Sideband Components Research Articles

URANS Prediction of the Hydrodynamic Interactions of Two Ship-like Floating Structures in Regular Waves

A side-by-side configuration of floating structures is commonly used in ocean exploration practices, such as offshore vessels for loading and offloading, floating cranes, and offshore floating wind turbines. Computational Fluid Dynamics (CFD) method is current practice for the analysis of hydrodynamic interactions of the side-by-side vessels. The purpose of this study is yo carry out a benchmark study of CFD method applied for the above analysis. URANS CFD method was applied utilizing a k-ε turbulence model and a volume of fluid (VOF) method to capture the free surface. Different ratios of wave length to vessel’s length and different gaps between between the vessels were considered in the study. Simulation results show that the wave length to vessel’s length ratio /L affects significantly the wave pattern around the vessels and inside the gap. For the shorter waves, the gap influences the wave pattern both inside and outside the gap. Further, the pressure distribution on the keel surface of the vessels is asymmetric about the vertical center plane along the vessel, which resulted in roll motion eventhough the vessel is in head seas. Roll motion was observed in all gap variations considered. Amplitude modulation was observed in the heave and pitch motions, while generation of side-band frequency components were observed in the roll motion, which indicate a non-linear fluid-structure interaction.

Stiffness Modeling of Tooth Interior Fatigue and Tooth Flank Fracture and Their Fault Characteristics in Electromechanical Coupling Systems

Tooth flank fracture (TFF) and tooth interior fatigue fracture (TIFF) usually occur on case-harden gears in electromechanical coupling systems, both starting from the core caused by metal fatigue. The cracks propagate rapidly compared with the total life of a gear, so that it is necessary to detect and identify the faults in time when they take place in order to avoid danger. In this paper, the time-varying mesh stiffness model of two types of faults is established by the potential energy method and validating by the finite element method. Based on the stiffness model, the influence of faults on the electromechanical system and their fault characteristics are analyzed, which provides a theoretical basis for the health detection of electromechanical coupling systems. The results indicate that in the early stage of the three faults, i.e., tooth root fracture, tooth interior fatigue fracture, and tooth flank fracture, it is hard to discriminate the faults. But after the second stage, the faults can be distinguished by the vibration amplitude, frequency band components, and phase diagrams. The TFF can be discerned into different stages by frequency domains and phase diagrams. When the fracture occurs completely, three faults can be easily distinguished by the time domain and phase diagram. In the frequency domain, the TRF can also be distinguished from the other two faults by referring to the sideband component near the meshing frequency.

Synthetic Meta-Signal Observations: The Beidou Case.

A Global Navigation Satellite System (GNSS) meta-signal is obtained when two or more side-band components from different frequencies are jointly processed as a single entity. This requires advanced signal processing techniques able to cope with the subcarrier, generated by the interaction of the side-band components, and handle possibly multi-peaked ambiguous correlation functions. An alternative approach to meta-signal processing is to reconstruct meta-signal observations using side-band measurements. Meta-signal high-accuracy pseudoranges can be reconstructed from the side-band code and carrier observations. The success of the reconstruction depends on several factors, including the frequency separation of the side-band components and the presence of measurement biases. The Beidou Navigation Satellite System (BDS), with its second- and third-generation signals, provides a wide range of components with various frequency separations. In this paper, we experimentally investigate the performance and limitations of the measurement reconstruction approach using Beidou observations. When the B1I and B1C components are considered, their reduced frequency separation leads to unambiguous measurements fully exploiting the potential of meta-signals. For larger frequency separations, jumps and discontinuities are observed in the position domain, which is a major limiting factor of this type of approach.

Detection of Broken Rotor Bars in Cage Induction Motors Using Machine Learning Methods.

