Vibration Sensor Research Articles

Condition Monitoring of Wind Turbine Drivetrain Bearings

Abstract As an extremely valuable and reliable energy source, the renewable energy is developing around the world at an unprecedented pace. By the end of 2022, the global installed capacity of offshore wind turbines is expected to reach 46.4 GW, among which 33.9 GW in Europe. Efficiencies in Operations and Maintenance (O&M) offer potential to achieve significant cost savings as it accounts for around 20%–30% of overall offshore wind farm costs. A recent study of approximately 350 offshore wind turbines indicates that gearboxes might have to be replaced as early as 6.5 years. Therefore sensing and condition monitoring (CM) systems are needed in order to obtain reliable information on the state and condition of different critical parts. The development and use of such technologies will allow companies to schedule actions at the right time. The reduced costs of O&M enable the wind energy at a competitive price thus strengthening productivity of the wind energy sector. At the academic level, a plethora of methodologies have been proposed during the last decades focusing toward early and accurate fault detection. Among others, Envelope Analysis is one of the most important methodologies, where the envelope of the vibration signal is estimated, usually after filtering around a selected frequency band excited by impacts due to the faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclostationary analysis and corresponding methodologies, i.e., the cyclic spectral correlation and the cyclic spectral coherence, have been proved as powerful tools for CM. On the other hand the application, test, and evaluation of such tools in general industrial cases is still rather limited. Therefore the main aim of this paper is the application and evaluation of advanced diagnostic techniques and diagnostic indicators, including the Enhanced Envelope Spectrum and the Spectral Flatness on real-world vibration data collected from vibration sensors on gearboxes in multiple wind turbines over an extended period of time of nearly four years. The diagnostic indicators are compared with classical statistic time and frequency indicators, i.e., Kurtosis, Crest Factor, etc. and their effectiveness is evaluated based on the successful detection of two failure events.

Widening the frontiers of elastography in biomechanics: simultaneous muscle elasticity measurements at high-sample rate with surface wave elastography

Introduction: In recent years, elastography has become a widely accepted methodology to assess the longitudinal shear elastic modulus of skeletal muscle. Ultrasound shear wave elastography is the gold standard used for such a purpose. However, its low sample rate (1–2 Hz) and the impossibility of being used in several muscles simultaneously limit potential biomechanical applications. In this work, we overcome such limitations by using a surface wave elastography method (NU-SWE).Methods: The NU-SWE comprises a wearable device suitable for measuring several muscles simultaneously. Elasticity can be measured at high-frequency rates (∼15 Hz), by propagating several pulse trains of low-frequency (∼100 Hz) superficial waves separated by a short time interval. These pulses propagate along the medium surface and are recorded by a linear array of vibration sensors placed on the skin of each measured muscle. In this context, this work carried out a proof of concept, showing how NU-SWE enables performing experimental protocols previously impracticable with ultrasound elastography. Thus, we measured the longitudinal shear elasticity of the biceps brachii and brachioradialis muscles simultaneously at 15 Hz during isometric elbow flexions exerted at different torque development rates. Furthermore, for comparison, we measured the electromyographic activity of both muscles.Results: Our results show that the maximum elasticity reached by the brachioradialis increases with contraction rate, while the biceps brachii behaves inversely.Discussion: This study provides new insights concerning muscle synergism, evidenced by changes in muscle elasticity during torque production. More generally, it shows that NU-SWE could help widen elastography-driven research in biomechanics.

Estimating Bridge Natural Frequencies Based on Modal Analysis of Vehicle-Bridge Synchronized Vibration Data.

This paper presents a method for accurately estimating the natural frequencies of bridges by simultaneously measuring the acceleration vibration data of vehicles and bridges and applying modal analysis theory. Vibration sensors synchronized with GPS timing were installed on both vehicles and bridges, achieving stable and high-precision time synchronization. This enabled the computation of the bridge's Frequency Response Functions (FRFs) for each mode, leading to a refined estimation of natural frequencies. The validity of the theory was confirmed through numerical simulations and experimental tests. The simulations confirmed its effectiveness, and similar trends were observed in actual bridge measurements. Consequently, this method significantly enhances the feasibility of bridge health monitoring systems. The proposed method is suitable for road bridges with spans ranging from short- to medium-span length, where the vehicle is capable of exciting the bridge.

