Vibration Monitoring Method Research Articles

Performance-enhanced tribovoltaic nanogenerator by regulating carrier transportation with an asymmetric heterostructure

The tribovoltaic nanogenerator (TVNG) is emerging as a promising circuit-integrative energy harvester, with notable advantages like direct current output and large current density. Nevertheless, the research on optimizing charge excitation and carrier transportation remains deficient. In this work, we report an alternative approach for practically promoting the output performance of silicon (Si)-based TVNG. A well-designed asymmetric heterostructure is achieved by inserting an appropriate interlayer between the friction layer and the bottom electrode. Carrier extraction efficiency has been promoted effectively, while carrier recombination has been restrained owing to the built-in electric field excited by p-Si/ZnO heterojunction. The coupling mechanism of the built-in electric field and the interfacial electric field has been revealed explicitly with a comprehensive theoretical model, which is based on the capacitance feature of the PN junction. The designed multilayer TVNG (MTVNG) has shown 20 times higher output compared to normal Si-based TVNGs. Apart from presenting fundamental insights into the tribovoltaic effect, we have developed a dual-mode analysis method for vibration monitoring. This work expands the path to improve TVNG output through multi-electric field coupling and provides new inspiration for miniaturized vibration sensors in real-time deployments.

A recursive calculation method of vibration displacements using blade tip timing in angular domain

Blade tip timing (BTT) is a non-contact measurement technique that can be used to monitor blade vibration in turbomachinery. The raw data measured by BTT is the arrival time of all blades at the same stage. However, most blade vibration monitoring methods based on BTT require the use of blade vibration displacements, which are derived from the raw arrival time data, the blade rotation radius and speed. Conventional BTT methods calculate blade tip displacements by comparing the measured arrival time with the ideal arrival time. The ideal arrival time is obtained by assuming that the rotational speed is constant in a revolution, which is inconsistent with the fact, especially when the rotational speed changes rapidly. In this paper, a recursive calculation method called recursive BTT is proposed to reduce the influence of rotational speed fluctuation on the accuracy of blade tip displacement calculation. Recursive BTT calculates the displacements in the angular domain instead of the time domain. A recursive formula is constructed in the angular domain to calculate the blade vibration displacement by using the angle between the vibrating blades. Compared with the conventional BTT method, which relies on the once-per-revolution (OPR) signal, recursive BTT makes full use of the arrival time of all blades at the same stage to calculate the displacements. The advantage of recursive BTT is illustrated through a simulation, a laboratory test and a full-scale aeroengine test. To evaluate the reliability of the calculated displacements, strain signals are resampled to compare with the calculated displacements in the laboratory test. In the full-scale aeroengine test, due to the lack of strain signals, BTT displacements are used to track the blade natural frequency to qualitatively indicate the influence of displacements on blade vibration monitoring. The results of finite element analysis and modal test are used for verification in the full-scale aeroengine test. Simulation and experimental results demonstrate that compared with existing methods, recursive BTT is robust for calculating blade vibration displacements.

Review on Vibration Monitoring and Its Application during Shield Tunnel Construction Period

With the rapid development of metro construction, shield machines inevitably have to traverse a variety of complex geological conditions, leading to the frequent occurrence of geological disasters, equipment failures, building vibration and other problems. Vibration, as an important feature of the shield tunneling process, has received more and more attention in recent years. This paper summarizes the relevant research progress of vibration monitoring during shield construction from 2015 to 2023. It analyzes the shield vibration generation mechanism, monitoring methods and application areas. Firstly, the shield vibration type is divided into mechanical vibration triggered by internal excitation and forced vibration triggered by external excitation, and the principles of vibration generated by shield main bearing, gearbox and disc cutter are discussed. Then, the commonly used vibration monitoring methods are outlined according to the installation location of the sensors (inside and outside of the shield). Finally, the applications of vibration signals in the diagnosis of shield faults, the identification of geologic conditions, and the evaluation of the current status of the interference with the buildings are summarized. This paper discusses the development trend of vibration monitoring during shield tunneling based on the current research situation and the current technology level, which provides valuable insights to enhance the safety and intelligence of shield construction.

