Piezoelectric Acceleration Sensor Research Articles

Research on failure mechanism of landslide with retaining-wall-like locked segment and instability prediction by inverse velocity method

The locked segment is critical for determining the stability of locked segment-type landslides. Research indicates that the volume expansion point marks the transition from the secondary creep stage to the tertiary creep stage in a landslide’s evolution, and also separates the stable crack growth stage from the unstable crack growth stage in the locked segment. Identifying the volume expansion point is essential for early warning and predicting locked segment-type landslides. A series of instruments (resistance strain gauges, acoustic emission system, piezoelectric acceleration sensors, etc.) were used to conduct physical model tests of the landslide with retaining-wall-like locked segment under external load on the landslide’s trailing edge. The evolution process of this landslide was analyzed through changes in slope shape and stress response characteristics. The experimental results reveal the failure mechanism of the landslide with retaining-wall-like locked segment: the upper part of the landslide thrusts and slides, the middle part squeezes and uplifts, the retaining-wall-like locked segment produces a locking effect, and compression-shear fracture of the retaining-wall-like locked segment leads to landslide failure. Based on the deformation and acoustic emission characteristics of the locked segment, a method for identifying the volume expansion point was established. This point was used as the onset of acceleration point in the inverse velocity method to predict the failure time of the locked segment-type landslides, incorporating the three-stage creep model and Fukumoto’s theory.

Study on fault characteristic of piezoelectric acceleration sensor

In order to explore the fault characteristics and failure mechanism of the sensor, staring from the working principle and structural characteristics of the piezoelectric acceleration sensor, the problems affecting the quality of the collected signal due to the fault of the component of the sensor are systematically studied. Firstly, according to the application scenario and structural characteristics of this kind of sensor, the main fault forms are analyzed, including: insufficient preload, crystal plate damage, crystal plate side loading and crystal plate phase loading reverse four kinds of faults. Secondly, the signal of the exciter is used to test the above sensors. It is found that except the sensor with insufficient preload does not affect the signal, other fault sensors will make the collected signal amplitude smaller, but the signal frequency does not change. In order to verify the accuracy of the exciter test results, the sensor signal test on rotor bearing vibration was continued. The test results show that not only the signal amplitude decreases, but also the high frequency part of the signal is seriously distorted. Finally, the fault characteristics of various components of piezoelectric acceleration sensor are obtained by combining the test results of the two groups.

Recent Development in Intelligent Compaction for Asphalt Pavement Construction: Leveraging Smart Sensors and Machine Learning.

Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors. Case studies on utilizing these sensors for particle behavior monitoring, strain measurement, and impact data collection were reviewed. Meanwhile, common ML algorithms including regression, classification, clustering, and artificial neural networks were discussed. Practical examples of applying ML to estimate mechanical properties, evaluate overall compaction quality, and predict soil firmness through supervised and unsupervised models were examined. Results indicated smart sensors have enhanced compaction monitoring capabilities but require robustness improvements. ML provides a data-driven approach to complement traditional empirical methods but necessitates extensive field validation. Potential integration with digital construction technologies such as building information modeling and augmented reality was also explored. In conclusion, leveraging emerging sensing and artificial intelligence presents opportunities to optimize the IC process and address key challenges. However, cooperation across disciplines will be vital to test and refine technologies under real-world conditions. This study serves to advance understanding and highlight priority areas for future research toward the realization of IC's full potential.

Experimental Investigation on the Transfer Behavior and Environmental Influences of Low-Noise Integrated Electronic Piezoelectric Acceleration Sensors

Acceleration sensors are vital for assessing engineering structures by measuring properties like natural frequencies. In practice, engineering structures often have low natural frequencies and face harsh environmental conditions. Understanding sensor behavior on such structures is crucial for reliable measurements. The research focus is on understanding the behavior of acceleration sensors in harsh environmental conditions within the low-frequency acceleration range. The main question is how to distinguish sensor behavior from structural influences to minimize errors in assessing engineering structure conditions. To investigate this, the sensors are tested using a long-stroke calibration unit under varying temperature and humidity conditions. Additionally, a mini-monitoring system configured with four IEPE sensors is applied to a small-scale support structure within a climate chamber. For the evaluation, a signal-energy approach is employed to distinguish sensor behavior from structural behavior. The findings show that IEPE sensors display temperature-dependent nonlinear transmission behavior within the low-frequency acceleration range, with humidity having negligible impact. To ensure accurate engineering structure assessment, it is crucial to separate sensor behavior from structural influences using signal energy in the time domain. This study underscores the need to compensate for systematic effects, preventing the underestimation of vibration energy at low temperatures and overestimation at higher temperatures when using IEPE sensors for engineering structure monitoring.

