Piezoelectric Vibration Sensor Research Articles

A piezoelectric vibration sensor with excellent performance based on Bi12SiO20 crystal for high-temperature applications

High-temperature piezoelectric vibration sensors play a crucial role in the accurate monitoring of the dynamic mechanical conditions in aerospace, automotive, and energy generation systems. However, the use of conventional piezoelectric materials in high-temperature environments is restricted owing to their limited Curie temperatures. In this study, we grew a piezoelectric crystal Bi12SiO20 (BSO) with the crystal cut optimized for high longitudinal piezoelectric coefficient and low piezoelectric crosstalk behaviors. Subsequently, a compression-type piezoelectric vibration sensor utilizing the BSO bulk crystal was developed and fabricated for structural health monitoring under high temperatures. The impact of pre-tightening torques on the sensor performance was investigated. Moreover, the sensor performance was analyzed under temperatures up to 650 °C. The BSO-based sensor exhibited an average sensitivity of ∼3.89 pC/g between 25 and 650 °C under 160 Hz frequency, with a variation of 5.5%. Additionally, the BSO-based sensor demonstrated ultra-stable sensitivity at 600 °C, highlighting its strong sensing capabilities and reliability under high temperatures. Thus, the BSO-based vibration sensor is a promising option for structural health monitoring applications under high temperatures.

RUL Prediction for Piezoelectric Vibration Sensors Based on Digital-Twin and LSTM Network

Piezoelectric vibration sensors (PVSs) are widely used in high-temperature environments, such as vibration measurements in aero-engines, because of their high accuracy, small size, and high temperature resistance. Accurate prediction of its RUL (Remaining Useful Life) is essential for applying and maintaining PVSs. Based on PVSs’ characteristics and main failure modes, this work combines the Digital-Twin (DT) and Long Short-Term Memory (LSTM) networks to predict the RUL of PVSs. In this framework, DT can provide rich data collection, analysis, and simulation capabilities, which have advantages in RUL prediction, and LSTM network has good results in predicting time sequence data. The proposed method exploits the advantages of those techniques in feature data collection, sample optimization, and RUL multiclassification. To verify the prediction of this method, a DT platform is established to conduct PVS degradation tests, which generates sample datasets, then the LSTM network is trained and validated. It has been proved that prediction accuracy is more than 99.7%, and training time is within 94 s. Based on this network, the RUL of PVSs is predicted using different test samples. The results show that the method performed well in prediction accuracy, sample data utilization, and compatibility.

Multichannel multimodal piezoelectric middle ear implant concept based on MEMS technology for next-generation fully implantable cochlear implant applications

This paper introduces a unique multimode, multichannel piezoelectric vibration sensor for the next-generation fully implantable cochlear implant (FICI) systems. The sensor, which can be implanted on the middle ear chain to collect and filter the ambient sound in eight frequency bands, comprises an array of 4 M-shape multimode and 11 single cantilevers. Finite element (FE) analysis indicates a 2.05-fold improvement in capturing frequency information for the multimodal sensor compared to its single-mode counterpart. Under an acoustic excitation at 100 dB SPL, the sensor, mounted on an artificial tympanic membrane, yielded a peak output voltage of 546.16 mVpp and a peak sensitivity of 285.28 mVpp/Pa at 1613 Hz. The extrapolated acoustic results indicated a dynamic frequency range between 300 Hz and 6 kHz, even at 30 dB SPL. Furthermore, a lightweight titanium coupler, employing a two-sided clipping structure with a maximum wall thickness of 70 μm, is micromachined for surgical attachment of the transducer to the middle ear chain. A commercial accelerometer, implanted on the incus short process (SP) of a cadaver using the titanium coupler, successfully recorded 0.1 g for 100 dB SPL at 500 Hz, revealing the potential feasibility of the coupler for vibration sensor implantation. Moreover, the presented anatomically accurate FE model of the middle ear, exhibiting a high correlation coefficient (R2) of 0.97 with the cadaveric experiment, suggests an efficient numerical approach for evaluating the implantation of middle ear prostheses. In this regard, the study holds great promise for clinical application in the field of implantable hearing aids.

Design and Experimental Evaluation of a Dual-Cantilever Piezoelectric Film Sensor with a Broadband Response and High Sensitivity.

Cantilever-beam-type PVDF (Polyvinylidene Fluoride) piezoelectric film sensors are commonly utilized for vibration signal detection due to their simple structures and ease of processing. Traditional cantilevered PVDF piezoelectric film sensors are susceptible to the influence of the second-order vibration mode and have a low lateral stress distribution at the free end, which limit their measurement bandwidth and sensitivity. This study is on the design of a dual-cantilever PVDF piezoelectric film sensor based on the principle of cantilevered piezoelectric film sensors. The results of the experiments indicate that, compared to a typical single-arm piezoelectric cantilever beam vibration sensor, the developed sensor has a longer second-order natural frequency that ranges from 112 Hz to 453 Hz, while the first-order natural frequency is maintained at around 12 Hz. This leads to a better ratio of the second-order natural frequency to the first-order natural frequency and a wider frequency response range. At the same time, the sensitivity is increased by a factor of 3.48.

