Features Of Spectra Research Articles

A strong blend in the morning: studying the circumgalactic medium before cosmic noon with strong, blended Ly α forest systems

ABSTRACT We study of the properties of a new class of circumgalactic medium absorbers identified in the Ly α forest: ‘Strong, Blended Lyman-α’ (or SBLA) absorption systems. We study SBLAs at 2.4 < z < 3.1 in SDSS-IV/eBOSS spectra by their strong extended Ly α absorption complexes covering 138 $\, \, {\rm km}\, {\rm s}^{-1}$ with an integrated $\log (N_{\rm H\, {\small I}}/\mathrm{cm}^{-2}) =16.04$$\substack{+0.05 \\ -0.06}$ and Doppler parameter b = 18.1$\substack{+0.7 \\ -0.4}$$\, \, {\rm km}\, {\rm s}^{-1}$. Clustering with the Ly α forest provides a large-scale structure bias of b = 2.34 ± 0.06 and halo mass estimate of $M_h \approx 10^{12}\, h^{-1}\, {\rm M_{\odot }}$ for our SBLA sample. We measure the ensemble mean column densities of 22 metal features in the SBLA composite spectrum and find that no single-population multiphase model for them is viable. We therefore explore the underlying SBLA population by forward modelling the SBLA absorption distribution. Based on covariance measurements and favoured populations we find that ≈25 per cent of our SBLAs have stronger metals. Using silicon only we find that our strong metal SBLAs trace gas with a log (nH/cm−3) > −2.40 for T = 103.5 K and show gas clumping on <210 parsec scales. We fit multiphase models to this strong subpopulation and find a low ionization phase with nH = 1 cm−3, T = 103.5 K, and [X/H] = 0.8, an intermediate ionization phase with log (nH/cm−3) = −3.05, T = 103.5 K and [X/H] = −0.8, and a poorly constrained higher ionization phase. We find that the low ionization phase favours cold, dense super-solar metallicity gas with a clumping scale of just 0.009 parsecs.

An efficient measure for controlling pollution in the dye industry: Experimental and DFT investigations on direct determination of 3-(N,N-diethylamino)acetanilide

The rapid expansion of the dye industry has led to severe environmental pollution. The lack of real-time direct determination methods for dye intermediates is a key factor in high pollution emissions and low product quality in the continuous synthesis of dyes. This study proposes an accessible, fast, and precise approach for the clean and direct determination of 3-(N,N-Diethylamino)acetanilide (DEAA), a dye intermediate used in the synthesis of the azo dye Disperse Violet 93:1. For precise DEAA quantification, we developed a multi-pathlength and multi-wavelength coupled differential photometric approach based on the absorption spectra characteristics of DEAA at various concentrations and optical pathlengths. A relatively stable analytical sensitivity (0.5671–66.2630) and a large concentration range of 0.01–11% were obtained. Compared to the traditional single-optical pathlength and single-wavelength quantification, this new method possessed 119 times higher sensitivity. The maximum quantitative relative error decreased from 9.17% to 2.44%. The orbital contribution and distinctive peak electronic excitation mechanism of DEAA were uncovered using TD-DFT. By comparing the oscillator strength and peak position variations between the target DEAA and coexisting sulfuric acid, the unique spectral behavior of DEAA, such as its high sensitivity and selectivity, was explained. In addition to providing a reference for real-time industrial dye and intermediate monitoring, this study lays the methodological groundwork for future research. In light of the new method's short time consumption and non-secondary pollution benefits, we further believe it will be crucial in controlling the industrial synthesis process in order to improve product quality, resource conversion efficiency, and effectively prevent excessive pollution generation.

BERTIVITS: The Posterior Encoder Fusion of Pre-Trained Models and Residual Skip Connections for End-to-End Speech Synthesis

Enhancing the naturalness and rhythmicity of generated audio in end-to-end speech synthesis is crucial. The current state-of-the-art (SOTA) model, VITS, utilizes a conditional variational autoencoder architecture. However, it faces challenges, such as limited robustness, due to training solely on text and spectrum data from the training set. Particularly, the posterior encoder struggles with mid- and high-frequency feature extraction, impacting waveform reconstruction. Existing efforts mainly focus on prior encoder enhancements or alignment algorithms, neglecting improvements to spectrum feature extraction. In response, we propose BERTIVITS, a novel model integrating BERT into VITS. Our model features a redesigned posterior encoder with residual connections and utilizes pre-trained models to enhance spectrum feature extraction. Compared to VITS, BERTIVITS shows significant subjective MOS score improvements (0.16 in English, 0.36 in Chinese) and objective Mel-Cepstral coefficient reductions (0.52 in English, 0.49 in Chinese). BERTIVITS is tailored for single-speaker scenarios, improving speech synthesis technology for applications like post-class tutoring or telephone customer service.

