16.5 μm) during a femtosecond laser machining process.The laser used in this experiment is an amplified Ti:sapphire femtosecond (10-15 s) laser system that generates 100 femtosecond pulses having an energy of 3.5 mJ/pulse with a 5 kHz repetition rate at a central wavelength of 790 nm.It is found that both the wall surface finish of the machined structures and the aspect ratio obtained using the frequency vibration assisted laser machining are improved compared with those derived via laser machining without vibration assistance.