Proposals of Frequency-Based and Direction Methods to Reduce the Influence of Surface Topography Measurement Errors

2022

Applied Sciences

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Studies of surface topography including processes of measurement and data analysis have an influence on the description of machined parts with their tribological performance. Usually, surface roughness is analysed when a scale-limited (S-L) surface, excluding short (S-) and length (L-) components from the raw measured data, is defined. Errors in the precise definition of the S-L surface can cause the false estimation of detail properties, especially its tribological performance. Errors can arise when the surface contains some burnished details such as oil pockets, dimples, scratches, or, generally, deep or wide features. The validation of proposed methods for S-L surface definition can also affect the accuracy of the ISO 25178 surface topography parameter calculation. It was found that the application of commonly used procedures, available in commercial software (e.g., least-square fitted cylinder element or polynomial planes, regular or robust Gaussian regression, spline, median or fast Fourier transform filters) can be suitable for precise S-L surface definition. However, some additional analyses, based on power spectral densities, autocorrelation function, texture direction graphs, or spectral characterisation, are strongly required. The effect of the definition of the S-L surface on the values of the ISO 25178 parameters was also comprehensively studied. Some proposals of guidance on how to define an appropriate S-L surface with, respectively, an objective evaluation of surface roughness parameters, were also presented.

Section: Selection Of Procedures For a High-frequency Errors Reductio...mentioning

confidence: 99%

“…Generally, the high-frequency measurement noise can be caused by the instability of the mechanics with any influences from the environment [50]. Nevertheless, in most cases, the high-frequency noise is caused by vibrations [51]. This problem seems to be even more significant when in situ measurement is provided [52,53].…”

Section: Introductionmentioning

confidence: 99%

Roughness Evaluation of Burnished Topography with a Precise Definition of the S-L Surface

2022

Applied Sciences

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“…It was found that various types of environmental disturbances can introduce noise in different bandwidths [ 35 ]. One of the types of errors caused by the environment of the measuring system is high-frequency noise (HFN) [ 36 ]; this can be caused by instability of the mechanics with any influences from the environment or by internal electrical noise, but in most cases the HFN is the result of vibration [ 37 ] and, simultaneously, in real measurement, this can greatly affect the stability of slope estimation [ 38 ].…”

Section: Introductionmentioning

confidence: 99%

Thresholding Methods for Reduction in Data Processing Errors in the Laser-Textured Surface Topography Measurements

2022

Materials

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There are many factors influencing the accuracy of surface topography measurement results: one of them is the vibrations caused by the high-frequency noise occurrence. It is extremely difficult to extract results defined as noise from the real measured data, especially the application of various methods requiring skilled users and, additionally, the improper use of software may cause errors in the data processing. Accordingly, various thresholding methods for the minimization of errors in the raw surface topography data processing were proposed and compared with commonly used (available in the commercial software) techniques. Applied procedures were used for the minimization of errors in the surface topography parameters (from ISO 25178 standard) calculation after the removal and reduction, respectively, of the high-frequency noise (S-filter). Methods were applied for analysis of the laser-textured surfaces with a comparison of many regular methods, proposed previously in the commercial measuring equipment. It was found that the application of commonly used algorithms can be suitable for the processing of the measured data when selected procedures are provided. Moreover, errors in both the measurement process and the data processing can be reduced when thresholding methods support regular algorithms and procedures. From applied, commonly used methods (regular Gaussian regression filter, robust Gaussian regression filter, spline filter and fast Fourier transform filter), the most encouraging results were obtained for high-frequency noise reduction in laser-textured details when the fast Fourier transform filter was supported by a thresholding approach.

“…It was proposed to use an analysis of some features to validate selected procedures for detecting and reducing some frequency-based errors, such as high-frequency noise. In previous studies, the feature-based decomposition approach (FBDA) was improved, and direction methods were valuable in the characterisation of turned topographies [50] or topographies with a defined direction [51]. The frequency analysis of surface topography can also be valuable in the determination of similarities [52] with the application of 2D FFT, where the description of the lateral resolution criterion for profile and areal surface topography measuring instruments is required according to the discussion in the international standardisation.…”

Section: Introductionmentioning

confidence: 99%

Feature-Based Characterisation of Turned Surface Topography with Suppression of High-Frequency Measurement Errors

2022

Sensors

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Errors that occur when surface topography is measured and analysed can be classified depending on the type of surface studied. Many types of surface topographies are considered when frequency-based errors are studied. However, turned surface topography is not comprehensively studied when data processing errors caused by false estimation (definition and suppression) of selected surface features (form or noise) are analysed. In the present work, the effects of the application of various methods (regular Gaussian regression, robust Gaussian regression, and spline and fast Fourier Transform filters) for the suppression of high-frequency measurement noise from the raw measured data of turned surface topography are presented and compared. The influence and usage of commonly used available commercial software, e.g., autocorrelation function, power spectral density, and texture direction, which function on the values of areal surface topography parameters from selected (ISO 25178) standards, are also introduced. Analysed surfaces were measured with a stylus or via non-contact (optical–white light interferometry) methods. It was found that the characterisation of surface topography, based on the analysis of selected features, can be crucial in reducing measurement and data analysis errors when various filters are applied. Moreover, the application of common functions can be advantageous when feature-based studies are proposed for both profile and areal data processing.