Deep Neural Network for Distinguishing Microseismic Signals and Blasting Vibration Signals Based on Deep Learning of Spectrum Features

ABSTRACT Similar waveforms and overlapping frequency ranges make distinguishing blasting vibrations and microseismic signals challenging, causing interference with coal mine microseismic monitoring systems. To address this problem, we propose a spectrum dataset (MSData) reflecting the spectrum features of both signal types and present a signal classification network (SCNet) combining CNNs and Transformers for signal classification. The network can learn multi-dimensional features of both signals from MSData and automatically and efficiently identify the two signal types. Experimental results yield F1-scores of 0.991 for microseismic signals and 0.993 for blasting vibration signals, meeting engineering application requirements.

Precision classification and quantitative analysis of bacteria biomarkers via surface-enhanced Raman spectroscopy and machine learning

The SERS spectra of six bacterial biomarkers, 2,3-DHBA, 2,5-DHBA, Pyocyanin, lipoteichoic acid (LTA), Enterobactin, and β-carotene, of various concentrations, were obtained from silver nanorod array substrates, and the spectral peaks and the corresponding vibrational modes were identified to classify different spectra. The spectral variations in three different concentration regions due to various reasons have imposed a challenge to use classic calibration curve methods to quantify the concentration of biomarkers. Depending on baseline removal strategy, i.e., local or global baseline removal, the calibration curve differed significantly. With the aid of convolutional neural network (CNN), a two-step process was established to classify and quantify biomarker solutions based on SERS spectra: using a specific CNN model, a remarkable differentiation and classification accuracy of 99.99 % for all six biomarkers regardless of the concentration can be achieved. After classification, six regression CNN models were established to predict the concentration of biomarkers, with coefficient of determination R2 > 0.97 and mean absolute error (MAE) < 0.27. The feature of important calculations indicates the high classification and quantification accuracies were due to the intrinsic spectral features in SERS spectra. This study showcases the synergistic potential of SERS and advanced machine learning algorithms and holds significant promise for bacterial infection diagnostics.

Optical absorption spectra in the far-infrared range and phonons of CdSe1−xTex thin films

Optical reflection spectra of CdSe1-xTex thin films deposited on quartz substrates are measured using the synchrotron radiation in the spectral range of 20–500 cm−1. The absorption bands of CdSe, CdTe, CdSe0.75Te0.25, CdSe0.5Te0.5, and CdSe0.25Te0.75 films are localized in the range of 20–220 cm−1. The imaginary parts of the dielectric function ε2(λ−1) of CdTe1-xSex crystals calculated in the framework of the density functional theory are in good agreement with the experimental reflection spectra of CdTe1-xSex films. The eigenvectors of the dynamical matrix CdTe1-xSex crystals are analyzed for several phonon modes to understand the difference between the frequency dependences of the calculated vibration density of states and the imaginary part of dielectric function ε2(λ−1). Small features of the experimental reflective spectra of CdSe1-xTex films in the ranges 50–70 cm−1 and 80–120 cm−1 are explained using the analysis of results of the molecular dynamics. During comparative molecular dynamics calculations, it was found that the vibration density of states of a thin CdTe slab with a surface-to-volume number of atoms relation of NS/NV = 0.2, experienced a redshift of approximately 30 cm−1. This shift was observed in comparison with the CdTe single crystal.

