Piezoelectric Accelerometer Research Articles

Comparative analysis of MEMS (Micro-Electro-Mechanical Sensor) and IEPE (Integrated Electronics Piezo-Electric) accelerometers for measurement of wide spectrum damping

Damping is an important material property for dynamically loaded structures, such as aircraft, vehicles, and rotary or reciprocating machinery. Low damping may increase vibration amplitudes which can cause excessive dynamic loading and can detrimentally affect a structures performance. Accurate prediction of the dynamic loads is necessary to avoid catastrophic failure especially during resonant vibrations. In this work, a MEMS (micro-electro-mechanical sensor) accelerometer system is constructed to measure vibration over a wide frequency range (from 0-3000 Hz). Measurements of the damping ratio taken with MEMS accelerometers were compared to similar measurements using IEPE (integrated electronics piezo-electric) accelerometers and the experimental results validated against a thermoelastic model and published studies. The damping measured using IEPE accelerometers was larger due to spurious damping effects attributed to the much larger cables. The low spurious damping of the MEMS accelerometers allows for the accurate determination of the damping of a material over a wide frequency range. The MEMS accelerometer setup used in this work offers a method to accurately measure the damping of dynamically loaded, lightweight structures, where attaching traditional accelerometers can cause significant error in the measured damping or where non-contact measurement may be unsuitable.

Acoustics and vibration based milling diagnostics using supervised machine learning approaches

In industrial machining processes, tool failures may result in losses in surface and dimensional accuracy of a finished part, or possible damage to both the work piece and the machine. Consequently, tool condition monitoring has become essential to achieve high-quality machining as well as cost-effective production. Moreover, cutting tool degradation may vary considerably under different operation conditions and materials behaviour. Therefore, real time identification of the tool state during machining is critical. In this study the acoustic and vibration responses of the cutting tool and of the workpiece material are measured with the help of a microphone and a piezoelectric accelerometer. Many milling experiments were conducted for different conditions and tool failures, from which features were calculated in time and frequency domains and then split into two groups: 80% for the machine learning model training, 20% for the test phase. Then several supervised machine learning approaches have been applied and compared. Results of our study are implemented in a real tool wear predictive maintenance framework.

Development and Field Test of Integrated Electronics Piezoelectric Accelerometer Based on Lead-Free Piezoelectric Ceramic for Centrifugal Pump Monitoring.

In this study, an Integrated Electronics Piezoelectric (IEPE)-type accelerometer based on an environmentally friendly lead-free piezoceramic was fabricated, and its field applicability was verified using a cooling pump owned by the Korea Atomic Energy Research Institute (KAERI). As an environmentally friendly piezoelectric material, 0.96(K,Na)NbO3-0.03(Bi,Na,K,Li)ZrO3-0.01BiScO3 (0.96KNN-0.03BNKLZ-0.01BS) piezoceramic with an optimized piezoelectric charge constant (d33) was introduced. It was manufactured in a ring shape using a solid-state reaction method for application to a compression mode accelerometer. The fabricated ceramic ring has a high piezoelectric constant d33 of ~373 pC/N and a Curie temperature TC of ~330 °C. It was found that the electrical and physical characteristics of the 0.96KNN-0.03BNKLZ-0.01BS piezoceramic were comparable to those of a Pb(Zr,Ti)O3 (PZT) ring ceramic. As a result of a vibration test of the IEPE accelerometer fabricated using the lead-free piezoelectric ceramic, the resonant frequency fr = 20.0 kHz and voltage sensitivity Sv = 101.1 mV/g were confirmed. The fabricated IEPE accelerometer sensor showed an excellent performance equivalent to or superior to that of a commercial IEPE accelerometer sensor based on PZT for general industrial use. A field test was carried out to verify the applicability of the fabricated sensor in an actual industrial environment. The test was conducted by simultaneously installing the developed sensor and a commercial PZT-based sensor in the ball bearing housing location of a centrifugal pump. The centrifugal pump was operated at 1180 RPM, and the generated vibration signals were collected and analyzed. The test results confirmed that the developed eco-friendly lead-free sensor has comparable vibration measurement capability to that of commercial PZT-based sensors.