GNSS blasting vibration monitoring and feature recognition method

Aiming at the problems of the current blasting vibration monitoring, such as unstable low-frequency performance, vulnerability to environmental interference, complex operation, and easily damaged, a new blasting vibration monitoring and feature recognition method of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and multiscale permutation entropy (MPE) and singular spectrum analysis (SSA) is proposed based on global navigation satellite system (GNSS). Initially, a new method of GNSS blasting vibration monitoring is proposed according to the blasting environment and blasting characteristics, it can provide a new reference for GNSS technology to be used in blasting vibration monitoring. Then, signal simulation proved that the proposed feature recognition method can effectively remove the low-frequency and high-frequency background noise as well as trend items of blasting vibration signals and accurately extract the dominant frequency of vibration compared with the traditional processing methods. Finally, the proposed method is demonstrated by factory open blasting and tunnel excavation blasting compared with the monitoring results of the conventional blasting recorder, it can accurately recognize the characteristics of blasting initiation time, particle peak velocity (PPV), initiation period, and dominant frequency of vibration. The RMSE of PPVs is 0.086, and other errors are within 5%, which is highly consistent with the monitoring results of blasting recorder. The GNSS blasting vibration monitoring and feature recognition method can improve the low-frequency stability, field adaptability, simple operation, and information richness of blasting monitoring, which can provide a new approach for blasting monitoring; it can also be an important supplement to existing blasting monitoring methods.

Parameter identification method of nonuniform and under-sampled blade tip timing based on extended DFT and compressed sensing

Vibration amplitude and frequency are the two most important indicators that characterize the health status of high-speed rotating blades, but the signal obtained by blade tip timing (BTT) technology, one of the best rotating blade vibration monitoring methods, is seriously nonuniform and under-sampled, which makes these two indicators difficult to identify. In view of this problem, the paper proposes a parameter identification method for the nonuniform and under-sampled BTT signal based on extended Discrete Fourier transform and compressed sensing (CS), with the Fourier integral transformation as the goal. It realizes the frequency analysis of nonuniform under-sampled signals by constructing and optimizing the transformation basis function instead of the exponential basis in the traditional FFT transformation in the extended frequency range, and then constructs a CS model through the obtained blade vibration frequency. The complete waveform of the blade vibration is restored by using a small number of under-sampled signals, thus obtaining the blade vibration amplitude and vibration frequency. On the one hand, the method proposed in this paper breaks through the limitation of Nyquist’s sampling theorem, and the number of analytical spectral lines is no longer limited to the number of sampling points, which improves the frequency resolution. On the other hand, only a small number of measurement signals can be reconstructed to achieve a complete vibration signal. The feasibility and reliability of the proposed method are verified by mathematical modeling, simulation analysis, and experimental testing. The results indicate that when the number of sensors is greater than or equal to four, the time domain and frequency domain signals of blade vibration can be accurately analyzed based on the proposed method, the vibration amplitude error is less than 0.01 mm, the frequency error is less than 0.1 Hz, and it has good anti-interference performance.

Enabling High-Resolution Micro-Vibration Detection Using Ground-Based Synthetic Aperture Radar: A Case Study for Pipeline Monitoring

