A new methodology for measuring galling wear severity in high strength steels

Voss, B.; Pereira, Michael; Rolfe, Bernard; Doolan, Matthew

doi:10.1016/j.wear.2017.09.002

Cited by 19 publications

(10 citation statements)

References 47 publications

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“…Although quantitative analysis can provide statistical analysis of data [27] and objective and precise merits [41], it is difficult in description and justification of variation direction. Qualitative analysis is versatile/ubiquitous and easy to apply [42,43]. Moreover, it can predict variation direction of test result and obtain overwhelming parameter [27], as well as offer evaluative general information [44], suit most practical conditions, and simplify experimental and measurement procedures [45].…”

Section: Resultsmentioning

confidence: 99%

Research on Erosion-Corrosion Rate of 304 Stainless Steel in Acidic Slurry via Experimental Design Method

Zhao

Wang

2019

Materials

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A full three-factor two-level factorial experimental design method was carried out to investigate the effects of a single factor and their combining actions on weight loss of 304 stainless steels (304 SS). Quantitative analysis was performed to calculate the contribution values of temperature, rotation speed, sulfuric acid concentration, and synergistic actions. In particular, an 8 × 8 matrix was designed for the first time to define variation direction of erosion wear rate by qualitative analysis. The results show that slurry temperature has the most significant influence followed by sulfuric acid concentration. Rotation speed has the smallest effect. The synergies of the parameters all accelerate the weight loss rate, but they exhibit different intensity. This research provides useful guidelines for estimating the effects of environmental factors and material design in practical engineering application.

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Section: Resultsmentioning

confidence: 99%

Research on Erosion-Corrosion Rate of 304 Stainless Steel in Acidic Slurry via Experimental Design Method

Zhao

Wang

2019

Materials

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“…The bandpower is high in the AE frequency range of 0.1-0.5 MHz at 10 s for D p 0.22 and at 12 s for D p 0.26. As mentioned above, this is mainly due to the intensity of abrasive wear events due to the galling wear [9,27]. Figure 21represents the frequency-magnitude graph of the AE burst waveforms from the scratch test.…”

Section: Frequency Characteristics Of the Ae Burst Waveform During Wementioning

confidence: 88%

“…For the entire scratch duration, the information related to the non-galling and galling wear is dominant in the AE frequency range of 0.1-0.5 MHz (Figure 21a,b). The high magnitude of the frequency peak observed at 10 and 9 s for D p 0.22 and 0.26 (Figure 21c,d), is due to the high intensity abrasive wear events on the workpiece due to the galling wear [9,27]. In Figure 21a,b, the increase in the magnitude of the frequency peak from 6 s for D p 0.22 and from 5 s for D p 0.26, indicate the onset of galling wear initiation.…”

Section: Frequency Characteristics Of the Ae Burst Waveform During Wementioning

confidence: 94%

“…From Figure 11d,e, along with ploughing wear, fracture is also observed. The presence of fracture on the sheet surface is likely due to the growth and work hardening of the lump on the tool (Figure 11f) that results in fracture/cutting wear mode on the sheet surface [9,27,28]. Figure 12represents the selected AE burst waveforms from the stamping test.…”

Section: Profilometry Study Of Stamped Partsmentioning

confidence: 99%

“…From Figure 19e, the maximum power intensity is observed to be in the AE frequency range of 0.02-0.5 MHz. The difference in the AE power concentration in Figure 19f, compared to that of the Figure 19c-e is due to the difference in the intensity of abrasive wear events due to galling wear [9,27]. To quantitatively study the dominant AE frequency range, the AE bandpower and frequencymagnitude study was performed.…”

Section: Frequency Characteristics Of the Ae Burst Waveform During Wementioning

confidence: 99%

See 2 more Smart Citations

Investigation of Galling Wear Using Acoustic Emission Frequency Characteristics

2020

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In the sheet metal stamping process, during sliding contact between the tool and sheet, it is expected that severe events such as tool wear or fracture on the sheet generate acoustic emission (AE) burst waveforms. Attempts have been made in the literature to correlate the AE burst waveform with the wear mechanisms. However, there is a need for additional studies to understand the frequency characteristics of the AE burst waveform due to the severity and progression of the galling wear. This paper will determine the AE frequency characteristics that can be used to monitor galling wear, independent of the experimental process examined. The AE burst waveforms generated during the stamping and scratch tests are analysed in this paper to understand the change in the AE frequency characteristics with the galling severity. These AE burst waveforms were investigated using the Hilbert Huang Transform (HHT) time-frequency technique, band power, and mean-frequency. Subsequently, these AE frequency features are correlated with the wear behaviour observed via high-resolution profilometer images of the stamped parts and scratch surfaces. Initially, the HHT technique is applied to the AE burst waveform to understand the influence of wear severity in the power distribution over the wide AE frequency range. Later, the AE bandpower feature is used to quantitatively analyse the power in each frequency interval during the unworn and worn tool conditions. Finally, the mean-frequency of AE signal is identified to be able to determine the onset of galling wear. The new knowledge defined in this paper is the AE frequency features and wear measurement feature that can be used to indicate the onset of galling wear, irrespective of the processes examined. Highlights •AE burst waveform can be used to investigate galling. • AE mean-frequency can indicate galling wear initiation at industrial and tribological condition. • Profile depth wear feature can be used quantitatively to correlate with AE frequency features. • Frequency-magnitude and bandpower increased with increase in galling severity.

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Relating wear stages in sheet metal forming based on short- and long-term force signal variations

et al. 2022

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Monitoring systems in sheet metal forming cannot rely on direct measurements of the physical condition of interest because the space between the die component and the material is inaccessible. Therefore, in order to gain further insight into the forming or stamping process, sensors must be used to detect auxiliary quantities such as acoustic emission and force that relate to the physical quantities of interest. While it is known that changes in force data are related to physical parameters of the process material, lubricant used, and geometry, the changes in data over large stroke series and their relationship to wear are the subject of this paper. Previously, force data from different wear conditions (artificially introduced into the system and not occurring in an industry-like environment) were used as input for clustering and classifying high and low wear force data. This paper contributes to fill the current research gap by isolating structural properties of data as indicators of wear growth to quantify the wear evolution during ongoing production in industry-like scenarios. The selected methods represent either established methods in sheet metal forming force data analysis, dimensionality reduction for local structure separation or generic feature extraction. The study is conducted on a set of four experiments with each containing about 3000 strokes.

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A new methodology for measuring galling wear severity in high strength steels

Cited by 19 publications

References 47 publications

Research on Erosion-Corrosion Rate of 304 Stainless Steel in Acidic Slurry via Experimental Design Method

Research on Erosion-Corrosion Rate of 304 Stainless Steel in Acidic Slurry via Experimental Design Method

Investigation of Galling Wear Using Acoustic Emission Frequency Characteristics

Relating wear stages in sheet metal forming based on short- and long-term force signal variations

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