Vibration Analysis at Castello Ursino Picture Gallery (Sicily, Italy) for the Implementation of Self-Generating AlN-MEMS Sensors.

This work explores the potential of self-powered MEMS devices for application in the preventive conservation of cultural heritage. The main objective is to evaluate the effectiveness of piezoelectric aluminum nitride MEMS (AlN-MEMS) for monitoring vibrations and to investigate its potential for harvesting energy from vibrations, including those induced by visitors. A preliminary laboratory comparison was conducted between AlN-MEMS and the commercial device Tromino®. The study was then extended to the Picture Gallery of Ursino Castle, where joint measurements with the two devices were carried out. The analysis focused on identifying natural frequencies and vibrational energy levels by key metrics, including spectral peaks and the Power Spectral Density (PSD). The results indicated that the response of the AlN-MEMS aligned well with the data collected by the commercial device, especially observing high vibrational energy around 100 Hz. Such results validate the potential of AlN-MEMS for effective vibration measurement and for converting kinetic energy into electrical power, thereby eliminating the need for external power sources. Additionally, the vibrational analysis highlighted specific locations, such as the measurement point Cu4, as exhibiting the highest vibrational energy levels. These points could be used for placing MEMS sensors to ensure efficient vibration monitoring and energy harvesting.

Modulus-Modulated All-Organic Core-Shell Nanofiber with Remarkable Piezoelectricity for Energy Harvesting and Condition Monitoring.

The low piezoelectricity of piezoelectric polymers significantly restricts their applications. Introducing inorganic fillers can slightly improve the piezoelectricity of polymers, whereas it is usually at the cost of flexibility and durability. In this work, using a modulus-modulated core-shell structure strategy, all-organic nanofibers with remarkable piezoelectricity were designed and prepared by a coaxial electrospinning method. It was surprisingly found that the introduction of a nonpiezoelectric polymeric core (e.g., polycarbonate, PC) can result in 110% piezoelectric coefficient (d33) enhancement in a poly(vinylidenefluoride-co-trifluoroethylene) (PVDF-TrFE) nanofiber. Accordingly, the all-organic PVDF-TrFE@PC core-shell nanofiber exhibits record-high energy-harvesting performance (i.e., 126 V output voltage, 710 mW m-2 power density) among the reported organic piezoelectric materials. In addition, the excellent sensing capability of the core-shell nanofiber enabled us to develop a wireless vibration monitoring and analyzing system, which realizes the real-time vibration detection of a power transformer.

The Great Wall Vibration Monitoring of Traffic and Natural Hazards Using MEMS Accelerometers.

The stability of the Great Wall is mainly affected by traffic vibrations and natural hazards, such as strong winds, heavy rainfall, and thunderstorms, which are extremely harmful to the safety of the Great Wall. To determine the impact of the above factors on the Great Wall, a comparative analysis based on MEMS (micro-electro-mechanical system) accelerometer data was conducted between the non-impacts and the impacts of the above factors. An analysis of the relationship between vibration acceleration and each potential hazard based on a visual time series chart was presented using the data of accelerometers, traffic video, meteorology, rainfall, and wind. According to the results, traffic vibration is one of the primary dangerous factors affecting the stability of the Great Wall, Moreover, the intensity of the vibrations increases with the traffic flow. Thunderstorms also influence the stability of the Great Wall, with enhanced thunderstorm excitation resulting in increased vibration displacement. Furthermore, wind load is an influencing factor, with average wind speeds greater than 9 m/s significantly affecting the stability of the Great Wall. Rainfall has no impact on the stability of the Great Wall in the short term. This research can provide important guidance for risk assessment and protection of the Great Wall.

Motion Magnification Applications for the Protection of Italian Cultural Heritage Assets.

In recent years, the ENEA has introduced a novel methodology based on motion magnification (MM) into the Italian cultural heritage protection and monitoring field. It consists of a digital video signal processing technique able to amplify enormously the tiny movements recorded in conventional videos, while preserving the general topology of the acquired frames. Though the idea of such a methodology is not new, it has recently been provided with an efficient algorithm that makes possible a viable and low-cost magnification. Applications are extremely varied in almost every field of science and technology; however, we are interested in its application to the safeguarding of architectural heritage, a sector of the utmost importance for Italy. As ancient buildings can be extremely sensitive to even minimally invasive instrumentation, most common monitoring sensors can be replaced by contactless tools and methods, such as video-based techniques like MM. It offers many advantages: easy to use, contactless devices, virtual sensors, reusability of the videos, practicality, intuitive graphical results, quantitative analyses capability and low costs. These characteristics are well suited to the monitoring of large ancient monuments; on the other hand, historical sites have peculiarities of their own, requiring careful approaches, proper tools and trained personnel. Moreover, outdoor applications of MM present quite notable difficulties from a practical point of view, e.g., the dimensions of the studied objects, uncontrolled environmental conditions, spurious vibrations, lighting change/instability, etc. Here we give a general idea of the potential of MM and related issues, using some relevant in-the-field case studies in Italian heritage protection.