A Pattern Recognition Method for Filter Bags in Bag Dust Collectors Based on Φ-Optical Time-Domain Reflectometry

The use of phase-sensitive optical time-domain reflectometry (Φ-OTDR)-distributed fiber vibration sensors to detect and identify damaged bags in bag dust collectors has the potential to overcome the inadequacy of traditional damaged bag detection methods. In our previous study, we verified the feasibility of applying this technique in the field of damaged bag detection in bag filters. However, many problems still occur in engineering applications when using this technology to detect and identify damaged filter bags in pulse-jet dust-cleaning bag dust collectors. Further studies are needed to characterize the fiber vibration signals inside different types of rectangular damaged filter bags. A filter bag damage identification and detection method based on empirical mode decomposition (EMD) and a backpropagation (BP) neural network is proposed. The signal feature differences between intact filter bags and damaged filter bags with different rectangular hole sizes and positions are comparatively analyzed, and optimal feature difference parameters are proposed. Support vector machine (SVM) and a BP neural network are used to recognize different types of filter bag signals, and the comparison results show that the BP neural network algorithm is better at recognizing different types of filter bags, obtaining the highest recognition rate of 97.3%.

Waterproofing a Thermally Actuated Vibrational MEMS Viscosity Sensor

An efficient and inexpensive post-process method to waterproof an electrically actuated microtransducer has been studied. The electrical signals of microtransducers operating in electrically conductive fluids must be effectively isolated from the surrounding environment while remaining in contact for sensing purposes. A thermally actuated MEMS viscosity sensor uses electrical signals for both actuation and sensing. Three post-processing materials, (1) Parylene-C, (2) flouroacrylate-based polymer, and (3) nitrocellulose-based polymer, were coated as thin layers of waterproofing materials on different sensors. All three coating materials provided adequate protection when tested under normal operating conditions. Although the vibration response of the sensors was slightly modified, it did not affect their functionality in a significant way when measuring conductive fluids based on glycerol–water mixtures. All the treated sensors lasted over 1.2 million actuations without any decay in performance or failures. When the test bias conditions were increased by 5x to accelerate failures, the flouroacrylate-based polymer samples lasted 2x longer than the others. Visual analysis of the failures indicates that the edge of the diaphragm, which undergoes the most significant stress and strain values during actuation, was the location of the mechanical failure. This work guides post-processed waterproofing coatings for microscale actuators operating in harsh and damaging environments.

Effects of Balance and Strength Training for Ankle Proprioception in People with Chronic Ankle Instability: A Randomized Controlled Study.

After an ankle sprain, the ligament and joint capsule are damaged, and as a result, proprioceptive sense is damaged, causing a feeling of giving away in the ankle and resulting in recurrent sprains. Given the relevant studies, it has been seen that people with chronic ankle instability (CAI) commonly have deficits in joint position sense and reinjury risks. Joint position sense plays an important role in ankle control, thereby reducing the risk of injury. Therefore, this study aims to compare the effects of balance and strength training on ankle proprioception in people with CAI. This single-blind randomized controlled study included 29 volunteer participants (21 women and eight men) aged 18 to 30 years. Participants with a Cumberland ankle instability scale score less than or equal to 24 were randomly divided into two treatment groups: strength training (n = 14) and balance training (n = 15). Y balance test, joint position, and vibration sense were evaluated at the beginning and end of the treatment. "Hop to stabilization" exercises were applied to the balance group and resistive bands exercises to the strength group, which were performed for 6 weeks, 35 minutes per day, two times per week. There was no significant difference between the two groups in the anterior, posterolateral, and posteromedial directions of the Y balance test (P = .89, P = .50, and P = .34, respectively), but the strength training group showed significant improvement in ankle proprioception (140°) and vibration sense (fifth finger) (P < .001), and the post hoc Cohen's d effect size values were medium (.52) and small (.25), respectively. The findings of this study show that strengthening and balance exercises have similar effects on dynamic balance, but strengthening exercises are more effective in improving joint position and vibration sense. Given the positive effects of both exercise programs, it is recommended to implement the two interventions separately or together for CAI rehabilitation.

PERANCANGAN SISTEM KENDALI PADA SISTEM KEAMANAN SEPEDA MOTOR DENGAN MIKROKONTROLER ESP32

Along with the rapid development of technology, of course, making the security system more sophisticated, efficient and innovative. Internet of Things (IoT)-based security is one of the options for implementing technology in the security sector. With the existence of IoT, every community can keep their vehicle safely through a protection or monitoring system. In this study, the authors design and manufacture a Motorcycle Security System using Face recognition and Bluetooth-based Keyless as a motorcycle lock and a SW-420 vibration sensor as a theft detection. The theft detection system is also supported by a telegram notification service when there is an indication of theft on a motorcycle. The motorcycle protection control system with Keyless on this System can function only at a distance of 0 – 8.35 meters between the iTag BLE module and the ESP32 microcontroller. In other control systems, face recognition verification services can be carried out at a minimum user distance of 25cm and a maximum user distance of 50cm. While the protection system with a vibration sensor has a working logic truth of 100%. In the next development, a device with better hardware specifications is needed so that the performance of the control system has a wider range of detection values