In this paper, the performance of machine learning methods for squirrel cage induction motor broken rotor bar (BRB) fault detection is evaluated. Decision tree classification (DTC), artificial neural network (ANN), and deep learning (DL) methods are developed, applied, and studied to compare their performance in detecting broken rotor bar faults in squirrel cage induction motors. The training data were collected through experimental measurements. The BRB fault features were extracted from measured line-current signatures through a transformation from the time domain to the frequency domain using discrete Fourier Transform (DFT) of the frequency spectrum of the current signal. Eighty percent of the data were used for training the models, and twenty percent were used for testing. A confusion matrix was used to validate the models' performance using accuracy, precision, recall, and f1-scores. The results evidence that the DTC is less load-dependent, and it has better accuracy and precision for both unloaded and loaded squirrel cage induction motors when compared with the DL and ANN methods. The DTC method achieved higher accuracy in the detection of the magnitudes of the twice-frequency sideband components induced in stator currents by BRB faults when compared with the DL and ANN methods. Although the detection accuracy and precision are higher for the loaded motor than the unloaded motor, the DTC method managed to also exhibit a high accuracy for the unloaded current when compared with the DL and ANN methods. The DTC is, therefore, a suitable candidate to detect broken rotor bar faults on trained data for lightly or thoroughly loaded squirrel cage induction motors using the characteristics of the measured line-current signature.

Metamaterial-based acoustic enhanced sensing for gearbox weak fault feature diagnosis

In gear fault diagnosis of practical engineering, the gear fault signal is affected by external strong noise interference, the multipath superposition and interface loss of the internal fault excitation transmission, which leads to weak feature of incipient fault signals, making the gear fault diagnosis difficult. Inspired by the acoustic manipulation capabilities of acoustic metamaterials, this study proposes a method for weak gear fault feature diagnosis via gradient acoustic metamaterial (GAM), which utilises the acoustic rainbow capture and compression ability to reduce the difficulty of gear incipient fault diagnosis. According to the gear frequency modulation/amplitude modulation modulation principle, enhancement of fault feature frequencies can be achieved by collecting gear acoustic signals from the selected air gaps in GAM structure. In this study, the feasibility of GAM-based gear weak fault feature diagnosis is proved by experiments, which verify the multiscale feature denoising and frequency selective enhancement characteristics of GAM. The results show that the amplitude of the target signal is amplified more than eight times, the sideband component containing the fault signal is enhanced obviously, and the effect of denoising outside the target sideband is evident, making the fault feature can be easily identified from the weak fault signal after demodulation. By comparing with digital filtering in traditional signal processing, this method is more straightforward in extracting weak gear fault features. Additionally, this method adopts non-contact measurement method with micro-electroMechanical system (MEMS) microphone, which has advantages over acceleration sensors in overcoming the space limitation. All in all, the proposed method is effective and facilitates the identification of weak gear faults.

Distortion Product Otoacoustic Emissions in Mice Above and Below the Eliciting Primaries.

Normal hearing is associated with cochlear nonlinearity. When two tones (f1 and f2) are presented, the intracochlear response contains additional components that can be recorded from the ear canal as distortion product otoacoustic emissions (DPOAEs). Although the most prominent intermodulation distortion component is at 2f1-f2, other cubic distortion products are also generated. Because these measurements are noninvasive, they are used in humans and in animal models to detect hearing loss. This study evaluated how loss of sensitivity affects DPOAEs with frequencies above and below the stimulating primaries, i.e., for upper sideband (USB) components like 2f2-f1 and for lower sideband (LSB) components like 2f1-f2. DPOAEs were recorded in several mouse mutants with varying degrees of hearing loss associated with structural changes to the tectorial membrane (TM), or with loss of outer hair cell (OHC) somatic electromotility due to lack of prestin or to the expression of a non-functional prestin. In mice with changes in sensitivity, magnitude reductions were observed for 2f1-f2 relative to controls with mice lacking prestin showing the greatest changes. In contrast, 2f2-f1 was minimally affected by reductions in cochlear gain due to changes in the TM or by the loss of OHC somatic electromotility. In addition, TM mutants with spontaneous otoacoustic emissions (SOAEs) generated larger responses than controls at 2f2-f1 when its frequency was similar to that for the SOAEs. Although cochlear pathologies appear to affect USB and LSB DPOAEs in different ways, both 2f1-f2 and 2f2-f1 reflect nonlinearities associated with the transducer channels. However, in mice, the component at 2f2-f1 does not appear to receive enhancement due to prestin's motor action.

