Spectrum Analysis Method Research Articles

An innovative approach for FMCW radar vital sign monitoring with removal of respiratory harmonics

Frequency Modulated Continuous Wave (FMCW) radar shows broad research potential in monitoring vital signs. However, the harmonic components generated by the human respiratory process overlap with the frequency band of the heartbeat signal, posing challenges to precisely monitoring the heartbeat signal. To address this issue, this paper introduces the singular spectrum analysis method, which accurately identifies and removes respiratory harmonics by adding a sine signal with the same frequency as the respiratory harmonics to the original time series. Furthermore, the paper introduces energy entropy and the Pearson correlation coefficient to comprehensively decompose physiological signals to optimize the traditional variational mode decomposition algorithm, proposing the EE-VMD and PCC-VMD algorithms. Experimental results demonstrate that the SNR increased, and the accuracy of measuring respiratory rate and heartbeat rate has significantly improved. The results presented in this paper not only advance theoretical methodologies for the monitoring of human vital signs but also underscore the practical applicability of FMCW radar in this domain.

Enhanced Mn(II)/peracetic acid by nitrilotriacetic acid to degrade organic contaminants: Role of Mn(V) and organic radicals

In this work, it was found that the presence of nitrilotriacetic acid (NTA) could enhance the elimination of sulfamethoxazole (SMX) significantly in Mn(II)/peracetic acid (PAA) process. NTA firstly complexed with Mn(II) to produce Mn(II)-NTA complex, which could activate PAA producing CH3C(O)O· and Mn(III)-NTA complex. Subsequently, Mn(V) was generated via two-electron transfer between Mn(III)-NTA complex and PAA. According to the results of UV–vis spectrum analysis, scavenging experiments and chemical probe method, organic radicals and Mn(V) were proved to participate in SMX abatement and Mn(V) was the predominant reactive oxidant. Four possible degradation pathways of SMX in Mn(II)/PAA/NTA process including hydroxylation, amino oxidation, bond cleavage and coupling reaction were proposed based on six identified degradation products. Mn(II)/PAA/NTA process worked only in acidic and neutral conditions and the increase in PAA, Mn(II) or NTA concentration could accelerate SMX removal. This study provides a strategy for improving PAA activation by Mn(II) and an insight into SMX degradation mechanism by Mn(II)/PAA/NTA process.

Deep Learning for Generating Phase-Conditioned Infrared Spectra.

Infrared (IR) spectroscopy is an efficient method for identifying unknown chemical compounds. To accelerate IR spectrum analysis, various calculation and machine learning methods for simulating IR spectra of molecules have been studied in chemical science. However, existing calculation and machine learning methods assumed a rigid constraint that all molecules are in the gas phase, i.e., they overlooked the phase dependency of the IR spectra. In this paper, we propose an efficient phase-aware machine learning method to generate phase-conditioned IR spectra from 2D molecular structures. To this end, we devised a phase-aware graph neural network and combined it with a transformer decoder. To the best of our knowledge, the proposed method is the first IR spectrum generator that can generate the phase-conditioned IR spectra of real-world complex molecules. The proposed method outperformed state-of-the-art methods in the tasks of generating IR spectra on a benchmark dataset containing experimentally measured 11,546 IR spectra of 10,288 unique molecules. All implementations of the proposed method are publicly available at https://github.com/ngs00/PASGeN.

Estimating Vertical Movement and Slip Distribution During the 2018 Boso, Japan, Slow Slip Event From Ocean Bottom Pressure Gauge Data and an Oceanic Model

AbstractMany slow slip events (SSEs) occur beneath the ocean, and continuous ocean‐bottom pressure gauge (OBP) observations provide useful data. OBPs record both oceanic variations and crustal movements, so we developed a multi‐channel singular spectrum analysis method to remove oceanic variations and applied our method to OBPs and oceanic model data. Then components of the oceanic model with good correlations to the OBP data were subtracted from the observed data. This method compensates for the incompleteness of the oceanic model and removes oceanic variations better than use of the original model. We applied the method to OBP data for the 2018 Boso, Japan, SSE to estimate its slip distribution. Comparing slip distributions obtained with and without the OBP data, we found that the distribution obtained using OBP data extended further offshore, and the offshore estimation error was smaller. Our study shows that offshore observations using OBPs are important for characterizing SSEs.

Research on frequency shift signal detection algorithm for jointless track circuits based on improved relaxation algorithm

The accuracy of ZPW-2000 frequency shift signal demodulation is related to the safety and efficiency of high-speed trains. This paper proposed a kind of ZPW-2000 frequency-shift signal detection algorithm based on improved Relaxation algorithm (ZFSD-IR) to address the issue of low accuracy in detecting ZPW-2000 frequency shift signal under strong noise interference, as the traditional fast Fourier transform (FFT) spectrum analysis methods are susceptible to fence effects and spectrum leakage effects. Firstly, the principle of ZPW-2000 jointless track circuit was analyzed, and then the ideal and simplified models of ZPW-2000 frequency shift signal were established, respectively. Finally, the simulation experiments were conducted on ZPW-2000 frequency shift signal detection under different sampling durations and signal-to-noise ratios (SNR). The effectiveness of the proposed algorithm was verified through comparative analysis with the traditional algorithms. The research results indicated that the ZFSD-IR algorithm has better accuracy in carrier-frequency and low-frequency estimation than traditional algorithms, and can achieve accurate detection of ZPW-2000 frequency shift signal under the lower SNR conditions. It has high detection accuracy and good anti-interference ability, ensuring the safe operation of high-speed trains.

