A contribution to the monitoring of ceramic surface quality using a low-cost piezoelectric transducer in the grinding operation

The grinding process is usually one of the last stages in the manufacturing process chain since it can provide superior surface finish and closer dimensional tolerances. However, due to peculiarities of the grinding process, a workpiece material is susceptible to many problems, and demands a reliable real-time monitoring system. Some grinding monitoring systems have been proposed by means of sensors. However, the literature is still scarce in terms of employing time–frequency analysis techniques during the grinding of ceramics. Thus, this paper proposes an application of a low-cost piezoelectric transducer (PZT) in the analysis of the surface quality of ceramic workpieces during the grinding process by means of the frequency–time domain technique along with the ratio of power (ROP) parameter. An integrated, high-cost, commonly-used acoustic emission (AE) sensor was employed in order to compare the results with the low-cost PZT transducer. Tests were performed using a surface grinding machine. Three depth of cut values were selected in order to represent slight, moderate, and severe grinding conditions. Signals were collected at 2 MHz. The short-time Fourier transform (STFT) was studied in order to obtain the frequency variations over time. An analysis of the ROP values was performed in order to establish a correlation with the surface roughness. The ROP values are highly desirable for setting a threshold to detect the workpiece surface quality and for implementing it into a monitoring system. The results using the PZT transducer showed a great similarity to those obtained using the AE sensor

Análise de Sinais de Emissao Acústica e Estatística Counts na Detecção da Alteração Microestrutural na Retificação de Aço 1045

Grinding is a high-precision, high-value-added finishing process as it is usually the last stage of the manufacturing chain. However, unsatisfactory results may occur, mainly due to changes in the microstructure of the ground workpiece. Such changes are caused by the high temperatures involved in the process due to the grinding conditions in which the part was subjected. In this way, the main objective of this work is the monitoring of the grinding process in order to detect changes in the signal and to relate them with damage occurred in the ground workpiece. The tests were carried out on a surface grinding machine, aluminum oxide grinding wheel and ABNT 1045 steel parts. Metallography was performed on the parts for a more further analysis of their microstructure. The recording of signals was obtained at a sample rate of 2 MHz through an acoustic emission sensor (AE). A frequency study for the selection of the best frequency bands that characterize damage occurred in the ground workpiece. The event counts statistic was applied to the filtered signal in the chosen frequency bands. The results of this work show that the grinding conditions influence the signal and, therefore, its frequency spectrum.Keywords: Manufacturing process; automation, monitoring; grinding process; acoustic emission, damage detectio

Emitter-receiver Piezoelectric Transducers Applied in Monitoring Material Removal of Workpiece during Grinding Process

Grinding is one of the most commonly used finishing processes in the manufacture of precision components that also needs to be monitoring. Monitoring of the workpiece surface quality is considered highly complex due to particularities of the cutting tool and material removal mechanism. In this context, the monitoring of the grinding process is very important for the metalworking industry and a topic of great interest for machining researchers. Many studies on grinding process monitoring have been developed and most of them focusing in process automation. The objective of this work is to monitor the workpiece material removal during grinding by using piezoelectric transducers in the emitter and receiver modes along with digital signal processing techniques. Tests were performed in a peripheral surface grinding machine equipped with an aluminum oxide grinding wheel. As workpiece material was used the SAE 4340 steel grade. The transducers signals were sampled at a sampling frequency of 2 MHz. The digital signal processing was performed through the spectrum analysis and the application of techniques such as root mean square. The mass of workpieces was measured by means of a digital scale prior and after grinding tests. The number of gridning passes was varied in order to increase the material removal. The results show that the monitoring technique proposed in this work is sensitive to the material removal in the grinding process. The appropriate selection of frequency bands allows for the best diagnosis in relation to the events that occur during the grinding process

Monitoring of the Ceramic Kerf During the Laser Cutting Process through Piezoelectric Transducer

Advanced ceramics are widely used in industry due to their unique properties. However, the machining of ceramic components by conventional methods is difficult due to their high level of hardness and brittleness. In this sense, laser beam machining (LBM) is presented as an alternative to conventional methods, enabling the machining of workpieces through more accurate and less invasive techniques. Despite the advantages of laser machining, the process still needs to be studied in detail, as advanced ceramic machining is considered a stochastic process. Thus, real-time monitoring systems are required in order to optimize the ceramic laser machining. Therefore, this paper proposes a novel method for monitoring the cutting kerf in the laser cutting process of ceramic components using a low-cost piezoelectric transducer (PZT) and digital signal processing. Tests were performed on the surface of an alumina ceramic workpiece under different machining conditions. The cutting kerf was measured by a digital microscope and the raw signals from the PZT transducer were collected at a sampling rate of 2 MHz. Time domain and frequency domain analyses were performed in order to find a frequency band that best correlates with the process conditions. Finally, a linear regression was calculated in order to correlate the PZT signal and the measured kerf. The results showed that the piezoelectric transducer was sensitive to the acoustic activity generated during the process, allowing the real-time monitoring of the cutting kerf. Thus, the approach proposed in this paper can be used efficiently in the monitoring of the laser cutting process