High-frequency distortion phenomenon and solution of low frequency vibration sensor

This paper analyzes the difference between several acceleration over-limit faults, and finds out the cause of false acceleration fault of wind turbines, which is because the low-frequency vibration sensor used by the unit is interfered with the high-frequency signal generated by the friction of the yaw system and causes the sensor output signal distortion. The performance of different manufacturers’ sensors under different installation positions is reproduced on the spot. A cost-effective solution to the high frequency distortion problem (installing a physical low-pass filter) is developed, and the comparative test results before and after its application are demonstrated experimentally.

Belt conveyor speed detection based on fiber-optic Sagnac interferometer vibration sensor

With their long transportation distance and high productivity, belt conveyors are characterized as the main equipment for bulk material transportation in coal mines and other key industries. However, its speed detection method has always been an engineering challenge under harsh working conditions. In this work, the elastic-optical effect of the polarization-maintaining fiber is used to design a fiber ring laser vibration sensing system based on a fiber-optic Sagnac interferometer vibration sensor and its packaging structure. The vibration detection is achieved by detecting the change in optical power at the working wavelength, and the belt conveyor speed measurement is completed by detecting the vibration frequency. With such a method, the belt conveyor speed measurement obtained a relative error of less than 1.88%. The proposed method bears the characteristics of anti-electromagnetic interference, intrinsic explosion-proof, and adapts to the harsh smoke and dust working environment, which has a wide range of application prospects in the fields of engineering, machinery, security, etc.

Detection and Diagnostics of Bearing and Gear Fault under Variable Speed and Load Conditions Using Heterogeneous Signals

In industrial applications, rotating machines operate under real-time variable speed and load regimes. In the presence of faults, the degradation of critical components is accelerated significantly. Therefore, robust monitoring algorithms able to identify these faults become crucial. In the literature, it is hard to find comprehensive monitoring systems that include variable speed and load regimes with combined gearbox faults using electrical and vibration signals. For this purpose, a novel signal processing methodology including a geometric classification technique is proposed. This methodology is based on using different types of sensors such as current, voltage and vibration sensors with a regime normalization, which allows the grouping of different regimes belonging to the same health state. It consists of reducing dispersion between the class observations and separating other classes representing different health states including the variation in speed and load. Then, a peripheral threshold is proposed in our classifier to diagnose new health states. To verify the effectiveness of the methodology, current, voltage and vibration data from a gearbox system are collected under variable speed and load levels.

Implementation of Smart Lock JT701 for Cargo Security System

The freight forwarding business, namely transportation services from various modes of transportation (carrier) and arranging a series of shipments from several senders is growing rapidly during the pandemic and post Covid-19 pandemic. However, this business development is not without problems. Security disturbances during the cargo delivery process are a major problem, and this often happens in Indonesia. For this reason, this research will build a cargo delivery security system using automation technology and based on the Internet of Things (IoT). The system is a Smart Lock installed on the cargo. This smart lock can be monitored remotely, such as opening or closing the lock and the condition of the cargo in the field. Only the cargo owner can open or close the cargo lock. In addition, this system is also equipped with temperature and vibration sensors to maintain the quality of the goods in the cargo. The results of this research will be useful for the security system and convenience of the cargo delivery process and the digitization process will be easier to do in the future.

К вопросу о развитии методов измерения вибрации строительных конструкций

Vibration processes contain useful information about the properties of both the signal source and the medium in which they propagate. Control of vibration parameters of structures is an integral part of monitoring. There are various methods and means of measuring vibration processes in building structures, as well as their registration. The development of technology and electronics allows us to steadily improve the parameters of vibration sensors, reduce their dimensions and create fundamentally new sensitive elements. Examples are given of vibration measuring equipment used by the staff of the Institute of Continuous Media Mechanics for testing large-scale building structures over the past 25 years. The results of vibration measurements of large-scale structures are shown, as well as the evolution of the natural frequency of a building structure during its long-term monitoring.