Thermal and Structural Performance Analysis of Piezoelectric Acceleration Sensor

Thermal and structural piezoelectric acceleration sensors are complicated and affected by many factors, especially when the sensor works in different temperature environments, its performance and structure will be affected to some extent. In this paper, the interference contact model of piezoelectric sensor is established with the method of bolt preloading, and the finite element analysis is carried out under different interference quantities. Moreover, based on the bolt preload model, the loading method of temperature load is studied, and the structural thermal adaptation characteristics of the sensor under the conditions of -70℃, -50℃, 0℃, 120℃, 160℃ and 200℃ are analyzed. Based on these thermal deformation and thermal stress analysis at different temperatures, the thermal adaptation characteristics of the sensor are analyzed. The normal operating temperature range of the sensor is -50℃ -120 ℃, and the structural parameter of the sensor (the thickness of the base) is optimized, so that the operating temperature of the sensor can reach 200℃. Ability to analyze.

High-sensitivity and low-volume-based piezoelectric MEMS acceleration sensor using PiezoMUMPs

High-sensitivity and low-volume-based piezoelectric MEMS acceleration sensor using PiezoMUMPs

The Impact of Vibrating Screen Startup Time on Vibration Amplitude and Energy Consumption in Transient State

The article presents the results of research on the trajectory and amplitude values during the startup of a vibrating screen, depending on the set startup time. The research was conducted using a suspended vibrating screen with a segmental vibration trajectory, where vibration excitation was achieved through two vibratory motors directly attached to the screen frame. The vibratory motors were powered with three-phase voltage and connected to the grid through frequency converters, allowing for current control in steady-state and startup conditions. The analysis focused on the vibration trajectory and the resulting amplitude values for nine selected startup times (ranging from 0 s to 8 s). Two measurement methods were employed: using piezoelectric acceleration sensors and optical recording. Additionally, the momentary power consumption by the screen drive was recorded, and the maximum current flowing in the power supply circuit was determined. These studies enabled the determination of the most favourable startup parameters that reduce the power demand of the drive without significantly affecting the kinematic parameters of the screen during its startup. The results of experimental research presented in the article regarding the startup time of the screening machine and its influence on vibration parameters have shown that the startup time significantly impacts the amplitude values that occur during startup. In the analysed case, the most favourable startup time was 3 s. Power consumption studies during startup revealed that startup time has a notable influence on momentary power consumption. The conducted research demonstrated that for startup times below 0.2 s, the maximum momentary power was the highest (reaching 5 kW, with a current consumption of 4.5 times the rated current). Regarding energy efficiency, the most favourable startup times exceed 2.0 s. Extending these startup times can significantly reduce the power demand of the drive, even up to threefold, thereby enabling the selection of motors with much lower power ratings.

Research on Three-Phase Asynchronous Motor Fault Diagnosis Based on Multiscale Weibull Dispersion Entropy.

Three-phase asynchronous motors have a wide range of applications in the machinery industry and fault diagnosis aids in the healthy operation of a motor. In order to improve the accuracy and generalization of fault diagnosis in three-phase asynchronous motors, this paper proposes a three-phase asynchronous motor fault diagnosis method based on the combination of multiscale Weibull dispersive entropy (WB-MDE) and particle swarm optimization-support vector machine (PSO-SVM). Firstly, the Weibull distribution (WB) is used to linearize and smooth the vibration signals to obtain sharper information about the motor state. Secondly, the quantitative features of the regularity and orderliness of a given sequence are extracted using multiscale dispersion entropy (MDE). Then, a support vector machine (SVM) is used to construct a classifier, the parameters are optimized via the particle swarm optimization (PSO) algorithm, and the extracted feature vectors are fed into the optimized SVM model for classification and recognition. Finally, the accuracy and generalization of the model proposed in this paper are tested by adding raw data with Gaussian white noise with different signal-to-noise ratios and the CHIST-ERA SOON public dataset. This paper builds a three-phase asynchronous motor vibration signal experimental platform, through a piezoelectric acceleration sensor to discern the four states of the motor data, to verify the effectiveness of the proposed method. The accuracy of the collected data using the WB-MDE method proposed in this paper for feature extraction and the extracted features using the optimization of the PSO-SVM method for fault classification and identification is 100%. Additionally, the proposed model is tested for noise resistance and generalization. Finally, the superiority of the present method is verified through experiments as well as noise immunity and generalization tests.

