Resonant Frequency Band Research Articles

Multiple-input multiple-output dual-band dual-circularly polarised SIW cavity-backed slot antenna for satellite and 5G systems

ABSTRACT A dual-band 2 1 multiple-input-multiple-output (MIMO) antenna based on substrate integrated waveguide (SIW) cavity for both satellite (in K-band) and 5 G applications is proposed. Initially, the SIW cavity consisting of metallic vias on all four sides is implemented. For MIMO configuration, this cavity is divided into two smaller SIW cavities using a row of metallic vias and excited using the coaxial feed. By etching an asymmetric cross-slot (AXS) with tuned dimensions on top of the SIW cavity, a dualsense of circular polarisation (CP) in both frequency bands is obtained. The fabricated prototype of the proposed SIW antenna shows impedance bandwidth (IBW) of 15.36% (22.60–26.36 GHz; BandI) and 4.64% (29.04–30.42 GHz; BandII). The completely overlapping axial-ratio bandwidth (ARBW) with IBW of 15.16% (22.62–26.33 GHz) and 3.10% (29.20–30.12 GHz) with a peak gain of 12.47 and 7.71 dBi is obtained in BandI and Band II, respectively. The proposed antenna shows front-to-back ratio (FBR) of more than 20 dB in both resonating frequency bands. The measured results of the proposed MIMO antenna agree well with the simulation.

Fast nonlinear Hoyergram for bearings fault diagnosis under random impact interference

Random impact interference has always been an important subject in fault diagnosis. In the fast kurtogram (FK), kurtosis is a sparsity index used to locate optimal resonance frequency bands. However, the shortcomings of the kurtosis measure are a tendency to select the random impact with a large amplitude and a relatively weak sparse measure ability, which reduces the accuracy and anti-interference of the FK method. To overcome the effects of random impact interference, this paper proposes a novel bearing fault diagnosis method named the fast nonlinear Hoyergram (FNH), in which the nonlinear Hoyer index is employed to replace kurtosis to improve the fault representation capability under random impulse interference. Firstly, Z-score normalization and a generalized nonlinear sigmoid activation function are used for signal preprocessing, and the scale distribution of the signal is changed to weaken the impact of random impact interference. Secondly, the Hoyer index, which can be viewed as the normalized form of the norm, is used to replace kurtosis to improve the sparsity measure capability. Thirdly, in the Hoyergram, the frequency band with the largest Hoyer value can be chosen as the best resonance frequency band for the squared envelope analysis. Finally, the proposed FNH is compared with the FK method through simulation and experimental signals, and the effectiveness of the proposed method is verified.

A novel rolling bearing fault diagnosis method based on generalized nonlinear spectral sparsity

In the fast kurtogram (FK), kurtosis is used as an indicator to locate the fault frequency band, and is widely aplied to fault diagnosis. However, kurtosis has been proven to favor a single large impulse rather than the required small fault characteristics, especially in the strong interference environment. To eliminate the impact of large-amplitude impact and further improve the accuracy of fault extraction, a method based on generalized nonlinear spectral sparsity (GNSS) is proposed for fault diagnosis of bearings. First, Z-score normalization and generalized nonlinear sigmoid activation function are used for signal preprocessing, and the scale distribution of the signal will be changed to eliminate the effects of large amplitude shocks under noisy environment. Then, to improve the sparsity measure capability, an improved L3/2 norm is used to replace kurtosis as the basis for selecting the best resonance frequency band. Finally, the effectiveness of the GNSS is verified by simulation data and experimental data. Compared with FK method, the performance of fault extraction of the proposed method is significantly improved, especially for the interference of abnormal impact.