Sensors, standards and analysis techniques for road transport vibration: A systematic review

This comprehensive review paper analyzes 20 published articles focused on the instrumentation and analysis of road transport vibrations. The study encompasses the distribution of articles based on databases, journals, and publication years, revealing trends in research sources. The examination of sensors and standards emphasizes the critical role of vibration sensor selection and the application of standards, with a focus on accelerometer designs and the prevalence of ASTM D4169-16. The paper delves into various analytical methods, highlighting the frequent use of power spectral density (PSD) and the application of these methods in understanding vibration frequencies and their effects on different transportation conditions. The review identifies key areas for future research, emphasizing the need for refined instrumentation methodologies, standardized standards, and exploration of advanced analytical techniques, considering the dynamic nature of real-world vibrations and emerging technologies in the road transport landscape. Additionally, the review suggests future investigations into optimizing packaging designs and developing innovative materials with vibration-damping properties to enhance the safety and efficiency of road transportation systems.

Dynamic plastic hinge rotation measurement for RC columns under seismic loads using MEMS inclinometers

Plastic hinge rotation is an efficient and essential response parameter for post-disaster damage assessment on RC structures. In this paper, a micro-electronic mechanical system (MEMS) inclinometer-based approach is developed to dynamically measure the plastic hinge rotation of RC columns under earthquake loads. The plastic hinge rotation is regarded as the relative angle of rotation, measured by inclinometers, between cross-sections such that influence from the absolute rotation of floors can be eliminated. Meanwhile, since the inclinometers are densely installed near the bottom, translational acceleration-induced error can be compensated by subtracting the lowest sensor’s output from others’. However, issues caused by rotational and translational vibration are considered as the major challenges in real applications. The contribution of external vibration to the sensor’s overall output is revealed via analysis on a simplified inclinometer model. A numerical study utilizing typical RC column’s deformation characteristics and dimensions is conducted to analyze the influence of major factors: vibrational frequency, sensor position and damage extent. A method for static and dynamic inclinometer calibration is presented. The related calibration experiments are carried out to quantify the sensor’s sensitivity as well as the relationship between rotational frequency and error. The calibration method is validated with a set of vibration tests that use three seismic waves as input. Finally, performance of the proposed approach in full scale structures is investigated through a shake table test.

Intelligent triboelectric V-belts with condition monitoring capability

In this study, the V-belt transmission structure and triboelectric nanogenerator (TENG) are combined, and an intelligent transmission system, the triboelectric V-belt (TVB), is proposed. Furthermore, its condition-monitoring capability is investigated to improve the intelligence level of the traditional mechanical transmission system. The designed TVB can be integrated with a belt pulley without additional structural space; moreover, it exhibits good reliability by avoiding contact with the working surface of the V-belt transmission. For the output characteristics of the TVB, the variation curves of the output voltage and current with load resistance were tested and the influence of several design variables was elucidated. Through monitoring the amplitude and time–frequency features of the TVB output current, the slipping failure of the V-belt drive can be detected in time, and typical faults of a bevel gearbox (including defective driving/driven gears and supporting bearings) were classified with an average accuracy exceeding 90%. The classification accuracy based on TVB was only slightly lower than that based on the vibration sensor. The designed TVB exhibits promising application prospects for monitoring industrial transmission systems.

Encoding of multi-modal emotional information via personalized skin-integrated wireless facial interface

Human affects such as emotions, moods, feelings are increasingly being considered as key parameter to enhance the interaction of human with diverse machines and systems. However, their intrinsically abstract and ambiguous nature make it challenging to accurately extract and exploit the emotional information. Here, we develop a multi-modal human emotion recognition system which can efficiently utilize comprehensive emotional information by combining verbal and non-verbal expression data. This system is composed of personalized skin-integrated facial interface (PSiFI) system that is self-powered, facile, stretchable, transparent, featuring a first bidirectional triboelectric strain and vibration sensor enabling us to sense and combine the verbal and non-verbal expression data for the first time. It is fully integrated with a data processing circuit for wireless data transfer allowing real-time emotion recognition to be performed. With the help of machine learning, various human emotion recognition tasks are done accurately in real time even while wearing mask and demonstrated digital concierge application in VR environment.

The FGF14 GAA repeat expansion in Greek patients with late-onset cerebellar ataxia and an overview of the SCA27B phenotype across populations.

