Spectral Amplitude Research Articles

An Enhanced Spectral Amplitude Modulation Method for Fault Diagnosis of Rolling Bearings

As a classic nonlinear filtering method, Spectral Amplitude Modulation (SAM) is widely used in the field of bearing fault characteristic frequency identification. However, when the vibration signal contains high-intensity noise interference, the accuracy of SAM in identifying fault characteristic frequencies is greatly reduced. To solve the above problems, a Data Enhancement Spectral Amplitude Modulation (DA-SAM) method is proposed. This method further processes the modified signal through improved wavelet transform (IWT), calculates its logarithmic maximum square envelope spectrum to replace the original square envelope spectrum, and finally completes SAM. By highlighting signal characteristics and strengthening feature information, interference information can be minimized, thereby improving the robustness of the SAM method. In this paper, this method is verified through fault data sets. The research results show that this method can effectively reduce the interference of noise on fault diagnosis, and the fault characteristic information obtained is clearer. The superiority of this method compared with the SAM method, Autogram method, and fast spectral kurtosis diagram method is proved.

Tunable topological phases in nanographene-based spin-1/2 alternating-exchange Heisenberg chains.

Unlocking the potential of topological order in many-body spin systems has been a key goal in quantum materials research. Despite extensive efforts, the quest for a versatile platform enabling site-selective spin manipulation, essential for tuning and probing diverse topological phases, has persisted. Here we utilize on-surface synthesis to construct spin-1/2 alternating-exchange Heisenberg chains by covalently linking Clar's goblets-nanographenes each hosting two antiferromagnetically coupled spins. Using scanning tunnelling microscopy, we exert atomic-scale control over chain lengths, parities and exchange-coupling terminations, and probe their magnetic response via inelastic tunnelling spectroscopy. Our investigation confirms the gapped nature of bulk excitations in the chains, known as triplons. Their dispersion relation is extracted from the spatial variation of tunnelling spectral amplitudes. Depending on the parity and termination of chains, we observe varying numbers of in-gap spin-1/2 edge excitations, reflecting the degeneracy of distinct topological ground states in the thermodynamic limit. By monitoring interactions between these edge spins, we identify the exponential decay of spin correlations. Our findings present a phase-controlled many-body platform, opening avenues toward spin-based quantum devices.

Generation of terahertz radiation with a specified spectral profile from a mosaic combined organic crystal.

We present a method for the generation of terahertz (THz) pulses with a high optical-to-THz conversion efficiency and a smooth spectrum. The method is based on the optical rectification of near-infrared femtosecond laser pulses with a wavelength of 1240 nm in a mosaic combined crystal, consisting of two pieces of nonlinear organic crystals, OH1 and DSTMS. The mosaic combined crystal produces a relatively smooth spectrum in the 0.3-4.5 THz range with no pronounced absorption dips and with a maximum in a spectral amplitude at about 2 THz. The peak field strength is 9.6 MV/cm for an effective crystal diameter of 4.3 mm.

Phase analysis of biphoton joint spectra by interference between different SPDC sources

In spontaneous parametric down-conversion, the spectral correlations between the signal and the idler are expressed by the joint spectral amplitude (JSA) function. However, in the standard coincidence measurements, the phase information of the JSA is lost, and only the square of the absolute value of the JSA is recorded, thus preventing full characterization of the biphoton state. Here, we present an experimental technique to investigate the interference of biphoton joint spectral amplitudes, unlocking new avenues in quantum photonics research. Our method explores phase-dependent phenomena within entangled biphoton spectra. This is achieved by simultaneously pumping two structured nonlinear photonic crystals and observing their interference, which reveals previously inaccessible effects with direct intensity measurements. We demonstrate the versatility of our technique by analyzing two types of joint spectra: one exhibiting a two-lobe shape and the other a three-lobe shape. Additionally, we reconstruct the joint spectral amplitudes for both scenarios and observe good agreement with theoretical predictions. These results pave the way for developing advanced quantum communication and information processing technologies using biphoton spectra.