Development of Harumanis Mango Insidious Fruit Rot (IFR) Detection by Utilising Vibration-Based Sensors and PCA with Random Forest

Utilising single or multiple modalities systems, non-destructive techniques have been used to assess and determine the quality of mango (magnifera indica L.). It is challenging to anticipate and varies by cultivar at what harvest maturity stage will result in the optimum postharvest quality. Insidious Fruit Rot (IFR) is a disease that affects mangoes. When infected with Insidious Fruit Rot (IFR), the mango variety Harumanis does not exhibit exterior mutilation at the time of harvest or during the mature stage. However, a lack of density in the sinus area can occasionally be detected. Traditional ways of locating the diseases or pests living in the mango are useless for the commercialization of the product. This research presents the investigation done on IFR infection detection using piezoelectric vibration sensors and electret microphones. Data derived by the sensors were processed using the PCA and Random Forest methods to determine the non-IFR and the mango afflicted with IFR. The proposed approach achieved correct classification and is expected to be useful for planters in detecting IFR correctly before Harumanis mangoes were marketed.

A Novel Self-Powered, High-Sensitivity Piezoelectric Vibration Sensor Based on Piezoelectric Combo Effect

A Novel Self-Powered, High-Sensitivity Piezoelectric Vibration Sensor Based on Piezoelectric Combo Effect

A Digital-Twin Framework for Predicting the Remaining Useful Life of Piezoelectric Vibration Sensors with Sensitivity Degradation Modeling.

Piezoelectric vibration sensors (PVSs) are widely applied to vibration detection in aerospace engines due to their small size, high sensitivity, and high-temperature resistance. The precise prediction of their remaining useful life (RUL) under high temperatures is crucial for their maintenance. Notably, digital twins (DTs) provide enormous data from both physical structures and virtual models, which have potential in RUL predictions. Therefore, this work establishes a DT framework containing six modules for sensitivity degradation detection and assessment on the foundation of a five-dimensional DT model. In line with the sensitivity degradation mechanism at high temperatures, a DT-based RUL prediction was performed. Specifically, the PVS sensitivity degradation was described by the Wiener-Arrhenius accelerated degradation model based on the acceleration factor constant principle. Next, an error correction method for the degradation model was proposed using real-time data. Moreover, parameter updates were conducted using a Bayesian method, based on which the RUL was predicted using the first hitting time. Extensive experiments on distinguishing PVS samples demonstrate that our model achieves satisfying performance, which significantly reduces the prediction error to 8 h. A case study was also conducted to provide high RUL prediction accuracy, which further validates the effectiveness of our model in practical use.

Investigation of laser-textured triboelectric nanogenerator for vibration sensing of machine tools

The breakdown of any industrial mechanical system can be predicted and identified using vibration sensing. Piezoelectric material-based vibration sensors are commercially available, but their use is limited by their reliance on external power sources and intricate data-gathering systems. Recently, contact electrification-based triboelectric nanogenerators (TENGs), which are reliable, affordable, and lightweight devices, have been developed as vibration sensors. The TENG is a high-voltage output device; however, its lower current output restricts its practical applications. In this work, we report a novel laser texturing technique for output enhancement of polytetrafluoroethylene (PTFE)- and aluminum (Al)-based TENG for machinery vibration sensing applications. An Nd3+: YAG pulse laser was used for texturing the PTFE sheet. A 50% spatial spot overlap with laser fluences of 10 and 50 J cm−2 was chosen to investigate the impact on the TENG electrical output. As compared to pristine TENG, the open-circuit voltage and short-circuit current of laser-textured (LT) TENG increased from 308 V to 368 V and 12.64 µA to 19.16 µA, respectively. The TENG device was attached to a lathe and a milling machine to sense the change in vibration state with respect to various machining parameters. Moreover, the proposed LT performance-enhanced TENG has excellent potential and broad applications in the fields of machinery monitoring, fault detection, and the Internet of Things and Industry 4.0.

