A New Approach For Dressing Operation Monitoring Using Voltage Signals Via Impedance-Based Structural Health Monitoring

Abstract

Among the methods used in structural health monitoring (SHM), the electromechanical impedance technique (EMI), which uses piezoelectric transducers of lead zirconate titanate (PZT), stands out for its low cost. This paper presents a new approach for monitoring of the dressing operation based on structural health monitoring from the digital processing of voltage signals based on the time-domain response of a PZT transducer by EMI method. Experimental tests of the dressing process were performed by using a single-point dresser equipped with a natural diamond. The voltage signals in the time-domain were collected in different damage levels using a measurements EMI System. By using damage metrics, it was possible to qualify different damage levels that the diamond suffered during the dressing operation, observing variations from the magnitude of the signals. The dressing operation is of utmost importance for the grinding process and the dresser wear negatively affects the result of the process, which owns high added value. In this way, this work contributes with a new monitoring tool which aims ensuring a consistent dressing operation. Keywords:Manufacturing process, automation, electromechanical impedance, dressing operation. ResumenDentre os métodos usados em SHM, à técnica de impedância eletromecânica (EMI), que utiliza transdutores piezelétricos de titanato de zirconato de chumbo (PZT), têm se destacado pelo baixo custo. Dessa forma, esse artigo apresenta uma nova abordagem para o monitoramento da operação de dressagem a partir do processamento digital de Palabras claves: Processos de manufatura, automação, operação de dressagem, impedância eletromecânica

Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 2—Neural Networks and K-Nearest Neighbor Classifier Approach

“…However, few studies were focused on the monitoring of dressing tool health in terms of wear, damage and breakage of dressing tools made of diamond [28,29]. Several studies have been focused on grinding wheel health monitoring in order to determine the best moment to carry out or to stop the dressing operation [30,31,32]. Kwak et al [33] used the grinding force signal based on discrete wavelet decomposition to establish the dressing time.…”