A Flexible, Adaptive, and Self-Powered Triboelectric Vibration Sensor with Conductive Sponge-Silicone for Machinery Condition Monitoring.

Vibration sensors for continuous and reliable condition monitoring of mechanical equipment, especially detection points of curved surfaces, remain a great challenge and are highly desired. Herein, a highly flexible and adaptive triboelectric vibration sensor for high-fidelity and continuous monitoring of mechanical vibration conditions is proposed. The sensor is entirely composed of flexible materials. It consists of a conductive sponge-silicone layer and a fluorinated ethylene propylene film. It can detect vibration acceleration of 5 to 50 m s-2 and vibration frequency of 10 to 100 Hz. It has strong robustness and stability, and the output performance barely changes after the durability test of 168 000 working cycles. Additionally, the flexible sensor can work even when the detection point of the mechanical equipment is curved, and the linear fit of the output voltage and acceleration is very close to that when the detection point is flat. Finally, it can be applied to monitoring the working condition of blower and vehicle engine, and can transmit vibration signal to mobile phone application through Wi-Fi module for real-time monitoring. The flexible triboelectric vibration sensor is expected to provide a practical paradigm for smart, green, and sustainable wireless sensor system in the era of Internet of Things.

Low-Cost and Paper-Based Micro-Electromechanical Systems Sensor for the Vibration Monitoring of Shield Cutters.

Vibration sensors are widely used in many fields like industry, agriculture, military, medicine, environment, etc. However, due to the speedy upgrading, most sensors composed of rigid or even toxic materials cause pollution to the environment and give rise to an increased amount of electronic waste. To meet the requirement of green electronics, biodegradable materials are advocated to be used to develop vibration sensors. Herein, a vibration sensor is reported based on a strategy of pencil-drawing graphite on paper. Specifically, a repeated pencil-drawing process is carried out on paper with a zigzag-shaped framework and parallel microgrooves, to form a graphite coating, thus serving as a functional conductive layer for electromechanical signal conversion. To enhance the sensor's sensitivity to vibration, a mass is loaded in the center of the paper, so that higher oscillation amplitude could happen under vibrational excitation. In so doing, the paper-based sensor can respond to vibrations with a wide frequency range from 5 Hz to 1 kHz, and vibrations with a maximum acceleration of 10 g. The results demonstrate that the sensor can not only be utilized for monitoring vibrations generated by the knuckle-knocking of plastic plates or objects falling down but also can be used to detect vibration in areas such as the shield cut head to assess the working conditions of machinery. The paper-based MEMS vibration sensor exhibits merits like easy fabrication, low cost, and being environmentally friendly, which indicates its great application potential in vibration monitoring fields.

Pullulan-1-Ethyl-3-Methylimidazolium Tetrafluoroborate Composite as a Water-Soluble Active Component of a Vibration Sensor.

In recent years, the issue of electronic waste production has gained significant attention. To mitigate the environmental impact of e-waste, one approach under consideration involves the development of biodegradable electronic devices or devices that dissolve in the environment at the end of their life cycle. This study presents results related to the creation of a sensor that effectively addresses both criteria. The device was constructed using a composite material formed by impregnating a pullulan membrane (a biodegradable water-soluble biopolymer) with 1-Ethyl-3-Methylimidazolium tetrafluoroborate (a water-soluble ionic liquid) and coating the product with a conductive silver-based varnish. Capitalizing on the piezoionic effect, the device has demonstrated functionality as a vibration sensor with a sensitivity of approximately 5.5 × 10-5 V/mm and a resolution of about 1 mm. The novelty of this study lies in the unique combination of materials. Unlike the use of piezoelectric materials, this combination allows for the production of a device that does not require an external potential difference generator to function properly as a sensor. Furthermore, the combination of a biopolymer, such as pullulan, and an ionic liquid, both readily soluble in water, in creating an active electronic component represents an innovation in the field of vibration sensors.

A Low-Frequency Vibration Sensor Based on Ball Triboelectric Nanogenerator for Marine Pipeline Condition Monitoring.

