Vibration Waveform Research Articles

Minimizing phase delay of feedback control signals for electromagnetic vibrators to reduce measurement uncertainty in ultra-low frequency vibration calibration

Suppressing the distortion of ultra-low frequency (ULF) vibration waveforms produced by an electromagnetic vibrator (EMV) presents significant challenges, leading to considerable measurement uncertainty during vibration calibration. A phase delay minimization method for feedback control signals is proposed to reduce the harmonic distortion of ULF vibration waveforms. The method quantitatively describes the influence law of the active viscoelastic approach on system frequency response characteristics. By selecting appropriate active stiffness and damping coefficients, the method minimizes the phase delay of the feedback control signal, thereby enhancing the disturbance suppression capability of the displacement and velocity composite negative feedback control. Experimental results indicate that harmonic distortion of the vibration waveform is reduced to less than 1.70 % within the ULF frequency range of 0.001 Hz ≤ f ≤ 1 Hz. Furthermore, the amplitude sensitivity calibration uncertainty, which arises from vibration waveform distortion, has been reduced to 0.038 % (k = 1.8), thereby improving the accuracy of vibration calibration.

Fault diagnosis of new type screw compressor of helium liquefier by vibration signal

A diagnostic method for screw compressor faults using vibration signals was introduced and applied to a new type of helium oil-injected screw compressor in the 80L/h helium liquefier. The study revealed that the destruction of the oil film due to impurity particles could lead to rotor rubbing and poor meshing, compromising the reliability of these compressors. Based on frequency-domain analysis, the major vibration occurred at the meshing frequency of screw rotors and a series of its harmonics. The vibration of the characteristic frequency of bearing parts also indicated that the bearing had slight wear in the early stage. The vibration waveform’s time domain diagram exhibited clear clipping, and the axis trajectory shew disorder, which were common characteristic of rotor rubbing. When compressing helium with low molecular weight, the meshing clearance, tooth tip clearance, and end clearance of the rotor were significantly lower than those of traditional refrigerants or air media. Additionally, the thermal gap caused by thermoelastic deformation was smaller due to the large adiabatic index of helium. Therefore, rubbing faults between rotors and between rotors and casing were more likely to occur. The article recommended establishing a vibration signal monitoring system, optimizing the design of helium screw rotor profiles, and setting up reliability standards for screw compressor operation, such as limiting the vibration speed to ≤ 8 mm/s. Additionally, attention should be given to cleaning gas pipelines in cryogenic engineering and monitoring compressor vibration and noise signals during operation to prevent rotor damage due to particle impurities.

Adaptive block-matching and 4D denoising scheme for a distributed vibration sensing system.

A noise reduction method based on the block-matching and 4D (BM4D) scheme is proposed to improve the signal-to-noise ratio (SNR) in distributed vibration sensing (DVS) systems. In the proposed scheme, the original Rayleigh backscattering (RBS) signal is converted into a three-dimensional image containing Rayleigh trajectory and energy information. The correlation between the time-domain and spatial-domain signals is then used to achieve the denoising operation. An experimental demonstration containing both one and two vibration points is conducted to verify the effectiveness of the proposed denoising scheme. The experimental results show that the BM4D scheme can provide higher SNR improvement than the current normalized least mean square (NLM), empirical mode decomposition combined with time-frequency peak filtering (EMD-TFPF), and BM3D schemes. Based on the BM4D scheme, the SNR is improved from 1.27 dB to 12.84 dB in the condition of one vibration point and from 6.23 dB to 20.14 dB in the condition of two vibration points. It is also indicated that the high-frequency noise of the vibration waveform after the denoising operation is mitigated by more than 30 dB, showing the potential for applications of accurate waveform characterization in cost-effective DVS systems.

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.

