Investigations on belt polishing of heat-resistant titanium alloys

Axinte, Dragoş; Kritmanorot, M.; Axinte, Mihai; Gindy, Nabil

doi:10.1016/j.jmatprotec.2004.08.030

Cited by 56 publications

(25 citation statements)

References 3 publications

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“…In step 4 the training and testing phase is accomplished. Finally in the last step the trained neural network was used to predict tool conditions [11] (2) broken/worn. In steps two the learning rate, momentum factor and the number of hidden layers/hidden neurons were defined.…”

Section: Neural Decision System Developmentmentioning

confidence: 99%

Detect Tool Breakage By Using Combination Neural Decision System & Anfis Tool Wear Predictor

Mohtaram¹

2013

IJMEA

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Abstract:The original contribution of the research is the developed monitoring system that can detect tool breakage in real time by using a combination of neural decision system and ANFIS tool wear predictor. The ANFIS method uses the relationship between flank wear and the resultant cutting force to estimate tool wear. Therefore, the ANFIS method is used to extract the features of tool states from cutting force signals. A neural network is used in tool condition monitoring system (TCM) as a decision making system to discriminate different malfunction states from measured signal. A series of experiments were conducted to determine the relationship between flank wear and cutting force as well as cutting parameters. The forces were measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge was monitored by using a tool maker's microscope. The experimental force and wear data were utilized to train the developed simulation environment based on ANFIS modeling. By developed tool condition monitoring system (TCM) the machining process can be on-line monitored and stopped for tool change based on a pre-set tool-wear limit.

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Section: Neural Decision System Developmentmentioning

confidence: 99%

Detect Tool Breakage By Using Combination Neural Decision System & Anfis Tool Wear Predictor

Mohtaram¹

2013

IJMEA

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“…In ultraprecision freeform polishing, the surface error profile and the tool removal characteristic are necessary. The removal characteristic of the polishing tool is also known as the removal function [10] and the influence function. Measurements are included in the acquisition of these data.…”

Section: Factors Affecting Surface Generation In Ultraprecision Freefmentioning

confidence: 99%

“…Most research involving the material removal mechanisms involved in polishing relates to classical polishing methods such as belt polishing [10], free *Corresponding author: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, People's Republic of China. email: mfbenny@inet.polyu.edu.hk abrasive polishing [11], fixed abrasive polishing [12], chemical mechanical polishing [13], fluid jet polishing [14], etc.…”

Section: Introductionmentioning

confidence: 99%

Analysis of surface generation in the ultraprecision polishing of freeform surfaces

Cheung

Charlton

et al. 2009

Proceedings of the Institution of Mechanical Engineers, Part B:

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The use of freeform designs in engineering surfaces has become increasingly popular over the last decade. Applications of freeform shapes range from aesthetics of components to the bending of light rays through advanced optic designs. The fabrication of the components for these applications requires submicrometre form accuracy, in some cases with surface roughness at nanometric levels. Ultraprecision polishing is an emerging technology for the fabrication of high-precision and high-quality freeform surfaces. However, the factors affecting nanosurface generation in ultraprecision polishing have received relatively little attention. Moreover, the quality of the polished surface relies heavily on appropriate selection of process conditions and polishing strategies. This paper presents an analytical study of the factors affecting surface generation in ultraprecision polishing. A series of polishing experiments have been designed and undertaken, allowing the relationships between various factors and the surface quality of the workpiece to be determined. The results of the study provide a better understanding of nanosurface generation, as well as the strategy for optimizing surface quality, in the ultraprecision polishing of freeform surfaces.

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“…Bigerelle et al showed that automotive designers impose morphological specifications obtained by the belt grinding process to prevent scuffing of the motor parts [27]. Axinte et al studied the workpiece surface integrity of Ti-6-4 heat-resistant alloy when employing different polishing methods [28,29].…”

Section: Introductionmentioning

confidence: 99%

Equivalent self-adaptive belt grinding for the real-R edge of an aero-engine precision-forged blade

Xiao

Huang

2015

Int J Adv Manuf Technol

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Because of the special characteristics of aeroengine precision-forged blade edges such as heat-resistant and high-strength materials, the unequal distribution and small removal allowance, and easy deformation in processing, edge profile shape errors are easily caused by using conventional processing methods. These errors include chamfered, sharp, flat, and obtuse edges and cervical part shrinkage, so the real-R shape of the edge is difficult to guarantee, and the aeroengine air dynamic performance is seriously affected. The purpose of this research is to improve the dimensional precision, profile shape errors, and surface quality of the real-R edge of the precision-forged blade. With these aims, the method of equivalent self-adaptive belt grinding (ESBG) using a cubic boron nitride (CBN) belt is developed in this study. First, the grinding characteristics and process planning to the blade real-R edge are analyzed. The methodologies of equivalent belt grinding (EBG) and ESBG using a CBN belt are then illustrated, the control equation for EBG is established, and the method of force adaptive control is introduced. Finally, the ESBG method using the CBN belt is verified by experimental investigation of the aero-engine precision-forged blade and comparison with manual and EBG methods. The experimental results showed that the ESBG method using the CBN belt achieved the requirements of the aero-engine precision-forged blade real-R edge. It was verified that the method of ESBG using the CBN belt has the advantages of real-R shape dimensional precision and surface quality for the blade edge compared with the conventional method.

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Investigations on belt polishing of heat-resistant titanium alloys

Cited by 56 publications

References 3 publications

Detect Tool Breakage By Using Combination Neural Decision System & Anfis Tool Wear Predictor

Detect Tool Breakage By Using Combination Neural Decision System & Anfis Tool Wear Predictor

Analysis of surface generation in the ultraprecision polishing of freeform surfaces

Equivalent self-adaptive belt grinding for the real-R edge of an aero-engine precision-forged blade

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