Marine pipeline vibration condition monitoring is a critical and challenging issue, on account of the complex marine environment, while powering the required monitoring sensors remains problematic. This study introduces a vibration sensor based on a ball triboelectric nanogenerator (B-TENG) for marine pipelines condition monitoring. The B-TENG consists of an acrylic cube, polyester rope, aluminum electrodes, and PTFE ball, which converts vibration signals into electrical signals without the need for an external energy supply. The experimental results show that B-TENG can accurately monitor the frequency, amplitude, and direction of vibration in the range of 1-5 Hz with a small error of 0.67%, 4.4%, and 5%, and an accuracy of 0.1 Hz, 0.97 V/mm, and 1.5°, respectively. The hermetically sealed B-TENG can monitor vibration in underwater environments. Therefore, the B-TENG can be used as a cost-effective, self-powered, highly accurate vibration sensor for marine pipeline monitoring.

Distributed Vibration Sensing Based on a Forward Transmission Polarization-Generated Carrier.

For distributed fiber-optic sensors, slowly varying vibration signals down to 5 mHz are difficult to measure due to low signal-to-noise ratios. We propose and demonstrate a forward transmission-based distributed sensing system, combined with a polarization-generated carrier for detection bandwidth reduction, and cross-correlation for vibration positioning. By applying a higher-frequency carrier signal using a fast polarization controller, the initial phase of the known carrier frequency is monitored and analyzed to demodulate the vibration signal. Only the polarization carrier needs to be analyzed, not the arbitrary-frequency signal, which can lead to hardware issues (reduced detection bandwidth and less noise). The difference in arrival time between the two detection ends obtained through cross-correlation can determine the vibration position. Our experimental results demonstrate a sensitivity of 0.63 mrad/µÎµ and a limit of detection (LoD) of 355.6 pε/Hz1/2 at 60 Hz. A lock-in amplifier can be used on the fixed carrier to achieve a minimal LoD. The sensing distance can reach 131.5 km and the positioning accuracy is 725 m (root-mean-square error) while the spatial resolution is 105 m. The tested vibration frequency range is between 0.005 Hz and 160 Hz. A low frequency of 5 mHz for forward transmission-based distributed sensing is highly attractive for seismic monitoring applications.

Cardiac Multi-Frequency Vibration Signal Sensor Module and Feature Extraction Method Based on Vibration Modeling.

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases.

Sub-Nanometer Acoustic Vibration Sensing Using a Tapered-Tip Optical Fiber Microcantilever.

We demonstrate a highly sensitive acoustic vibration sensor based on a tapered-tip optical fiber acting as a microcantilever. The tapered-tip fiber has a unique output profile that exhibits a circular fringe pattern, whose distribution is highly sensitive to the vibration of the fiber tip. A piezo transducer is used for the acoustic excitation of the fiber microcantilever, which results in a periodic bending of the tip and thereby a significant output power modulation. Using a multimode readout fiber connected to an electric spectrum analyzer, we measured the amplitude of these power modulations over the 10-50 kHz range and observed resonances over certain frequency ranges. Two types of tapered-tip fibers were fabricated with diameter values of 1.5 µm and 1.8 µm and their frequency responses were compared with a non-tapered fiber tip. Thanks to the resonance effect as well as the sensitive fringe pattern of the tapered-tip fibers, the limit of detection and the sensitivity of the fiber sensor were obtained as 0.1 nm and 15.7 V/nm, respectively, which were significantly better than the values obtained with the non-tapered fiber tip (i.e., 1.1 nm and 0.12 V/nm, respectively). The sensor is highly sensitive, easy to fabricate, low-cost, and can detect sub-nanometer displacements, which makes it a promising tool for vibration sensing, particularly in the photoacoustic sensing of greenhouse gases.

A Rolling Bearing Fault Feature Extraction Algorithm Based on IPOA-VMD and MOMEDA.