Analysis of Time-Varying Mesh Stiffness and Dynamic Response of Gear Transmission System with Pitting and Cracking Coupling Faults

The gear transmission system is an important part of the mechanical system, so it is essential to judge its running state accurately. To solve the difficult problem of identifying the components of coupling faults, this paper derives the calculation method of gear time-varying mesh stiffness for coupling faults of pitting and cracking based on the energy method and considering the coupling between teeth, establishes the dynamics model of two-stage gear transmission system with coupling faults and studies the influence of coupling faults on gear time-varying mesh stiffness and dynamic characteristics. The accuracy of the proposed method is verified by experiments. The results show that both pitting and cracking can lead to a reduction in mesh stiffness. The stiffness of pitting will fluctuate irregularly due to the influence of pitting on the tooth surface, while the stiffness of cracked teeth is relatively smooth. The coupling fault stiffness is dominated by more serious faults. By analyzing the periodic impact components in time domain and the sideband components around the harmonics in frequency domain the faulty gears in the transmission system can be distinguished. It provides an effective reference for the diagnosis of faulty gears.

Reconstructing GNSS Meta-Signal Observations Using Sideband Measurements

<h3>Summary</h3> Global navigation satellite systems (GNSSs) provide several signals on different frequencies: Two or more components can be processed jointly as a meta-signal. Despite significant effort devoted to developing effective techniques for meta-signal processing, limited research has been conducted to characterize meta-signal measurements. In this work, the observations obtained by processing a GNSS meta-signal are characterized and fundamental relationships between GNSS meta-signal and dual-frequency measurement combinations are derived. We show that subcarrier phase observations can be estimated as the wide-lane linear combination of the carrier phases obtained from the two original sideband components. Moreover, meta-signal code measurements can be reconstructed from the pseudoranges and carrier phases of the original components. Thus, meta-signal pseudoranges are mixed code and carrier observations. The experimental results confirm the validity of the theoretical formulas that can be used to reconstruct meta-signal measurements from dual-frequency observations.

Sideband Vibro-Acoustic Responses and Improvements With Different Pulsewidth Modulation Strategies in Permanent Magnet Synchronous Motor for Electric Vehicle

This article presents a comprehensive investigation into the sideband vibro-acoustics with continuous and discontinuous pulsewidth modulation (PWM) strategies in permanent magnet synchronous motor (PMSM). The primary motivation for the evaluation reveals the frequency distributions of the sideband components and the magnitudes suppression with the space-vector PWM (SVPWM) and the discontinuous PWM (DPWM). The principle and implementation of the conventional SVPWM and six basic DPWM modes are firstly presented. The sideband harmonic components are provided by the analytical derivations, in which the frequency distributions are established by coupling the temporal features between the current harmonics and radial electromagnetic force. To evaluate and compare the sideband current harmonics and vibro-acoustic responses among the PWM schemes, the experimental tests are presented in a study case of 12/10 PMSM. Significant deterioration is observed in each of the basic DPWMs compared with that in SVPWM. Developed with periodic dithering modulation, notable sideband harmonics suppression and vibro-acoustic improvements in DPWM schemes are observed. This work is expected to provide a guidance for a hybrid modulation strategy in electric vehicles (EVs).

Bearing Scratch Fault Detection by Three‐Dimensional Features and a Support Vector Machine

Induction motors play a crucial role in various industries owing to their high robustness. The demand for early fault detection is getting attention to avoid serious damage to the machines. Bearing fault is the most common failure in induction motors and the possibility of scratches has a higher probability among the various classes of the bearing faults. Recently, the effective diagnosis method considering the progression and orientation of the scratch fault by using a machine learning algorithm have been reported. However, the diagnosis of such scratch faults with high accuracy is still required and challenging for early fault detection. In this article, the scratch faults are diagnosed with high accuracy rate and the detailed analysis are conducted. A support vector machine algorithm is used to diagnose the faults, where sideband frequency components of the load current are used as the features. In order to obtain high accuracy rate, additional features are considered, where in this study, the rotating speed of the motor and a higher order frequency component are selected as candidates and compared. The rotating speed along with sideband components of load current shows high accuracy rate. Furthermore, the robustness of the method is tested against the multiple faults. The results show that the rotating speed is an effective feature for highly sensitive diagnoses of bearing scratch faults. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A GNSS meta-signal SAGE-based multipath-mitigating loop design