Development of cable-climbing robot with inspection function

Abstract The primary purpose of this study is to research and develop a crawler-type cable climbing robot to meet the demand of Sinotech Engineering Consultants, Ltd, using excellent structural design to meet the current practical requirements of the application of cable diameter varies greatly and simplify the operation process, improve the efficiency of the safety inspection of bridge cables and reduce the related risks, and through numerical analysis and the finite element method to optimize the design. The design is mainly divided into three parts: vibration measurement mechanism, robot control system, and cable climbing mechanism. The vibration measurement mechanism adopts the micro-vibration measurement method, in which a 3-axis piezoelectric accelerometer is tightly attached to the cable to measure the resonance frequency of the cable and detect the cable force. The robot control system adopts the fourth-generation Raspberry Pi as the central controller, with a ground remote control system and a backup system to prevent the robot from losing control due to the failure of the central system. The drive unit adopts a stepping motor with a planetary gearbox to drive the crawler. The cable-climbing mechanism uses a compression device to keep the robot’s track close to the cable to achieve a maximum speed of 0.04 m/s and to cross an obstacle limit of 9 mm over a 60-200 mm vertical or horizontal cable. The tracked cable-climbing robot is tested to be installed and operated by a single person and is adaptable to different cable environments with rapid deployment and operation.

Experimental and numerical analyses on the modal behaviour of an aluminium alloy sheet

Abstract The study of modal behaviour for vehicle body panels represents a field of interest for automotive engineering, having a major influence on automotive comfort, with respect to vehicle noise, vibration and harshness, but also concerning the durability of vehicle body. The investigation of natural frequencies and vibration mode shapes is crucial in the design phase, because essential information can be obtained concerning the behaviour of the components in dynamic conditions. The current paper focuses on the investigation of vibration modes and frequency response function on an aluminium alloy sheet. The aim of the paper is to perform the study of modal behaviour both experimentally and theoretically, through measurements using the impact hammer method and respectively through finite element analysis. The CAD model of the aluminium alloy sheet has been developed in Catia V5 environment in view of elaborating the finite element model, which has been used for investigation of modal behaviour, taking into account the case of free vibrations. Through the modal finite element analysis performed in Ansys Workbench, the natural frequencies of the aluminium alloy sheet, as well as the corresponding mode shapes have been obtained. Experiments have been performed on an aluminium alloy sheet, mounted on an elastic support with low natural frequency. The impact hammer method has been used for obtaining the natural frequencies, through frequency analysis of accelerations measured with two piezoelectric accelerometers mounted on the aluminium alloy sheet. The frequency response function has been computed from the response acceleration measured on the aluminium alloy sheet and the impact force measured using the force transducer of the impact hammer. Virtual instruments have been developed in LabVIEW environment for data acquisition, time domain and frequency analysis, as well as for determining the frequency response function using the measured signals. The natural frequencies obtained from the finite element analyses have been compared to the results of measurements and very good similarities have been ascertained. The experimental investigation of modal behaviour contributed to the validation of the finite element model, but further research is required to investigate the possibilities of improving the modal behaviour of the aluminium alloy sheet.

Multi-hole liquid CO2 flashing jet: A novel method for achieving trade-off between impact region and impact force through phase transition

A novel multi-hole liquid CO2 flashing jet for coalbed methane exploitation is proposed, which undergoes phase transition during the injection of superheated CO2. The thermal stress generated during the phase-transition process is beneficial for rock fragmentation. Different types of nozzles were compared, and a conical convergent nozzle was selected owing to its wider jets. The proposed jet interaction criteria based on the fuel were examined using CO2, and discrepancies due to the internal phase transition and stronger cooling effects were observed. Nozzles with larger drilling angles were found to be more prone to transition from cone-shaped to jet-shaped morphologies. Coal-breaking experiments were also performed, and three distinct coal-breaking patterns induced by multi-hole flashing CO2 jets were identified. The effects of thermal stress on rock-breaking were evaluated using a beam-scanning electron microscope and wave velocity measurement with a piezoelectric accelerometer. Thermal cracks induced by matrix contraction were identified, indicating the potential to enhance breakage efficiency. The results indicate that the trade-off between the impact region and impact force should be carefully adjusted to achieve the desired coal-breaking performance. This study provides a potential method to utilize CO2, as well as some guidance for the issues that must be addressed in energy exploration using CO2.