Since the rolling bearing fault signal captured by a vibration sensor contains a large amount of background noise, fault features cannot be accurately extracted. To address this problem, a rolling bearing fault feature extraction algorithm based on improved pelican optimization algorithm (IPOA)-variable modal decomposition (VMD) and multipoint optimal minimum entropy deconvolution adjustment (MOMEDA) methods is proposed. Firstly, the pelican optimization algorithm (POA) was improved using a reverse learning strategy for dimensional-by-dimensional lens imaging and circle mapping, and the optimization performance of IPOA was verified. Secondly, the kurtosis-square envelope Gini coefficient criterion was used to select the optimal modal components from the decomposed components of the signal, and MOMEDA was used to process the optimal modal components in order to obtain the optimal deconvolution signal. Finally, the Teager energy operator (TEO) was employed to demodulate and analyze the optimally deconvoluted signal in order to enhance the transient shock component of the original fault signal. The effectiveness of the proposed method was verified using simulated and actual signals. The results showed that the proposed method can accurately extract failure characteristics in the presence of strong background noise interference.

Quasi-Zero Stiffness Vibration Sensing and Energy Harvesting Integration Based on Buckled Piezoelectric Euler Beam.

This paper presents a novel quasi-zero stiffness vibration sensing and energy harvesting integration system for absolute displacement measurements based on a buckled piezoelectric Euler beam (BPEB) with quasi-zero stiffness (QZS) characteristics. On one hand, BPEB provides negative stiffness to the system, thus creating a vibration-free point within the system and transforming the absolute displacement measurement problem into a relative motion sensing problem. On the other hand, during the measurement process, the BPEB collects the vibration energy from the system, which can provide electrical energy for low-power relative motion sensing devices and remarkably suppress the frequency range of the jump phenomenon, thereby further expanding the frequency domain measurement range of the sensing system. The research results have shown that this system can measure the absolute motion signal of the tested object in low-frequency vibration with small excitation. By adjusting parameters such as the force-electric coupling coefficient and damping ratio, the measurement accuracy of the sensing system can be improved. Furthermore, the system can convert the mechanical energy of vibrations into electrical energy to power the surrounding low-power sensors or provide partial power. This could potentially achieve self-powering integrated quasi-zero stiffness vibration sensing, offering another approach and possibility for the automation development in wireless sensing systems and the Internet of Things field.

A Digital-Twin Framework for Predicting the Remaining Useful Life of Piezoelectric Vibration Sensors with Sensitivity Degradation Modeling.

Piezoelectric vibration sensors (PVSs) are widely applied to vibration detection in aerospace engines due to their small size, high sensitivity, and high-temperature resistance. The precise prediction of their remaining useful life (RUL) under high temperatures is crucial for their maintenance. Notably, digital twins (DTs) provide enormous data from both physical structures and virtual models, which have potential in RUL predictions. Therefore, this work establishes a DT framework containing six modules for sensitivity degradation detection and assessment on the foundation of a five-dimensional DT model. In line with the sensitivity degradation mechanism at high temperatures, a DT-based RUL prediction was performed. Specifically, the PVS sensitivity degradation was described by the Wiener-Arrhenius accelerated degradation model based on the acceleration factor constant principle. Next, an error correction method for the degradation model was proposed using real-time data. Moreover, parameter updates were conducted using a Bayesian method, based on which the RUL was predicted using the first hitting time. Extensive experiments on distinguishing PVS samples demonstrate that our model achieves satisfying performance, which significantly reduces the prediction error to 8 h. A case study was also conducted to provide high RUL prediction accuracy, which further validates the effectiveness of our model in practical use.

Sagnac with Double-Sense Twisted Low-Birefringence Standard Fiber as Vibration Sensor.

