This work experimentally addresses damage calibration of an unmanned aerial vehicle in operational condition. A wide range of damage level and types are simulated and controlled by an electric motor via pulse width modulation in this regard. The measurement is carried out via established protocols of using a piezo-patch on one of the 8 arms, utilising the vibration sensitivity and flexibility of the arms, demonstrating repeatability of such protocol. Subsequently, recurrence analysis on the voltage time series data is performed for detection of damage. Quantifiers of damage extent are then created for the full range of damage conditions, including the extreme case of complete loss of power. Experimental baseline condition for no damage condition is also established in this regard. Both diagonal-line and vertical-line based indicators from recurrence analysis are sensitive to the quantitative estimates of damage levels and a statistical test of significance analysis confirms that it is possible to automate distinguishing the levels of damage. The damage quantifiers proposed in this paper are useful for rapid monitoring of unmanned aerial vehicle operations of connection.

Self-powered wearable piezoelectric sensing devices demand flexibility and high voltage electrical properties to meet personalized health and safety management needs. Aiming at the characteristics of piezoceramics with high piezoelectricity and low flexibility, this study designs a high-performance piezoelectric sensor based on multi-phase barium titanate (BTO) flexible piezoceramic film, namely multi-phase BTO sensor. The substrate-less self-supported multi-phase BTO films had excellent flexibility and could be bent 180° at a thickness of 33 μm, and exhibited good bending fatigue resistance in 1 × 10 4 bending cycles at a thickness of 5 μm. The prepared multi-phase BTO sensor could maintain good piezoelectric stability after 1.2 × 10 4 piezoelectric cycle tests. Based on the flexibility, high piezoelectricity, wearability, portability and battery-free self-powered characteristics of this sensor, the developed smart mask could monitor the respiratory signals of different frequencies and amplitudes in real time. In addition, by mounting the sensor on the hand or shoulder, different gestures and arm movements could also be detected. In summary, the multi-phase BTO sensor developed in this paper is expected to develop convenient and efficient wearable sensing devices for physiological health and behavioral activity monitoring applications.
自供电可穿戴压电传感设备需要柔韧性和高压电性以满足个性化健康安全管理需求。针对压电陶瓷压电性高、柔性差的特点，本文设计了一种基于多相钛酸钡（BTO）柔性压电陶瓷膜的高性能压电传感器，即多相BTO传感器。无衬底自支撑的多相BTO膜具有优异的柔韧性，厚度为33 μm时可实现180°弯曲，厚度为5 μm时可在1 × 10 4次弯曲循环中表现出良好的抗弯曲疲劳性。所制备的多相BTO传感器在经过1.2 × 10 4次压电循环测试后仍能保持良好的压电稳定性。基于此传感器的柔韧性、高压电性、可穿戴性、便携性和无电池自供电特性，开发的智能面罩可以实时监测不同频率和振幅的呼吸信号。此外，将传感器安装在手部或肩部，还可以检测到不同的手势和手臂动作。综上，本文开发的多相BTO传感器有望为生理健康和行为活动监测应用开发出便捷高效的可穿戴传感设备。.

Self-powered wearable pressure sensors based on flexible electronics have emerged as a new trend due to the increasing demand for intelligent and portable devices. Improvements in pressure-sensing performance, including in the output voltage, sensitivity and response time, can greatly expand their related applications; however, this remains challenging. Here, we report on a highly sensitive piezoelectric sensor with novel light-boosting pressure-sensing performance, based on a composite membrane of copper phthalocyanine (CuPC) and graphene oxide (GO) (CuPC@GO). Under light illumination, the CuPC@GO piezoelectric sensor demonstrates a remarkable increase in output voltage (381.17 mV, 50 kPa) and sensitivity (116.80 mV/kPa, <5 kPa), which are approximately twice and three times of that the sensor without light illumination, respectively. Furthermore, light exposure significantly improves the response speed of the sensor with a response time of 38.04 µs and recovery time of 58.48 µs, while maintaining excellent mechanical stability even after 2000 cycles. Density functional theory calculations reveal that increased electron transfer from graphene to CuPC can occur when the CuPC is in the excited state, which indicates that the light illumination promotes the electron excitation of CuPC, and thus brings about the high polarization of the sensor. Importantly, these sensors exhibit universal spatial non-contact adjustability, highlighting their versatility and applicability in various settings.

An outstanding event related to the understanding of the physics of mechanical sensors occurred and was announced in 1954, exactly seventy years ago. This event was the discovery of the piezoresistive effect, which led to the development of semiconductor strain gauges with a sensitivity much higher than that obtained before in conventional metallic strain gauges. In turn, this motivated the subsequent development of the earliest micromachined silicon devices and the corresponding MEMS devices. The science and technology related to sensors has experienced noteworthy advances in the last decades, but the piezoresistive effect is still the main physical phenomenon behind many mechanical sensors, both commercial and in research models. On this 70th anniversary, this tutorial aims to explain the operating principle, subtypes, input-output characteristics, and limitations of the three main types of mechanical sensor: strain gauges, capacitive sensors, and piezoelectric sensors. These three sensor technologies are also compared with each other, highlighting the main advantages and disadvantages of each one.

Milk and dairy products are included in the list of the Food Security Doctrine and are of paramount importance in the diet of the human population. At the same time, the presence of many macro- and microcomponents in milk, as available sources of carbon and energy, as well as the high activity of water, cause the rapid development of native and pathogen microorganisms in it. The goal of the work was to assess the possibility of using an array of gas chemical sensors based on piezoquartz microbalances with polycomposite coatings to assess the microbiological indicators of milk quality and to compare the microflora of milk samples. Piezosensors with polycomposite coatings with high sensitivity to volatile compounds were obtained. The gas phase of raw milk was analyzed using the sensors; in parallel, the physicochemical and microbiological parameters were determined for these samples, and species identification of the microorganisms was carried out for the isolated microorganisms in milk. The most informative output data of the sensor array for the assessment of microbiological indicators were established. Regression models were constructed to predict the quantity of microorganisms in milk samples based on the informative sensors\' data with an error of no more than 17%. The limit of determination of QMAFAnM in milk was 243 ± 174 CFU/cm3. Ways to improve the accuracy and specificity of the determination of microorganisms in milk samples were proposed.