8-Plate Multi-Resonant Coupling Using a Class-E2 Power Converter for Misalignments in Capacitive Wireless Power Transfer

Misalignment is a common issue in wireless power transfer systems. It shifts the resonant frequency away from the operating frequency that affects the power flow and efficiency from the charging station to the load. This work proposes a novel capacitive wireless power transfer (CPT) using an 8-plate multi-resonant capacitive coupling to minimize the effect of misalignments. A single-active switch class-E2 power converter is utilized to achieve multi-resonance through the selection of different resonant inductors. Simulations show a widening of the resonant frequency band which offers better performance than a regular 4-plate capacitive coupling for misalignments. The hardware results of the 8-plate multi-resonant coupling show an efficiency of 88.5% for the 20.8 W test, which is 18.3% higher than that of the regular 4-plate coupling. Because of the wider resonant frequency band {455–485 kHz}, compared with the regular 4-plate coupling, the proposed design minimized the output voltage drop by 15% for a 10% misalignment. Even for large misalignments, the 8-plate performance improved by 40% compared with the 4-plate coupling.

Bionic paw-inspired structure for vibration isolation with novel nonlinear compensation mechanism

Inspired by the compensation effect of fat pad on toes in a paw of digitigrade, a unique paw-inspired structure (PIS) is proposed and systematically investigated to explore its advantages in passive vibration isolation. The PIS consists of two key parts, one is the toe-like structure (TLS) simulated by two rods and a spring, and the other is fat pad mimicked by a pair of repulsive magnets. Based on the principle of virtual work, the static stiffness characteristics of the TLS are firstly analyzed. Then, the stiffness compensation mechanism of fat pad to toe is comprehensively studied. The hardening stiffness of the fat pad can compensate the negative stiffness of the TLS so that the PIS can realize quasi-zero stiffness (QZS) over large displacement range. It is for the first time to reveal this nonlinear stiffness compensation mechanism, which is essentially different from the conventional realization of QZS (connecting negative stiffness mechanism and linear spring in parallel). A dynamic model is established to estimate the vibration isolation performance. The displacement transmissibility derived by harmonic balance method (HBM) indicates that the PIS can achieve low resonance frequency and wide effective vibration isolation frequency band. Static tests are completed to verify effectiveness of the stiffness compensation mechanism. Tests under different external excitations (including periodic, sweep and random) show that the PIS can effectively suppress frequency components above 4 Hz. The PIS provides a new low-frequency vibration isolation method with high application prospects. And the proposed nonlinear stiffness mechanism can also be extended as a guideline to design nonlinear vibration isolators.

Detection of Internal Defects in Concrete and Evaluation of a Healthy Part of Concrete by Noncontact Acoustic Inspection Using Normalized Spectral Entropy and Normalized SSE.

Non-destructive testing, with non-contact from a remote location, to detect and visualize internal defects in composite materials such as a concrete is desired. Therefore, a noncontact acoustic inspection method has been studied. In this method, the measurement surface is forced to vibrate by powerful aerial sound waves from a remote sound source, and the vibration state is measured by a laser Doppler vibrometer. The distribution of acoustic feature quantities (spectral entropy and vibrational energy ratio) is analyzed to statistically identify and evaluate healthy parts of concrete. If healthy parts in the measuring plane can be identified, the other part is considered to be internal defects or an abnormal measurement point. As a result, internal defects are detected. Spectral entropy (SE) was used to distinguish between defective parts and healthy parts. Furthermore, in order to distinguish between the resonance of a laser head and the resonance of the defective part of the concrete, spatial spectral entropy (SSE) was also used. SSE is an extension of the concept of SE to a two-dimensional measuring space. That is, based on the concept of SE, SSE is calculated, at each frequency, for spatial distribution of vibration velocity spectrum in the measuring plane. However, these two entropy values were used in unnormalized expressions. Therefore, although relative evaluation within the same measurement surface was possible, there was the issue that changes in the entropy value could not be evaluated in a unified manner in measurements under different conditions and environments. Therefore, this study verified whether it is possible to perform a unified evaluation for different defective parts of concrete specimen by using normalized SE and normalized SSE. From the experimental results using cavity defects and peeling defects, the detection and visualization of internal defects in concrete can be effectively carried out by the following two analysis methods. The first is using both the normalized SE and the evaluation of a healthy part of concrete. The second is the normalized SSE analysis that detects resonance frequency band of internal defects.

An improved Autogram and MOMEDA method to detect weak compound fault in rolling bearings.

