Real-time Vibration Monitoring Research Articles

Cooperation mechanism between the vacuum levels and interface dipole energy of triboelectric materials for real-time vibration recognition

Triboelectric Nanogenerator (TENG) device, acting as sensors of energy harvesting and material identification, are attracting intensive attention. Nevertheless, vibration wave recognition cannot be achieved by the developed devices owing to device structure and working mechanism limitations. Here, a cooperation mechanism between the vacuum level and interface dipole energy of triboelectric materials is proposed to explore triboelectric charge generation and migration. Hence, metallized cottons of high specific surface area encapsulated by polydimethylsiloxane (PDMS) of low elastic modulus are developed as TENG-based sensors to realize vibration recognition. The results indicate electrons flow from PDMS to metallized cotton with the generation of an extremely thin interfacial dipole barrier layer because the vacuum level of metallized cotton is higher than that of PDMS, resulting in the accumulation of triboelectric charges on the PDMS surface under vibration, further leading to generating distinct triboelectric signals that can be simply differentiated using signal amplitude or peak shape with 98.3% recognition accuracy for vibration waveform. Besides, combined with the deep machine learning and triboelectric effect, a vibration perception system integrated with a TENG-based sensor, data processing and display modules is also developed for real-time vibration monitoring. This work contributes to further clarifying the theoretical mechanisms of triboelectric charge excitation under vibration.

Cooperation mechanism between the vacuum levels and interface dipole energy of triboelectric materials for real-time vibration recognition

Triboelectric Nanogenerator (TENG) device, acting as sensors of energy harvesting and material identification, are attracting intensive attention. Nevertheless, vibration wave recognition cannot be achieved by the developed devices owing to device structure and working mechanism limitations. Here, a cooperation mechanism between the vacuum level and interface dipole energy of triboelectric materials is proposed to explore triboelectric charge generation and migration. Hence, metallized cottons of high specific surface area encapsulated by polydimethylsiloxane (PDMS) of low elastic modulus are developed as TENG-based sensors to realize vibration recognition. The results indicate electrons flow from PDMS to metallized cotton with the generation of an extremely thin interfacial dipole barrier layer because the vacuum level of metallized cotton is higher than that of PDMS, resulting in the accumulation of triboelectric charges on the PDMS surface under vibration, further leading to generating distinct triboelectric signals that can be simply differentiated using signal amplitude or peak shape with 98.3% recognition accuracy for vibration waveform. Besides, combined with the deep machine learning and triboelectric effect, a vibration perception system integrated with a TENG-based sensor, data processing and display modules is also developed for real-time vibration monitoring. This work contributes to further clarifying the theoretical mechanisms of triboelectric charge excitation under vibration.

Cat paw-inspired magnetorheological elastomer embedded mechanical metamaterials with active sensing and switching stiffness for vibration isolator

Real-time vibration monitoring, assessment, and isolation play critical roles in the safety and maintenance of engineering industries and traffic facilities. Recently, magnetorheological elastomers (MRE) with tunable stiffness have been considered promising solutions for vibration isolation. However, for some heavy-load conditions, such as motors or machine tools, MRE vibration isolators are insufficient for realizing vibration sensing and high bearing capacity. Therefore, it is critical to design a novel MRE isolator system that enables real-time vibration monitoring, isolation, and bearing capacity. Herein, we propose a cat's paw-inspired oct-MRE vibration isolator coupled with a soft MRE for energy buffering embedded in octet metamaterials to support the load. For vibration sensing, a sliding triboelectric nanogenerator (TENG) was constructed using polytetrafluoroethylene (PTFE) and a copper foil around the oct-MRE inside a vibration isolator to monitor and evaluate the vibration state in real-time. Experimental tests show that our all-in-one vibration isolator can monitor motor vibration accurately and actively modulate it under resonant conditions, the vibration acceleration can be reduced from 17.0 m/s2 to 12.9 m/s2. This study provides an ideal solution for intelligent health monitoring of motors and other autonomous, smart, and long-term engineering tasks.