The wellbeing of pipelines is influenced by a range of factors, such as internal and external pressures, as well as deterioration over time due to issues like erosion and corrosion. It is thus essential to establish a reliable monitoring system that can precisely examine pipeline behavior over time in order to prevent potential damages. To this end, pipelines are inspected based on internal and external approaches. Radar, as a non-contact sensing system, can be a suitable choice for external pipeline inspection. Radar is capable of the transmission and receiving of thousands of signals in a second, which reconstructs the displacement signal and is used for a vibration analysis. Synthetic aperture radar (SAR) imaging adds cross-range resolution to radar signals. However, a data acquisition rate of longer than several seconds makes it unsuitable for sub-second vibration monitoring. This study aims to address this limitation by presenting a method for high-resolution vibration monitoring using ground-based SAR (GBSAR) signals. To this end, a signal processing method by modifying the radar’s signal model is presented, which allows for estimating scattering targets’ vibration parameters and angle of arrival with high resolution. The proposed method is validated with numerical simulation and a real case study comprising water pipelines. Moreover, various analyses are presented for the in-depth evaluation of the method’s performance in different situations. The results indicate that the proposed method can be effective in detecting pipeline vibration frequencies with micro-scale amplitudes while providing high spatial resolution for generating accurate vibration maps of pipelines. Also, the comparison with the radar observations shows a high degree of agreement between the frequency responses with the maximum error of 0.25 Hz in some rare instances.

Online long-distance monitoring of subway vibration reduction effect using ultra-weak fiber Bragg grating arrays

Monitoring the subway vibration reduction effect is vital since subway train-induced vibration brings great damage and distress to the buildings and residents along the metro line. To deal with the problems encountered in traditional electrical monitoring methods, such as severe electromagnetic interference and short monitoring distance, we propose an online long-distance vibration monitoring method based on ultra-weak fiber Bragg grating vibration sensing arrays. First, two parallel fiber optic cables are laid separately on the metro line's track bed and tunnel wall for the real-time acquisition of the dynamic response signals of passing trains. Next, the time–frequency and correlation signal characteristics of specific measurement points are extracted and analyzed to show the single-point performance of the sensing arrays. Finally, the subway vibration reduction effect of the entire monitoring area in the metro line is calculated to verify the feasibility of the proposed method.

A Wind Turbine Vibration Monitoring System for Predictive Maintenance Based on Machine Learning Methods Developed under Safely Controlled Laboratory Conditions

Wind energy is one of the most relevant clean energies today, so wind turbines must have good health and be reliable in operation. Current wind turbines have slender and elastic structures that can be easily damaged through vibrations and compromise their health; therefore, vibration monitoring is essential to ensure safe operation. Here, we present a method for simple wind turbine vibration monitoring in the laboratory by means of an accelerometer placed on a weathervane under different scenarios, with recording of different amplitudes of vibrations caused at a constant speed of 10 km/h. The variables, trends, and data captured during vibration monitoring were then used to implement a prediction system of synthetic failure using machine learning methods such as: Medium Trees, Cubic SVN, Logistic Regression Kernel, Optimized Neural Network, and Bagged Trees, with the last demonstrating an accuracy of up to 0.87%.

Effects of Vibration on Adjacent Pipelines under Blasting Excavation

Exploring a pipeline’s response to blast vibration during tunnel excavation is critical for ensuring the safety of the pipeline. In this paper, the vibration monitoring and numerical simulation methods are used to evaluate the dynamic response of ground soil and pipelines to blasts. The attenuation law of peak particle velocity (PPV) and the distribution characteristics of peak effective stress (PES) in pipe sections under different working conditions are studied. The following findings are recorded: (1) A three-dimensional model considering in situ stress is established, and it is found the triangular equivalent load simulation blast effect method used in this paper can effectively reflect the impact of blasting on pipelines. The simulation error is controlled at 7.69%. (2) The ground PPV of each monitoring point decays continuously with the increase in horizontal and axial distance, and the cavity enlargement effect is exhibited above the excavation area. The oncoming blast side PPV of the pipe section is more significant than that behind the blast side. (3) When the blast vibration is transmitted to the pipe, there are differences in the PPV and PES distribution characteristics across the pipe cross-section. The PPV is greater in the lower part of the pipe section, while the PES value is greater in the upper part of the pipe section. The maximum PES of 1.53 MPa is significantly lower than the safety threshold (≤4.6 MPa) at the hazardous-section-monitoring point. (4) A pipeline PPV prediction model is proposed to guide subsequent blasting program development. An empirical formula for the safety criterion applicable to this study is proposed for the scientific implementation of safety assessments for subsequent construction. This safety evaluation framework can be used as a reference for similar projects.