When weak compound fault occurs in rolling bearing, the faint fault features suffer from serious noise interference, and different type faults are coupled together, making it a great challenge to separate the fault features. To solve the problems, a novel weak compound fault diagnosis method for rolling bearing based on improved Autogram and multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is proposed. Firstly, the kurtosis index in Autogram is modified with multi-scale permutation entropy, and improved Autogram finds the optimal resonance frequency band to preliminarily denoise the weak compound fault signal. Then, MOMEDA is performed to deconvolute the denoised signal to decouple the features of compound fault. Finally, square envelope analysis is applied on the separated deconvoluted signals to identify different type faults according to the fault characteristic frequencies in the spectrums. The proposed method is performed to analyze the simulated signal and experimental datasets of different types of rolling bearing weak compound faults. The results indicate that the proposed method can accurately diagnose the weak compound faults, and comparison with the analysis results of parameter-adaptive variational mode decomposition algorithm verifies its effectiveness and superiority.

Nonlinear compensation method for quasi-zero stiffness vibration isolation

Various quasi-zero stiffness (QZS) vibration isolators have been emerged in recent years and applied successfully in low-frequency vibration isolation. However, in most cases, the general approach to achieving QZS is still limited to compensating the negative stiffness of the bistable structure by linear springs. Here, a nonlinear compensation method (NCM) for realizing QZS is developed and the corresponding methodology is systematically investigated. Specifically, for a certain negative stiffness structure (not limited to bistable structure), QZS can be obtained by utilizing hardening stiffness to compensate. A confirmatory QZS vibration isolation system is established to fully verify the effectiveness of the NCM. The confirmatory system exploits rhombus structure to generate nonlinear negative stiffness, which can be compensated by nonlinear positive stiffness (provided by repulsive magnets). The static analysis is completed to reveal the inherent stiffness compensation mechanism. The dynamic and experimental results demonstrate that the proposed QZS system has low resonant frequency and wide effective vibration isolation frequency band. The NCM has reference significance in realizing QZS and is beneficial to develop diversified low-frequency vibration isolators.

Fabrication of microchannel and diaphragm for a MEMS acoustic sensor using wet etching technique

This paper reports a new technique for fabrication of diaphragm and microchannel in a single step for the development of a piezoelectric MEMS acoustic sensor. It describes the design of the sensor based on ZnO to be utilized for aero-acoustic measurements. A primary requirement for such devices is a high maximum sound pressure level [(SPL) ~180 dB] and flat frequency response in the audio band (20 Hz - 20 kHz). The Si-diaphragm thickness was optimized for the desired SPL range using Coventorware. The complete frequency response of the structure was determined using analytical formulations based on lumped element modeling (LEM). The fabricated device was tested using Laser Doppler Vibrometer (LDV). The lower cut-off frequency, bandwidth, resonance frequency and flat band sensitivity of the optimized device have been found to be 26.3 Hz, 40.0 kHz, 78.688 kHz and 148 μV/Pa respectively.

Fully interpretable neural network for locating resonance frequency bands for machine condition monitoring

In recent years, various neural networks have been developed to process vibration signals for machine condition monitoring. Nevertheless, the physical interpretation of neural networks is still on-going and not fully explored. This paper aims to design a fully interpretable neural network for machine condition monitoring from the aspects of signal processing and physical feature extraction. The main idea of the fully interpretable neural network is to extend the uninterpretable structure of extreme learning machine (ELM) to an interpretable structure for machine condition monitoring. From the aspect of signal processing, wavelet transform, square envelope and Fourier transform are incorporated into the input layer of the original ELM to extract repetitive transients, localize informative frequency bands for an enhancement of a signal-to-noise ratio, and realize square envelope spectra for exhibiting cyclo-stationarity of repetitive transients. Hence, the first to four layers of the proposed network are physically interpretable. From the aspect of physical feature extraction, popular sparsity measures are innovatively incorporated into all random nodes in the single-hidden layer of the original ELM to interpret the use of all hidden nodes in the fifth layer of the proposed network to characterize cyclo-stationarity of repetitive transients. The significance of this paper is to show that signal processing algorithms and physical feature extraction can be reformulated as the architecture of an interpretable neural network to automatically localize informative frequency bands for machine condition monitoring. This paper attempts to inspire researchers in the field of signal processing and machine learning to think about the design of more advanced interpretable neural networks for machine condition monitoring.