MFD: Multi-object Frequency Feature Recognition and State Detection Based on RFID-single Tag

Vibration is a normal reaction that occurs during the operation of machinery and is very common in industrial systems. How to turn fine-grained vibration perception into visualization, and further predict mechanical failures and reduce property losses based on visual vibration information, which has aroused our thinking. In this article, the phase information generated by the tag is processed and analyzed, and MFD is proposed, a real-time vibration monitoring and fault-sensing discrimination system. MFD extracts phase information from the original RF signal and converts it into a Markov transition map by introducing White Gaussian Noise and a low-pass filter for denoising. To accurately predict the failure of machinery, a deep and machine learning model is introduced to calculate the accuracy of failure analysis, realizing real-time monitoring and fault judgment. The test results show that the average recognition accuracy of vibration can reach 96.07%, and the average recognition accuracy of forward rotation, reverse rotation, oil spill, and screw loosening of motor equipment during long-term operation can reach 98.53%, 99.44%, 97.87%, and 99.91%, respectively, with high robustness.

Design and development of SiteHive MEMS based system for real-time vibration monitoring

Construction projects need to proactively manage their works that may cause vibration impacts to nearby structures and stakeholders. Risks of vibration include cosmetic and structural damage to buildings and threats to human comfort. The advent of MEMS accelerometers offers significant opportunities to improve on traditional vibration monitoring practices based on geophones. Geophones measure velocity which preclude acceleration based measurements and calculations like vibration dose value (the measure for human comfort), groundborne noise, and auto-levelling. The inability to capture these results means additional monitoring devices are required to capture all key measurements. MEMS-based vibration monitoring systems can be much cheaper, smaller, and more power efficient than traditional vibration monitoring systems. This enables easier installation, greater mobility, and more monitoring to be conducted. SiteHive has worked extensively with the National Measurement Institute (NMI) and the University of Technology Sydney (UTS) to test and validate the efficacy of the MEMS-based accelerometers and develop a calibration system for MEMS-based devices. This paper will outline the design research and findings that have gone into this development, results from field testing, and details on the value offered by this innovation.

Experimental study and comparative analysis of pitting fault in spur gear system

This paper uses a dynamic six-degree-of-freedom model that considers torsional and lateral motions to predict the impact of pitting on vibration parameters in a spur gearbox for various operating speeds and torque loads. The study examines the dynamic characteristics of a gearbox with localized pitting damage on a single gear tooth using theoretical and experimental approaches. The research analyzes the forced vibrations of a single-stage spur gear system with pitting damage, which includes variations in mesh stiffness, damping, and gear error excitation, to identify symptoms of default. The equation of motion for the rotary gearbox system is established using the Lagrangian method in tandem with Short-Time Fourier Transform (STFT) and frequency-RPM map fault diagnosis. During real-time vibration monitoring, vibration signals are captured via accelerometers and processed in both the time and frequency domains using the LabVIEW data acquisition signal processing package to extract diagnostic information. The experimental findings demonstrate how vibration analysis combined with time-frequency processing can recognize machine conditions even in harsh operational conditions. Moreover, the experimental results indicate a significant similarity with the theoretical analysis and validate the effectiveness of the RPM frequency technique-based pitting detection method, which can be an asset in gear fault monitoring.

Time-Domain Structural Damage and Loss Estimates for Wind Loads: Road to Resilience-Targeted and Smart Buildings Design

A time-domain wind-induced damage evaluation for the risk- and resilience-targeted design of building structures requires nonlinear dynamic analysis (NDA) solvers to handle long duration input loads. Moreover, post-construction damage identification based on real-time vibration monitoring depends on accurate damage simulation from the design stage and available artificial intelligence (AI)-based technology. In this paper, an integrated time-domain approach for the performance-based analysis and design for wind is presented. The nonlinear dynamic analysis (NDA) is performed with the Force Analogy Method (FAM) and the state–space formulation to solve the nonlinear equations of motion. Then, the Incremental Dynamic Analysis (IDA) is used to perform probabilistic fragility analyses for a typical reinforced concrete (RC) frame structure. The analysis also provides estimates of expected losses, gives the building owners business support data to compare, e.g., the final annual building income (FABI), the cost of repair and the function recovery duration for various wind events in an integrated resilience-based building design framework. This provides the basis for mapping structural damage on large urban scales and for straightforward quantification of wind-induced damage from available response acceleration time-series acquired from real-time vibration monitoring.