In this work, we study a double-sense twisted low-birefringence Sagnac loop structure as a sound/vibration sensing device. We study the relation between the adjustments of a wave retarder inside the loop (which allows controlling the transmission characteristic to deliver 10, 100, and 300 µW average power at the output of the system) and the response of the Sagnac sensor to vibration frequencies ranging from 0 to 22 kHz. For a 300 m loop Sagnac, two sets of experiments were carried out, playing at the same time all the sound frequencies mixed for ∼1 s, and playing a sweep of frequencies for 30 s. In both cases, the time- and frequency-domain transmission amplitudes are larger for an average power of 10 µW, and smaller for an average power of 300 µW. For mixed frequencies, the Fourier analysis shows that the Sagnac response is larger for low frequencies (from 0 to ∼5 kHz) than for high frequencies (from ∼5 kHz to ∼22 kHz). For a sweep of frequencies, the results reveal that the interferometer perceives all frequencies. However, beyond ∼2.5 kHz, harmonics are present each ∼50 Hz, revealing that some resonances are present. The results about the influence of the power transmission through the polarizer and power emission of laser diode (LD) on the Sagnac interferometer response at high frequencies reveal that our system is robust, and the results are highly reproducible, and harmonics do not depend on the state of polarization at the input of the Sagnac interferometer. Furthermore, increasing the LD output power from 5 mW to 67.5 mW allows us to eliminate noisy signals at the system output. in our setup, the minimum sound level detected was 56 dB. On the other hand, the experimental results of a 10 m loop OFSI reveal that the response at low frequencies (1.5 kHz to 5 kHz) is minor compared with the 300 m loop OFSI. However, the response at high frequencies is low but still enables the detection of these frequencies, yielding the possibility of tuning the response of the vibration sensor by varying the length of the Sagnac loop.

Self-Powered Self-Contained Wireless Vibration Synchronous Sensor for Fault Detection.

Failure in dynamic structures poses a pressing need for fault detection systems. Interconnected sensor nodes of wireless sensor networks (WSN) offer a solution by communicating information about their surroundings. Nonetheless, these battery-powered sensors have an immense labor cost and require periodical battery maintenance and replacement. Batteries pose a significant environmental threat that is expected to cause irreversible damage to the ecosystem. We introduce a fully integrated vibration-powered energy harvester sensor system that is interfaced with a custom-developed fault detection app. Vibrations are used to power a radio frequency (RF) transmitter that is integrated with the vibration sensor subunit. The harvester-sensor unit is comprised of dual moving magnets that are bordered by coil windings for power and signal generation. The power generated from the harvester is used to operate the transmitter while the signal generated from the sensor is transmitted as a vibration signal. Transmitted values are streamed into a high precision fault detection app capable of detecting the frequency of vibrations with an error of 1%. The app employs an FFT algorithm on the transmitted data and notifies the user when a threshold vibration level is reached. The total energy consumed by the transmitter is 0.894 µJ at a 3 V operation. The operable acceleration of the system is 0.7 g [m/s2] at 5-10.6 Hz.

Single-Channel Blind Signal Separation of the MHD Linear Vibration Sensor Based on Singular Spectrum Analysis and Fast Independent Component Analysis.

An MHD vibration sensor, as a new type of sensor used for vibration measurements, meets the technical requirements for the low-noisy measurement of acceleration, velocity, and micro-vibration in spacecraft during their development, launch, and orbit operations. A linear vibration sensor with a runway type based on MHD was independently developed by a laboratory. In a practical test, its output signal was mixed with a large amount of noise, in which the continuous narrowband interference was particularly prominent, resulting in the inability to efficiently carry out the real-time detection of micro-vibration. Considering the high interference of narrowband noise in linear vibration signals, a single-channel blind signal separation method based on SSA and FastICA is proposed in this study, which provides a new strategy for linear vibration signals. Firstly, the singular spectrum of the linear vibration signal with noise was analyzed to suppress the narrowband interference in the collected signal. Then, a FastICA algorithm was used to separate the independent signal source. The experimental results show that the proposed method can effectively separate the useful linear vibration signals from the collected signals with low SNR, which is suitable for the separation of the MHD linear vibration sensor and other vibration measurement sensors. Compared with EEMD, VMD, and wavelet threshold denoising, the SNR of the separated signal is increased by 10 times on average. Through the verification of the actual acquisition of the linear vibration signal, this method has a good denoising effect.