The Application of Cathodoluminescence (CL) for the Characterization of Blue Pigments

The combined application of Cathodoluminescence (CL) with Scanning Electron Microscopy (SEM) on paintings and painted surfaces has the potential to identify both organic and inorganic pigments on a micrometre or even nanometre scale. Additionally, the combination with Energy-Dispersive Spectrometry (EDS) allows for a more holistic, elemental, and mineralogical characterization of pigments. In addressing the need for the creation of a robust, open access database of characteristic CL spectra of pigments, a large project has been undertaken, focusing primarily on common organic and inorganic pigments. The present paper focuses on the CL characterization of 10 significant blue pigments in pure powder form: cerulean blue, Egyptian blue, Han blue, indigo, lapis lazuli, Maya blue, phthalo blue, vivianite, ultramarine blue, and zirconium blue. The CL spectra present characteristic bands for most of the pigments, allowing their secure identification, especially when combining the results with the EDS analyses. The effect of binding media and of the mixture of different pigments was also studied, via the analysis of mixtures of pigments with oil painted over canvas. Overall, both the binding medium and the mixture of pigments do not appear to create significant differences in the occurring spectra, thus allowing the identification of individual pigments. EDS and RAMAN spectra are included in order to facilitate comparison with other databases.

Oil saturation quantitative evaluation in lacustrine shale: Novel insights from NMR T1-T2 and displacement experiments

Oil saturation is important for shale reservior to identify favorable sections and determine the geological sweet spots. Current oil saturation evaluation methods, including experiments and empirical formulas, are not suitable for shale reservoir because of the complex mineral, fluid components and pore structure characteristics. A novel method was proposed to accurately calculate the shale oil saturation through the morphological dynamic variation characteristics of the 1D NMR T2 spectra and the signal intensity of the different hydrocarbon-bearing components of the 2D NMR T1-T2 map of shale samples with different oil and water saturation The results (1) indicated that the NMR T2 spectrum revealed that the pore structure of shale samples is complex and highly heterogeneous, and the primary factor that determines the volume of displaced oil in the displacement experiment with slight differences in wettability is the shale’s pore size distribution. (2) shown that the NMR T1-T2 map serves as a useful tool in distinguishing different hydrocarbon-bearing components of shale samples, including kerogen, adsorbed oil, free oil, structural, adsorbed water, and free water. Typically, kerogen is found in the top left region of the T1-T2 map with 10 < T1 < 100 ms & 0.02 < T2 < 0.2 ms. Based on this, T2 threshold for free oil and adsorbed oil are 2 and 0.2 ms, and the corresponding threshold of pore radius are 40 and 4 nm according to the NMR theory. (3) found that the morphological characteristics of 1D NMR T2 spectra vary with the variation of shale oil saturation. Specifically, T2 geometric mean (T2gm) and interval porosity corresponding to the first peak (Ap1) are positively and negatively correlated with oil saturation respectively. Then, oil saturation calculation method is established using the above two parameters and the Root Mean Square Error (RMSE) between the measured and calculated results is 5.85 %, which reflecting the accuracy and validity. In general, this method allows the shale oil saturation to be accurately calculated and provides basis for the determination of favorable sections and evaluation of resource of shale oil reservoir. Moreover, it also offers a new idea for the oil saturation prediction by NMR logging.

Synthesis of conducting polymer by gamma Co-60 ray in aqueous solution

This report presents the findings of a study on the synthesis of the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) using gamma Co-60 radiation in an aqueous solution saturated with N2 gas, containing 5 mM EDOT monomer and 0.2 M isopropanol. Gamma radiation with doses ranging from 12 kGy to 58 kGy from a gamma Co-60 source was employed. To assess the chemical composition of the solution before and after irradiation, UV-Vis and FTIR absorption spectra were examined. The results indicated the formation of yellow suspensions in the solution after irradiation, along with the emergence of dimers, oligomers, and PEDOT polymers as evidenced by UV-Vis spectra. The dried powders obtained from the irradiated solutions confirmed the successful synthesis of PEDOT, exhibiting distinct chemical structural characteristics in the FTIR spectra. These findings demonstrate the effective radiation-induced synthesis of conducting PEDOT polymer using gamma Co-60 irradiation.

Oxygen and Air Density Retrieval Method for Single-Band Stellar Occultation Measurement

The stellar occultation technique is capable of atmospheric trace gas detection using the molecule absorption characteristics of the stellar spectra. In this paper, the non-iterative and iterative retrieval methods for oxygen and air density detection by stellar occultation are investigated. For the single-band average transmission data in the oxygen 761 nm A-band, an onion-peeling algorithm is used to calculate the effective optical depth of each atmospheric layer, and then the optical depth is used to retrieve the oxygen number density. The iteration method introduces atmospheric hydrostatic equilibrium and the ideal gas equation of state, and it achieves a more accurate retrieval of the air density under the condition of a priori temperature deviation. Finally, this paper analyzes the double solution problem in the iteration process and the ideas to improve the problem. This paper provides a theoretical basis for the development of a new type of atmospheric density detection method.

