The electromechanical impedance (EMI) technique is considered to be one of the most promising methods for developing structural health monitoring (SHM) systems. This technique is simple to implement and uses small and inexpensive piezoelectric sensors. However, practical problems have hindered its application to real-world structures, and temperature effects have been cited in the literature as critical problems. In this paper, we present an experimental study of the effect of temperature on the electrical impedance of the piezoelectric sensors used in the EMI technique. We used 5H PZT (lead zirconate titanate) ceramic sensors, which are commonly used in the EMI technique. The experimental results showed that the temperature effects were strongly frequency-dependent, which may motivate future research in the SHM field.

Power transformers are crucial in an electric power system. Failures in transformers can affect the quality and cause interruptions in the power supply. Partial discharges are a phenomenon that can cause failures in the transformers if not properly monitored. Typically, the monitoring requires high-cost corrective maintenance or even interruptions of the power system. Therefore, the development of online non-invasive monitoring systems to detect partial discharges in power transformers has great relevance since it can reduce significant maintenance costs. Although commercial acoustic emission sensors have been used to monitor partial discharges in power transformers, they still represent a significant cost. In order to overcome this drawback, this paper presents a study of the feasibility of low-cost piezoelectric sensors to identify partial discharges in mineral insulating oil of power transformers. The analysis of the feasibility of the proposed low-cost sensor is performed by its comparison with a commercial acoustic emission sensor commonly used to detect partial discharges. The comparison between the responses in the time and frequency domain of both sensors was carried out and the experimental results indicate that the proposed piezoelectric sensors have great potential in the detection of acoustic waves generated by partial discharges in insulation oil, contributing for the popularization of this noninvasive technique.

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Ideally, an insulation system must be capable of electrically insulating the active components of a machine or device subjected to high voltages. However, due to the presence of polluting agents or imperfections inside or on the surface of the insulation, small current pulses called partial discharges (PDs) are common, which partially short-circuit the insulation and cause it to lose its insulating properties, and thus its insulation capacity, over time. In some cases, measurements of this phenomenon are limited by the type of sensor used; if it is not adequate, it can distort the obtained results, which can lead to a misdiagnosis of the state of the device. The inductive loop sensor has experimentally been demonstrated to be capable of properly measuring different types of PDs. However, because of its current design, there are several practical limitations on its use in real devices or environments. An example is the presence of a primary conductor located at a fixed distance from the sensor, through which PD pulses must flow for the sensor to capture them. In this article, the sensor’s behavior is studied at different separation distances from the line through which the PD pulses flow. In addition, the measuring capacity of the sensor is tested by removing the presence of the primary conductor and placing the sensor directly over the line through which the PD pulses of a real device flow.

Milk is an important dietary requirement for many populations due to its high nutritional value. However, increased demand has also made it prone to fraudulent activity. In this sense, scientists have sought to develop simple, low-cost, and portable techniques to achieve quality control of milk in industry and farms as well. This work proposes a new instrumentation system based on acoustic propagation and advanced signal processing techniques to identify milk adulteration by industrial contaminants. A pair of transmitter-receiver low-cost piezoelectric transducers, configured in a pitch-catch mode, propagated acoustic waves in the bovine milk samples contaminated with 0.5% of sodium bicarbonate, urea, and hydrogen peroxide. Signal processing approaches such as chromatic technique and statistical indexes like the correlation coefficient, Euclidian norm and cross-correlation square difference were applied to identify the contaminants. According to the presented results, CCSD and RMSD metrics presented more effectiveness to perform the identification of milk contaminants. However, CCSD was 2.28 × 10⁵ more sensitivity to distinguish adulteration in relation to RMSD. For chromatic clustering technique, the major selectivity was observed between the contamination performed by sodium bicarbonate and urea. Therefore, results indicate that the proposed approach can be an effective and quick alternative to assess the milk condition and classify its contaminants.

Sensors applied in the food industry are important tools for quality control. Current analyses checking adulteration in milk are expensive and time consuming, because the samples need to be evaluated in a laboratory environment. Thus, is important to develop methodologies and sensors to monitor milk production. A common type of fraud is performed adding substances such as sodium hydroxide in order to increase the shelf life of milk. In this study, we propose to use low-cost piezoelectric diaphragms transducers to implement a methodology that identifies milk adulteration using the mechanical waves propagation method (vibration and acoustic emission). Two piezoelectric diaphragms were used, the first was excited by a chirp signal with 1 V of amplitude and a frequency band since 0 to 65 kHz with 2 Hz of step, and concomitantly acquired the response signal of the second sensor installed in the opposite side of the actuator with a rate of 250 kHz. After acquiring the data, these were processed using the chromatic technique, which extracts three features: energy, average band and equivalent bandwidth, in order to classify the raw and the contaminated milk through clustering. The experimental results indicated that the methodology can differentiate between raw and contaminated milk with 1% of sodium hydroxide. Therefore, the results reported in this study indicate that low-cost piezoelectric diaphragms are promising for liquids quality control.