Research on the Vibration Characteristics of Pumped Storage Unit Stator Core Based on Fiber Optic Sensing

Stator core vibration (SCV) response of pumped storage units (PSU) can effectively reflect its operation status and provide reference for excitation winding inter-turn short circuit (ITSC) fault diagnosis. Considering that traditional piezoelectric acceleration sensors (PAS) are difficult to be installed on the stator core surface, this study proposes an online monitoring method based on fiber optic vibration sensing (FOVS). Firstly, this study derives the SCV response equations for the normal and ITSC states of the excitation winding, and obtains the vibration characteristic harmonics corresponding to each state. Secondly, a three-dimensional finite element simulation model of PSU with a generating capacity of 278 MVA is built, and the acceleration amplitude and characteristic frequency harmonics of the stator core are calculated to provide a reference for fiber optic vibration detection. Thirdly, this study focuses on the principle of modulation and demodulation of optical phase, builds an optical frequency-domain reflectometer (OFDR) - based FOVS system, and calibrates its sensitivity, amplitude and frequency characteristics as well as the lower detection limit. Finally, FOVS probes are installed on the surface of synchronous generator stator core to capture the vibration signals under different degrees of ITSC, and compared with the collected signals of PAS. The experimental results prove that the proposed method has obvious advantages in vibration monitoring in the low frequency band below 100 Hz.

П’яти координатні верстати з ЧПК: процеси обробки та проблеми функціонування верстатів з ЧПК

The current state of machines with CNC (computer numerical control) and the problems that arise when using them are considered. The existing solutions to problems are described, and a new way of protecting machine components from breakdowns is proposed. Protection is based on the use of piezoelectric force and acceleration sensors. Additional protection can be imple-mented with the help of software in the CNC device.

Automatized Scaling Monitoring in Pipelines with Resonance Testing

Scaling is a significant cause of efficiency loss, downtime and maintenance costs in almost all industries in which pipelines play an integral role. In this work, a non-invasive, cost-effective and automatized monitoring approach to detect the onset and evolution of scaling growth was developed. The designated field of interest was geothermal plants, which particularly struggle with calcitic scaling in Bavaria. An additional criterion that had to be met was therefore applicability at high temperatures. A resonance testing setup, consisting of automatized excitation using a solenoid-based impactor, piezoelectric acceleration sensors coupled to the pipe, an oscilloscope, a signal conditioner and mounting gear, serves to collect a number of amplitude-time signals. These are Fourier transformed, averaged and evaluated in the frequency domain. By coupling the sensors (standard operating temperature limit ~ 120 °C) to the pipe with a high-temperature couplant and samarium-cobalt magnets, the setup is robust in an environment with elevated temperatures. Such an environment is presented by the injection borehole at a geothermal power plant where in-situ measurements are currently being carried out (60 – 80 °C). It can be observed that the frequency peak positions shift with scaling thickness. In order to analyze this shift in frequency, an experiment was conducted in which a heavily scaled piece of pipeline from the production well of a geothermal power plant in Bavaria was inserted in a specially designed descaling test rig. An acidic solution was pumped through the pipe, gradually etching away the calcitic scaling. By carrying out resonance tests at regular time intervals over the course of the descaling process, a continuous reduction in peak frequencies could be determined with decreasing scaling thickness. With an adequately chosen time interval and appropriate measurement parameters (sampling rate, signal length, gain), the onset- and growth of scaling are measurable in the submillimeter regime.

A Review of Flexible Acceleration Sensors Based on Piezoelectric Materials: Performance Characterization, Parametric Analysis, Frontier Technologies, and Applications

Acceleration sensors are tools for detecting acceleration and serve purposes like fault monitoring and behavior recognition. It is extensively employed in a variety of industries, including aerospace, artificial intelligence, biology, and many more. Among these, one of the major research hotspots and challenges is the development of low-energy, self-powered, miniature, mass-produced sensors. Due to its capacity to perceive human behavior and identify errors, the flexible acceleration sensor offers a distinct advantage in the use of flexible and miniaturized sensing systems. This review analyzes the current state of piezoelectric flexible acceleration sensors’ applications in the areas of sensitive materials, processing technology, and device structure and briefly summarizes the fundamental properties of these sensors. Additionally, it ends with a prognosis for the future growth of flexible piezoelectric acceleration sensors.

