Tool wear monitoring through online measured cutting force and cutting temperature during face milling Inconel 718

Liu, Delin; Wang, Qingqing; Zhao, Jiaqi; Song, Qinghua; Ren, Xiaoping; Ma, Haifeng

doi:10.1007/s00170-022-09950-2

Cited by 22 publications

(7 citation statements)

References 33 publications

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“…Based on the previous work of the authors [36], the directional spectral emissivity ε can be sketched using Equation (9),…”

Section: Derivation Of Directional Spectral Emissivitymentioning

confidence: 99%

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Prediction of Isotropic Rough Surface Directional Spectral Emissivity with Surface-Morphology-Dependent Modelling

Hu,

Liu,

Zhao

et al. 2023

Metals

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The surface directional spectral emissivity of rough metal surfaces in industry is of concern in infrared temperature measurement. In this research, the height and slope possibility density functions are introduced as variables, and the directional spectral emissivity of isotropic rough surface is modelled accordingly. The model is designed to derive the directional spectral emissivity of rough metal surfaces from the surface morphology (possibility distribution of the height and slope) and the material property parameters (refractivity). Then, a sandblasted surface is taken as a case study. The sandblasted surface morphology is measured. A Polynomial surface is proposed to describe the sandblasted surface morphology and is compared with a Gaussian surface and a Cox–Munk surface. Finally, the directional spectral emissivity measurement and infrared temperature measurement are conducted. It is shown that the predicted directional spectral emissivity and measured temperature with the surface-morphology-dependent isotropic rough surface directional spectral emissivity model have high precision. In this work, the possibility distribution of the height and slope of the surface is introduced as independent variables to provide better accuracy compared to the reported models. In some cases, the error of the infrared temperature measurement could be reduced to 20% (80 degrees, compared to Gaussian surface). This work contributes to improving the accuracy of IR temperature measurement of rough surfaces.

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“…Based on the previous work of the authors [36], the directional spectral emissivity ε can be sketched using Equation (9),…”

Section: Derivation Of Directional Spectral Emissivitymentioning

confidence: 99%

“…The temperature field drawn in the experiment was compared to theoretical results, and the influence of the tool rake angle was studied. Liu et al [9] applied infrared imaging on the milling of Inconel 718. The thermos image was compared to the predicted temperature as verification.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Isotropic Rough Surface Directional Spectral Emissivity with Surface-Morphology-Dependent Modelling

Hu,

Liu,

Zhao

et al. 2023

Metals

Self Cite

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“…[3][4][5] To address this, a variety of physical indicators and analysis and evaluation methods for evaluating the degree of milling cutter wear have been proposed, and based on the law of friction, friction work, and friction coefficient model, using the structural parameters of the milling cutter and the cutting parameters of the milling cutter on the friction variables in the milling process of the friction characteristics of the milling cutter cutting process, to obtain the prediction of milling cutter wear and the optimization of process parameters, and to develop the prediction of the milling cutter service life method and the monitoring system. [6][7][8][9] The above research points out the direction for revealing the friction and wear process of high-efficiency milling cutters and realizing the effective control of milling cutter service life.…”

Section: Introductionmentioning

confidence: 98%

Identification method for unsteady friction of tool flank for high efficiency milling cutter

Jiang,

Wang,

Zhao

et al. 2023

Advances in Mechanical Engineering

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Under the cutting loads of high efficiency and intermittent, the friction status between the tool flank and transition surface has time-varying characteristics, which directly affects friction and wear performance of the milling cutter. The dynamic distribution of instantaneous friction on tool flank under milling vibration needs to be revealed. In this work, the effect of milling vibration on instantaneous cutting contact relationship between milling cutter and workpiece was researched, a calculation method for the instantaneous friction velocity and friction energy consumption on tool flank was proposed. The variation of instantaneous friction between tool flank and transition surface under milling vibration was identified and evaluated by power spectral entropy and cross-correlation function. A method for identifying the unsteady friction of tool flank was proposed. The response analysis and experimental verification were conducted. The results showed that the frequency domain parameter distribution of friction energy consumption on tool flank had a strong correlation with the wear depth distribution, and was obviously sensitive to the milling parameters. The above models and methods could be used to reveal the influence of key milling process variables on unsteady friction and wear process of milling cutter’s multiple tool flank.

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“…Different types of sensors have been investigated in previous studies for tool wear monitoring, including the current sensor [10,11], dynamometer [12][13][14][15][16][17], accelerometer [18][19][20][21], acoustic emission (AE) sensor [22][23][24][25][26], microphone [27][28][29][30], and vision sensor [31,32]. Multi-sensor systems were also studied to improve system reliability [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Cutting Path Effect on Spindle Vibration and AE Signal Features for Tool Wear Monitoring in Micro Milling

Huang

2023

Applied Sciences

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In the development of a tool wear monitoring system in milling, the complex cutting path always brings challenges to the system’s reliability in the production line. The cutting path effect on the acoustic emission (AE) and vibration signals during the micro milling processes was investigated in this study by implementing three types of cutting paths in a micro milling experiment. To generate the data for analysis, an experiment was conducted on a micro milling research platform using an AE sensor and an accelerometer installed on a fixture attached to the spindle housing. To demonstrate the effect of the cutting path on the performance in the monitoring of tool wear, a simple linear classifier is proposed, along with the signal features generated from the different signal lengths and the bandwidth size in the frequency domain. The results show that the signal features generated from the cutting of a straight line, the corner of the square path, and the circle path are different from each other. The increase in the signal length to generate features, which will reduce the corner effect, could improve the performance of the developed monitoring system. However, the results suggest that avoiding the complex cutting path for feature generation might be a better strategy for developing a micro milling tool wear monitoring system.

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Tool wear monitoring through online measured cutting force and cutting temperature during face milling Inconel 718

Cited by 22 publications

References 33 publications

Prediction of Isotropic Rough Surface Directional Spectral Emissivity with Surface-Morphology-Dependent Modelling

Prediction of Isotropic Rough Surface Directional Spectral Emissivity with Surface-Morphology-Dependent Modelling

Identification method for unsteady friction of tool flank for high efficiency milling cutter

Investigation of Cutting Path Effect on Spindle Vibration and AE Signal Features for Tool Wear Monitoring in Micro Milling

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