Optical Fiber Vibration Signal Identification Method Based on Improved YOLOv4.

In the traditional peripheral-security-early-warning system, the endpoint detection and pattern recognition of the signals generated by the distributed optical fiber vibration sensors is completed step-by-step and in an orderly manner. The method by which these two processes may be placed end-to-end in a network model and processed simultaneously to improve work efficiency has increasingly become the focus of research. In this paper, the target detection algorithm combines the endpoint-detection and pattern-recognition processes of the vibration signal, which can not only quickly locate the start and end vibration positions of the signal but also accurately identify a certain type of signal. You Only Look Once v4 (YOLOv4) is one of the most advanced target detection algorithms, achieving the optimal balance of speed and accuracy. To reduce the complexity of the YOLOv4 model and solve the dataset's unbalanced sample classification problem, we use a deep separable convolution (DSC) network and a focal loss function to improve the YOLOv4 model. In this paper, the five kinds of signals collected in real-time are visualized as two different datasets in oscillograph and time-frequency diagrams as detection objects. According to the experimental results, we obtained 98.50% and 93.48% mean Average Precision (mAP) and 84.8 and 69.9 frames per second (FPS), respectively, which are improved compared to YOLOv4. Comparing the improved algorithm with other optical fiber vibration signal recognition algorithms, the mAP and FPS values were improved, and the detection speed was about 20 times faster than that of other algorithms. The improved algorithm in this paper can quickly and accurately identify the vibration signal of external intrusion, reduce the false-alarm rate of the early-warning system, and improve the real-time detection rate of the system while ensuring high recognition accuracy.

A vibration sensor approach to detect intra-articular needle tip placement in the knee joint: a proof-of-concept study.

BACKGROUND: Intra-articular injection in the dry knee joint is technically challenging particularly for the beginners. The aim of this study was to investigate the possible use of the vibration sensor to detect if the needle tip was at the knee intra-articular position by characterizing the frequency component of the vibration signal during empty syringe air injection. METHODS: Two milliliters of air were injected supero-laterally at extra- and intra-articular positions of a cadaveric knee joint, using needles of size 18, 21 and 24 gauge (G). Ultrasonography was used to confirm the positions of needle tip. A piezoelectric accelerometer was mounted medially on the knee joint to collect the vibration signals which were analyzed to characterize the frequency components of the signals during injections. RESULTS: The vibration frequency band power in the range of 500-1500 Hz was visually observed to potentially localize the needle tip placement during air injection whether they were at the knee extra-articular or intra-articular positions, as demonstrated by the higher band power (over - 40 dB or dB) for all the needle sizes. The differences of frequency band power between extra- and intra-articular positions were 18.1 dB, 26.4 dB and 39.2 dB for the needle size 18G, 21G and 24G respectively. The largest difference in spectral power was found in the smallest needle diameter (24G). CONCLUSIONS: A vibration sensor approach was preliminarily proved to distinguish the intra-articular from extra-articular needle placement in the knee joint. This study demonstrated a possible implementation of an alternative electronic device based on this technique to detect the intra-articular knee injection.

Wearable Vibration Sensor for Measuring the Wing Flapping of Insects.

In this study, we fabricated a novel wearable vibration sensor for insects and measured their wing flapping. An analysis of insect wing deformation in relation to changes in the environment plays an important role in understanding the underlying mechanism enabling insects to dynamically interact with their surrounding environment. It is common to use a high-speed camera to measure the wing flapping; however, it is difficult to analyze the feedback mechanism caused by the environmental changes caused by the flapping because this method applies an indirect measurement. Therefore, we propose the fabrication of a novel film sensor that is capable of measuring the changes in the wingbeat frequency of an insect. This novel sensor is composed of flat silver particles admixed with a silicone polymer, which changes the value of the resistor when a bending deformation occurs. As a result of attaching this sensor to the wings of a moth and a dragonfly and measuring the flapping of the wings, we were able to measure the frequency of the flapping with high accuracy. In addition, as a result of simultaneously measuring the relationship between the behavior of a moth during its search for an odor source and its wing flapping, it became clear that the frequency of the flapping changed depending on the frequency of the odor reception. From this result, a wearable film sensor for an insect that can measure the displacement of the body during a particular behavior was fabricated.