A Positioning Alarm System for Explosive Impact Debris Protective Suit Based on an Accelerometer Array.

Protection suits are vital for firefighters' safety. Traditional protection suits physically protect firemen from burns, but cannot locate the position of bodily injuries caused by impact debris. Herein, we present a wearable impact debris positioning system for firefighter protection suits based on an accelerometer array. Wearable piezoelectric accelerometers are distributed regularly on the suit to detect the vibration on different body parts, which is conducive to determining the position of injured body parts. In addition, the injured parts can be displayed on a dummy body model on the upper computer with a higher localization accuracy of 4 cm. The positioning alarm system has a rapid response time of 0.11 ms, attributed to the smart signal processing method. This work provides a reliable and smart method for locating and assessing the position of bodily injuries caused by impact debris, which is significant because it enables fire commanders to rescue injured firefighters in time.

Evaluation of the Diagnostic Sensitivity of Digital Vibration Sensors Based on Capacitive MEMS Accelerometers.

In recent years, there has been an increasing use of digital vibration sensors that are based on capacitive MEMS accelerometers for machine vibration monitoring and diagnostics. These sensors simplify the design of monitoring and diagnostic systems, thus reducing implementation costs. However, it is important to understand how effective these digital sensors are in detecting rolling bearing faults. This article describes a method for determining the diagnostic sensitivity of diagnostic parameters provided by commercially available vibration sensors based on MEMS accelerometers. Experimental tests were conducted in laboratory conditions, during which vibrations from 11 healthy and faulty rolling bearings were measured using two commercial vibration sensors based on MEMS accelerometers and a piezoelectric accelerometer as a reference sensor. The results showed that the diagnostic sensitivity of the parameters depends on the upper-frequency band limit of the sensors, and the parameters most sensitive to the typical fatigue faults of rolling bearings are the peak and peak-to-peak amplitudes of vibration acceleration. Despite having a lower upper-frequency range compared to the piezoelectric accelerometer, the commercial vibration sensors were found to be sensitive to rolling bearing faults and can be successfully used in continuous monitoring and diagnostics systems for machines.

Failure analysis in predictive maintenance: Belt drive diagnostics with expert systems and Taguchi method for unconventional vibration features

Predictive maintenance to avoid fatigue and failure enhances the reliability of mechanics, herewith, this paper explores vibrational time-domain data in advancing fault diagnosis of predictive maintenance. This study leveraged a belt-drive system with the properties: operating rotational speeds of 500–2000 RPM, belt pretensions at 70 and 150 N, and three operational cases of healthy, faulty and unbalanced, which leads to 12 studied cases. In this analysis, two one-axis piezoelectric accelerometers were utilized to capture vibration signals near the driver and pulley. Five advanced statistics were calculated during signal processing, namely Variance, Mean Absolute Deviation (MAD), Zero Crossing Rate (ZCR), Autocorrelation Coefficient, and the signal's Energy. The Taguchi method was used to test the five selected features on the basis of Signal-to-Noise (S/N) ratio. For classifications, an expert system was used based on artificial intelligence where a Random Forest (RF) model was trained on untraditional parameters for optimizing the accuracy. The resulted 0.990 and 0.999, accuracy and AUC, demonstrate the RF model's high dependability. Evidently, the methodology highlights the features potential when progressed into expert systems, which advances predictive maintenance strategies for belt-drive systems.