Enhanced bearing fault diagnosis using integral envelope spectrum from spectral coherence normalized with feature energy

Enhanced envelope spectrum (EES) and improved envelope spectrum (IES) generated from spectral coherence (SCoh) are proven to be more robust fault detection tools than squared envelope spectrum (SES). However, EES cannot effectively detect the fault-induced components under strong interference noise and IES can only capture the information of a fault-sensitive resonance spectral frequency band. To overcome these problems, weighted combined envelope spectrum (WCES) from SCoh is proposed as a novel fault detector. WCES integrates the fault components distributed in multiple resonance frequency bands using normalized feature energy and removes the envelope spectrum slices with less fault information to exclude disturbance noises. The performance of WCES is validated using simulations and experiments and compared with the advanced envelope spectra. The results demonstrate that WCES can effectively detect bearing faults under strong interference noise and multiple resonances compared with the SES, EES and IES, and has potential application value in bearing diagnostics.

CPW-Fed Penta Band Monopole Antenna for Multiservice Wireless Applications

A compact triple T-shaped stub with meander loaded strip antenna for penta band applications is proposed. The rectangular patch antenna with meandered and open-ended slot cuts is utilized to realize four operating bands at 2.45 GHz, 3.1 GHz, 5.3 GHz, and 6.5 GHz with an impedance bandwidth of 400 MHz (2.15-2.550 GHz), 1000 MHz (2.7-3.7 GHz), 200 MHz (5.4-5.6 GHz), and 200 MHz (6.4-6.6 GHz), respectively. For an additional resonance frequency, the length of the central T-shaped stub is slightly modified which causes the variation in the current distribution. As a result, the resonance frequency of 5.5 GHz is divided into two resonance frequency bands which are operating at 5.25 GHz and 5.85 GHz with an impedance bandwidth of 100 MHz (5.25-5.35 GHz) and 200 MHz (5.75-5.95 GHz), respectively. Furthermore, a parametric reflection coefficient and surface current distribution analysis is carried out to understand the strip and slot behavior at resonance frequency bands. Finally, a prototype is fabricated and its reflection coefficient, gain, and radiation pattern are measured. The experimental result shows that the proposed antenna is reliable for penta band applications.

Research on Centroid Distribution and Dynamic Characteristics of Irregular Tooth End Milling Cutters

For irregular end milling cutters, the incomplete equality of the pitch angle and helix angle will lead to an uneven mass distribution. The problems of centroid distribution caused by this, and whether it would affect the dynamic characteristics of milling cutters, have not been systematically studied. In this paper, through the proposed mathematical model, the centroid positions of each radial section of four types of end milling cutters, with equal overall eccentricities and different structures, are calculated, respectively. The centroid distribution of end milling cutters is studied and analyzed. Combined with finite element analysis, the vibration mode, frequency, and resonance frequency band of each type of end milling cutter, under the same dynamic excitation, is obtained. Based on a study of the dynamic characteristics of various types of end milling cutters, it is found that the response displacement of the variable pitch variable helix end milling cutter is the smallest, which is 0.043800 mm. With the same level of accuracy, its dynamic performance is the best. On the premise of not changing the overall eccentricity of the end milling cutter, a new idea for the structural design to improve the dynamic characteristics of the end milling cutter is provided.