Determination and application study of optimal delay time for tunnel millisecond blasting based on interference vibration reduction method

In tunnel excavation, blasting is widely adopted as an efficient excavation method. However, the influence of vibration on tunnel surrounding rock and support structures during the blasting process cannot be ignored. In this study, based on the background of tunnel blasting construction, we theoretically analyze the reasonable range for selecting the optimal delay time, considering the wave superposition cancellation effect and rock fragmentation effect. We use field measured single-hole waveform and calculate superimposed predicted waveforms for different delay time through linear superposition. This allows us to determine the optimal delay time; it is then validated through numerical simulation and field experiment. The results indicate that, based on the principles of interference vibration reduction and rock fragmentation, the optimal delay time in theory should be in the range of 6.14–8.06 ms. By performing superposition calculation on the measured single-hole waveforms, we determined that the optimal delay time for continuous detonation of cut-holes is 7 ms. The delay time of 7 ms falls within a reasonable millisecond range and it is consistent with the results of numerical simulation. When the optimal delay time was applied to field blasting, the measured vibration waveforms exhibited uniform distribution. Compared to blasting without delay, the peak vibration velocity of the cut-holes decreased from 2.08 cm/s to 0.20 cm/s, and the dominant frequency band shifted from 20 Hz–60 Hz to 30 Hz–120 Hz. This achieved the desired effects of reducing vibration and enhancing frequency. These findings can serve as a reference for future similar engineering projects.

Prediction of Vibration Waveform and Division of Influenced Partitions under the Action of Blasting

To study the impact of cutting blasting on the surface, a vibration waveform prediction function was constructed, and a method of dividing the affected area was proposed. Based on the equivalent spherical charge theory, it is possible to establish a connection between the fitting coefficient and the engineering parameters in the equivalent source intensity function. Furthermore, a blasting vibration waveform function suitable for engineering can be constructed. Secondly, the reliability of the method introduced is verified through the data monitored on-site. Finally, the affected partitions of blasting vibration are divided based on the peak particle velocity and vibration displacement as standards. The results show that the vibration waveform prediction system introduced can restore the vibration waveform corresponding to cutting blasting. In addition, the zoning method can reasonably divide the scope of the affected area.

Physiological sensing system integrated with vibration sensor and frequency gel dampers inspired by spider.

Recent advances in bioelectronics in mechanical and electrophysiological signal detection are remarkable, but there are still limitations because they are inevitably affected by environmental noise and motion artifacts. Thus, we develop a gel damper-integrated crack sensor inspired by the vibration response of the viscoelastic cuticular pad and slit organs in a spider. Benefitting from the specific crack structure design, the sensor possesses excellent sensing behaviors, including a low detection limit (0.05% strain), ultrafast response ability (3.4 ms) and superior durability (>300 000 cycles). Such typical low-amplitude fast response properties allow the ability to accurately perceive vibration frequency and waveform. In addition, the gel damper exhibits frequency-dependent dynamic mechanical behavior that results in improved stability and reliability of signal acquisition by providing shock resistance and isolating external factors. They effectively attenuate external motion artifacts and low-frequency mechanical noise, resulting in cleaner and more reliable signal acquisition. When the gel damper is combined with the crack-based vibration sensor, the integrated sensor exhibits superior anti-interference capability and frequency selectivity, demonstrating its effectiveness in extracting genuine vocal vibration signals from raw voice recordings. The integration of damping materials with sensors offers an efficient approach to improving signal acquisition and signal quality in various applications.

Integrated Distributed Sensing and Quantum Communication Networks.

The integration of sensing and communication can achieve ubiquitous sensing while enabling ubiquitous communication. Within the gradually improving global communication, the integrated sensing and communication system based on optical fibers can accomplish various functionalities, such as urban structure imaging, seismic wave detection, and pipeline safety monitoring. With the development of quantum communication, quantum networks based on optical fiber are gradually being established. In this paper, we propose an integrated sensing and quantum network (ISAQN) scheme, which can achieve secure key distribution among multiple nodes and distributed sensing under the standard quantum limit. The continuous variables quantum key distribution protocol and the round-trip multiband structure are adopted to achieve the multinode secure key distribution. Meanwhile, the spectrum phase monitoring protocol is proposed to realize distributed sensing. It determines which node is vibrating by monitoring the frequency spectrum and restores the vibration waveform by monitoring the phase change. The scheme is experimentally demonstrated by simulating the vibration in a star structure network. Experimental results indicate that this multiuser quantum network can achieve a secret key rate of approximately 0.7 Mbits/s for each user under 10-km standard fiber transmission, and its network capacity is 8. In terms of distributed sensing, it can achieve a vibration response bandwidth ranging from 1 Hz to 2 kHz, a strain resolution of 0.50 , and a spatial resolution of 0.20 m under shot-noise-limited detection. The proposed ISAQN scheme enables simultaneous quantum communication and distributed sensing in a multipoint network, laying a foundation for future large-scale quantum networks and high-precision sensing networks.