Role of chirping in pulsed single-photon spectroscopy

We investigate the precision of estimating the interaction strength between a two-level system (TLS) and a single-photon pulse when the latter is subject to chirping. We consider linear, quadratic, and sinusoidal temporal phases applied to Gaussian and exponential temporal profiles. At the asymptotic time, when the TLS has fully decayed to its ground state, the fundamental precision depends solely on the magnitude of its spectral amplitude. For quadratically phase-modulated Gaussian pulses, this is entirely determined by the spectral bandwidth. We provide expressions for evaluating the fundamental precision for general temporal profiles and phase modulations. Finally, we show that experimentally feasible mode-resolved measurements are optimal, or close to it, for chirped, pulsed single-photon spectroscopy. Published by the American Physical Society 2024

Near-field terahertz electro-optical imaging based on a polarization image sensor

Abstract This paper presents a hyperspectral microscopy system that offers two-dimensional (2D) measurement of the spectral phase and amplitude information of terahertz (THz) radiation without the need for raster scanning. To achieve this, a new THz imaging method is introduced, wherein the distribution of the THz electric field is spatially measured using the electro-optic effect with a commercial polarization image sensor. This method enables the direct measurement of polarization components, eliminating the need for the polarization optics usually required in conventional electro-optical imaging. The performance of this imaging method is compared with a conventional 2D imaging system based on a standard visible camera. Finally, the sub-wavelength resolution capabilities of this new sensor are demonstrated by imaging a sample in the near field.

Deep-neural-network model for predicting ground motion parameters using earthquake horizontal-to-vertical spectral ratios

This study proposed a deep-neural-network (DNN) model for seismic ground motion prediction by utilizing a unified strong motion database by the National Research Institute for Earth Science and Disaster Resilience, and earthquake horizontal-to-vertical spectral ratio (EHVR) database in Japan. The model aims to enhance the accuracy of predictions by incorporating the EHVRs for complementing site effects, and utilizing existing ground motion prediction equations (GMPE) as the base model for source and propagation path effects. The hybrid approach enables the prediction of peak ground accelerations (PGAs), peak ground velocities (PGVs), and 5% damped absolute acceleration response spectra (SAs). After classifying the training and test sets from the database, the trained DNN models were applied on the test set to evaluate the performance of the predicted results. The accuracy assessment by the residuals, R-squared ( R2), and root mean square error (RMSE) between the predicted and observed values in the test set revealed the superior performance of the proposed model compared with the traditional GMPE with proxy-based site effects such as V S30s especially in predicting both the spectral amplitude and shape of SAs.

Performance analysis of MDM-OCDMA free space optical system using shift ZCC codes

Abstract Free space optical communication is promising wireless technology which saves cost, saves time, has high security and acts as backend, backhaul system. Optical code division multiplexing based on spectral amplitude coding is a potential method to support many users with high data speeds. Optical code division multiplexing reliant spectral amplitude coded zero cross-correlation free space optical communication is proposed in this work incorporating shift zero cross-correlation codes. Mode Division Multiplexing is used to lower the cost of the system and to minimize the interferences. With the realization of the proposed system, the capacity of 100 Gbps is accomplished supporting 10 different users. Different atmospheric turbulences are also analyzed over FSO to investigate their effects on BER.

Real‐Time Detection of Coherent Vibrational Dynamics in TiN Films

AbstractTitanium nitride (TiN) has recently gained considerable interest because of its remarkable plasmonic properties and for its strong electron–phonon (e–ph) coupling, leading to extremely fast (<100 fs) electron‐lattice cooling. Here, the generation of coherent phonons in TiN films is reported, along with their real‐time detection by means of broadband transient reflection spectroscopy with sub‐15‐fs temporal resolution. The measurements show damped oscillations, superimposed to excited state electronic decay. A coherent vibrational mode is revealed, with ≈10 THz frequency ascribed to defect‐activated normal modes, consistent with spontaneous Raman scattering data, and a dephasing time of ≈250 fs. Two π‐phase flips are also observed located at photon energies corresponding to interband optical transitions (at 3.2 and 2.5 eV), ascribed to selective coupling of the vibrational mode to these transitions; the energy modulation induced by the vibrational coherence is evaluated. It is shown that the displacive excitation of coherent phonons model describes the coherent response in terms of temporal behavior and of spectral amplitude profile. Overall, a comprehensive and detailed analysis of coherent phonons in TiN films, so far undected, is provided and relevant information on TiN photo‐physical properties, potentially useful for its applications, is given.

Research on a new pressure pulsator

Pulsators are widely used to study the dynamic characteristics of liquid flow components. However, it is difficult to adapt the existing actuators to the excitation requirements under high pressures, low temperatures, and toxic media. This study describes the design of a novel pressure pulsation device and presents the results of simulations and experimental tests. The flow field is simulated under a series of working conditions, and the effects of the rotation speed, flow rate, inlet pressure, and gap between the rotor and stator on the peak-to-peak amplitude, spectral amplitude, and flow resistance coefficient of the actuator outlet are analyzed. A prediction model for the corresponding parameters is developed using multiple linear regression. In high-pressure (20 MPa) hydraulic pipeline tests, the excitation device can generate pulsating flow with peak-to-peak amplitudes of more than 7 MPa in the time domain and 2 MPa in the frequency domain. The upstream and downstream regions of the internal flow field are periodically joined and detached by the blade rotation, which results in periodic variations in flow velocity and pressure. The relative error between the model predictions and the three-dimensional simulation and experimental values is less than 7%, satisfying industrial requirements. This work facilitates a solution to the problem of dynamic excitation when analyzing the response characteristics of fluid equipment in high-pressure pipelines and provides a method for forecasting actuator output effects.