Design and Evaluation of Low-Cost Vibration-Based Machine Monitoring System for Hay Rotary Tedder.

Vibration monitoring provides a good-quality source of information about the health condition of machines, and it is often based on the use of accelerometers. This article focuses on the use of accelerometer sensors in fabricating a low-cost system for monitoring vibrations in agricultural machines, such as rotary tedders. The aim of the study is to provide useful data on equipment health for improving the durability of such machinery. The electronic prototype, based on the low-cost AVR microcontroller ATmega128 with 10-bit ADC performing a 12-bit measurement, is able to acquire data from an accelerometer weighing up to 10 g. Three sensors were exposed to low accelerations with the use of an exciter, and their static characteristics were presented. Standard experimental tests were used to evaluate the constructed machine monitoring system. The self-contained prototype system was calibrated in a laboratory test rig, and sinusoidal and multisinusoidal excitations were used. Measurements in time and frequency domains were carried out. The amplitude characteristic of the preformed system differed by no more than 15% within a frequency range of 10 Hz-10 kHz, compared to the AVM4000 commercial product. Finally, the system was experimentally tested to measure acceleration at three characteristic points in a rotational tedder, i.e., the solid grease gearbox, the drive shaft bearing and the main frame. The RMS amplitude values of the shaft vibrations on the bearing in relation to the change in the drive shaft speed of two tedders of the same type were evaluated and compared. Additionally, the parameters of kurtosis and crest factor were compared to ascertain the bearing condition.

Performance Evaluation of an IoT Sensor Node for Health Monitoring of Artwork and Ancient Wooden Structures.

In this paper, an IoT sensor node, based on smart Bluetooth low energy (BLE), for the health monitoring of artworks and large wooden structures is presented. The measurements from sensors on board the node are collected in real-time and sent to a remote gateway. The sensor node allows for the monitoring of environmental parameters, in particular, temperature and humidity, with accurate and robust integrated sensors. The developed node also embeds an accelerometer, which also allows other mechanical quantities (such as tilt) to be derived. This feature can be exploited to perform structural monitoring, exploiting the processing of data history to detect permanent displacements or deformations. The node is triggered by acceleration transients; therefore, it can also generate alarms related to shocks. This feature is crucial, for instance, in the case of transportation. The developed device is low-cost and has very good performance in terms of power consumption and compactness. A reliability assessment showed excellent durability, and experimental tests proved very satisfactory robustness against working condition variations. The presented results confirm that the developed device allows for the realization of pervasive monitoring systems, in the context of the IoT paradigm, with sensor nodes devoted to the monitoring of each artwork present in a museum or in a church.

Long-Range Low-Power Multi-Hop Wireless Sensor Network for Monitoring the Vibration Response of Long-Span Bridges.

Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations.

A Medium-Frequency Fiber Bragg Grating Accelerometer Based on Flexible Hinges.

Mediumfrequency fiber Bragg grating (FBG) acceleration sensors are used in important applications in mechanical, aerospace and weapon equipment, and have strict requirements in terms of resonance frequency and sensitivity. A novel medium-frequency accelerometer, based on fiber Bragg grating and flexible hinges, is proposed in this paper. The differential structure doubles the sensitivity of the sensor while avoiding temperature effects. The structure model and principle for the sensor are introduced, the sensor's sensing characteristics are theoretically analyzed, and the structure parameters for the sensor are determined through numerical analysis. The sensing experiments show that the resonance frequency of the sensor is approximately 2800 Hz, the sensitivity is 21.8 pm/g in the flat frequency range of 50-1000 Hz, and the proposed sensor has a good temperature self-compensation function and lateral anti-interference capability.

Interoperable Nanoparticle Sensor Capable of Strain and Vibration Measurement for Rotor Blade Monitoring.