Real-Time Vibration Visualization Using GPU-Based High-Speed Vision

In this study, we developed a real-time vibration visualization system that can estimate and display vibration distributions at all frequencies in real time through parallel implementation of subpixel digital image correlation (DIC) computations with short-time Fourier transforms on a GPU-based high-speed vision platform. To help operators intuitively monitor high-speed motion, we introduced a two-step framework of high-speed video processing to obtain vibration distributions at hundreds of hertz and video conversion processing for the visualization of vibration distribution at dozens of hertz. The proposed system can estimate the full-field vibration displacements of 1920 × 1080 images in real time at 1000 fps and display their frequency responses in the range of 0–500 Hz on a computer at dozens of frames per second by accelerating phase-only DICs for full-field displacement measurement and video conversion. The effectiveness of this system for real-time vibration monitoring and visualization was demonstrated by conducting experiments on objects vibrating at dozens or hundreds of hertz.

A self-powered vibration sensor based on the coupling of triboelectric nanogenerator and electromagnetic generator

Vibration sensor that relies on the mechanical vibration of machinery to monitor its operational stability for the purpose of preventing mechanical failure and reducing the loss of life and property is of desired practical significance. Here, we propose a self-powered mechanical vibration sensor based on the coupling of electromagnetic generator (EMG) for energy harvesting and triboelectric nanogenerator (TENG) for active sensing. For EMG, a magnetic levitation system has been established that can easily respond to tiny external mechanical vibration, and the rationally designed voltage amplifier rectifier circuit as well as corresponding energy storage unit can effectively collect and store mechanical vibration energy. Furthermore, a pendulum-shaped single-electrode mode TENG can respond to vibration in the orthogonal direction and activate the pulse trigger circuit with high sensitivity. The cooperation of the two modules can realize real-time vibration monitoring and alarm signal transmission. The multi-mechanism coupled self-powered vibration sensor reported here can be applied to many scenarios, such as conveyor belt, high-speed train, and freight elevator.

Multi-channel monitoring data compression method for industrial robot based on compressed sensing

To address the problems of considerable redundancy and weak transmission security of multi-channel real-time vibration monitoring data of industrial robots, in this research a compressed sensing (CS)-based method to compress multi-channel industrial robot monitoring data has been proposed. Firstly, the multi-sensor data of the robot is fused into a comprehensive signal by the cross-correlation function fusion algorithm, which can significantly reduce the signal redundancy among sensors and improve the signal quality. Then, the discrete cosine transform matrix is used for sparse decomposition analysis of the synthetic signal. Finally, CS technology and chaotic matrix are used to encrypt and compress the integrated signal to achieve efficient encryption transmission. The experimental results show that the method can significantly reduce the amount of data transmitted and enhance the encryption performance during transmission without sacrificing helpful information and ensuring signal transmission efficiency and security.

A Torsional Vibration Measurement Method for Rotating Blades Based on Blade Tip Timing

During the working process of the turbine, some types of faults can cause changes in the vibration characteristics of the blades. The real-time vibration monitoring of the blades is of great significance to the stable operation and state-based maintenance. Torsional vibration is a kind of blade vibration modes and results in failures such as cracks easily. Thus, it is important to measure it due to the harmfulness of torsional vibration. Firstly, the principle of blade tip timing (BTT) is introduced, and the models of the blade are built to analyze the characteristics of torsional vibration. Then, the compressed sensing theory is introduced, and its related parameters are determined according to the measurement requirements. Next, based on the condition that the blade rigidity axis is not bent and bent, respectively, the layout method of sensors is proposed and the numerical simulation of the measurement process is performed. The results of the above two types of numerical simulation verify the proposed measurement method. Finally, by analyzing the influencing factors of measurement uncertainty, the optimization method of sensors’ layout is further proposed. This study can provide important theoretical guidance for the measurement of blade torsional vibration.