Vibration monitoring and analysis of strip rolling mill based on the digital twin model

A vibration monitoring method of strip rolling mill based on the digital twin model was proposed which could effectively reduce the structure complexity and test cost of the traditional monitoring system. Firstly, the coupling vibration mechanism model of the dynamic characteristics of roll system and bearings of four-high mill was established. Secondly, the digital twin model of strip rolling mill vibration was built based on the mechanism model. At the same time, the traditional monitoring test of the rolling mill was carried out to verify the accuracy of the digital twin model. Through analyzing the experimental results, it could be found that the roll system is vibrating intensely with the increase of rolling force obvious fluctuation. Finally, based on the above research results, the corresponding measures were put forward to suppress the rolling mill vibration. In conclusion, the rolling mill vibration monitoring theory based on the digital twin model provided the technical support and theoretical basis for improving equipment operation stability and reducing testing costs.

Study on the stability of high and steep slopes under deep bench blasting vibration in open-pit mines

In order to study the stability of the high and steep slope of an open-pit mine under deep bench blasting vibration, a mine in Inner Mongolia is taken as the engineering background, and the mechanical parameters of rock samples were determined based on uniaxial and triaxial instruments. The stability of the high and steep slope of the open-pit mine under static and dynamic loads was analyzed by using field vibration monitoring and numerical simulation methods. The results show that the vibration range of the vibration wave is -1.25–1.25 cm/s, and the vibration wave shows a gradual attenuation trend. The Sadovsky regression equation was used to analyze and fit the monitoring data and the corresponding regression equations in each direction were obtained. Under static action, the safety factor of the high and steep slope is 1.20, and the displacement of the sliding zone passing through the slope is small, so the slope stability is good. Under the action of dynamic blasting load, the overall displacement of the slope is small, and the change of displacement decreases with the decrease of the vibration wave.

A relative torsional vibration monitoring method for intelligent ships and associated error analysis

In this era of rapidly developing transport technology, shipping accounts for two thirds of the total international trade and transport industry. Nowadays, 'ship intelligence' is an important avenue to pursue in the development of the shipping industry and it requires ships and their working machinery to undergo real-time and high-precision inspection and diagnoses of their operational state. This paper develops a simple method for monitoring relative torsional vibration using multiple measuring points, which is suitable for the monitoring of intelligent ship rotating machinery. A proof-ofprinciple prototype is also designed to verify whether this calculational method can achieve clearer and more accurate physical significance and engineering practicability compared with the traditional single-point measuring method. According to the test results, under the condition of 100 pulses per revolution and at a speed of less than 3000 r/min, the relative error of speed measurement of the proof-of-principle prototype is within ±0.011%, which is close to the theoretical maximum accuracy of a 54 MHz sampling rate. The measurement result for the relative torsional angle shows that the maximum error is less than 0.17 mrad, the relative error is less than 1.75% and the maximum error in the amplitudes of the first and third harmonics is 9 mdeg. These accuracies are higher than those of the traditional method, which are 2.62% and 12 mdeg, respectively, in this study. Under the condition of speed fluctuations and rolling vibration, distortion occurs in the time-domain and frequency-domain torsional angle curves when the single-point measuring method is adopted. With the multi-point measuring method, much more accurate measurement values of the torsional angle are acquired compared with the single-point measuring method and accurate time-domain and frequency-domain curves are also obtained. Finally, the health status of the torsional angle is evaluated using an intelligent dynamic alarm system with a torsional vibration threshold, which has a better evaluation effect in line with the engineering practice and specification requirements. Therefore, this simple multi-point relative torsional vibration inspection method has universal applicability and wide application value.