Recent advances in nanomaterials technology create the new possibility to fabricate high performance sensors. However, there has been limitations in terms of multivariate measurable and interoperable sensors. In this study, we fabricated an interoperable silver nanoparticle sensor fabricated by an aerodynamically focused nanomaterial (AFN) printing system which is a direct printing technique for inorganic nanomaterials onto a flexible substrate. The printed sensor exhibited the maximum measurable frequency of 850 Hz, and a gauge factor of 290.62. Using a fabricated sensor, we evaluated the sensing performance and demonstrated the measurement independency of strain and vibration sensing. Furthermore, using the proposed signal separation algorithm based on the Kalman filter, strain and vibration were each measured in real time. Finally, we applied the printed sensor to quadrotor condition monitoring to predict the motion of a quadrotor.

Design and Validation of Android Smartphone Based Wireless Structural Vibration Monitoring System.

Vibration monitoring is one of crucial functions of structural health monitoring (SHM) systems. Traditional structural vibration monitoring usually relies on specialized sensors, data transmission and acquisition equipment, which are expensive and may not be easily available in urgently needed situations like post-disaster structural evaluation. Therefore, developing an affordable and efficient structural vibration monitoring technique becomes an important topic in SHM research. In this paper, the authors developed an android system APP that can easily convert multiple android smartphones into a wireless structural vibration monitoring system. To make the designed system reliable and easy to use, the server/client architecture is adopted. One smartphone is designated as the serve of the system to remotely control all other smartphones, which function as sensors to measure structural vibration. An efficient method is proposed herein to establish the smartphone-based structural vibration monitoring network, allowing the server smartphone to quickly and easily connect multiple sensor smartphones to form the wireless network for structural vibration monitoring. Additionally, a synchronization method is also proposed to synchronize different smartphones for simultaneously measuring structural vibration. To verify the time synchronization accuracy of the developed system, an experiment is designed and conducted. Moreover, a new analysis method of the time synchronization accuracy is also proposed, which verifies that the designed smartphone-based monitoring can achieve the millisecond-level time synchronization accuracy. Finally, a shaking table experiment is conducted on a three-story bench-scale structural model, the results of which demonstrate that the designed smartphone-based wireless structural vibration monitoring system can quite accurately identify the modal parameters of the tested structure.

On a Sensor Placement Methodology for Monitoring the Vibrations of Horizontally Excited Ground.

In this paper, the problem of optimal sensor arrangement during vibration monitoring is analysed. The wave propagation caused by horizontal excitation is investigated to predict the areas of the largest ground and structure response. The equations of motion for a transversally isotropic elastic medium with appropriate absorbing boundary conditions are solved using the finite element method (FlexPDE software). The possibility of an amplified soil medium response is examined for points located on the ground surface and at various depths. The results are presented in the form of a dimensionless vibration reduction factor, defined as the ratio of the peak particle velocity observed at the selected depth to the corresponding value observed at the ground surface. Significant amplifications (≈50%) can be observed below the ground surface, especially in the case of a weak layer below a stiff layer. The effect of vibration amplification is most significant near the boundary surface of two layers. For the points located on the ground surface, the greatest peak particle velocities are observed in the direction perpendicular to the load direction. However, the greatest vertical velocity component at the ground surface is observed in front of the applied force.

Low Frequency Vibration Visual Monitoring System Based on Multi-Modal 3DCNN-ConvLSTM.

Low frequency vibration monitoring has significant implications on environmental safety and engineering practices. Vibration expressed by visual information should contain sufficient spatial information. RGB-D camera could record diverse spatial information of vibration in frame images. Deep learning can adaptively transform frame images into deep abstract features through nonlinear mapping, which is an effective method to improve the intelligence of vibration monitoring. In this paper, a multi-modal low frequency visual vibration monitoring system based on Kinect v2 and 3DCNN-ConvLSTM is proposed. Microsoft Kinect v2 collects RGB and depth video information of vibrating objects in unstable ambient light. The 3DCNN-ConvLSTM architecture can effectively learn the spatial-temporal characteristics of muti-frequency vibration. The short-term spatiotemporal feature of the collected vibration information is learned through 3D convolution networks and the long-term spatiotemporal feature is learned through convolutional LSTM. Multi-modal fusion of RGB and depth mode is used to further improve the monitoring accuracy to 93% in the low frequency vibration range of 0-10 Hz. The results show that the system can monitor low frequency vibration and meet the basic measurement requirements.