Properties of tape cast (Na, K, Li) (Nb, Sb, Ta)O3 -based ceramics sintered in reduced atmosphere and its application in triaxial piezoelectric accelerometer

In this study, we utilized the tape-casting method to produce Pb-free (Na0·52K0·4425Li0.0375) (Nb0·8925Sb0·07Ta0.0375)O3 + 2 mol% MnCO3 + y mol% LiF (y = 0 to 3) piezoelectric ceramics. We investigated the impact of LiF sintering in a reduced atmosphere on microstructure, dielectric properties, impedance spectroscopy, and piezoelectric performance. By analyzing the degree of diffuse phase transition, we observed increased density and enhanced long-range order in the sample doped with 1 mol% LiF, which exhibited optimal piezoelectric properties (d33 = 265 pC/N and kp = 0.437) and a minimal diffusion parameter. Moreover, LiF doping enabled sintering at 1020 °C under low PO2, facilitating potential co-firing with Cu inner electrodes to further enhance the piezoelectric performance. Using the optimized parameters, we fabricated a cross-type triaxial piezoelectric accelerometer, demonstrating sensitivities of 2.33, 2.44, and 10.6 mV/g along the X, Y, and Z axes, respectively, with a resonance frequency of ∼2600 Hz and frequency range of ∼1300 Hz. This accelerometer holds promise for vibration measurements in low-frequency mechanical systems.

Deep learning based fault detection of automobile dry clutch system using spectrogram plots

Dry friction clutches are extremely important in the context of power transmission systems. Continuous exposure to extreme heat and loading makes clutch extremely susceptible to various faults. The timely detection and diagnosis of such faults are of utmost importance to prevent any damage to internal components and also helps in avoiding transmission system failures. In this research study, a novel approach that leverages the power of transfer learning (a famous deep learning technique) is proposed to diagnose multiple types of clutch faults including, worn release fingers, fractured pressure plates, deteriorated pressure plates, loss of friction material and distorted tangential strips using spectrogram plots. To train and validate the diagnostic system, vibration readings were taken from a specially designed test rig with the help of piezoelectric accelerometer while the clutch system was operated under different load conditions of 0 (no load), 5 and 10 kg This procedure of data collection was then repeated to acquire the vibration data for all of the fault conditions by replacing the good with fault components individually. These vibration signals were further processed and transformed into spectrogram plots that serves as the input data for the deep learning models considered. Fine-tuning techniques were applied on pretrained networks to maximise the prediction accuracy of the models to effectively determine and diagnose faults in the clutch system. For this study 12 pre-trained networks were chosen namely, Xception, InceptionResNet, DenseNet, AlexNet, VGG16, GoogLeNet, VGG19, ResNet101, ResNet50, InceptionV3, MobileNetV2 and ShuffleNet. To optimize the performance of deep learning models, a systematic adjustment of hyperparameters such as the train-test split ratio, learning rate, optimizer and batch size for each network model was carried out. Through careful experimentation and analysis, significant improvements in fault classification accuracy were achieved thereby enhancing the reliability and effectiveness of the diagnostic system. From the results it was noted that 100% classification accuracy was displayed by AlexNet (for the no load condition and the 10 kg load condition) and GoogLeNet (for 5 kg load condition) with extremely low computation times.

Polymeric piezoelectric accelerometers with high sensitivity, broad bandwidth, and low noise density for organic electronics and wearable microsystems

Piezoelectric accelerometers excel in vibration sensing. In the emerging trend of fully organic electronic microsystems, polymeric piezoelectric accelerometers can be used as vital front-end components to capture dynamic signals, such as vocal vibrations in wearable speaking assistants for those with speaking difficulties. However, high-performance polymeric piezoelectric accelerometers suitable for such applications are rare. Piezoelectric organic compounds such as PVDF have inferior properties to their inorganic counterparts such as PZT. Consequently, most existing polymeric piezoelectric accelerometers have very unbalanced performance metrics. They often sacrifice resonance frequency and bandwidth for a flat-band sensitivity comparable to those of PZT-based accelerometers, leading to increased noise density and limited application potentials. In this study, a new polymeric piezoelectric accelerometer design to overcome the material limitations of PVDF is introduced. This new design aims to simultaneously achieve high sensitivity, broad bandwidth, and low noise. Five samples were manufactured and characterized, demonstrating an average sensitivity of 29.45 pC/g within a ± 10 g input range, a 5% flat band of 160 Hz, and an in-band noise density of 1.4 µg/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{{Hz}}$$\\end{document}. These results surpass those of many PZT-based piezoelectric accelerometers, showing the feasibility of achieving comprehensively high performance in polymeric piezoelectric accelerometers to increase their potential in novel applications such as organic microsystems.