Stockwell transform spectral amplitude modulation method for rotating machinery fault diagnosis

Spectral amplitude modulation (SAM) method, as an automated and empirical nonlinear filtering approach, has shown great promise for rotating machinery fault diagnosis. However, due to the inherent shortcomings of Fourier transform in SAM, leading to significant errors in the edited amplitude, also it is easy to fail with selecting the optimal weight value manually under intense background noise. To solve the aforementioned drawbacks, the Stockwell transform spectral amplitude modulation (STSAM) method is proposed. The Stockwell transform (S-transform) is first utilized to obtain the phase and amplitude with time–frequency information. Then, the edited signals can be reconstructed by inverse S-transform with the above actual phase and the modified amplitudes under different weights. Hence, more comprehensive and accurate information about the amplitude can be computed. After that, their normalized square envelope spectra under each cyclic frequency are calculated to showcase the fault characteristics. Moreover, a novel indicator is proposed to automatically choose the optimal weight in STSAM, thus clearer characteristic frequencies can be represented by the optimal square envelope spectrum (OSES). Finally, the effectiveness and superiority of the STSAM and OSES methods are systematically demonstrated by the comparative studies with the SAM and time–frequency SAM approaches using simulated signals and real-world datasets.

Predicting improvement in biofeedback gait training using short-term spectral features from minimum foot clearance data.

Stroke rehabilitation interventions require multiple training sessions and repeated assessments to evaluate the improvements from training. Biofeedback-based treadmill training often involves 10 or more sessions to determine its effectiveness. The training and assessment process incurs time, labor, and cost to determine whether the training produces positive outcomes. Predicting the effectiveness of gait training based on baseline minimum foot clearance (MFC) data would be highly beneficial, potentially saving resources, costs, and patient time. This work proposes novel features using the Short-term Fourier Transform (STFT)-based magnitude spectrum of MFC data to predict the effectiveness of biofeedback training. This approach enables tracking non-stationary dynamics and capturing stride-to-stride MFC value fluctuations, providing a compact representation for efficient processing compared to time-domain analysis alone. The proposed STFT-based features outperform existing wavelet, histogram, and Poincaré-based features with a maximum accuracy of 95%, F1 score of 96%, sensitivity of 93.33% and specificity of 100%. The proposed features are also statistically significant (p 0.001) compared to the descriptive statistical features extracted from the MFC series and the tone and entropy features extracted from the MFC percentage index series. The study found that short-term spectral components and the windowed mean value (DC value) possess predictive capabilities regarding the success of biofeedback training. The higher spectral amplitude and lower variance in the lower frequency zone indicate lower chances of improvement, while the lower spectral amplitude and higher variance indicate higher chances of improvement.

Unveiling Ultrafast-Weak-Field Coherent Control of Indirect Dissociation Reactions.

Coherent control of molecular photodissociation through one-photon transitions has become a topic of interest in physical chemistry. Previous studies have shown that modulating the spectral phase of a single ultrafast laser pulse while keeping its spectral amplitude constant does not affect the dissociation yield of reactions originating from a pure eigenstate of the ground electronic state. Here, we explore the indirect photodissociation reaction of NaI molecules using theoretical and numerical methods. Our findings show that, in contrast to the outcomes achieved with negatively chirped pulses, time-dependent population of the eigenstates of the excited adiabatic potential induced by positively chirped laser pulses, acting as intermediates in the reaction, cannot be periodically restored to that caused by the unchirped pulse. This gives rise to an intriguing phenomenon: the sign of the pulse's chirp rate influences the distribution of dissociation fragments in coordinate and momentum space over extended periods. This work highlights the potential of using spectral-phase modulated pulses to manipulate indirect photodissociation reactions, offering a way to modify the transient photofragment distributions by controlling reaction intermediates.