Representing Fine Texture of Pencil Hardness by High-Frequency Vibrotactile Equivalence Conversion Using Ultra-Thin PZT-MEMS Vibrators.

This study aims to represent fine texture differences in pencil hardness using intensity segment modulation (ISM), a sensory equivalent conversion method of vibration from high to low frequencies. This method enables the presentation of delicate tactile sensations even with small transducers. We integrated this approach in the world's thinnest ultra-thin PZT-MEMS vibrator with a stylus-type device. The vibration waveforms of four types of pencil hardness were captured under the same conditions, and the differences in the frequency components were confirmed. We compared the fine texture feelings under raw signal, ISM, and ISM below 1 kHz conditions by conducting discrimination tests and subjective similarity evaluations. The results showed that ISM could reproduce similar feelings of the pencil hardness.

Characteristics of blasting vibration induced by short-delay cylindrical charges based on Heelan model

As the electronic detonators can control the detonation error within 1 ms, short-delay blasting was nowadays proposed to replace multi-hole simultaneous blasting to reduce the vibration hazards. In this study, the Heelan model was used to study blast-induced vibration of short-delay cylindrical charges. The influence of delay time on the vector peak particle velocity ( VPPV) of superimposed vibration waveforms was analyzed and the calculating formula of the shortest delay time between adjacent holes based on vibration reduction was established. It is found that as the delay time increases, the overlapping area of VPPV becomes further away from the explosion source. The main influencing factors for the shortest delay time between holes include the distance between the monitoring point and the explosion source, the difference between P wave and S wave velocities, and the duration of S wave in the first and second explosion holes. As the distance from the explosion source increases, the shortest inter hole delay time based on vibration reduction also increases. The research results have guiding significance for the control of blasting vibration in underground mines.

Ultrasensitive Soft Sensor from Anisotropic Conductive Biphasic Liquid Metal-Polymer Gels.

Subtle vibrations, such as sound and ambient noises, are common mechanical waves that can transmit energy and signals for modern technologies such as robotics and health management devices. However, soft electronics cannot accurately distinguish ultrasmall vibrations owing to their extremely small pressure, complex vibration waveforms, and high noise susceptibility. This study successfully recognizes signals from subtle vibrations using a highly flexible anisotropic conductive gel (ACG) based on biphasic liquid metals. The relationships between the anisotropic structure, subtle vibrations, and electrical performance are investigated using rheological-electrical experiments. The refined anisotropic design successfully realized low-cost flexible electronics with ultrahigh sensitivity (Gauge Factor: 12787), extremely low detection limit (strain: 0.01%), and excellent frequency recognition accuracy (>99%), significantly surpassing those of current flexible sensors. The ultrasensitive flexible electronics in this study are beneficial for diverse advanced technologies such as acoustic engineering, wearable electronics, and intelligent robotics.

Graph neural network-based bearing fault diagnosis using Granger causality test

Detecting bearing faults helps ensure the healthy operation of machinery and prevents serious accidents. However, fault diagnosis method based on deep learning relies on the correlation between the extracted vibration signal features. It does not consider the causal relationship between fault, noise, and vibration waveform changes, resulting in lower bearing fault diagnosis accuracy under realistic working conditions. This study proposes a graph neural network (GNN) method based on the Granger causality test for bearing fault detection called GCT-GNN to address this issue. The proposed method first performs feature transformation on the original signals to extract time-domain and frequency-domain features, forming a feature matrix. Then, spectral analysis is conducted on both faulty signals with noise and healthy signals to calculate the lag order between them. Subsequently, the Granger causality test is employed to quantify the impact of faults and noise on signal changes, and the quantified results are used to calculate weights, constructing an adjacency matrix. The completed adjacency matrix and feature matrix are input into the GNN for feature mapping, last classifying the bearing fault data. In this paper, five models, Deep residual shrinkage Network (DRSN), GNN, Support Vector Machines(SVM), Random Forests (RF), and Convolutional Neural Network(CNN) were selected, and comparative experiments were carried out on two public data sets. The results show that, compared with other models, GCT-GNN has better anti-noise ability and is better than other models in various fault diagnoses.