Gravitational waves produced by domain walls during inflation

We study the properties of the stochastic gravitational-wave background (SGWB) produced by domain walls (DWs) during inflation without forming a network. We numerically simulate the DW production caused by a second-order phase transition and calculate the SGWB spectrum using a 1000×1000×1000 lattice. We show that the SGWB can be observed directly by future terrestrial and space gravitational-wave detectors and through the B-mode spectrum in the cosmic microwave background. With numerical simulations, we derive an empirical formula for the strength and qualitative features of the SGWB spectrum. The details of the SGWB spectrum also contain information about the later evolution of the Universe. Published by the American Physical Society 2024

A sex- and gender-based analysis of alcohol treatment intervention research involving youth: A methodological systematic review.

While there is widespread consensus that sex- and gender-related factors are important for how interventions are designed, implemented, and evaluated, it is not currently known how alcohol treatment research accounts for sex characteristics and/or gender identities and modalities. This methodological systematic review documents and assesses how sex characteristics, gender identities, and gender modalities are operationalized in alcohol treatment intervention research involving youth. We searched MEDLINE, Embase, Cochrane Central Registry of Controlled Trials, PsycINFO, CINAHL, LGBT Life, Google Scholar, Web of Science, and grey literature from 2008 to 2023. We included articles that reported genders and/or sexes of participants 30 years of age and under and screened participants using AUDIT, AUDIT-C, or a structured interview using DSM-IV criteria. We limited the inclusion to studies that enrolled participants in alcohol treatment interventions and used a quantitative study design. We provide a narrative overview of the findings. Of 8,019 studies screened for inclusion, 86 articles were included in the review. None of the studies defined, measured, and reported both sex and gender variables accurately. Only 2 studies reported including trans participants. Most of the studies used gender or sex measures as a covariate to control for the effects of sex or gender on the intervention but did not discuss the rationale for or implications of this procedure. Our findings identify that the majority of alcohol treatment intervention research with youth conflate sex and gender factors, including terminologically, conceptually, and methodologically. Based on these findings, we recommend future research in this area define and account for a spectrum of gender modalities, identities, and/or sex characteristics throughout the research life cycle, including during study design, data collection, data analysis, and reporting. It is also imperative that sex and gender variables are used expansively to ensure that intersex and trans youth are meaningfully integrated. Registration: PROSPERO, registration number: CRD42019119408.

Iterative feature mode decomposition: a novel adaptive denoising method for mechanical fault diagnosis

Remaining useful life prediction of rolling bearings highly relies on feature extraction of signals. The use of denoising algorithms helps to better eliminate noise and extract features, thereby constructing health indicators to predict remaining useful life. This paper proposes a novel adaptive denoising method based on iterative feature mode decomposition (IFMD) to accurately and efficiently extract fault features. The feature mode decomposition (FMD) employs correlation kurtosis (CK) as the objective function for iterative filter bank updates, enabling rapid identification of fault features. To achieve IFMD, the sparrow search algorithm combines sine-cosine algorithm and cauchy variation (SCSSA) to optimize two key parameters in FMD. During the continuous iteration process of the SCSSA algorithm, filter length and number of modes were determined. IFMD does not require empirical setting of initial parameters. During iterative process, the signal is accurately decomposed and the noise is eliminated. Compared with other optimization algorithms, SCSSA has obvious advantages in iterative rate and global optimization. The envelope spectrum feature energy ratio (ES-FER) is used to select decomposed modes, and the mode with the largest ES-FER is chosen as the optimal mode. Bearing fault diagnosis is realized by envelope spectrum analysis of the optimal mode. The numerical simulations and experimental verifications both validate the effectiveness and superiority of the proposed IFMD in mechanical fault diagnosis.

