The main difficulty in the grinding process is to identify the correct moment to dress the grinding wheel. Therefore, the cutting tool (grinding wheel) must be monitored. In this context, an innovative technique was developed in this study to obtain an image from surface of the grinding wheel during the dressing process, based on acoustic images acquired through a piezoelectric diaphragm, or piezoelectric buzzer. To this end, scratches (faults) were made on a grinding wheel, after which tests were performed at various dressing depths and signals were collected by an acoustic emission (AE) sensor and a piezoelectric diaphragm. Based on these signals, frequency bands were evaluated to obtain acoustic images that would accurately and clearly represent the scratches imprinted on the grinding wheel. Lastly, the performance of the two sensors (AE sensor and piezoelectric diaphragm) were compared and the results were analyzed in light of the dressing conditions under study. The results indicated that the piezoelectric diaphragm was as efficient in obtaining acoustic maps of the grinding wheel surface as the AE sensor, and that in some machining conditions, it provided superior results to those obtained when monitoring the tool with the AE sensor.

The grinding process is a manufacturing process that is performed at the end of the machining chain. In such step, the workpiece has a high added-value and therefore critical problems are not allowed, as they may lead to scrap and significant financial loss. Regenerative chatter is the most common form of self-excited vibration. It can occur often because most metal cutting operations involve overlapping cuts which can be a source of vibration amplification. The occurrence of the chatter phenomenon in the grinding process is considered a critical problem because it causes several negative effects, such as poor surface quality, unacceptable inaccuracy, and disproportionate tool wear, to name a few. The objective of this research work is to monitor the onset of the chatter phenomenon in grinding of SAE 1045 steel with an aluminum oxide grinding wheel by digital signal processing techniques of the acceleration signals. Experimental tests were performed in a surface grinding machine and using a data acquisition system with sampling frequency of 2 MHz. The data was analyzed with respect to the frequency content and the Ratio of Power (ROP) statistical parameter obtained for normal and chatter conditions. Visual inspections through digital images of the workpieces surfaces were conducted and then chatter frequency was determined. Results showed that the magnitudes related to the frequencies close to 30 Hz change as chatter phenomenon occurs. The ROP shows features related to the chatter vibrations. The methodology presented herein therefore allows for the automation and optimization of the grinding process.

High voltage direct current (HVdc) detection is essential to ensure the suitability and operation of electrical systems, as well as personal safety. Today there are commercial sensing devices equipped with a safety system that emits audible warnings, but they do not indicate voltage and polarity levels. Likewise, although the scientific literature describes various solutions with satisfactory results, very few of these achievements are found in real-world applications. The purpose of this article is to present a technological alternative based on the study and development of a simple and portable electronic device to enable the detection and quantification of high voltage and polarity in HVdc systems. The principle is based on the detection of corona current by means of an aluminum tip held at a distance of about 5 mm from the energized surface through a radial contact rod. The detected electrical current signal is collected and processed through an electronic system. The performance was analyzed by means of corona discharge models and high voltage experimental tests in real-world conditions. The results demonstrated the satisfactory response of the proposed approach in the detection, quantification, and identification of polarity in a ±600 kV HVdc transmission system, with an error varying from 1.79% to 2.72% compared to theoretical values, as well as its ability to withstand the influence of temperature variations between 18 °C to 29 °C, relative humidity between 56% and 78%, and an atmospheric pressure kept constant at 101.6 kPa. The proposed approach contributes to HVdc monitoring and inspection activities, helping to ensure their operation and suitability.

Acoustic emission (AE) sensors have been widely used for tool condition monitoring in the grinding process. Recently, the piezoelectric diaphragm (piezoelectric buzzer) was introduced as a low-cost alternative for the same purpose. In this context, the present research work aims to study the efficiency of the piezoelectric diaphragm as a viable substitute to AE sensors in monitoring the dressing of structurally distinct aluminum oxide grinding wheels. Dressing tests were conducted using two industrial wheels, which were subjected to various dressing conditions. The signals generated by the AE and piezoelectric diaphragm sensors were collected simultaneously and subsequently analyzed in both time and frequency domains. The most relevant features related to the dressing were extracted through the following metrics: energy criterion, Pearson correlation coefficient, power spectral density (PSD), fast Fourier transform (FFT), and magnitude-squared coherence (MSC). Correlation greater than 80% was found between the piezoelectric diaphragm and AE sensor signals for determining the actual grinding wheel condition, which indicates the piezoelectric diaphragm as a viable alternative to the commercial AE sensors in dressing operation monitoring.