Signal processing and acoustic calibration method of millimeter-wave vibration sensor

Millimeter-wave sensors can be utilized as non-contact vibration sensors. Applications of millimeter-wave vibration sensors are the vital sensing of humans (heartbeat, respiration, body motion), factory machines, and vibration sensing of social infrastructures, such as buildings and bridges. Millimeter-wave vibration sensors can simultaneously detect the position and the waveforms of the vibration displacements of vibration objects. The primary signal processing of millimeter-wave sensors is two-dimensional fast Fourier transform (2D-FFT), detecting the arrival direction (DOA) and processing the micro-Doppler signals. The detectable areas of the millimeter-wave vibration sensors are defined using the parameters related to these three signal-processing blocks. Measured vibration waveforms by millimeter-wave vibration sensors include all components of the vibration displacements in the defined detectable area. Therefore, the waveform of the vibration displacement is influenced by the definition of the detectable area and the vibration form of the vibrating object. The measured values of millimeter-wave vibration sensors must be calibrated with attention to these influences. The vibration waveforms of vibrating objects are estimated by acoustic measuring methods, such as the laser Doppler vibrometer and the parallel-phase shifting interferometry. This paper describes calibration methods of millimeter-wave vibration sensors employing these two measuring methods.

Design and Experiment of a Multi-DOF Shaker Based on Rotationally Symmetric Stewart Platforms with an Insensitive Condition Number

This study proposes a method for designing a class of rotationally symmetric Stewart platforms (RSSPs) with an insensitive condition number (ICN), which is used to minimize the condition number to achieve a high accuracy for a multi-degree-of-freedom (multi-DOF) shaker. Considering the rotational symmetry of RSSPs, an analytical relationship between the architecture parameters and transfer coefficients is first established. Then, the decoupling conditions of the RSSPs are derived, and the transfer coefficient formulas are simplified by the given decoupling conditions and iso-length assumption. Following further analyses and discussions, the ICN condition and analytical form of the condition number are provided. The area of the ICN (AICN) is, subsequently, derived to evaluate the insensitivity of the condition number. To validate the effectiveness of the method, a design example (ICN-RSSP), along with a numerical analysis, is implemented, and, finally, a multi-DOF shaker is developed. The results of the numerical analysis show a smaller condition number and a larger AICN than those of the RSSP, for comparison. And the experiment results of the multi-DOF shaker show a high accuracy of vibration waveform reproduction. The method can reduce the condition number of RSSPs, improve the insensitivity, and further improve the accuracy of the multi-DOF shaker.

Numerical and experimental investigations on dynamic behaviors of a bolted joint rotor system with pedestal looseness

Pedestal looseness is a common fault in rotating machines. To enhance the economy and convenience of the assembly of the aero-engine rotor system, the bolted joint structures are a useful tool for fastening multiple parts of different materials into an integrated system. To our knowledge, the time-varying bending stiffness and looseness fault at the pedestal significantly influence rotor dynamics. The present work aims to gain insight into the dynamic behaviors and mechanical behaviors of a rotor-bearing system with a bolted joint structure subjected to a pedestal looseness fault. Firstly, the dynamic model of a bolted joint rotor-bearing system supported by pedestals was set up taking into account the time-varying bending stiffness of bolted joint and the pedestal looseness fault. The feature of the pedestal looseness fault that occurs in a bolted joint rotor system was investigated by comparing the variation ranges of bending stiffness and dynamic responses. An experimental study was then performed using a rotor-bearing test rig equipped with a bolted joint and pedestals. Finally, dynamic phenomena such as offset of the equilibrium position of the vibration waveform, appearance of continuous frequency spectra, and irregular shaft orbits can be known as the dynamic features for the pedestal looseness fault.

A harmonic suppression method for low-frequency electromagnetic vibrators

Due to various nonlinear factors in an ordinary electromagnetic vibrator, the distortion of its output vibration waveform will always happen, especially at low frequencies (≤20 Hz), which blocks its application in a lot of area. To improve the acceleration waveform precision and reduce distortions at low frequencies, a waveform harmonic suppression method for low-frequency electromagnetic vibrators is proposed. After extracting the harmonic components in the output acceleration waveforms, a digital composite signal with harmonic compensation components is prospected according to the frequency response characteristic of the vibrator, and then sent back to drive the vibrator, which results in that the harmonic components in the formal waveform is suppressed. The proposed method was verified by simulations and experiments, and results show that the total harmonic distortions (THDs) of accelerations are reduced effectively at low frequencies, typically from 23% to less than 2% at the frequency as low as 0.1 Hz. The method is stable and robust because there is no real-time feedback loop in the system.