A promising new tool for fault diagnosis of railway wheelset bearings: SSO-based Kurtogram

A promising method is proposed systematically to select an accurate resonance frequency band and separate refined resonance response from periodic excitation in this study. This work expanded the short-time Fourier transform (STFT)- and wavelet transform (WT)-based Kurtograms and developed a hybrid signal separation operator (SSO)–spectral kurtosis computational scheme to implement Kurtogram by introducing the SSO method—SSO-based Kurtogram. The ability to accurately extract the refined resonance frequency band of SSO greatly improves its adaptivity for engineering applications. The effectiveness of the SSO-based Kurtogram is studied by using a bearing fault simulation signal, and the influence of window function on the detection effect of the proposed method is explored. Furthermore the validity of the SSO-based Kurtogram for bearing fault detection is verified by a set of railway wheelset-bearing experiments on the wheelset running-in testbed bench. Experimental results show that the SSO-based Kurtogram performs highly in detecting various kinds of single and compound faults of bearings. Compared with the WT- and STFT-based Kurtogram, the proposed method has obvious advantages in terms of effectiveness and visual inspection ability. In engineering practice, a railway wheelset-bearing-fault experiment on an in-service high-speed train in the real world is taken as a case study, which makes the verification of SSO-based Kurtogram more convincing and demonstrates the practical engineering value of the proposed method. The results show that in case of equal effectiveness, SSO-based Kurtogram has an absolute advantage in the visual inspection ability, embodied in eliminating other vibrations unrelated to the target fault and making the fault feature frequency and its harmonics remarkable.

Automatic Bayesian modal identification method for structures based on blind source separation

ABSTRACT An automatic Bayesian modal identification method is proposed using the blind source separation (BSS) technique. The determination of resonant frequency bands, which is the initial step of the fast Bayesian FFT (fast Fourier transform) method, requires human intervention and hence, is labour-intensive and subjective. To automate the determination of resonant frequency bands, the BSS technique is introduced here for band selection process. After estimating the modal responses from measured data, the hump criterion curves are drawn to sharpen the border of the resonant humps. And the frequency bands can thus be determined automatically by locating the resonant humps with a peak picking algorithm. The proposed method was validated with a simulated 6- degree-of-freedom spring-mass model, a simulated 4-story benchmark model, the Heritage Court Tower in Vancouver, Canada. The robust identification results indicate that the proposed method can identify automatically and accurately the physical modes together with their uncertainty.

An electrically small inverted L‐shaped asymmetric coplanar strip‐fed antenna with split‐ring resonator for multiband applications

SummaryIn this paper, an electrically small inverted L‐shaped asymmetric coplanar strip‐fed antenna with a split‐ring resonator structure is proposed for multiband applications. It possesses an extended monopole antenna and a rectangular split‐ring resonator (RSRR) structure. A monopole is responsible for generating the first and last resonance frequencies. Similarly, the RSRR structure produces center frequency (5.5 GHz) among three resonance frequency bands and improves impedance matching at a higher frequency. The antenna has an electrical size of 0.176 λ0 × 0.096 λ0 × 0.012 λ0. The proposed antenna has a triband resonance response at 2.45, 5.5, and 7.5 GHz with a bandwidth of 560 MHz, 680 MHz, and 3 GHz, respectively, which covers WiBro (2.3 GHz), WLAN (2.4/5.2 GHz), WiMAX (2.5/5.5 GHz), X‐band downlink (7.4 GHz), and ITU band (8.5 GHz). The antenna design is simulated and validated with measured results and has better radiation characteristics in all the required frequency bands. The presence of metamaterial property in the proposed RSRR is analyzed. The design is an electrically small antenna, and it has a radian sphere (ka) = 0.64. Further, the proposed antenna performances are compared with the various existing literature.

Blade damage monitoring method base on frequency domain statistical index of shaft’s random vibration

The shaft vibration based blade damage monitoring method has become another research focus in addition to tip timing technology because of its simple testing system. However, how to extract the accurate and effective blade damage information from the vibration response of the shaft is the key to the implementation of this method. In this paper, a blade damage monitoring method based on the frequency domain statistical index of shaft’s random vibration is proposed. Firstly, a continuum dynamic model of blade disk shaft system is established and verified for the statistical feature analysis of rotor system with blade damages, in which the coupling among shaft’s bending, torsion and blade’s bending is considered. Then, base on the vibration response from the dynamic model, a blade damage monitoring method is constructed, in which the harmonic components of forced vibrations are removed, the random vibration component is retained, and the mean frequency and bandwidth index in the resonance frequency band of the random torsional vibration is adopted as the blade damage monitoring index. After that, a blade-disk-rotor system test bed is designed and the vibration measurement system is constructed. The experimental results verify the effectiveness of the proposed methods and indicators. To sum up, the verified dynamic model can provide abundant simulation data under various working conditions and various fault parameters for the research of diagnosis index and methods. The random excitation is inherent in the running rotor system, so the random vibration based blade damage monitoring method is easy to implement. The statistical index based method is a simple and effective way to extract the damage information of blade in random vibration. Therefore, the research results of this paper can provide important supplements to the blade damage monitoring.