A novel optimization algorithm based PID controller design for real-time optimization of cutting depth and surface roughness in finish hard turning processes

This paper proposes a novel method to improve surface finish in turning processes by effectively controlling the cutting depth. A metaheuristic algorithm based PID control system, in combination with a piezoelectric vibration sensor for feedback, is introduced to regulate the position of the servo motor that controls the cutting tool. The PID controller is optimized using Q-learning based Sand Cat Optimization algorithm to achieve the best performance in terms of cutting depth accuracy and surface finish quality. The piezoelectric sensor provides real-time feedback information about the cutting process and allows for precise adjustments to the cutting depth. The results demonstrate the proposed system's ability to handle variations in cutting conditions and tool's wear and tear. Compared to highly optimized standard PID control, improved robustness and stability has been achieved in experimental results by proposed framework. Experimental results demonstrate improved robustness and stability compared to standard PID control. Several materials with high hardness of 20–65 HRC including Phenolic Bakelite, Copper, Thermoplastic, and Stainless Steel (AISI-420, AA6061-T6, and AISI-316) are tested. Minimum value of Vibration amplitude achieved is 0.598 μm for cutting depth of 0.25 mm. The sustained minimum amplitude of vibration and Ra value of the surface finish is found comparable to standard models with less than 10% error.

Solar Powered Vibration Propagation Analysis System using nRF24l01 based WSN and FRBR

Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.

Technological features of surface treatment of a piezoelectric vibration sensor parts

Technological features of surface treatment of a piezoelectric vibration sensor parts

Design, fabrication, and characterization of high-temperature piezoelectric vibration sensor based on the Ho: CNGS crystal

In this letter, a Ho3+: Ca3NbGa3Si2O14 (Ho: CNGS) piezoelectric crystal with high quality and large size (Φ 34 mm × 52 mm) was grown by the Czochralski method, and a compressive mode piezoelectric vibration sensor with longitudinal d11 mode was fabricated based on the good properties of Ho: CNGS. The resistivity at elevated temperatures of Ho: CNGS could be enhanced significantly by doping Ho3+, and the ρ11 was three orders of magnitude higher than La3Ga5SiO14 and one order of magnitude higher than Ca3NbGa3Si2O14. The low dielectric loss and stable electro-elastic properties at high temperatures were also presented, and the electro-elastic constants were effectively improved compared with the pure Ca3NbGa3Si2O14 crystal. The sensor exhibited a maximum sensitivity temperature deviation of less than 5.2% from room temperature to 600 °C under the excitation frequency of 80 ̶ 315 Hz.

DEVELOPMENT OF VIBRATIONS DUE TO CHANGING SPINDLE SPEEDS DURING MILLING

The article analyses the problem of measuring and examining the magnitudes of vibration amplitudes at the machining of materials by milling technology. By measuring the vibration parameter on the spindle head of a universal milling machine, the level of the vibration amplitudes magnitude during the milling process was acquired using a piezoelectric vibration sensor. The magnitudes of the vibration amplitudes were recorded during machining when the spindle speed varied between 1200 rpm and 1600 rpm. The measured values were evaluated in the form of FFT spectra, and the information required to design measures to avoid excess vibration amplitudes in such a case was obtained.

Multiferroic Cantilevers Containing a Magnetoactive Elastomer: Magnetoelectric Response to Low-Frequency Magnetic Fields of Triangular and Sinusoidal Waveform.

In this work, multiferroic cantilevers comprise a layer of a magnetoactive elastomer (MAE) and a commercially available piezoelectric polymer-based vibration sensor. The structures are fixed at one end in the horizontal plane and the magnetic field is applied vertically. First, the magnetoelectric (ME) response to uniform, triangle-wave magnetic fields with five different slew rates is investigated experimentally. Time and field dependences of the generated voltage, electric charge, and observed mechanical deflection are obtained and compared for four different thicknesses of the MAE layer. The ME responses to triangular and sinusoidal wave excitations are examined in contrast. Second, the ME response at low frequencies (≤3 Hz) is studied by the standard method of harmonic magnetic field modulation. The highest ME coupling coefficient is observed in the bias magnetic field strength of ≈73 kA/m and it is estimated to be about 3.3 ns/m (ME voltage coefficient ≈ 25 V/A) at theoretically vanishing modulation frequency ( Hz). Presented results demonstrate that the investigated heterostructures are promising for applications as magnetic-field sensors and energy harvesting devices.

The positive effect of A-site nonstoichiometry on the electrical properties of Sr2Nb2O7 ceramics for high temperature piezoelectric sensor application

The structure and electrical properties of A-site nonstoichiometric perovskite layered structured (PLS) Sr2-xNb2O7-x piezoelectric ceramics prepared by the traditional solid-state reaction method are studied. The piezoelectric constant increases from 1.0 pC/N to 2.1 pC/N. Through XRD refinement and Raman analysis, the enhancement of the piezoelectric performance is mainly achieved by enhancing the distortion and/or rotation of the oxygen octahedron. The dielectric breakdown field strength at room temperature increases from 206 kV/cm to 435 kV/cm. The mechanism of dielectric breakdown enhancement has been explored by intrinsic factors such as dielectric constant and band gap. The resistivity at 700 °C increases from 6.7 × 105 Ω cm to 1.1 × 107 Ω cm which meets the requirements of high temperature vibration sensors at 650 °C. The improvement of high temperature resistance may be related to the inversion of oxygen vacancies. This work provides promising PLS piezoelectric ceramics for potential applications in high-temperature piezoelectric vibration sensors which uses a simple synthesis method without doping any elements.