Generation of synthetic spectrum-compatible bi-directional ground motions with specific directionality

Ground motions compatible with the maximum-direction response spectrum (RotD100) condition are emphasized in performance-based design and seismic risk assessment of civil structures in different regions. Due to the complex nature and uncertainty of earthquakes, the comprehensive inclusion of essential characteristics of ground motions is crucial. Recently, the directionality effect of horizontal bi-directional ground motions, representing the variation of the response spectral ordinate amplitude along various directions, on the seismic performance assessment of certain structures or key structural elements has received increasing attention in seismic analysis. However, from the seismic design perspective, there is still a lack of a method that can generate bi-directional ground motions comprehensively reflecting the directionality effect. This study focuses on the correction of ground motion directionality when generating synthetic bi-directional ground motions for a given target response spectrum. An efficient and integrated algorithm is proposed. To demonstrate the applicability of the proposed algorithm, three different target RotD100 response spectra are determined according to modern seismic design codes, and 20 pairs of bi-directional ground motions are generated using the proposed algorithm for each target spectrum. It is shown that with the proposed algorithm, the generated motions present a close match to the target RotD100 response spectrum and meet the specific directionality requirement. In addition, due to the iterative modification of the envelope function, the energy of the generated ground motion is also consistent with the scaled natural records.

A 1D-CNN model for the early detection of citrus Huanglongbing disease in the sieve plate of phloem tissue using micro-FTIR

Among the most frequently diagnosed diseases in citrus, citrus Huanglongbing disease has caused severe economic losses to the citrus industry worldwide since there is no curable method and it spreads quickly. As callose accumulation in phloem is one of the early response events to Asian species Candidatus Liberibacter asiaticus (CLas) infection, the dynamic perception of the sieve plate region can be used as an indicator for the early diagnosis of citrus HLB disease. In this study, one-dimensional convolutional neural network (1D-CNN) models were established to achieve early detection of HLB disease based on spectral information in the sieve plate region using Fourier transform infrared microscopy (micro-FTIR) spectrometer. Partial least squares regression (PLSR) and the least squares support vector machine regression (LS-SVR) models are used for the prediction of callose based on the micro-FTIR information in the sieve plate region of the citrus midrib. Furthermore, an improved data augmentation method by superimposing Gaussian noise was proposed to expand the spectral amplitude. The proposed method has achieved 98.65 % classification accuracy, which was higher than that of other traditional algorithms such as the logistic model tree (LMT), linear discriminant analysis (LDA), Bayes (BS), support vector machine (SVM) and k-nearest neighbors (kNN), and also than that of the molecular detection qPCR (Quantitative real-time polymerase chain reaction) method. Finally, based on the established early detection model with laboratory samples, it can also be used to detect the citrus HLB in complex field samples by using model updating methods, and the overall detection accuracy of the model reached 91.21 %. Our approach has potential for the early diagnosis of citrus HLB disease from the microscopic scale, which would provide useful and precise guidelines to prevent and control citrus HLB disease.

Improved Non-Negative Matrix Factorization-Based Noise Reduction of Leakage Acoustic Signals.

The detection of gas leaks using acoustic signals is often compromised by environmental noise, which significantly impacts the accuracy of subsequent leak identification. Current noise reduction algorithms based on non-negative matrix factorization (NMF) typically utilize the Euclidean distance as their objective function, which can exacerbate noise anomalies. Moreover, these algorithms predominantly rely on simple techniques like Wiener filtering to estimate the amplitude spectrum of pure signals. This approach, however, falls short in accurately estimating the amplitude spectrum of non-stationary signals. Consequently, this paper proposes an improved non-negative matrix factorization (INMF) noise reduction algorithm that enhances the traditional NMF by refining both the objective function and the amplitude spectrum estimation process for reconstructed signals. The improved algorithm replaces the conventional Euclidean distance with the Kullback-Leibler (KL) divergence and incorporates noise and sparse constraint terms into the objective function to mitigate the adverse effects of signal amplification. Unlike traditional methods such as Wiener filtering, the proposed algorithm employs an adaptive Minimum Mean-Square Error-Log Spectral Amplitude (MMSE-LSA) method to estimate the amplitude spectrum of non-stationary signals adaptively across varying signal-to-noise ratios. Comparative experiments demonstrate that the INMF algorithm significantly outperforms existing methods in denoising leakage acoustic signals.