DIMENSONAREA ȘI CONSTRUCȚIA TRADUCTOARELOR PIEZOELECTRICE DE VIBRAȚII

The paper presents the construction of piezoelectric accelerometers, the mechano-electrical transfer mode, typical constructions, basic characteristics, and theoretical approaches to the vibration phenomenon appearing in accelerometry and calculation possibilities of the various characteristics of the transducers. In the second part of the paper, the functional testing of such a transducer is also presented, piezoelectric vibration transducers being useful for vibration determination and dynamic balancing of electric machines. In general, vibration transducers provide, through mechano-electrical conversion according to different principles, an electrical signal directly proportional to a vibration parameter (acceleration, travel speed, amplitude); depending on the principle, they can be piezoelectric, electrodynamic, inductive, capacitive, resistive or based on the Hall effect, with magnetic fluids, interferometric, laser, servo-accelerometers, etc. Since there is no universal accelerometer, each one is intended to encompass the characteristics of a concrete application best, the way of stressing the photosensitive medium in the first place, the design,, as well as the other characteristics, vary from one construction to another.

Fault detection in the gas turbine of the Kirkuk power plant: An anomaly detection approach using DLSTM-Autoencoder

Developing a maintenance schedule for different parts of a power plant can help to prevent serious system damage while also having a direct effect on reducing maintenance time and costs. Moreover, the proposed procedure can provide a better understanding of the health state of the system. The occurrence of problems (anomalous behavior) in power plants usually takes time and happens gradually. Predicting the possibility of anomalous behavior arising can therefore result in the prediction of a failure. In this paper, the authors tried to propose a new method for reducing the volume of input data by extracting the latent layer output of an Autoencoder, which was then applied to identify features. We achieved this by keeping relevant features and learning the anomalous behavior's encoded representation. Furthermore, the latent layer output from the encoder was used to train a Deep Long-Short-Term Memory (DLSTM) model with three hidden layers for fault occurrence prediction by considering an anomaly detection approach. To this end, a threshold approach was used to determine the possibility of a fault occurring in the turbine, with data collected from the Kirkuk gas turbine power plant. Piezoelectric accelerometer CA 202 was utilized as a sensor to collect data in industry. Since most of the recorded data were normal and the amount of abnormal data was small, various techniques, i.e., flipping and jittering, were employed to create synthetic abnormal data and augment the applicable dataset. In summary, according to the proposed methodology, the system is modelled as a time series classification problem to mimic the anomaly detection problem. The results showed that the accuracy of the trained model for detecting turbine vibration as a system abnormality is over 86%. Also, the implementation of the proposed prediction model on the experimental dataset yielded satisfactory results for detecting and predicting the occurrence of faults in Kirkuk gas turbine power plant.

Clinker storage silos: Validation of dynamic performance through measurements and finite element simulation

The paper describes the design and application of a structural health monitoring system aimed at analysing the dynamic response of reinforced concrete silos for the storage of clinker. The in-situ dynamic measurements, supported by finite element simulations to assess the structural safety, were prompted by reports from people working in facilities near the silos in question, who complained of strong vibrations. The proposed approach combines the advantages of theoretical and operational modal analysis based on monitoring during normal use of the silos, including their emptying. The measurements were performed automatically and continuously over time, and only significant events, like shocks caused by clinker masses falling off the side walls of the silos, were saved into the remote server as the acceleration-time waveforms. They were registered with 4000 Hz frequency by piezoelectric accelerometers mounted on the bottom of the silos within the support structure. The data management system with predefined post-processing algorithms allow to extract dynamic parameters of the structure, which were then used to validate the spatial finite element model (FEM). What is worth underlying, the analysis took into account different degrees of filling of the silos, as these directly affect the dynamics of the structure. The results described hereafter were the basis for providing expertise on structural safety. The presented case study is an example of how automatic monitoring over a specified period of time can assist engineers in making rational decisions.

