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Coolants play an important role in controlling thermal damage in high-efficiency deep grinding (HEDG). The cooling condition in the grinding contact zone (GCZ) determines the cooling effect during ...

The plunger component is a key part of the plunger pump in the aircraft hydraulic system. Neck-spinning process is commonly used to fabricate plunger components, of which the quality of the spinning process significantly affects the performance of plunger pumps. One of the bottlenecks faced by the industry in the spinning process is to choose a suitable neck-spinning process so as to ensure the quality of plunger components. It is necessary to propose a reliable method to optimize the process parameters which affect the neck-spinning quality of plunger components. In this study, a calculable finite element analysis (FEA) model is established to simulate the three-roller neck-spinning process of the plunger component, which includes six typical slipper structures, two roller structures, and two spinning parameters. The FEA model is then validated by comparing the simulated spinning forces with the corresponding experimental results. The influence of the process conditions on the neck-spinning quality is investigated. And the orthogonal simulation results are analyzed by a combination of range method and fuzzy mathematical analysis method to recommend a reasonable slipper structure, roller structure and neck-spinning parameters. This study provides a promising method to improve the manufacturing quality of the typical plunger components.

Hollow blades, which are important components of aeroengines, have thin-walled structures and are subjected to vibrations in the machining process owing to its low rigidity and damping. This paper proposes an approach to enhance the machining stability of titanium hollow blades by introducing multiple damping and rigid supporters to the blade machining system in multi-axis milling process. A theoretical prediction model, considering the influence of original system, transmission and supporter, is established to predict the dynamic parameters of blade with a single damping or rigid supporter. Then, the model is applied in multi-supporter system and an optimization algorithm is used to determine reasonable positions of multiple supporters. The stability lobe diagrams of blade system with no supporter, optimized damping supporters and optimized rigid supporters are analysed and validated by blade machining experiment. The conclusion can be achieved that the sound signal is suppressed up to 40 % by adding optimized supporters and the machining stability is enhanced effectively.

On-machine measurement is being used increasingly to inspect the features of machined components without removing the workpiece from the machine tool. In the present work, a laser displacement sensor is integrated on a machine tool to measure the elementary features of a step, hole, cylinder, and plane. An iterative calibration method is introduced to obtain the position and direction of the sensor accurately, and data processing is performed for filtration and edge recognition. The accuracy and uncertainty of detecting the characteristic parameters of height, diameter, roundness, and flatness by the laser-based on-machine measurement are evaluated and are compared with those of a mechanical probe. Furthermore, the capability of the on-machine measurement process on the adopted machine tool is assessed according to ISO 22514-7. The results show that the difference between the calibrated and actual sphere center is reduced to 4.7 μm after five iterations. The on-machine measurement by the mechanical probe is more accurate, while that by the laser displacement sensor is more efficient. The uncertainties of the two methods are evaluated as being in the ranges of 2.4–3.7 μm and 4.8–5.8 μm, respectively. The accessible tolerances can be obtained to determine whether the machine tool is competent for requirement as a measuring device.

On-machine measurement (OMM) is increasingly used to inspect freeform surfaces without unloading the workpiece from the machine tool. Compared to the mechanical probe deployed in many OMM processes, a laser displacement sensor has its advantage of high scanning efficiency. However, the accuracy has been a bottleneck limiting its application in precision inspection, due to the lack of a rigorously planned path. In this work, an error compensation model is established and verified considering laser triangulation error, misalignment from calibration, tooling error, and preevaluated error. Essentially, error modeling contributes to improve the measurement accuracy of laser triangulation OMM (LTOMM). After understanding these errors, a reliable measuring path is crucial to maintain the given accuracy of LTOMM. This path generated is capable of minimizing the measurement time at a given accuracy constraint. In a particular case study, a turbine blade surface was inspected using LTOMM following generated path against a built-in probe. The measurement time was reduced by 77.4% for a constraining accuracy of $\pm 10~\mu \text{m}$ . The time could be further reduced by 38.6%, for a constraining accuracy of $\pm 13~\mu \text{m}$ . This study has demonstrated that LTOMM could potentially replace the on-machine probe during measurement of freeform surfaces, toward more efficient industrial applications in the future.