To ensure the structural integrity of concrete and prevent unanticipated fracturing, real-time monitoring of early-age concrete\'s strength development is essential, mainly through advanced techniques such as nano-enhanced sensors. The piezoelectric-based electro-mechanical impedance (EMI) method with nano-enhanced sensors is emerging as a practical solution for such monitoring requirements. This study presents a strength estimation method based on Non-Destructive Testing (NDT) Techniques and Long Short-Term Memory (LSTM) and artificial neural networks (ANNs) as hybrid (NDT-LSTMs-ANN), including several types of concrete strength-related agents. Input data includes water-to-cement rate, temperature, curing time, and maturity based on interior temperature, allowing experimentally monitoring the development of concrete strength from the early steps of hydration and casting to the last stages of hardening 28 days after the casting. The study investigated the impact of various factors on concrete strength development, utilizing a cutting-edge approach that combines traditional models with nano-enhanced piezoelectric sensors and NDT-LSTMs-ANN enhanced with nanotechnology. The results demonstrate that the hybrid provides highly accurate concrete strength estimation for construction safety and efficiency. Adopting the piezoelectric-based EMI technique with these advanced sensors offers a viable and effective monitoring solution, presenting a significant leap forward for the construction industry\'s structural health monitoring practices.

Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasive and non-restrictive monitoring of vital signs, including the heart rate and respiration, to detect changes in the health status of several elderly individuals. A ballistocardiogram with a piezoelectric sensor was tested using seven individuals. The frequency spectra of the biosignals acquired from the piezoelectric sensors exhibited multiple peaks corresponding to the harmonics originating from the heartbeat. We aimed for individual identification based on the shapes of these peaks as the recognition criteria. The results of individual identification using deep learning techniques revealed good identification proficiency. Altogether, the monitoring system integrated with piezoelectric sensors showed good potential as a personal identification system for identifying individuals with abnormal biological signals.

With the advent of bonded composites in today\'s aircraft, there is a need to verify the structural integrity of the bonded joints that comprise their structure. To produce adequate joint integrity, strict process control is required during bonding operations. The latest non-destructive joint inspection techniques cannot quantify the strength of the bond and only indicate the presence of disbonds or delaminations. Expensive and timely proof-load testing of the joints is required to demonstrate structural performance. This work focuses on experimentally evaluating joint-health monitoring with piezoelectric sensors exposed to repeated loadings until failure. Single-lap-shear composite joints are structurally tested while using sensor electromechanical impedance response as a health indicator. Based on these experiments, validation of this novel method is achieved through detailed evaluation of the sensor impedance response characteristics during loading, which enable initial and prognostic joint health assessments. The experimental results indicate that the embedded piezoelectric sensors are able to measure the sensor impedance radial and thickness resonance response changes prior to joint failure, without sacrificing the joints\' structural performance.

Flexible piezoelectric devices have attracted much attention in the fields of intelligent devices and biomedicine because of their high sensitivity, stability, and flexibility. In this paper, a multifunctional flexible pressure sensor was prepared by adding polyacrylonitrile (PAN) and carboxylic-terminated multi-walled carbon nanotubes (c-MWCNTs) with polyvinylidene difluoride (PVDF) as the substrate. Theβ-phase content of PVDF/PAN blended fibers compounded with c-MWCNT was up to 95%. At the same time, when PAN was added, the mechanical properties of the composite fibers were constantly improved. The results show that the polymer blending method can improve the comprehensive properties of PVDF composite. The flexible sensor prepared from the PVDF/PAN/c-MWCNT composite film has an output voltage of 2.1 V and a current of 7μA. The addition of c-MWCNT can largely improve the sensitivity of the sensor (4.19 V N-1). The sensor is attached to the finger and shows good output performance under different degrees of bending of the finger. The maximum output voltage of the sensor is 0.4 V, 0.56 V and 1.15 V when the finger bending angle is 30°, 60°, and 90°, respectively. Moreover, the developed piezoelectric sensor can monitor large-scale movements of various parts of the human body. Therefore, this composite material shows potential in areas such as motion monitoring and energy storage devices.

Abnormal oculomotor movements are known to be linked to various types of brain disorders, physical/mental shocks to the brain, and other neurological disorders, hence its monitoring can be developed into a simple but effective diagnostic tool. To overcome the limitations in the current eye-tracking system and electrooculography, a piezoelectric arrayed sensor system is developed using single-crystalline III-N thin-film transducers, which offers advantages of mechanical flexibility, biocompatibility, and high electromechanical conversion, for continuous monitoring of oculomotor movements by skin-attachable, safe, and highly sensitive sensors. The flexible piezoelectric eye movement sensor array (F-PEMSA), consisting of three transducers, is attached to the face temple area where it can be comfortably wearable and can detect the muscles\' activity associated with the eye motions. Output voltages from upper, mid, and lower sensors (transducers) on different temple areas generate discernable patterns of output voltage signals with different combinations of positive/negative signs and their relative magnitudes for the various movements of eyeballs including 8 directional (lateral, vertical, and diagonal) and two rotational movements, which enable various types of saccade and pursuit tests. The F-PEMSA can be used in clinical studies on the brain-eye relationship to evaluate the functional integrity of multiple brain systems and cognitive processes.