Audio signal analysis for tool wear monitoring in sheet metal stamping

Ubhayaratne, Indivarie; Pereira, Michael; Xiang, Yong; Rolfe, Bernard

doi:10.1016/j.ymssp.2016.09.014

Cited by 55 publications

(27 citation statements)

References 37 publications

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“…Qualitative visual assessment is often used to determine the severity of wear on tooling and parts, and remains the most ubiquitous and effective method for characterising and identifying the severity of galling wear. The effectiveness of visual assessment has led to its use in numerous wear studies, often in addition to other quantitative measures [7,8,[10][11][12][13][14][15][16][17][18][19][20][21]. Due to the difficulty of assessing tooling during forming operations visual assessment of formed parts is a primary method used in industrial applications for determining if tool maintenance is required [22].…”

Section: Galling Wear Measurementmentioning

confidence: 99%

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

Voss

Pereira

Rolfe

et al. 2017

Wear

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A new methodology for measuring galling wear severity in high strength steels, Wear, http://dx. AbstractWith the increased usage of Advanced High Strength Steels, galling wear has become a significant challenge for sheet metal stamping industries. Galling, in particular, can have a large economic impact due to the high costs and lost productivity associated with manual monitoring, refinishing/resurfacing damaged tooling and formed parts, and the need to apply expensive treatments or coatings to tool surfaces. This has led to a push for automated galling wear detection systems. However, developing such systems requires an accurate measurement of galling wear severity that can be easily implemented in industrial situations. Parameters used for measuring galling wear are often difficult to collect in large industrial style trials, and can be inaccurate as they are not targeted towards characterising the localised features associated with galling wear damage. In this study, a new galling wear characterisation and measurement methodology is introduced that accurately measures galling wear severity by targeting the localised features on sheet metal parts. This methodology involves calculating Discrete Wavelet Transform detail coefficients of 2D surface profiles. A case study on a series of deep drawn channel parts demonstrates the accuracy of the Discrete Wavelet Transform methodology when compared to visual assessment of galling wear severity. Based on comparison to visual assessment the presented Discrete Wavelet Transform galling wear measurement methodology outperforms other commonly used wear measures. The methodology provides a targeted, repeatable and non-subjective measure of galling wear severity. The specific outcome of this work provides an important tool for research into galling wear monitoring and detection systems in sheet metal forming, and the study of galling wear and its prevention in general.

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Section: Galling Wear Measurementmentioning

confidence: 99%

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

Voss

Pereira

Rolfe

et al. 2017

Wear

Self Cite

View full text Add to dashboard Cite

show abstract

“…The increased use of advanced and ultra-high strength steels in car body panels has led to an increase in stamping force and stress on the stamping tools used in vehicle body manufacturing, leading to untimely failure of stamping tools [1]. Failure of stamping tools is primarily attributed to an adhesive wear mechanism called galling.…”

Section: Introductionmentioning

confidence: 99%

“…Further condition monitoring studies are required to identify the progressive behaviour of tool wear. Ubhayaratne et al [1] performed condition monitoring on a semi-industrial stamping setup using audio sensors. The relative cumulative spectral power index feature of the audio signal was proposed to monitor progressive wear behaviour of stamping tool.…”

Section: Introductionmentioning

confidence: 99%

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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“…Some people have gradually turned their attention to the study of acoustic emission (AE) signals. AE signals are well studied and applied in the classification of composite material damage mechanisms [ 18 , 19 ], tool wear analysis [ 20 , 21 ] and detection of crack damage based on ultrasonic testing [ 22 ]. However, in the aspect of identification and recognition of bone layers, the AE signals are still in a research phase.…”

Section: Introductionmentioning

confidence: 99%

State Recognition of Bone Drilling Based on Acoustic Emission in Pedicle Screw Operation

Guan

Sun

et al. 2018

Sensors

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Pedicle drilling is an important step in pedicle screw fixation and the most significant challenge in this operation is how to determine a key point in the transition region between cancellous and inner cortical bone. The purpose of this paper is to find a method to achieve the recognition for the key point. After acquiring acoustic emission (AE) signals during the drilling process, this paper proposed a novel frequency distribution-based algorithm (FDB) to analyze the AE signals in the frequency domain after certain processes. Then we select a specific frequency domain of the signal for standard operations and choose a fitting function to fit the obtained sequence. Characters of the fitting function are extracted as outputs for identification of different bone layers. The results, which are obtained by detecting force signal and direct measurement, are given in the paper. Compared with the results above, the results obtained by AE signals are distinguishable for different bone layers and are more accurate and precise. The results of the algorithm are trained and identified by a neural network and the recognition rate reaches 84.2%. The proposed method is proved to be efficient and can be used for bone layer identification in pedicle screw fixation.

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Audio signal analysis for tool wear monitoring in sheet metal stamping

Cited by 55 publications

References 37 publications

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

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

Investigation of Galling Wear Using Acoustic Emission Frequency Characteristics

State Recognition of Bone Drilling Based on Acoustic Emission in Pedicle Screw Operation

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