Surface Mounted Active Vibration Cancellation Device Using Raspberry Pi

Active vibration cancellation device detects vibrations on a host surface using a piezoelectric vibration sensor, amplifies them using a signal amplifier, and sends them to a Raspberry Pi board implemented with PID control, responsible for signal processing, which further actuates Piezoelectric actuators vibrating at a phase difference of 180° to the vibrating surface (destructive interference) and reduces the vibrations over the surface. The device presented in this paper suggests an application that tries to make it accessible to a large group of people.

Tailoring structure and piezoelectric properties of CaBi2Nb2O9 ceramics by W6+-Doping

Calcium bismuth niobate (CaBi2Nb2O9) is a typical bismuth-layer structured piezoelectrics (BLSPs) with a high Curie temperature (TC) of ∼943 °C, but it has low piezoelectric coefficient and high-temperature resistivity which severely limits signal acquisition in the high-temperature piezoelectric vibration sensors. Ion-doping modification is regarded as an effective way to enhance electrical properties. In this work, W6+ donor-doping at Nb5+ site in the CaBi2Nb2-xWxO9 (x = 0, 0.020, 0.025, 0.030, 0.035 and 0.040) piezoelectric ceramics with TC of 931 ± 2 °C were fabricated by the conventional solid-state reaction method. The effects of W6+-doping on crystal structure of CaBi2Nb2-xWxO9 as well as microscopic morphology and electrical properties of ceramics were investigated systematically. The tetragonality, isotropy and electrical properties of the ceramics were enhanced with the introduction of W6+ dopant. It was found that x = 0.025 was the optimal W6+-doping ratio that yielded remnant polarization of 8.0 μC/cm2, electrical resistivity of 3.0 × 106 Ω cm at 600 °C, piezoelectric coefficient (d33) of 14.4 pC/N, and good thermal depoling property. Our work has established a feasible approach to tune the structure of CaBi2Nb2O9 to improve piezoelectric properties for potential applications in high-temperature piezoelectric vibration sensors.

Impact Position Estimation for Baseball Batting with a Force-Irrelevant Vibration Feature.

In this work we propose a novel method for impact position estimation during baseball batting, which is independent of impact intensity, i.e., force-irrelevant. In our experiments, we mount a piezoelectric vibration sensor on the knob of a wooden bat to record: (1) 3600 vibration signals (waveforms) from ball–bat impacts in the static experiment—30 impacts from each of 40 positions (distributed 1–40 cm from the end of the barrel) and 3 intensities (drop heights at 75, 100, and 125 cm, resp.), and (2) 45 vibration signals from actual battings by three baseball players in the dynamic experiment. The results show that the peak amplitude of the signal in the time domain, and the peaks of the first, second, and third eigenfrequencies (EFs) of the bat all increase with the impact intensity. However, the ratios of peaks at these three EFs (1st/2nd, 2nd/3rd, and 1st/3rd) hardly change with the impact intensity, and the observation is consistent for both the static and dynamic experiments across all impact positions. In conclusion, we have observed that the ratios of peaks at the first three EFs are a force-irrelevant feature, which can be used to estimate the impact position in baseball batting.

Pedestrian Counting Based on Piezoelectric Vibration Sensor

Pedestrian counting has attracted much interest of the academic and industry communities for its widespread application in many real-world scenarios. While many recent studies have focused on computer vision-based solutions for the problem, the deployment of cameras brings up concerns about privacy invasion. This paper proposes a novel indoor pedestrian counting approach, based on footstep-induced structural vibration signals with piezoelectric sensors. The approach is privacy-protecting because no audio or video data is acquired. Our approach analyzes the space-differential features from the vibration signals caused by pedestrian footsteps and outputs the number of pedestrians. The proposed approach supports multiple pedestrians walking together with signal mixture. Moreover, it makes no requirement about the number of groups of walking people in the detection area. The experimental results show that the averaged F1-score of our approach is over 0.98, which is better than the vibration signal-based state-of-the-art methods.

Method for fabricating highly crystalline polyvinylidene fluoride for piezoelectric energy-harvesting and vibration sensor applications

Humidity controlled preparation of highly crystalline polyvinylidene fluoride (PVDF) films for energy-harvesting and sensor applications.