Optimization and assessment of blade tip timing probe layout with concrete autoencoder and reconstruction error

Blade tip timing (BTT) is a promising non-contact measurement method for blade vibration monitoring. The limited number of probes leads to the inherent under-sampled problem of BTT signal. The quality of the analysis result of under-sampled signal depends on the probe layout. However, the application of existing probe layout optimization methods requires domain knowledge about blade vibration. Additionally, the lack of comparisons of probe layouts generated by different probe layout optimization methods makes it difficult to evaluate the performance of different methods. In this paper, we proposed a new probe layout optimization method based on a concrete autoencoder to reduce the reliance on the domain knowledge. The probe layouts were compared using an independently trained reconstructor in the time domain. And the spectral distance was defined to evaluate the performance of different probe layouts in the frequency domain. The validation results showed that the proposed method has superior time domain reconstruction performance and decent frequency domain reconstruction performance compared to other methods. The most informative and representative probe layout can be effectively selected by the proposed method.

Iot monitoring lathe machine performance

Machines have to operate effectively and free from faults in order to enhance productivity, increase quality, and decrease costs. With automated and flexible action, this is far more likely. An accurate identification of the underlying cause Causes of failure that need repairs and the time for restoration include: A lot of Various monitoring methods are available to track the experimentally-recorded machine health. Maintaining instruments and sensors. The vibration monitoring methods in this list. It is the right fit, and it has shown itself over time. Measuring vibrations in this job three different locations resembling the stock of a gun: headstock, tailstock. When conducting turning operation with mild steel, the tool post of the lathe machine is made of metal. Data that is gathered through sensors is sent straight to the cloud in this case, such as Ubidots IoT platform. via way of nodeMCU. Whether a task is impacted or a tool is impacted, mission failure has occurred. Thus, in either instance, early warning is provided by a signature, thus the development does not progress as quickly machining. If the tail-stock seems to be broken, and this appears to be a consistent problem, then the whole batch must be inspected for errors to be inspected closely is anything that has been created under such circumstances. An optimal decision-making procedure light may be thrown on CM so processes may be machine-wise instituted in a shop there. Tools while talking about lathes that are large, medium, or tiny. Overall it is a method which is easy but yet capable of benefitting people at all levels, from the absolute beginner to experts Floor productivity is aided by training elements that are almost unnecessary.

Vibration monitoring of wind turbine tower based on XGBoost

A tower vibration monitoring method based on XGBoost is proposed to predict the tower vibration trends under different operating conditions. Firstly, the wind turbine operating conditions are classified based on the Kmeans clustering algorithm. Secondly, the impact of state parameters of the wind turbine on the tower vibration is analyzed, and the tower vibration monitoring model is established based on XGBoost algorithm. Finally, the actual SCADA data of the wind farm is used to verify the proposed method. The results show that the vibration monitoring accuracy of tower is effectively improved by considering the operating conditions of the wind turbine.

Design of Vibration Frequency Method with Fine-Tuned Factor for Fault Detection of Three Phase Induction Motor

This research article focuses on industrial applications to demonstrate the characterization of current and vibration analysis to diagnose the induction motor drive problems. Generally, the induction motor faults are detected by monitoring the current and proposed fine-tuned vibration frequency method. The stator short circuit fault, broken rotor bar fault, air gap eccentricity, and bearing fault are the common faults that occur in an induction motor. The detection process of the proposed method is based on sidebands around the supply frequency in the stator current signal and vibration. Moreover, it is very challenging to diagnose the problem that occur due to the complex electromagnetic and mechanical characteristics of an induction motor with vibration measures. The design of an accurate model to measure vibration and stator current is analyzed in this research article. The proposed method is showing how efficiently the root cause of the problem can be diagnosed by using the combination of current and vibration monitoring method. The proposed model is developed for induction motor and its circuit environment in MATLAB is verified to perform an accurate detection and diagnosis of motor fault parameters. All stator faults are turned to turn fault; further, the rotor-broken bar and eccentricity are structured in each test. The output response (torque and stator current) is simulated by using a modified winding procedure (MWP) approach by tuning the winding geometrical parameter. The proposed model in MATLAB Simulink environment is highly symmetrical, which can easily detect the signal component in fault frequencies that occur due to a slight variation and improper motor installation. Finally, this research article compares the other existing methods with proposed method.