A major challenge suffered by Global Navigation Satellite System (GNSS) receivers is the multipath interference, which results in serious tracking performance degradation and increased positioning errors. Growing evidence suggests that wide-bandwidth signals and multi-antenna technology are set to become two vital factors to improve the GNSS multipath mitigation, leading to the concept of meta-GNSS signal and multi-dimensional processing. To estimate the time delay of line-of-sight (LOS) ray in a multipath environment, we propose a meta-signal Space Alternating Generalized Expectation (SAGE) based locked loop (SAGELL) design, which exploits the high-resolution of the meta-signal together with the characteristics from spatial and temporal domains. The SAGELL design comprises two main setups: the SAGE-based discriminator and combinational loops. Benefiting from the multi-dimensional processing and meta-signal bandwidth, the SAGE-based discriminator first estimates the LOS ray and the multipath rays in single side-band components and achieves the global estimates of the dual side-band components coherently. Aiming to accurately track each ray of the meta-signal, we further close the SAGELL via angle, code phase, and carrier phase locked loops to filter and predict the estimates. The proposed GNSS meta-signal multipath-mitigating loop design allows for GNSS high-precision discrimination and tracking in multipath scenarios, even in the presence of highly correlated rays, as confirmed by the numerical results.

A Multi-Frequency Input-Admittance Model of Locomotive Rectifier Considering PWM Sideband Harmonic Coupling in Electrical Railways

Electrical railway harmonic instability issues are common in the high-frequency range. The effective frequency of the traditional converter’s small-signal averaging model is below 1/2 switching frequency since the pulse width modulation (PWM) sideband harmonic components are ignored. In this article, the dynamic propagations of perturbation frequency and the generated PWM sideband components are constructed first. Then the locomotive rectifier’s multi-frequency input-admittance model is derived appropriately. Afterward, an admittance conversion approach is used to convert the multi-frequency model into the single-input–single-output (SISO) model whereas retaining the sideband frequency couplings. The proposed SISO model is more accurate than the traditional small-signal averaging model in the frequency range higher than 1/2 switching frequency. It is found that PWM sideband harmonics dominate the locomotive rectifier’s input-admittance characteristic higher than 1/2 switching frequency. Finally, based on the proposed model, the influence of different switching frequencies, control bandwidths, and traction network impedance on system harmonic stability is revealed by the hardware-in-the-loop (HIL) results.

Accurate Small-Signal Modeling and Stability Analysis of Wide-Input Buck Converter Considering Modulation Waveform Ripples

Buck converters are widely used in consumer electronics, electric vehicles, and dc microgrids. Small-signal models are necessary tools to design high-quality controllers. However, most of them neglect modulation waveform ripples, which introduces significant errors under high-bandwidth controls. Recently, two models explain the influences of nondifferentiable modulation waveform ripples by their left-side derivatives at crossing points. However, this conclusion is built on the premise that infinite sideband components caused by switching have been considered, which largely complicates these models. The accurate small-signal model with finite sideband components is proposed for nondifferentiable modulation waveform ripples in this article. Based on it, the stable working region and control design of wide-input high-bandwidth Buck converters are talked about. Simulations and experiments validate the accuracy and effectiveness of the proposed model.

