Monitoring of Grinding Wheel Wear

Brinksmeier, E.; Werner, Frank

doi:10.1016/s0007-8506(07)61225-6

Cited by 49 publications

(19 citation statements)

References 2 publications

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“…To avoid the problem, some researchers have implemented the non-contact technique, e.g. White Light Interferometry (WLI) [8,9], Optical profilometer [10], Scanning Laser Microscope (SLM) [11,12], laser microscope [13], laser triangulation system [14], binocular vision system [15]. Additional algorithms are required to extract the useful information of grains from the measured data given by the methods above because such methods do not extract the abrasives from the wheel, which are of important in the wheel's performance.…”

Section: Introductionmentioning

confidence: 99%

Extraction of the grains topography from grinding wheels

Cui

Huang

et al. 2013

Measurement

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Section: Introductionmentioning

confidence: 99%

Extraction of the grains topography from grinding wheels

Cui

Huang

et al. 2013

Measurement

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“…8,12 Consequently, thermal damage on ground surface doesn't necessarily evidence higher temperature of cutting edge.…”

Section: Methodsmentioning

confidence: 99%

A study on aspects of attrition wear of cutting grains in grinding process

Yamada

Ueda

Hosokawa

2011

Int. J. Precis. Eng. Manuf.

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In this study, the influences caused by the wear of grinding wheel are investigated experimentally. The infrared radiation pyrometer with an optical fiber is developed and applied for the temperature measurement in the surface grinding process of carbon steels. Experimental data such as the temperature, the number and the size of effective cutting grains and the grinding forces are obtained over the wheel life, and they are used for the calculation of the thermal energy fraction to the workpiece, the grinding wheel and the chips. Thermal damage begins to be caused on the ground surface, as the attrition wear of grains decreases the number of effective cutting grains and degrades the efficiency of grinding wheel. The measuring of radiation pulses from the cutting grains makes it possible to detect the degradation of grinding wheel at an early stage of wheel life and prevent the severe damages on work surface.

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“…Thus each single measurement consisted of at least 2500 measuring samples. The Abbott's bearing ratio curve (BRC) and its special parameters (PN EN ISO 13565-2:1999) were used to describe the grinding wheel micro-geometry (Brinksmeier and Werner 1992;Lajmert and Lezanski 2013). The BRC, determined along an assumed measuring length, is replaced by a linear description which divides the whole height of the measured profile into the three characteristic quantities: the core roughness depth R k , the reduced peak height R pk and the reduced valley depth R vk .…”

Section: Direct Measures Of Wheel State and Work-piece Qualitymentioning

confidence: 99%

The dominance-based rough set approach to cylindrical plunge grinding process diagnosis

Piłacińska

2016

J Intell Manuf

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The dominance-based rough set approach is proposed as a methodology for plunge grinding process diagnosis. The process is analyzed and next its diagnosis is considered as a multi-criteria decision making problem based on the modelling of relationships between different process states and their symptoms using a set of rules induced from measured process data. The development of the diagnostic system is characterized by three phases. Firstly, the process experimental data is prepared in the form of a decision table. Using selected methods of signal processing, each process running is described by 17 process state features (condition attributes) and 5 criteria evaluating process state and results (decision attributes). The semantic correlation between all the attributes is modelled. Next, the phase of condition attributes selection and knowledge extraction are strictly integrated with the phase of the model evaluation using an iterative approach. After each loop of the iterative feature selection procedure the induction of rules is conducted using the VC-DomLEM algorithm. The classification capability of the induced rules is carried out using the leave-one-out method and a set of measures. The classification accuracy of individual models is in the range of 80.77-98.72 %. The induced set of rules constitutes a classifier for an assessment of new process run cases.

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Monitoring of Grinding Wheel Wear

Cited by 49 publications

References 2 publications

Extraction of the grains topography from grinding wheels

Extraction of the grains topography from grinding wheels

A study on aspects of attrition wear of cutting grains in grinding process

The dominance-based rough set approach to cylindrical plunge grinding process diagnosis

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