Vibration monitoring for composite structures using buckypaper sensors arrayed by flexible printed circuit

ABSTRACT Fiber-reinforced resin-based plastics are widely used in structural composites for aerospace and automotive applications, and they often face extreme load conditions in actual working environments. It is challenging to monitor the damage of the structure during the vibration process. This study was aimed at using buckypaper (BP) sensors to monitor the structural health status of composite structures under ambient vibrations. First, the feasibility of flexible printed circuit instead of wire is verified by the tensile experiment. Then the vibration monitoring experiment of the composite cantilever beam is carried out by using BP sensors systematically. The sweep frequency experiment determines the excitation frequency of the cantilever beam. Low-period vibration fatigue cycle and high-period vibration fatigue cycle experiments are designed to verify the vibration monitoring method using BP sensors. Besides, the signal response of BP sensors in the vibration experiment is analyzed, and the relationship between ΔR/R0 and vibration acceleration is obtained. Finally, through the change law of ΔR/R0 of the sensor, the cumulative damage caused by vibration fatigue is visualized. It is demonstrated that the monitoring method based on BP sensors can be applied to study the damage behavior of composite structure under the vibration environment. Abbreviations: FRP, fiber-reinforced resin-based plastics; SHM, structural health monitoring; SEM, scanning electron microscopic; FPC, flexible printed circuit; FBG, Fiber Bragg Grating; AE, acoustic emission.

Technology of Coal Seam Long Borehole Blasting and Comprehensive Evaluation Method of Pressure Relief Effect in High Rockburst Proneness Longwall Panel

On August 2, 2019, a catastrophic rockburst disaster occurred in Tangshan mine, causing death of 7 miners. After the investigation, the coal mine is facing reproduction. Taking the 0291 panel as the engineering background, this paper studies the coal seam blasting pressure relief and ground stress monitoring technology in working face retreat. During the roadway development and working face excavation, coal seam blasting was adopted to transfer the high ground stress of coal seam to the deep ground of the coal body. The blasting operation is presented in detail in this paper. In the working face retreat stage, drilling powder method, hydraulic shield resistance monitoring, roof displacement, and vibration monitoring methods are implemented. The results show that the pressure relief range of coal seam is 4–12 m in the coal mass after blasting. The shield working resistance is stable at 20–30 MPa. The range of relative displacement of the roof is about −1.0 to 2.5 mm, and the maximum vertical vibration velocity is in the range of 7–11 cm/s, up to 12 cm/s. The measured parameters are acceptable, so it is concluded that 0291 panel can be safely mined. This study provides a reference for the coal seam blasting design for rockburst coal mine and provides a technical means for the analysis of pressure release effect and dynamic pressure monitoring during working face retreating.

Simulation and experimental study of the blade vibration monitoring (BVM) method based on blade tip timing

Simulation and experimental study of the blade vibration monitoring (BVM) method based on blade tip timing

Field Test of Online Leakage Noise Monitoring for Pressure Water Pipeline

In order to study the applicability of leakage noise (vibration) monitoring method, an online leakage monitoring test was carried out on a large pipeline. In the test, the emptying valve on the pipeline was used to simulate the leakage point, and the vibration signal caused by leakage was monitored by the hydrophone and other floating cables installed in the pipeline. By controlling the opening degree of the emptying valve, the different degrees of leakage between 10L/s and 105L/s was simulated, and the monitoring data for 10 minutes were recorded from 5 minutes before valve opening. The analysis results of the test data showed that although the environmental background of the monitoring was very disturbing, the leakage could be detected when the leakage degree was more than 0.05% of the pipeline flow. The monitoring results also showed that the noise caused by the leakage of large buried water pipelines was mainly transmitted in the form of vibration along the soil around the pipeline.