A General Approach to Sampled-Data Modeling for Ripple-Based Control—Part I: Peak/Valley Current Mode and Peak/Valley Voltage Mode

This article is aiming to unify the modeling methods for various ripple-based control schemes. It is divided into two parts, and the first part presents a sampled-data modeling method for the peak/valley current mode (PCM/VCM) control and the peak/valley voltage mode (PVM/VVM) control. It is pointed out that due to the high bandwidth of the dc–dc converter under PCM/VCM or PVM/VVM control, the sideband effect cannot be ignored in the modeling process. Meanwhile, with the small-signal assumption, the feedback perturbation signal has a discontinuity of the first kind at each sampling instant, so the perturbation value at this instant should be obtained according to the Dirichlet conditions, which is equal to half of the sum of the limit values on the left and right sides of the signal. Then, by using Shannon's sampling theorem, the transfer functions of the modulator and the loop gain are derived, and they are used to analyze the influence of the sideband components on the converter stability. Finally, the experimental results from a PCM controlled buck converter validate the proposed modeling technique.

High-Frequency Damping Analysis and Compensation Method Above Half PWM Sampling Frequency for Train Grid-Connected Converter

There are serious harmonic overvoltage phenomena in the electric railway system caused by the high-frequency resonance or instability issues, which is rooted in the region not only below, but also above half the PWM sampling frequency. To effectively evaluate the high-frequency admittance of train and further suppress the harmful high-frequency instability issue, a multi-frequency averaging model combining sampling sideband components is developed. Compared with the single-frequency model, the multi-frequency model is more accurate in the region near sampling frequency. After simplification, it is found that the time delay of digital control system is the cause of high-frequency negative damping. However, the time delay may make the traditional virtual impedance method fail in the high-frequency domain. Therefore, a virtual-impedance-controller (VIC) with variable damping characteristic is proposed to reshape the train admittance. The proposed VIC has the same structure as PID control. The detailed design method is given to offset the influence of time delay. The multiple high-frequency negative damping regions of train can be eliminated simultaneously by using multiple parallel VICs. The proposed method is applicable when changing the switching frequency. Hardware-in-the-loop test and low-power physical experiments validate the effectiveness of the proposed VIC strategy.

Nonlinear evolution and low-frequency acoustic radiation of ring-mode coherent structures on subsonic turbulent circular jets

By adapting the triple decomposition of an instantaneous turbulent flow into a time-averaged mean field, large-scale coherent motion and fine-scale random fluctuations, and treating the coherent motion as instability modes on the mean flow, a mathematical theory is developed to describe the nonlinear spatial–temporal modulation and acoustic radiation of a coherent structure (CS) on a circular jet in the form of a wavepacket consisting of an axisymmetric (ring) mode and its sideband components. The effect of fine-scale turbulence on the CS is characterised via a gradient closure model, and the non-parallelism due to the axial variation and radial velocity of the mean flow is taken into account. By employing the matched asymptotic expansion and multi-scale techniques, a strongly nonlinear system is derived, which governs the envelope of the CS and its vorticity and temperature in the critical layer. Numerical solutions to the evolution system show that the theory captures the nonlinear amplitude attenuation and vorticity roll-up as observed in experiments. The large-distance asymptotic properties of the CS allow us to describe and predict its acoustic radiation on the basis of first principles. The CS is trapped within the jet, but its self-interaction generates a temporally and axially modulated mean-flow distortion, which acts as the emitter to radiate low-frequency sound waves, with the Reynolds stresses driving this mean-flow distortion being identified unambiguously to be the physical source in the present context. An equivalent source in the Lighthill type of acoustic analogy is also identified. For the present ring-mode CS in the fully developed region of a circular jet, the equivalent source can be determined before the acoustic field is, and the intensity of the radiated sound waves is found to be $O(\epsilon ^3)$ , where $\epsilon$ measures the magnitude of the CS. The directivity and spectrum of the acoustic far field are calculated for representative parameters, and the predicted features resemble experimental measurements.