Micro-electromechanical systems sensor characterization for acoustic prognostic health management

Prognostic Health Management (PHM) is the process used to optimize machinery use by detecting faults and predicting failures and a machine’s remaining useful life. PHM is especially important to electro-mechanical systems in order to maximize a system’s availability and effective operation. The use of Micro-Electromechanical Systems (MEMS) accelerometers and microphones for PHM analysis is beneficial because it enables non-destructive acoustic testing with reduced cost, reduced size, and more efficient vehicle integration with other electronics than current methods. This research quantitatively studies a variety of MEMS sensors to understand how they measure acoustic data in a lab setting and on a truck with a diesel engine compared to piezoelectric accelerometers and condenser microphones. Diesel engines are common in many vehicles and hybrid-electric power systems, so the results will be applicable to a variety of situations. By applying signal processing techniques and PHM condition indicators to the data, standardized metrics can be developed to determine the best sensor for different PHM analyses.

Comprehensive Noise Modeling of Piezoelectric Charge Accelerometer with Signal Conditioning Circuit.

This paper reports on noise modeling of a piezoelectric charge accelerometer with a signal conditioning circuit. The charge output is converted into voltage and amplified using a JFET operational amplifier that has high input resistance and low noise. The noise sources in the whole system include electrical and mechanical thermal noises of the accelerometer, thermal noises of resistors, and voltage and current noises of the operational amplifier. Noise gain of each source is derived from small signal circuit analysis. It is found that the feedback resistor of the operational amplifier is a major source of noise in low frequencies, whereas electrical thermal noise of the accelerometer dominates the rest of spectrum. This method can be used to pair a highly sensitive sensor with a single JFET operational amplifier instead of a multi-stage signal conditioning circuit.

Operational modal analysis, seismic vulnerability assessment and retrofit of a degraded RC bell tower

This paper presents damage assessment through Operational Modal Analysis (OMA) and Finite Element (FE) model updating of the bell tower of the church of Castro in Bergamo, Italy. The tower is a 39 m high reinforced concrete structure with hollow cross-section and double-curved shape. The research was dictated by the need to identify the actual damage state of the structure, which was found through visual inspections. Piezoelectric accelerometers were used to record the ambient vibrations in subsequent test setups, using the roving technique for system identification. A detailed FE model was created with shell elements and calibrated to match the system identification results. A simplified beam model was then developed based on the modal analysis results of the detailed model. A sensitivity analysis was performed to identify the most influential model parameters on the modal characteristics of the system. Subsequently, the optimal values of these parameters were determined by an optimisation procedure carried out using a typical global optimization algorithm. The updating results allowed assessment of the actual condition of the bell tower and its seismic vulnerability. Finally, a seismic strengthening solution was recommended.

Shear-structured piezoelectric accelerometers based on KNN lead-free ceramics for vibration monitoring

A study of KNN-based ceramic coefficients enabled the development of a shear-mode piezoelectric accelerometer with excellent performance. This work proposes using the effective piezoelectric coefficient dij (eff) to evaluate sensor materials.

The possibility of shifting the resonant frequencies magnetically active elastomer

A sample of magnetically active elastomer composite material under the influence of external loads is experimentally studied to determine the possible ranges of resonance frequency shift. To record the experimental dynamic characteristics, a complex of vibration test equipment is used, which includes various types of equipment ensuring the operation of the vibration test bench in a given frequency range. In the investigated range the method of smooth frequency sweep of sinusoidal oscillations is used. Signals received from vibration sensors (piezoelectric accelerometers) installed on the specimen are transformed, recorded, processed by software and displayed on the computer screen. Different methods of loading the specimen are used for the determined ranges of resonance frequency locations. One of the loading methods used is a weight with a mass attached to the specimen. Another variant of loading was the effect of magnetic forces on the sample. According to the results of the conducted tests, after processing the obtained experimental data, the shifts of resonance frequencies were recorded and the amplitude-frequency characteristics were plotted, showing the ranges of shift or displacement of resonance frequencies in the investigated material. Under the influence of the considered external loads applied to the tested material, the oscillograms of acceleration of the specimen show the shift of resonance frequencies to the low-frequency range by more than three times and the shift of resonance frequencies to the high-frequency range by two times. The obtained results show additional possibilities of application of different modes in solving the problem of control of dynamic and antivibration properties of the tested material by shifting of resonance frequencies.