Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

Guo, Jian; Shi, Yaoyao; Chen, Zhe; Yu, Tao; Shirinzadeh, Bijan

doi:10.3390/sym11121526

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…According to the grey correlation analysis theory, the greater the grey correlation degree, the closer the corresponding target sequence is to the optimal (Guo et al, 2019). Figure 5 shows the average grey correlation degree of each parameter level.…”

Section: Key Influence Parameter Selectionmentioning

confidence: 99%

Multi-objective optimization of PEMFC performance based on grey correlation analysis and response surface method

Luo

2023

Front. Energy Res.

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This paper aims to combine grey correlation analysis and response surface method to propose a fast and effective performance optimization method for PEMFC. First, based on orthogonal test data, grey correlation analysis method is used to select four variables that have significant influence on PEMFC’s comprehensive performance from eight common parameters. Secondly, based on grey correlation analysis, the multi-objective optimization problem is transformed into a single objective optimization problem about correlation degree, and applying the response surface method to build the key parameters and the correlation between the second order prediction model. Therefore, the current density, system efficiency and oxygen distribution uniformity on cathode catalyst layer of PEMFC were optimized as a whole. Finally, the optimal parameter combination was obtained by optimizing the prediction model. The simulation results show that the optimized operating conditions are significantly improved in the three performance indexes compared with the basic model, which confirms the feasibility of this method in solving the multi-objective optimization problem, and can provide some reference for the optimal design of hydrogen fuel cells.

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Section: Key Influence Parameter Selectionmentioning

confidence: 99%

Multi-objective optimization of PEMFC performance based on grey correlation analysis and response surface method

Luo

2023

Front. Energy Res.

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“…Surface integrity is carefully examined after complex surface treatments of titanium alloys. For example, in [11], a multi-criteria method to optimize process parameters was proposed to reduce surface roughness and improve the material removal rate. In [12], the effect of grinding parameters, such as the cutting speed, feed rate, grinding depth, and abrasive size, on surface integrity was experimentally studied.…”

Section: Introductionmentioning

confidence: 99%

Machinability Features of Ti-6Al-4V Alloy with Ultrafine-Grained Structure

Semenova,

Polyakov,

Gareev

et al. 2023

Metals

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Titanium alloys are widely used in various industries. The most common and well-known titanium alloy is titanium alloy with aluminum and vanadium (Ti-6Al-4V). This alloy is used, for example, in the manufacture of aircraft engines. As part of the development of technologies and the emergence of the evolving requirements for materials, Ti-6Al-4V alloys with ultrafine grains less than 1 μm may become promising. This modification of the alloy has excellent strength characteristics, such as increased fatigue resistance. However, manufacturers are aware of the machinability problem of titanium alloys. To date, a sufficiently high level of understanding of this problem has already been achieved. But, there is practically no information about the machinability of ultrafine-grained alloys and their comparison, in this regard, with the usual coarse-grained version. This study presents the results of experimental studies on the influence of cutting parameters (cutting speed, V, m/min; feed rate, Fz, mm/rev) on the roughness and microstructure of the surface of Ti-6Al-4V samples with coarse-grained and ultrafine-grained structures produced via equal-channel angular pressing. It is shown that turning at a low cutting speed (V = 48 m/min) results in a better surface roughness, Ra, for the coarse-grained sample compared to its ultrafine-grained alloy counterpart. When the cutting speed is increased by 1.5 times (up to V = 72 m/min), on the contrary, the ultrafine-grained sample has a lower surface roughness, Ra, compared to the coarse-grained sample. The differences in the morphology and microstructure of the chips, depending on the microstructure type of the processed alloy, are discussed: the presence of plastic flow lines in the chip microstructure of the turned ultrafine-grained sample and the formation of shear bands, cleavages, and microcracks in the chips of the turned coarse-grained alloy.

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“…Many researchers have extensively researched the surface integrity of complex surface machining of titanium alloys. Guo et al (2019) proposed a multi-objective method for optimising process parameters. Through the experimental study of belt polishing, they achieved the optimum parameter combination, which may reduce the surface roughness and improve the material removal rate.…”

Section: Introductionmentioning

confidence: 99%

Titanium alloys surface integrity of belt grinding considering different machining trajectory direction

et al. 2022

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The interplay of abrasive grains and materials complicates the grinding of titanium alloys by abrasive belts. Notably, the influence relationship of surface generation for complex curved workpieces such as hollow blades needs to be clarified, making precise control of the surface integrity of complex surfaces difficult in abrasive belt grinding applications. This paper thus proposes a trajectory planning method based on the direction of interaction between grinding grains and materials to reveal its influence law on the surface integrity of complex curved surfaces of titanium alloy with unevenly distributed machining allowances. First, a machining trajectory with different angles between the grinding direction and feed direction is proposed. In order to determine the corresponding experimental scheme for titanium alloy hollow blades. Experimental results are used to analyze the influence of different grinding trajectory directions on the surface roughness, residual stress, surface topography, and accuracy of the contours. The results show that different grinding trajectory directions significantly affect the workpiece’s surface integrity. By varying the grinding trajectory direction, it is possible to reduce the surface roughness of titanium alloy workpieces by approximately 40%, increase the surface residual compressive stress by approximately 50%, provide a finer workpiece surface and improve the consistency of the surface texture. This work is expected to guide the efficient and high-quality machining of complex curved parts such as titanium alloy hollow blades.

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Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

Cited by 5 publications

References 19 publications

Multi-objective optimization of PEMFC performance based on grey correlation analysis and response surface method

Multi-objective optimization of PEMFC performance based on grey correlation analysis and response surface method

Machinability Features of Ti-6Al-4V Alloy with Ultrafine-Grained Structure

Titanium alloys surface integrity of belt grinding considering different machining trajectory direction

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