Design and simulation of micro piezoelectric fiber triaxial acceleration sensor

Aiming at the demand for passive sonar systems for medium and low-frequency detection, low cost, and small working platform working sensor, a three-axis pressure piezoelectric accelerometer based on piezoelectric ceramic fiber is designed. Firstly, based on the acoustic vibration pick-up principle and extended Hamilton, the action mode of the accelerometer is analyzed theoretically to determine the accelerometer structure size. The accelerometer with a special mass structure is designed by using axially polarized piezoelectric ceramic fiber. The characteristic frequency and frequency domain analysis of the accelerometer are simulated by the FEM method. The results show that the overall size of the piezoelectric accelerometer is 20 mm ×20 mm×35 mm, the first-order natural frequency is 410 Hz, the external field directivity is standard “8” type, and the acceleration sensitivity reaches 112.2 mV/g, which verifies the great potential of the three-axis accelerometer designed by piezoelectric ceramic fiber material in the field of medium and low frequency.

Lead-Free Piezoelectric Acceleration Sensor Built Using a (K,Na)NbO3 Bulk Ceramic Modified by Bi-Based Perovskites

Piezoelectric accelerometers using a lead-free (K,Na)NbO3 (KNN) piezoceramic modified by a mixture of two Bi-based perovskites, Bi(Na,K,Li)ZrO3 (BNKLZ) and BiScO3 (BS), were designed, fabricated and characterized. Ring-shaped ceramics were prepared using a conventional solid-state reaction method for integration into a compression-mode accelerometer. A beneficial rhombohedral-tetragonal (R-T) phase boundary structure, especially enriched with T phase, was produced by modifying intrinsic phase transition temperatures, yielding a large piezoelectric charge coefficient d33 (310 pC/N) and a high Curie temperature Tc (331 °C). Using finite element analyses with metamodeling techniques, four optimum accelerometer designs were obtained with high magnitudes of charge sensitivity Sq and resonant frequency fr, as evidenced by two key performance indicators having a trade-off relation. Finally, accelerometer sensor prototypes based on the proposed designs were fabricated using the KNN-BNKLZ-BS ceramic rings, which exhibited high levels of Sq (55.1 to 223.8 pC/g) and mounted fr (14.1 to 28.4 kHz). Perfect charge-to-acceleration linearity as well as broad flat frequency ranges were achieved with excellent reliability. These outstanding sensing performances confirm the potential application of the modified-KNN ceramic in piezoelectric sensors.

In-situ measurement of the acoustic performance of a nearly-enclosed barrier prototype on an existing line in the urban rail transit system

The acoustic performance of a nearly-enclosed prototype meant to attenuate urban rail transit (URT) noise was measured in situ on an existing line. The prototype is constructed on a viaduct on Line 1, Ningbo, China, with a 2-meter-wide opening at the top. A series of measurements while trains passed by were carried out with twelve receiver positions at the site without and with the prototype. Train speeds were measured using a piezoelectric acceleration sensor located on a rail foot. By correcting pass-by levels for train speed, the measured results show that the nearly-enclosed prototype provides an attenuation with a maximum of 17 dB(A), and a minimum of 6 dB(A). One-third octave band spectrum analysis shows that the insertion loss specific to rolling noise yields on average more than 15 dB. Furthermore, comparisons between measured and predicted results by using 2.5-D boundary element method (2.5-D BEM) show that both of the employed PC and PMMA sheets could not provide sufficient transmission loss for the prototype in a real situation. Nevertheless, the nearly-enclosed prototype is effective against rolling noise for the URT system.

Determination of Dynamic Range of Stand-alone Shock Recorders

Abstract In aircraft construction, when creating samples of new equipment, shock tests are often performed, both on individual components and the entire product. It requires introducing non-destructive testing devices into production, it is one of the most important factors in accelerating scientific and technological progress, raising the quality and competitiveness of manufactured products. Applying modern means of non-destructive testing, there is the problem of their protection from external vibrations, which affect the sensitivity, accuracy and reliability of high-precision measurements. In such cases, the conversion of measuring information during powerful vibration and shock tests, as a rule, is carried out by piezoelectric acceleration sensors. Although to provide impact testing, there is a need to develop and use stand-alone recorders. The main requirements for these recorders are to ensure the autonomy and operability of the recorder onboard the test product and to ensure the synchronization of the registration of the shock load.