The SDSS-V Black Hole Mapper Reverberation Mapping Project: C iv Broad Absorption Line Acceleration in the Quasar SBS 1408+544

We present the results of an investigation of a highly variable C iv broad absorption line (BAL) feature in spectra of the quasar SBS 1408+544 (z = 2.337) that shows a significant shift in velocity over time. This source was observed as a part of the Sloan Digital Sky Survey (SDSS) Reverberation Mapping project and the SDSS-V Black Hole Mapper Reverberation Mapping project, and has been included in two previous studies, both of which identified significant variability in a high-velocity C iv BAL on timescales of just a few days in the quasar rest frame. Using ∼130 spectra acquired over 8 yr of spectroscopic monitoring with SDSS, we have determined that this BAL is not only varying in strength, but is also systematically shifting to higher velocities. Using cross-correlation methods, we measure the velocity shifts (and corresponding acceleration) of the BAL over a wide range of timescales, measuring an overall velocity shift of Δv=−683−84+89 km s−1 over the 8 yr monitoring period. This corresponds to an average rest-frame acceleration of a = 1.04 −0.13+0.14 cm s−2, though the magnitude of the acceleration on shorter timescales is not constant throughout. We place our measurements in the context of BAL-acceleration models and examine various possible causes of the observed velocity shift.

Analysis of the Spectrum of Common Pathogens and the Resistance of Mycoplasma in Sialidase-Positive Bacterial Vaginosis.

The objective of this study is to understand the characteristics of the common spectrum of pathogen and the resistance of Mycoplasma in Sialidase-positive bacterial vaginosis. The vaginal secretion specimens collected from August 2018 to October 2018 for the analysis of bacterial vaginosis (BV) were subjected to various techniques. These included routine leukorrhea examination, bacterial vaginosis sialidase testing, routine culture for common pathogens, mass spectrometry identification, and Mycoplasma resistance testing. A total of 238 patients with BV were identified. The cleanliness grading was mostly clean (+) and clean (2+), accounting for 38.24% and 30.67%, respectively. The bacterial vaginosis test for vaginal secretions showed leukocyte esterase positivity in 220 cases, resulting in a positivity rate of 92.44%. The spectrum of routine culture was analyzed and divided into four groups: A, B, C, and D. Group A consisted of Candidal vaginitis (13.45%); group B consisted of Gardnerella vaginalis vaginitis (32.77%); group C consisted of gram-negative bacillus vaginitis (46.22%); and group D consisted of Streptococcus agalactiae vaginitis (7.56%). The identification and antimicrobial susceptibility testing results for Mycoplasma showed a high detection rate of BV, with a positivity rate of 86.13%. There was a high sensitivity to tetracyclines for Ureaplasma urealyticum and Mycoplasma hominis, but a high resistance to macrolides and quinolones. Bacterial vaginosis existed in various complex forms, including Candida, Gardnerella vaginalis, Gram-negative bacillus, and Streptococcus agalactiae types. Moreover, there was an increasing trend of multi-drug resistance in Mycoplasma hominis. Therefore, it is crucial to pay attention to this condition and make accurate judgments based on the etiological characteristics and common antimicrobial susceptibility tests. This will enable the implementation of effective therapeutic interventions.

Improving constraints on inflation with CMB delensing

The delensing of cosmic microwave background (CMB) maps will be increasingly valuable for extracting as much information as possible from future CMB surveys. Delensing provides many general benefits, including sharpening of the acoustic peaks, more accurate recovery of the damping tail, and reduction of lensing-induced B-mode power. In this paper we present several applications of delensing focused on testing theories of early-universe inflation with observations of the CMB. We find that delensing the CMB results in improved parameter constraints for reconstructing the spectrum of primordial curvature fluctuations, probing oscillatory features in the primordial curvature spectrum, measuring the spatial curvature of the universe, and constraining several different models of isocurvature perturbations. In some cases we find that delensing can recover almost all of the constraining power contained in unlensed spectra, and it will be a particularly valuable analysis technique to achieve further improvements in constraints for model parameters whose measurements are not expected to improve significantly when utilizing only lensed CMB maps from next-generation CMB surveys. We also quantify the prospects of testing the single-field inflation tensor consistency condition using delensed CMB data; we find it to be out of reach of current and proposed experimental technology and advocate for alternative detection methods.