Improved VMD-FRFT based on initial center frequency for early fault diagnosis of rolling element bearing

The extraction of weak fault signatures with periodic impulse characteristics is a crucial aspect of detecting an early fault of bearing. In order to suppress the interference of background noise to the weak fault signatures extraction by variational mode decomposition (VMD), some scholars recently proposed to use fractional Fourier transform (FRFT) to make the weak fault signatures concentrate more energy in the narrowband, which is called VMD-FRFT. Nevertheless, VMD-FRFT is more sensitive to the initial center frequency (ICF) than VMD according to our study, which will make it derive undesirable mode components due to unreasonable ICFs. Inspired by the resonant demodulation method to find the appropriate frequency band for demodulation, an improved VMD-FRFT with the guidance of ICF is proposed, which is to take the center frequencies corresponding to K selected frequency bands as the initial values of VMD-FRFT. Hence, the modal components hidden in multiple resonant frequency bands can be obtained in terms of performing iterative optimization. In this paper, a novel indicator named reciprocal of spectral autocorrelation smoothness index being sensitive to the periodic impulses is introduced to detect resonance frequency bands. Both simulated and experimental examples are used to verify the proposed method. The results show that the proposed method can effectively identify weak faults and detect bearing faults at an earlier time than other methods such as Infogram, reciprocal of spectral smoothness index and improved VMD.

A highly selective absorber based on Archimedes-spiral-shaped metasurfaces

In this paper, a chiral metamaterial absorber based on an Archimedes spiral structure is designed whose operating band can be extended by adjusting array elements and array layout factors. Thanks to its circular dichroism, it is highly selective for left-handed and right-handed circular polarized (LCP and RCP) incident waves at 19.172 GHz, absorbing 95% for LCP, while RCP is basically not absorbed. Meanwhile, a 2 × 2 unit structure is constructed, achieving efficient absorption ranging from 17.55 to 18.13 GHz by overlapping the resonant frequency bands of four different structures, whose relative bandwidth is six times the original single frequency. Then, because of the particularity of the helix, the structure has the characteristics of large-angle incident stability and 360° insensitivity in polarization. Ultimately, we analyze the absorption mechanism arising from the current and electric field distribution of the topological arrangement. In the model improvement, the size can be shrunk proportionally to realize the absorption of 1.337 THz waves. This design can be used in military stealth, photon detection, energy collection, and other scenarios.

Modified minkowski fractal multiband antenna with circular-shaped split-ring resonator for wireless applications

In this article, a modified Minkowski fractal antenna with a circular-shaped split-ring resonator (CSSRR) structure is proposed for wireless applications. Fractal geometry is accountable for creating dual-band resonance, and CSSRR is responsible for obtaining a middle resonance frequency band. The proposed antenna has a compact dimension of 23.5 × 26.5 × 1.6 mm3 to be fabricated and measured. Antenna iterations performed to achieve the desired frequency band. Antenna design has three resonance frequency bands at 2–2.7 GHz (700 MHz), 3.4–3.6 GHz (200 MHz) and 5.45–5.95 GHz (500 MHz), respectively. It can be used to cover 2.4/5 GHz wireless local area network (WLAN), 2.5/3.5 GHz wireless interoperability for microwave access (WiMAX), 2.1/2.3 GHz 3 generation (3G)/4 generation (4G) and 5.9 GHz safety applications. It is observed that the proposed antenna has good radiation characteristics in both E-plane and H-plane in the desired frequencies. Further, it has better antenna parameters than the various antenna designs reported in the literature.