Design and Optimization of a Triangular Shear Piezoelectric Acceleration Sensor for Microseismic Monitoring

Aiming at the characteristics of low sensitivity and narrow frequency range of existing microseismic monitoring sensors for mine water hazard prevention and control, a piezoelectric acceleration sensor for microseismic monitoring based on a kind of triangular shear structure is proposed. Firstly, the structure of the triangular shear piezoelectric acceleration sensor is designed, and its dynamic model is built. The structural and material parameters related to natural frequency and sensitivity are analyzed. Then, the selection of piezoelectric ceramic materials is discussed. The parametric design of the designed sensor is carried out, and its finite element structural model is built by ANSYS. The modal analysis, resonance response analysis, and piezoelectric analysis of the designed sensor are carried out. The simulation results indicate that the working frequency and sensitivity of the designed sensor meet the requirements of microseismic monitoring. Response surface optimization is adopted to analyze the influence of sensor element design variables on the sensitivity and resonant frequency of the designed sensor. The reoptimized design of the reference sensor improves the resonant frequency of the designed sensor by 9.46% and the charge sensitivity by 18.96%. Finally, the designed sensor is calibrated, and the microseismic signal detection experiment is carried out. The results indicate that the resonant frequency of the designed sensor is 6150 Hz, the working frequency is 0.1-2050 Hz, and the charge sensitivity is 1600 pC/g. The sensor can detect microseismic signals with a wide frequency range and high sensitivity.

Finding the Dynamic Range of Recorders During Impact Tests

In aircraft construction, when creating samples of new equipment, impact tests are often performed, both of individual components and of the entire product. It requires to introduce non-destructive testing devices into production, it is one of the most important factors in accelerating scientific and technological progress, raising the quality and competitiveness of manufactured products. Applying modern means of non-destructive testing, there is the problem of their protection from external vibrations, which affect the sensitivity, accuracy and reliability of high-precision measurements. In such cases the conversion of measuring information during powerful vibration and impact tests, as a rule, is carried out by piezoelectric acceleration sensors. Although to provide impact testing, there is a need to develop and use stand-alone recorders. The main requirements for these recorders are to ensure the autonomy and operability of the recorder on board the test product and to ensure the synchronization of the registration of the impact load.

Research on fault signal detection method of mechanical vibration based on Kalman filtering algorithm

There are some problems in traditional mechanical fault signal detection, such as large fault detection error and is time-consuming. A mechanical vibration fault signal detection method based on Kalman filter algorithm is proposed. The time-varying nonlinear oil film force of mechanical equipment under different working conditions is analysed. The piezoelectric acceleration sensor is set in the mechanical equipment to obtain the mechanical vibration fault signal. The energy difference between the normal signal and the fault signal is obtained by arranging them according to the acquisition time sequence. The mechanical vibration fault signal is pre-processed by Kalman filtering algorithm to obtain the state prediction of the fault signal. The frequency and amplitude characteristics of mechanical vibration fault signal are obtained to complete the detection of mechanical vibration fault signal. The results show that the error of the proposed method is small and the detection time is 2 s.

EXPERIMENTAL ANALYSIS OF DAMPING PROPERTIES OF VISCOELASTIC MATERIALS

This study presents results of an experimental investigations of the materials used in passive damping vibrations. The main purpose of this paper was to examine the damping properties of selected viscoelastic materials (VEM), using the modal analysis. In presented analysis three configurations of specimens were considered. At first, the separated steel beam was analyzed. As results of this analysis, the frequencies and amplitudes of the beam during resonance were obtained. In next part of the work the modified specimen was investigated. In this modification the bitumen-based material (as a damper) was fixed to the surface of the beam. This method is known as free layer damping (FLD) treatment. In last configuration, the butyl rubber layer was connected to the steel beam. Using the Unholtz-Dickie UDCO-TA250 electrodynamic vibration system, the natural frequencies and amplitudes of free vibrations for all examined specimens were obtained. The vibration amplitude of the beam was measured using piezoelectric acceleration sensors. In order to define the damping capabilities of both the bitumen based material and the butyl rubber, the relative amplitude of specimens and the loss factor using half-power bandwidth method were calculated.