Analysis and Detection of Rotor Eccentricity in Permanent Magnet Synchronous Machines Based on Linear Hall Sensors

Rotor eccentricity commonly exists in permanent magnet synchronous machines (PMSMs) due to improper assembly, excessive vibration, and continuous operation. Consequently, the unbalanced magnetic pull, introduced by rotor eccentricity, may lead to unfavorable noise, vibration, and even bear damage, which makes the detection of eccentricity meaningful. Although motor current signal analysis is the most popular method to diagnose eccentricity based on the amplitudes of sideband component, it is a big challenge to classify different types of eccentricities and quantify the eccentric ratio due to the spatiotemporal coupling effect. In this article, by installing a set of Hall sensors at stator slots of PMSMs to measure the magnetic flux density in time domain, the static eccentricity and dynamic eccentricity can be easily separated. This article provides a novel complex-analytical model to reveal the single side band modulation effect in air-gap filed due to dynamic eccentricity. Moreover, a diagnosis algorithm based on frequency-adaptive notch filter is designed to identify the eccentricity type and the corresponding degree. The effectiveness of the novel diagnosis method is validated by both simulations and experiments.

Parametric Tracking of Electrical Current Components Using Gradient Descent Algorithm

In the last few years, Motor Current Signature Analysis (MCSA) has proven to be an effective method for electrical machines condition monitoring. Indeed, compared to vibration and temperature analysis, current measurement proves to be a convenient and non-invasive alternative. Moreover, it has proven to be a reliable method since many mechanical and electrical faults manifest as side-band spectral components generated around the fundamental frequency component of the motor’s current. These components are called interharmonics and they are a major focus of fault detection using MCSA. However, the main drawback of this approach is that the interference of other more prevalent components such as the fundamental and noise components can obstruct the effect of interharmonics in the spectrum and may therefore affect fault detection accuracy. Thus, we propose in this paper an alternative approach that aims to decompose the different current components using a model based on a Vandermonde matrix, in order to monitor each component independently. Then, the tracking of each distinct component in time and spectral domains is implemented. This is achieved by estimating their respective relevant parameters using the Gradient Descent algorithm. This method has been favorably compared to an existing estimation algorithm (MUSIC) and its efficiency has been validated. The results of this work prove to be promising and establish the parametric tracking of the electrical current components using the Gradient Descent algorithm as a reliable monitoring approach.

Sideband Peak Count in a Vibro-Acoustic Modulation Method for Crack Detection

This paper presents a new method of signal processing for vibro-acoustic modulation (VAM) methods in order to detect damage accumulation in steel samples. Damage in the tested samples was produced by cycle loading, which, with a small amplitude, was used as a pump wave to modulate an ultrasonic probe wave. Multiple sideband peaks were observed, which were used to characterize the modulation effect. We propose the effectiveness sideband peak number (SPN) method as an indicator of any damage accumulation when the load cycle is applied. Moreover, after comparing the SPN with the previously used modulation index (MI), we concluded that, for some of the samples, the SPN provided better damage indication than the MI. The presented results can be explained by a simple model of bilinear crack nonlinearity. This model demonstrates that the amplitude dependences of the sideband components on the pump and the probe wave amplitudes are very different from the quadratic crack model that is usually used for MI test explanation.

Evaluation and comparison of sideband harmonics and acoustic responses with continuous and discontinuous PWM strategies in permanent magnet synchronous motor for electric vehicles

High-frequency vibro-acoustics, introduced by voltage source inverter (VSI) and control strategies, are the critical features affecting the noise, vibration and harshness (NVH) performances of electric vehicles (EVs). In this paper, a comprehensive evaluation and comparison into sideband current harmonics and high-frequency vibro-acoustic responses has been studied with different control strategies in the study case of permanent magnet synchronous motor (PMSM). At first, the principles and implementation of continuous and discontinuous pulse-width modulations (PWM) techniques are explored. Then, the features of the sideband current harmonic and radial electromagnetic forces are deduced with analytical derivations, in which the frequency characteristics are also presented. Furthermore, all PWM schemes have been improved by a standard periodic dithering modulation with square signal-based to reduce the sideband harmonics. The experimental results show that the sideband current harmonics and vibro-acoustics are generally clustered around the carrier frequency and have a particular orders and spectral distributions. The overall level of the obtained DPWM schemes present a slight deterioration compared to the SVPWM ones. With the periodisation of the carrier frequency, the sideband components show a significant suppression, which is above 15 dBA reduced in the acoustic noise responses.