Hybrid Edge–Cloud-Based Smart System for Chatter Suppression in Train Wheel Repair

The contact profile of a train wheel has a key role in its operation performance. Rolling smoothly and with reduced resistance results in an increase in the efficiency and safety of rail transport. The original shape and dimensions of the profile of the wheel are altered under operation of the train, especially due to braking events and the presence of external objects between the wheel and the railway. With the purpose of recovering the optimum contact profile, train wheels are periodically machined using special lathes. This repair operation is particularly critical in freight trains, which are only reshaped a few times throughout their service life and, therefore, high depths of cut are required to recover the wheel in a productive way. As the presence of chatter vibrations limits the productivity of these operations, a hybrid edge–cloud computing approach has been developed for chatter vibration suppression. An expert system based on automatic chatter detection and suppression has been developed in the edge. The expert system is based on continuous real-time vibration monitoring and combines continuous spindle speed variation (CSSV) and cutting speed reduction to suppress chatter. Cloud computing is used to extract wheel profile machining fingerprints and obtain insights from multiple aggregated machined wheels. An industrial implementation of the system is described in the present work.

Study of a Space-Time Monitoring of High-Speed Railway Underline Structure Using Distributed Optical Vibration Sensing Technology

The phenomenon of vibration is quite frequent in various engineering works. Vibration analysis and monitoring occupy a significant place in scientific measurements and engineering applications. The quality of the underline structure actively influences the response of high-speed railway track plate and trackside. Due to years of service and under the action of train loads, bond failure between supporting track plate and cement asphalt mortar layer will imminently occur. And this will significantly influence the vertical dynamic response of a track slab and severely affect the safe operation of the entire railway system which can subsequently lead to a risk of derailment. Firstly, the purpose of the present study is to develop a practical 2D dynamic interaction model of vehicle-track subgrade based on a two-step simulation capable of analyzing the dynamic response of a track slab under different fault distribution in the CA mortar layer by using the commercial software Abaqus. Secondly, the distributed optical vibration sensing (DOVS) technology is discussed and applied on a section of high-speed railway near the Hongqiao station which has been in operation after a long period of degradation for real-time vibration monitoring. Overall, the numerical simulation results show that, in the elastic field, the track plate defects have a significant amplification effect on the vibration, and the magnification can be more than 2 to 3 times. The vibration monitoring results reveal two elements of the fault effects on the track slab dynamic response: the amplification of the dynamic response when the train is arriving and leaving the monitoring section and also causing extreme resonance when the train is passing increasing the vibration signal largely.

Perceptual Vibration Hashing by Sub-Band Coding: An Edge Computing Method for Condition Monitoring

High data throughput during real-time vibration monitoring can easily lead to network congestion, insufficient data storage space, heavy computing burden, and high communication costs. As a new computing paradigm, edge computing is deemed to be a good solution to these problems. In this paper, perceptual hashing is proposed as an edge computing form, aiming not only to reduce the data dimensionality but also to extract and represent the machine condition information. A sub-band coding method based on wavelet packet transform, two-dimensional discrete cosine transform, and symbolic aggregate approximation is developed for perceptual vibration hashing. When the sub-band coding method is implemented on a monitoring terminal, the acquired kilobyte-long vibration signal can be transformed into a machine condition hash occupying only a few bytes. Therefore, the efficiency of condition monitoring can benefit from the compactness of the machine condition hash, while comparable diagnostic and prognostic results can still be achieved. The effectiveness of the developed method is verified with two benchmark bearing datasets. Considerations on practical condition monitoring applications are also presented.

MONITORING OF VIBRATIONS FOR THE CONSERVATION OF CULTURAL HERITAGE：THE CASE OF THE SUMMER PALACE IN BEIJING

Abstract. In order to research the influence of the environmental vibration and the protection of the architectural heritage, CMG-5TCDE accelerometer was used to obtain the real-time vibration monitoring data of the Grand Stage in the Garden of Virtuous Harmony in Summer Palace. This paper employs the control variable method and the multivariate statistical analysis, integrating monitoring statistics with wind speed and transportation observation statistics to make interrelated analysis, in order to study the response rules and impact degree of the Grand Stage under the environmental vibration impact. The analyses of the vibration monitoring statistic of the recent two years show that the vibration acceleration of the Grand Stage is below 10mm/s2, which is remarkable related with factors such as visitors flow rate, transportation and weather.