Developing IoT Sensing System for Construction-Induced Vibration Monitoring and Impact Assessment.

Construction activities often generate intensive ground-borne vibrations that may adversely affect structure safety, human comfort, and equipment functionality. Vibration monitoring systems are commonly deployed to assess the vibration impact on the surrounding environment during the construction period. However, traditional vibration monitoring systems are associated with limitations such as expensive devices, difficult installation, complex operation, etc. Few of these monitoring systems have integrated functions such as in situ data processing and remote data transmission and access. By leveraging the recent advances in information technology, an Internet of Things (IoT) sensing system has been developed to provide a promising alternative to the traditional vibration monitoring system. A microcomputer (Raspberry Pi) and a microelectromechanical systems (MEMS) accelerometer are adopted to minimize the system cost and size. A USB internet dongle is used to provide 4G communication with cloud. Time synchronization and different operation modes have been designed to achieve energy efficiency. The whole system is powered by a rechargeable solar battery, which completely avoids cabling work on construction sites. Various alarm functions, MySQL database for measurement data storage, and webpage-based user interface are built on a public cloud platform. The architecture of the IoT vibration sensing system and its working mechanism are introduced in detail. The performance of the developed IoT vibration sensing system has been successfully validated by a series of tests in the laboratory and on a selected construction site.

In Situ Diagnosis of Industrial Motors by Using Vision-Based Smart Sensing Technology.

This study uses machine vision, feature extraction, and support vector machine (SVM) to compose a vibration monitoring system (VMS) for an in situ evaluation of the performance of industrial motors. The vision-based system respectively offers a spatial and temporal resolution of 1.4 µm and 16.6 ms after the image calibration and the benchmark of a laser displacement sensor (LDS). The embedded program of machine vision has used zero-mean normalized correlation (ZNCC) and peak finding (PF) for tracking the registered characteristics on the object surface. The calibrated VMS provides time-displacement curves related to both horizontal and vertical directions, promising remote inspections of selected points without attaching additional markers or sensors. The experimental setup of the VMS is cost-effective and uncomplicated, supporting universal combinations between the imaging system and computational devices. The procedures of the proposed scheme are (1) setting up a digital camera, (2) calibrating the imaging system, (3) retrieving the data of image streaming, (4) executing the ZNCC criteria, and providing the time-displacement results of selected points. The experiment setup of the proposed VMS is straightforward and can cooperate with surveillances in industrial environments. The embedded program upgrades the functionality of the camera system from the events monitoring to remote measurement without the additional cost of attaching sensors on motors or targets. Edge nodes equipped with the image-tracking program serve as the physical layer and upload the extracted features to a cloud server via the wireless sensor network (WSN). The VMS can provide customized services under the architecture of the cyber-physical system (CPS), and this research offers an early warning alarm of the mechanical system before unexpected downtime. Based on the smart sensing technology, the in situ diagnosis of industrial motors given from the VMS enables preventative maintenance and contributes to the precision measurement of intelligent automation.

Reconstructed Order Analysis-Based Vibration Monitoring under Variable Rotation Speed by Using Multiple Blade Tip-Timing Sensors.

On-line vibration monitoring is significant for high-speed rotating blades, and blade tip-timing (BTT) is generally regarded as a promising solution. BTT methods must assume that rotating speeds are constant. This assumption is impractical, and blade damages are always formed and accumulated during variable operational conditions. Thus, how to carry out BTT vibration monitoring under variable rotation speed (VRS) is a big challenge. Angular sampling-based order analyses have been widely used for vibration signals in rotating machinery with variable speeds. However, BTT vibration signals are well under-sampled, and Shannon's sampling theorem is not satisfied so that existing order analysis methods will not work well. To overcome this problem, a reconstructed order analysis-based BTT vibration monitoring method is proposed in this paper. First, the effects of VRS on BTT vibration monitoring are analyzed, and the basic structure of angular sampling-based BTT vibration monitoring under VRS is presented. Then a band-pass sampling-based engine order (EO) reconstruction algorithm is proposed for uniform BTT sensor configuration so that few BTT sensors can be used to extract high EOs. In addition, a periodically non-uniform sampling-based EO reconstruction algorithm is proposed for non-uniform BTT sensor configuration. Next, numerical simulations are done to validate the two reconstruction algorithms. In the end, an experimental set-up is built. Both uniform and non-uniform BTT vibration signals are collected, and reconstructed order analysis are carried out. Simulation and experimental results testify that the proposed algorithms can accurately capture characteristic high EOs of synchronous and asynchronous vibrations under VRS by using few BTT sensors. The significance of this paper is to overcome the limitation of conventional BTT methods of dealing with variable blade rotating speeds.