LiteBIRD science goals and forecasts. A case study of the origin of primordial gravitational waves using large-scale CMB polarization

We study the possibility of using the LiteBIRD satellite B-mode survey to constrain models of inflation producing specific features in CMB angular power spectra. We explore a particular model example, i.e. spectator axion-SU(2) gauge field inflation. This model can source parity-violating gravitational waves from the amplification of gauge field fluctuations driven by a pseudoscalar “axionlike” field, rolling for a few e-folds during inflation. The sourced gravitational waves can exceed the vacuum contribution at reionization bump scales by about an order of magnitude and can be comparable to the vacuum contribution at recombination bump scales. We argue that a satellite mission with full sky coverage and access to the reionization bump scales is necessary to understand the origin of the primordial gravitational wave signal and distinguish among two production mechanisms: quantum vacuum fluctuations of spacetime and matter sources during inflation. We present the expected constraints on model parameters from LiteBIRD satellite simulations, which complement and expand previous studies in the literature. We find that LiteBIRD will be able to exclude with high significance standard single-field slow-roll models, such as the Starobinsky model, if the true model is the axion-SU(2) model with a feature at CMB scales. We further investigate the possibility of using the parity-violating signature of the model, such as the TB and EB angular power spectra, to disentangle it from the standard single-field slow-roll scenario. We find that most of the discriminating power of LiteBIRD will reside in BB angular power spectra rather than in TB and EB correlations.

First and second K Banhatti indices of a fuzzy graph applied to decision making

Topological index of a graph is a numerical representation linked to the graph or the molecular structure associated with the graph, shedding light on its topological and structural properties. Different topological indices showcase unique attributes rooted in their degree, spectrum, and distance characteristics. Among these, the first and second K Banhatti indices, introduced by Kulli, involving both vertex and edge degrees, have garnered significant scholarly interest, prompting extensive discussions in graph theory. Within this research paper, a thorough exploration delves into the attributes surrounding the fuzzified first and second K Banhatti indices. This exploration is directed towards several bounds of the index and index of various structures like cycles, complete fuzzy graphs, complete bipartite graphs and stars. Relation between a fuzzy graph and its partial subgraphs, fuzzy graph and its complement graph in connection with the indices is also found. Additionally, the research paper investigates the first and second K Banhatti indices concerning graph operations such as the corona product and coalescence. Additionally, the paper outlines an algorithm designed to accurately compute the first and second K Banhatti indices and proposes an application in decision-making.

Application of Acoustic Emission Technology for Bearing Condition Monitoring on Passenger Ropeway

Rolling bearings are important stressed components of driving wheels and detour wheels on passenger ropeway, and their failure may lead to accidents and casualties. After the ropeway is installed and put into operation, the rolling bearings in the wheels are difficult to disassemble. Once disassembled, the bearing may be damaged. Due to the installation position and the complex operation environment, the health status of the rolling bearings is a blind spot for ropeway inspection and detection. Acoustic emission detection technology is used to monitor the rolling bearings of passenger ropeways. After a large number of field tests, the acoustic emission monitoring program and signal analysis method of rolling bearing on ropeway were proposed. The parameter characteristics of acoustic emission signals obtained in bearing operating were analyzed from two aspects: the ropeway operating cycle and the bearing operating cycle. Spectrum analysis of typical signals was performed, and the spectrum characteristics of typical acoustic emission signals of rolling bearing during the operation of the ropeway were obtained. On-site tests results show that using acoustic emission technology to perform condition monitoring and fault diagnosis of low-speed rolling bearings on passenger ropeways has good application prospects.

Fluctuation of the unsteady force on the rotor blade surface under circumferential distortion in axial flow compressor

To deeply understand the negative impact of circumferential inlet distortion on the internal flow of the compressor, by using the unsteady force testing technique of a rotor blade surface under a rotating coordinate system, the pressure fluctuations on the rotor blade surface are successfully captured when the rotor blade rotates through the distortion region. Results show that the pressure on the suction surface increases and the inlet angle of attack decreases before the rotor blade enters the distorted region. The pressure difference between the pressure and suction surface is obviously enhanced, thereby sharply increasing the blade load and intensifying the flow separation, which is easy to induce instability. When the rotor blade rotates out of the distortion region, the pressure on the suction surface is still low; thus, the inlet angle of attack in this position is larger than before entering the distorted region. It also shows that the outlet of the distorted region is prone to trigger stall. In addition, the dynamic spectrum characteristics of unsteady forces on the blade surface demonstrate that the energy of the rotor frequency and its harmonics increases significantly and the energy of low frequency disturbance is enhanced when the rotor blade rotates through the distorted region. As a result, the vibration is more obvious in the distorted region, especially the energy of natural vibration frequency of the rotor blade is enhanced. When the compressor stalls, the vibration at the rotor blade root is intensified, which is significantly stronger than at the rotor blade tip. It provides support for evaluating the influence of stall and surge on the lifecycle of rotor blade when suffering from circumferential inlet distortion.