Bloch equations in terahertz magnetic-resonance ellipsometry

A generalized approach derived from Bloch's equation of motion of nuclear magnetic moments is presented to model the frequency, magnetic field, spin density, and temperature dependencies in the electromagnetic permeability tensor for materials with magnetic resonances. The resulting tensor model predicts characteristic polarization signatures which can be observed, for example, in Mueller matrix element spectra measured. When augmented with thermodynamic considerations and suitable Hamiltonian description of the magnetic eigenvalue spectrum, important parameters such as density, spectral amplitude distribution, relaxation time constants, and geometrical orientation parameters of the magnetic moments can be obtained from comparing the generalized model approach to experimental data. We demonstrate our approach by comparing model calculations with full Mueller matrix element spectra measured at an oblique angle of incidence in the terahertz spectral range, across electron spin resonance quintuplet transitions observed in wurtzite-structure GaN doped with iron. Our model correctly predicts the complexity of the polarization signatures observed in the 15 independent elements of the normalized Mueller matrix for both positive and negative magnetic fields and will become useful for future analysis of frequency and magnetic field-dependent magnetic resonance measurements. Published by the American Physical Society 2024

Evaluating impact damage on carbon fiber-reinforced polymer plates utilizing zero-group-velocity Lamb waves

This paper presents an effective method for evaluating the impact damage of composite plates using zero-group-velocity (ZGV) Lamb waves. A finite element (FE) model of the carbon fiber-reinforced polymer (CFRP) plate is established to analyze in detail the propagation characteristics of the S1-ZGV Lamb wave mode with a specified propagation direction. The study investigates the changes in the S1-ZGV mode with varying damage levels, characterized by a decrease in elastic moduli. Results indicate that as the damage level increases, the corresponding S1-ZGV frequency and amplitude decrease proportionally. The spectral amplitude (SA) at the initial S1-ZGV frequency exhibits a consistent and significant decrease with increasing damage levels, offering a reliable method for accurately assessing damage in CFRP plates. Additionally, the S1-ZGV mode of the CFRP plate is experimentally excited using the pitch-catch technique with air-coupled ultrasonic transducers to explore the variations in the S1-ZGV mode with different impact damages. Experimental findings show that the SA of the S1-ZGV mode at the initial S1-ZGV frequency decreases monotonically and sensitively with an increasing number of impacts. These experimental results correlate with the FE analysis, validating the effectiveness of accurately evaluating impact damage in CFRP plates based on the SA of S1-ZGV modes.

Evaluation of surface corrosion damage in thin plates by Zero-Group Velocity Lamb waves based on PVDF comb transducers

This paper introduces a novel method for assessing surface corrosion damage in thin plates by leveraging the high sensitivity of Zero-Group Velocity (ZGV) Lamb waves and the versatility of polyvinylidene fluoride (PVDF) comb transducers. Theoretical analyses of ZGV Lamb wave modes and their differentiation from thickness vibration modes were conducted. The functionality and utility of the PVDF comb transducer tailored for the specific S1-ZGV mode were assessed. Experimental findings demonstrate that the PVDF comb transducer efficiently excites and captures the S1-ZGV mode, enabling effective assessment of surface corrosion damage in thin aluminum plates. Compared to the variations in wave velocity of surface acoustic waves (SAW) and the S1-ZGV frequency, the spectral amplitude at the initial S1-ZGV frequency exhibits a monotonically decreasing trend with increasing corrosion levels, proving to be more sensitive and reliable for evaluating surface corrosion damage. This research offers theoretical underpinnings and experimental validation for damage assessment using ZGV Lamb waves with the PVDF comb transducer, showcasing significant potential for practical engineering applications.

Linear stability analysis of compressible boundary layer over an insulated wall using compound matrix method: Existence of multiple unstable modes for Mach number beyond 3

The linear spatial stability of a parallel two-dimensional (2D) compressible boundary layer on an adiabatic plate is investigated by considering both 2D and three-dimensional (3D) disturbances. The compound matrix method is employed here, for the first time, for compressible flows, which, unlike other conventional techniques, can efficiently eliminate the stiffness of the equations governing the spectral amplitudes. The method is first validated with published results in the literature corresponding to spatial and temporal instability of flows ranging from low subsonic to high supersonic Mach numbers (M), which shows a good match depending upon the proper choice of free-stream temperature and the wall dispersion relation. Subsequently, flow compressibility effects and the spanwise variation of disturbances are also investigated for M ranging from low subsonic to high supersonic cases (from M = 0.1 to 6). Mack (AGARD Report No. 709, 1984) reported the existence of two unstable modes for M > 3 from viscous calculations (the so-called “second mode”) that subsequently fuse to create only one unstable zone when M increases. Our calculations show a series of higher-order unstable modes for M > 3 in addition to the findings of Ma and Zhong [“Receptivity of a supersonic boundary layer over a flat plate. Part 1. Wave structures and interactions,” J. Fluid Mech. 488, 31–78 (2003)], where such higher-order modes for supersonic boundary layers are all noted to be spatially stable. The number and the frequency extent of the corresponding unstable zones increase with an increase in M beyond 3 while propagating downstream at a higher speed than those corresponding to incompressible, subsonic, and low supersonic (M < 2) cases.