Software Defined Doppler Radar as a Contactless Multipurpose Microwave Sensor for Vibrations Monitoring.

A vibration sensor based on the use of a Software-Defined Radio (SDR) platform is adopted in this work to provide a contactless and multipurpose solution for low-cost real-time vibrations monitoring. In order to test the vibration detection ability of the proposed non-contact method, a 1 GHz Doppler radar sensor is simulated and successfully assessed on targets at various distances, with various oscillation frequencies and amplitudes. Furthermore, an SDR Doppler platform is practically realized, and preliminary experimental validations on a device able to produce a harmonic motion are illustrated to prove the effectiveness of the proposed approach.

A Low Frequency FBG Accelerometer with Symmetrical Bended Spring Plates.

To meet the requirements for low-frequency vibration monitoring, a new type of FBG (fiber Bragg grating) accelerometer with a bended spring plate is proposed. Two symmetrical bended spring plates are used as elastic elements, which drive the FBG to produce axial strains equal in magnitude but opposite in direction when exciting vibrations exist, leading to doubling the wavelength shift of the FBG. The mechanics model and a numerical method are presented in this paper, with which the influence of the structural parameters on the sensitivity and the eigenfrequency are discussed. The test results show that the sensitivity of the accelerometer is more than 1000 pm/g when the frequency is within the 0.7-20 Hz range.

Monitoring Bridge Dynamic Responses Using Fiber Bragg Grating Tiltmeters.

In bridge health monitoring, tiltmeters have been used for measuring rotation and curvature; however, their application in dynamic parameter identification has been lacking. This study installed fiber Bragg grating (FBG) tiltmeters on the bearings of a bridge and monitored the dynamic rotational angle. The dynamic features, including natural frequencies and mode shapes, have been identified successfully. The innovation presented in this paper is the first-time use of FBG tiltmeter readings to identify the natural frequencies of a long-span steel girder bridge. The identified results have been verified using a bridge finite element model. This paper introduces a new method for the dynamic monitoring of a bridge using FBG tiltmeters. Limitations and future research directions are also discussed in the conclusion.

A Two Fiber Bragg Gratings Sensing System to Monitor the Torque of Rotating Shaft.

By fixing two FBGs on the surface of a rotating shaft along the direction of ± 45° and using dynamic wavelength demodulation technology, we propose an optical fiber sensing system to monitor the driving torque and torsion angle of the rotating shaft. In theory, the dependence relation of the dynamic difference of central wavelengths on the torque and torsion angle of the rotating shaft has been deduced. To verify an optical fiber sensing system, a series of sensing experiments have been completed and the measured data are approximately consistent with the theoretical analysis. The difference of two central wavelengths can be expressed as the sum of two parts: a "DC" part and a harmonic "AC" part. The driving torque or torsion angle is linear with the "DC" part of the difference of two central wavelengths, the harmonic "AC" part, meaning the torsion angle vibration, illustrates that periodic vibration torque may be caused by inhomogeneous centrifugal forces or inhomogeneous additional torques produced by the driving system and the load.

Crack-Based Composite Flexible Sensor with Superhydrophobicity to Detect Strain and Vibration.

Vibration sensors are widely applied in the detection of faults and analysis of operational states in engineering machinery and equipment. However, commercial vibration sensors with a feature of high hardness hinder their usage in some practical applications where the measured objects have irregular surfaces that are difficult to install. Moreover, as the operating environments of machinery become increasingly complex, there is a growing demand for sensors capable of working in wet and humid conditions. Here, we present a flexible, superhydrophobic vibration sensor with parallel microcracks. The sensor is fabricated using a femtosecond laser direct writing ablation strategy to create the parallel cracks on a PDMS film, followed by spray-coating with a conductive ink composed of MWCNTs, CB, and PDMS. The results demonstrate that the developed flexible sensor exhibits a high-frequency response of up to 2000 Hz, a high acceleration response of up to 100 m/s2, a water contact angle as high as 159.61°, and a linearity of 0.9812 between the voltage signal and acceleration. The results indicate that the sensor can be employed for underwater vibration, sound recognition, and vibration monitoring in fields such as shield cutters, holding significant potential for mechanical equipment vibration monitoring and speech-based human-machine interaction.