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

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

Simulation and Optimization of Hemispherical Resonator's Equivalent Bottom Angle for Frequency-Splitting Suppression.

As an inertial sensor with excellent performance, the hemispherical resonator gyro is widely used in aerospace, weapon navigation and other fields due to its advantages of high precision, high reliability, and long life. Due to the uneven distributions of material properties and mass of the resonator in the circumferential direction, the frequencies of the two 4-antinodes vibration modes (operational mode) of resonator in different directions are different, which is called frequency splitting. Frequency splitting is the main error source affecting the accuracy of the hemispherical resonator gyro and must be suppressed. The frequency splitting is related to the structure of the resonator. For the planar-electrode-type hemispherical resonator gyro, in order to suppress the frequency splitting from the structure, improve the accuracy of the hemispherical resonator gyro, and determine and optimize the equivalent bottom angle parameters of the hemispherical resonator, this paper starts from the thin shell theory, and the 4-antinodes vibration mode and waveform precession model of the hemispherical resonator are researched. The effect of the equivalent bottom angle on the 4-antinodes vibration mode frequency value under different boundary conditions is theoretically analyzed and simulated. The simulation results show that the equivalent bottom angle affects the 4-antinodes vibration mode of the hemispherical resonator through radial constraints. The hemispherical resonator with mid-surface radius R=15 mm and shell thickness h=1 mm is the optimization object, and the stem diameter D and fillet radius R1 are experimental factors, with the 4-antinodes vibration mode frequency value and mass sensitivity factor as the response indexes. The central composite design is carried out to optimize the equivalent bottom angle parameters. The optimized structural parameters are: stem diameter D=7 mm, fillet radii R1=1 mm, R2=0.8 mm. The simulation results show that the 4-antinodes vibration mode frequency value is 5441.761 Hz, and the mass sensitivity factor is 3.91 Hz/mg, which meets the working and excitation requirements wonderfully. This research will provide guidance and reference for improving the accuracy of the hemispherical resonator gyro.

Broad-bandwidth and accurate optical vibration sensing by using FDM Φ-OTDR with linear regression analysis of multi-frequency phase responses.

We demonstrate Φ-OTDR distributed acoustic sensing (DAS) that realizes both a broad bandwidth for the vibration frequency and wide dynamic range for the vibration amplitude based on optical frequency-division-multiplexing (FDM). We enhance the sampling rate of DAS by using FDM while suppressing waveform distortion in time domain (spurious components in spectral domain) caused by sensor nonlinearity inherent in Φ-OTDR, thus improving dynamic range, with linear regression analysis of multi-frequency phase responses. The proposed method compares the phase offsets and responses of each frequency to those of a common reference frequency and uses the information to calibrate each of the different responses. We clarify the physical origin of the problem and the validity of the proposed method in both simulations and experiments. Experimental results show an improvement in dynamic range by above 8 dB on average for vibration waveforms with nɛ-order amplitudes and kHz-order frequencies over 10-km single-mode fiber.

A vibration model of a flexible rotor-bearing system considering the defect in a double-row cylindrical roller bearing

Vibration analysis of double-row cylindrical roller bearing systems is useful for controlling the vibrations of rotating transmission systems. However, most current works only formulated the rotor system with single-row cylindrical roller bearings. Moreover, the vibration characteristics of the rotor system with defective double-row cylindrical roller bearings are not clearly. To overcome this problem, a vibration model of a flexible rotor system with the defective double-row cylindrical roller bearing is proposed in this work. The effects of the speed and defect on the vibrations of flexible rotor systems are studied. The vibrations from flexible and rigid models are compared under different rotation speeds. Note that the vibration waveforms from rigid and flexible models are similar. The vibrations of different nodes are different under different speeds, which cannot be formulated by the previous rigid models. The vibration model can better represent the vibrations of rotor systems with and without the defect. Moreover, this paper can provide a comprehensive analytical method for vibrations and acoustics of flexible rotor systems with the double-row cylindrical roller bearings.