Real-Time Distributed Vibration Monitoring System Using $\Phi$ -OTDR

The purpose of this paper is to theoretically analyze and experimentally demonstrate the investigation on a distributed optical fiber sensor based on phase-sensitive optical time domain reflectometry ( $\Phi $ -OTDR) for real-time vibration monitoring with different signal processing methods. The $\Phi $ -OTDR system is investigated in two aspects: the hardware parameter and the interrogation scheme. The effect of pulsed light power that enters into the sensing fiber on $\Phi $ -OTDR is first discussed. Then, two systems based on the differential method and the Prewitt edge detection method applied for $\Phi $ -OTDR are presented for 1-D and 2-D vibration location, respectively. Finally, a high-speed acquisition system based on FPGA is applied to realize the 3-D real-time vibration monitoring. This new distributed vibration sensor can be used as an ideal source for the third-party intrusion identification, pipeline monitoring, and ultrasonic wave detection in explosive environment.

국민안전처 통합관리시스템 연계 가능한 시설물 진동 감지 및 분석 시스템 개발

A frequency of earthquake occurrence in the Republic of Korea is increasing over the past few decades. In this situation, an importance of earthquake prevention comes to the fore because the earthquake does damage to structures and causes severe damage of human life. For the earthquake prevention, a real-time vibration measurement for structures is important. As an example, the United States of America and Japan have already been monitoring real-time earthquake acceleration for the important structures and the measured acceleration data has been managed by forming database. This database could be used for revising the seismic design specifications or predicting the damage caused by earthquake. In Korea, Earthquake Recovery Plans Act and Enforcement Regulations are revised and declared lately. Ministry of Public Safety and Security is constructing a integrated management system for the measured earthquake acceleration data. The purpose of this research is to develop a real-time vibration monitoring and analysis system for structures which links to the integrated management system. The developed system contains not only a monitoring function to show real-time acceleration data but also an analysis system to perform fast fourier transform, to obtain natural frequency and earthquake magnitude, to show response spectrum and power spectrum, and to evaluate structural health. Additionally, this system is designed to be able to link to the integrated management system of Ministry of Public Safety and Security. It is concluded that the developed system can be useful to build a safety management network, minimize maintenance cost of structures, and prevention of the structural damage due to earthquake.

Integrated active sensor system for real time vibration monitoring.

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

Vibration Sensor Based Intelligent Fault Diagnosis System for Large Machine Unit in Petrochemical Industries

Fault diagnosis is an area which is gaining increasing importance in rotating machinery. Along with the continuous advance of science and technology, the structures of rotating machinery become increasingly of larger scale and higher speed and more complicated, which result in higher probability of various failure in practice. In case one of the most critical components of machinery or equipment breaks down, it cannot only cause enormous economic loss, but also easily cause the loss of many people's lives. It is important to enable reliable, safe, and efficient operation of large-scale and critical rotating machinery, which requires us to achieve accurate and fast diagnosis of fault which has occurred. Aiming at dynamic real-time vibration monitoring and vibration signal analysis for large machine unit in petrochemical industry, which cannot realize real-time, online, and fast fault diagnosis, an intelligent fault diagnosis system using artificial immune algorithm and dimensionless parameters is developed in this paper, innovated with a focus on reliability, remote monitoring, and practicality and applied to the third catalytic flue gas turbine in a petrochemical enterprise, with good effects.

Modeling and Prediction Using Regression, ANN and Fuzzy Logic of Real Time Vibration Monitoring on Lathe Machine in Context of Machining Parameters

Modeling and Prediction Using Regression, ANN and Fuzzy Logic of Real Time Vibration Monitoring on Lathe Machine in Context of Machining Parameters