A pathogenic GAA repeat expansion in the first intron of the fibroblast growth factor 14 gene (FGF14) has been recently identified as the cause of spinocerebellar ataxia 27B (SCA27B). We herein screened 160 Greek index cases with late-onset cerebellar ataxia (LOCA) for FGF14 repeat expansions using a combination of long-range PCR and bidirectional repeat-primed PCRs. We identified 19 index cases (12%) carrying a pathogenic FGF14 GAA expansion, a diagnostic yield higher than that of previously screened repeat-expansion ataxias in Greek LOCA patients. The age at onset of SCA27B patients was 60.5 ± 12.3 years (range, 34-80). Episodic onset (37%), downbeat nystagmus (32%) and vertigo (26%) were significantly more frequent in FGF14 expansion-positive cases compared to expansion-negative cases. Beyond typical cerebellar signs, SCA27B patients often displayed hyperreflexia (47%) and reduced vibration sense in the lower extremities (42%). The frequency and phenotypic profile of SCA27B in Greek patients was similar to most other previously studied populations. We conclude that FGF14 GAA repeat expansions are the commonest known genetic cause of LOCA in the Greek population and recommend prioritizing testing for FGF14 expansions in the diagnostic algorithm of patients with LOCA.

Advance of research on Hereditary spastic paraplegia type 4

Spastic paraplegia type 4 (SPG4) is the most common type of autosomally inherited spastic paraplegia. Its main clinical features include typical simple hereditary spastic paraplegia, with neurological impairments limited to lower limb spasticity, hypertonic bladder dysfunction, and mild weakening of lower limb vibration sensation, without accompanying features such as nerve atrophy, ataxia, cognitive impairment, seizures, and muscle tone disorders. SPAST is the main pathogenic gene underlying SPG4, and various pathogenic SPAST variants have been discovered. This disease has featured a high degree of clinical heterogeneity, and the same pathogenic variant can have different age of onset and severity among different patients and even within the same family. There is a lack of systematic research on the correlation between the genotype and phenotype of SPG4, and the pathogenic mechanism has remained controversial. This article has provided a review for the clinical characteristics, pathogenic gene characteristics, correlation between the genotype and phenotype, and pathogenic mechanism of this disease, with an aim to provide reference for its clinical diagnosis and treatment.

SPONTANEOUS THIRD-DEGREE ATRIOVENTRICULAR BLOCK IN A DIABETIC PATIENT PRESENTING AS RECURRENT SYNCOPE

Chronic, uncontrolled hyperglycemia is associated with an increased incidence of coronary artery disease, cardiac failure, diabetic nephropathy, diabetic retinopathy, and associated mortality. A 72-year-old female presented to the OPD with multiple episodes of loss of consciousness for the past 1 month. The patient also had other comorbidities such as hypertension, diabetes mellitus (DM), and hypothyroidism. On systemic examination, her blood pressure was 124/77 mmHg (supine) and 116/72 mmHg (standing), and her pulse rate was 56 beats/min. She had a loss of vibration sense in both lower limbs up to the ankle. Fundus examination showed non-proliferative diabetic retinopathy. The rest of the systemic examination was clinically normal. Her HbA1C was 8.1%, and other routine investigations were within normal limits. Electrocardiography (ECG) showed sinus bradycardia. Echocardiography showed normal ventricular function with no evidence of ischemic heart disease (IHD). 24-h Holter ECG revealed sinus bradycardia with an intraventricular conduction defect, a third-degree AV block with junctional beats, and rare supraventricular ectopics. This is a case of Type 2 DM with complete heart block (CHB) of spontaneous onset. Other causes of AV block have been ruled out, and it seems that this case of CHB is possibly due to cardiac autonomic neuropathy (CAN). Multiple factors, such as the duration of diabetes, poor glycemic control, metabolic derangements, and genetic factors, determine CAN. This case emphasizes that patients with type 2 diabetes without IHD can develop CHB spontaneously.

Intelligent programmable metasurface for vibration field sensing and electromagnetic reflection modulation

While existing research has explored control strategies in multi-dimensional fields, the interconnectedness between electromagnetic and vibrational fields remains relatively uncharted. To explore this intersection and harness its potential, we propose an intelligent programmable metasurface that modulates electromagnetic fields based on vibration intensity information. This paper introduces a groundbreaking approach that synergizes the physical fields of mechanical (vibrational) waves with electromagnetic waves, facilitating the detection and manipulation of information from both fields. By combining a programmable metasurface, vibration sensors, and microcontroller units, we have achieved regulation of the electromagnetic field through utilization of vibration intensity information. In this work, we have introduced six coding patterns that facilitate dual-beam scanning with variable deflection angles. A 20 × 20 metasurface is fabricated and measured, and the measured results are in good agreement with the simulated results. This research opens a new avenue for manipulating electromagnetic waves. Furthermore, the findings have the potential to impact a wide range of fields, including building structuralhealth monitoring, industrial production, mechanical equipment monitoring, and earthquake monitoring.