In order to better understand the dressing behavior, an investigation was carried out to detect the contact zone between vitrified bonded cubic boron nitride (V-CBN) abrasive wheel and diamond grit dresser. The grinding experiment of single diamond grit dresser on V-CBN abrasive segment was designed and conducted to approach the actual dressing process. The moving trajectory during dressing was calculated and discussed. Acoustic emission (AE) signals were applied to evaluate the wear progression of V-CBN abrasive wheel. Results obtained discovered that the different trajectory length would result in different wear patterns of diamond grit dresser and vitrified bond of V-CBN abrasive wheel. With the increase of wear ratio, the AE root-mean-square (RMS) voltages also had an increasing trend during dressing V-CBN wheel. Furthermore, a shorter dressing trajectory length produced a lower and more stable surface roughness, a lower tool radial wear and a higher grinding ratio in the grinding experiment of Inconel 718 nickel-based superalloy.

Hollow blades with honeycomb structures are increasingly used in the turbine engines for reducing weight and saving costs. The hollow blade is a typical thin-walled structural part with low stiffness, the machining system of which is often unstable and likely to chatter. The most effective solution to avoid the machining chatter is to guide the hollow blade to be machined in a stable machining zone. This paper proposes a measurement-based approach for modal analysis and stability prediction of turn-milling hollow blade. The impact test was carried out to achieve the FRF curves on the hollow blade and the milling tool. An extremum method was employed to obtain an equivalent FRF curve, from which the modal parameters involving the natural frequency, damping ratio, and stiffness were computed. Afterwards, the semidiscretization method was used to draw a stability lobe diagram to predict the stability when turn-milling hollow blades. The experimental results confirm the feasibility of the predicted stability lobe diagram.

During the high-efficiency deep grinding of a turbine blade root, localized thermal damage of the profile surface could easily occur owing to the complexity of the grinding dynamics and cooling conditions in the grinding zone. Therefore, it is worthwhile to investigate the generation of the grinding heat, the grinding temperature and its distribution, and the grinding surface quality, particularly for superalloys used to produce aero-turbine blades. In this study, the specific grinding energy and grinding heat flux during the profile grinding of a fir tree-shaped root of a DZ125 superalloy turbine blade were investigated. The grinding temperature at four points on the profile were measured and the results were used to conduct a three-dimensional simulation to analyze the temperature distribution on the machined surface and in the direction of the cutting depth. The effects of the heat source shape and contact length on the temperature distribution were also examined. A moderately high material removal rate was found to be beneficial to the surface quality, with a maximum material removal rate of 50.6 mm3/mm·s producing a surface roughness of Ra 0.6 μm without saturation or microstructural changes. Residual compressive stress was also achieved on the ground surface.

Localization plays an important role in manufacturing the curved thin-walled parts, which can determine the distribution of machining allowance and has great influence on the manufacturing accuracy. The registration algorithm is the most efficient way to locate the billet in the machining coordinate system of the machine tool by computing a transformation matrix. However, the localization of the curved thin-walled parts is complicated and challenging since the billets are individual, the shape and location of which are unknown. This paper attempts to develop an adaptive localization approach with the constraints of the profile and thickness based on on-machine measured data. The framework for constrained adaptive localization approach is illustrated, in which on-machine measurement, registration, isometric mapping and allowance optimization are involved. The details of the on-machine measurement for both the profile inspection and the thickness measurement are presented. An isometric mapping method is employed to build the separate point pairs between the measured points and the nominal shape of the part. A constrained optimization algorithm for the machining allowance is performed iteratively until meeting the constraints of the profile and thickness tolerance ranges. Finally, a case study of constrained adaptive localization was carried out, the results of which confirm the validity of the proposed approach.

Polycrystalline CBN (PCBN) grinding wheel has self-sharpening ability, which is beneficial in maintaining its cutting ability, due to its unique structure. However, only few quantitative methods to evaluate the self-sharpening ability of PCBN are available. In this research, wear experiments of PCBN grinding wheel were carried out. The wear phenomena were discussed on the basis of SEM images and grain protrusion height. The self-sharpening ability of the grinding wheel was evaluated using fractal dimension. The grinding performance was discussed. Grinding experiments of monocrystalline CBN (MCBN) grinding wheel were conducted for comparison. Results showed that the main wear modes of PCBN grinding wheel were intergranular fractures and attrition wear of abrasive grains, whereas that of MCBN grinding wheel was transgranular fracture of grain. The fractal dimensions of PCBN grinding wheel nearly remained constant, whereas those of MCBN grinding wheel decreased continuously in the initial and steady wear stages. Lower standard deviation of grain protrusion height was obtained using PCBN grinding wheel than using MCBN grinding wheel during the steady wear stage. The active grain ratio of PCBN grinding wheel was 1.84 times larger and its grinding force was 18.6% lower than those of MCBN grinding wheel. An enhanced workpiece surface was obtained using PCBN grinding wheel.