Fiber Optic Based Distributed Mechanical Vibration Sensing.

The distributed long-range sensing system, using the standard telecommunication single-mode optical fiber for the distributed sensing of mechanical vibrations, is described. Various events generating vibrations, such as a walking or running person, moving car, train, and many other vibration sources, can be detected, localized, and classified. The sensor is based on phase-sensitive optical time-domain reflectometry (ϕ-OTDR). Related sensing system components were designed and constructed, and the system was tested both in the laboratory and in the real deployment, with an 88 km telecom optical link, and the results are presented in this paper. A two-fiber sensor unit, with a double-sensing range was also designed, and its scheme is described. The unit was constructed and the initial measurement results are presented.

A Coupled Piezoelectric Sensor for MMG-Based Human-Machine Interfaces.

Mechanomyography (MMG) is a technique of recording muscles activity that may be considered a suitable choice for human-machine interfaces (HMI). The design of sensors used for MMG and their spatial distribution are among the deciding factors behind their successful implementation to HMI. We present a new design of a MMG sensor, which consists of two coupled piezoelectric discs in a single housing. The sensor's functionality was verified in two experimental setups related to typical MMG applications: an estimation of the force/MMG relationship under static conditions and a neural network-based gesture classification. The results showed exponential relationships between acquired MMG and exerted force (for up to 60% of the maximal voluntary contraction) alongside good classification accuracy (94.3%) of eight hand motions based on MMG from a single-site acquisition at the forearm. The simplification of the MMG-based HMI interface in terms of spatial arrangement is rendered possible with the designed sensor.

Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions.

It is proposed a novel instantaneous frequency estimation technology, multi-generalized demodulation transform, for non-stationary signals, whose true time variations of instantaneous frequencies are unknown and difficult to extract from the time-frequency representation due to essentially noisy environment. Theoretical bases of the novel instantaneous frequency estimation technology are created. The main innovations are summarized as: (a) novel instantaneous frequency estimation technology, multi-generalized demodulation transform, is proposed, (b) novel instantaneous frequency estimation results, obtained by simulation, for four types of amplitude and frequency modulated non-stationary single and multicomponent signals under strong background noise (signal to noise ratio is -5 dB), and (c) novel experimental instantaneous frequency estimation results for defect frequency of rolling bearings for multiple defect frequency harmonics, using the proposed technology in non-stationary conditions and in conditions of different levels of noise interference, including a strong noise interference. Quantitative instantaneous frequency estimation errors are employed to evaluate performance of the proposed IF estimation technology. Simulation and experimental estimation results show high effectiveness of the proposed estimation technology.

Research on the Potential of Spherical Triboelectric Nanogenerator for Collecting Vibration Energy and Measuring Vibration.

The traditional downhole drilling vibration measurement methods which use cable or battery as power supplies increase the drilling costs and reduce the drilling efficiency. This paper proposes a spherical triboelectric nanogenerator, which shows the potential to collect the downhole vibration energy and measure the vibration frequency in a self-powered model. The power generation tests show that the output signal amplitude of the spherical triboelectric nanogenerator increases as the vibration frequency increases, and it can reach a maximum output voltage of 70 V, a maximum current of 3.3 × 10-5 A, and a maximum power of 10.9 × 10-9 W at 8 Hz when a 10-ohm resistor is connected. Therefore, if the power generation is stored for a certain period of time when numbers of the spherical triboelectric nanogenerators are connected in parallel, it may provide intermittent power for the low-power downhole measurement instruments. In addition, the sensing tests show that the measurement range is 0 to 8 Hz, the test error is less than 2%, the applicable working environment temperature is below 100 degrees Celsius, and the installation distance between the spherical triboelectric nanogenerator and the vibration source should be less than the critical value of 150 cm because the output signal amplitude is inversely proportional to the distance.