Monitoring of grinding wheel defects using recursive estimation

Abstract

In production engineering, highest surface qualities and low tolerances are produced by grinding processes. Defects of the grinding wheel caused by unbalance, wrong dressing cycles, cavities, or waviness result in vibrations and damage of workpiece or spindle. Therefore, monitoring of the tool is important in practical use. In order to avoid scrap, small faults of the grinding wheel and very small amplitudes of the resulting vibrations are of major interest. This paper presents a new monitoring method, which estimates the defects recursively during the grinding process. Different sensors are analyzed using this method. Among sensors for academic purposes, typical sensors in grinding machines such as the displacement, acceleration, motor current, and acoustic emission are in use for monitoring. Compared to monitoring in the frequency domain and signal feature extraction by filtering, the recursive estimation can reduce noise. In cylindrical plunge grinding, wavy tool defects may result in unequal wear and self-exiting waviness of the wheel over a long period of grinding and start at very low amplitudes. This regenerative chatter is subject of monitoring of highest productivity of grinding processes and is therefore analyzed in this paper as well as the strongly depending selection of dressing cycles initiated by the monitoring algorithm.

Review on grinding-induced residual stresses in metallic materials

“…After assessing the system's capability for monitoring grinding and dressing processes, tests in an industrial environment show the reliability of the monitoring system, which therefore becomes the basis for controlling the grinding process and surely the resultant residual stresses. Meanwhile, considering that the defects of a grinding wheel caused by unbalance, wrong dressing cycles, cavities, or waviness could result in vibrations and workpiece damages, Denkena et al [258] presented a monitoring method, which estimates the defects recursively in grinding; accordingly, the noise is reduced with the recursive estimation in comparison with the monitoring in the frequency domain and signal feature extraction by filtering. Based on this method, a possibility is provided to decrease the amount of fault workpieces and reduce the tool wear by omitted unnecessary dressing cycles.…”

In-process monitoring and analysis of bearing outer race way grinding based on the power signal

“…Compared to other common types of grinding, internal plunge grinding has unique characteristics regarding the spindle stiffness and cutting mechanism. To date, in an industrial environment, the internal plunge grinding quality control and productivity are primarily determined based on operator experience and trial and error [2][3] . Due to a lack of process information, it is difficult to select the best grinding cycle parameters to achieve the required workpiece tolerances while avoiding process instability.…”

“…Effective monitoring and analysis of an internal plunge grinding process require the estimation and prediction of important process variables, such as the part quality and wheel conditions [3] . Many researchers have used different methods to conduct studies on monitoring and analysis of the grinding process.…”

“…To date, in an industrial environment, the internal plunge grinding quality control and productivity are primarily determined based on operator experience and trial and error. 2,3 Due to a lack of process information, it is difficult to select the best grinding cycle parameters to achieve the required workpiece tolerances while avoiding process instability. Therefore, an effective approach is needed to monitor the process and detect abnormalities in the precision internal plunge grinding system.…”

Review on Grinding Tool Wear With Regard to Sustainability

“…[44,[64][65][66][67]. Tool condition monitoring in real life processes can reveal tool wear and defects, such as unbalance, cavities, or waviness, [68] and continues to be a pressing need [65].…”