Research on in-vivo electron paramagnetic resonance spectrum classification and radiation dose prediction based on machine learning

The in-vivo electron paramagnetic resonance (EPR) method can be used for on-site, rapid, and non-invasive detection of radiation dose to casualties after nuclear and radiation emergencies. For in-vivo EPR spectrum analysis, manual labeling of peaks and calculation of signal intensity are often used, which have problems such as large workload and interference by subjective factors. In this study, a method for automatic classification and identification of in-vivo EPR spectra was established using support vector machine (SVM) technology, which can in-batch and automatically identify and screen out invalid spectra due to vibration and dental surface water interference during in-vivo EPR measurements. In this study, a spectrum analysis method based on genetic algorithm optimization neural network (GA-BPNN) was established, which can automatically identify the radiation-induced signals in in-vivo EPR spectra and predict the radiation doses received by the injured. The experimental results showed that the SVM and GA-BPNN spectrum processing methods established in this study could effectively accomplish the automatic spectra classification and radiation dose prediction, and could meet the needs of dose assessment in nuclear emergency. This study explored the application of machine learning methods in EPR spectrum processing, improved the intelligence level of EPR spectrum processing, and would help to enhance the efficiency of mass EPR spectra processing.

Production cross sections of 102mRh and 108mAg in proton bombed natPb target with 400 MeV energy

The accelerator-driven subcritical system (ADS) is a competitive option for next-generation nuclear energy systems. Production cross sections of long-lived residual radioactive nuclides in a proton-nuclide reaction are basic quantities for the calculation of accumulated radioactivity in the use of ADS systems. This work presents the production cross sections of 102mRh and 108mAg in a natural lead (natPb) target activated by 400 MeV protons. The natPb target was irradiated by a 400 MeV proton beam in NRC “Kurchatov Institute” and measured two decades later by a low background gamma spectrometer in China Jinping Underground Laboratory (CJPL). A spectrum analysis method based on simulated single-isotope spectrum and Bayesian peak fitting was employed to compute the activities and production cross sections of the residual nuclides. The experimentally measured cross-sections for 102mRh and 108mAg were 0.72 ± 0.05 mb and 0.76 ± 0.09 mb respectively. These values are approximately twice as high as those predicted by the QGSP_INCLXX_HP model and fall within the range predicted by the INCL4+ABLA and LAQGSM+GEM2 models for mass numbers A=102 and A=108. These findings offer new experimental insights for ADS research and provide a practical benchmark for theoretical models concerning proton-lead interactions.

The correlation between the active/buried faults and aeromagnetic data in inner and inner-east Anatolia, Turkey

The paper focuses on investigating the active/buried faults in inner and inner-east Anatolia, Turkey based on aeromagnetic data and comparison with the active fault map. This region includes the major tectonic units of Turkey and the largest basins of Turkey (Tuzg.lü Basin (TB) and Sivas Basin (SB)). Thus, the region deserves a detail investigation to delineate the lineaments of the active/buried fault system or the causative sources located in the upper crust. To this end, the region has been divided into two parts as region-1 and 2 including TB and SB, respectively. In this context, the geophysical data processing techniques including power spectrum analysis, high‑pass filter, and second vertical derivative method (SVD) have been applied to the aeromagnetic data of the both regions. Firstly, by utilizing power spectrum analysis, the average depths of the deep and shallow causative sources in the region-1 have been calculated as 11.37 km and 5.01 km whereas those depths are 8.5 km and 3.24 km for region-2. Afterwards, to enhance the responses of the residual anomalies, the high‑pass filter and the SVD method have been applied to the data. Hereby, these potential lineaments produced from the SVD map have been compared with the active fault map to delineate the uncovering buried faults and their lineaments in the region. Contrary to the discussion in the literature, this study revealed for the first time that the Tuzgölü fault zone located in the eastern part of lake does not merge with the Ecemis fault (EF) zone. Furthermore, the study has shown that this fault zone extended from Kayseri city to Sivas city does not junction with North Anatolian Fault Zone in the north, as well.

Singular spectrum analysis to estimate core inflation in Brazil

This paper presents a set of new core inflation measures for Brazil based on the Singular Spectrum Analysis (SSA) method. The measures are based on the official target used in the Brazilian inflation targeting regime. The period of analysis ranges from the beginning of the inflation targeting regime in 1999 and 2021. The SSA measures were compared to the inflation core ones used by the Central Bank of Brazil, through the evaluation of unbiasedness, short-term adjustment dynamics and predictive ability. The measures estimated by SSA meet the desired properties and have a greater predictive capacity than the other inflation cores.

Seismic vulnerability analysis of hospitals and school buildings considering the Gaussian regression algorithm

This study combines the Gaussian regression algorithm to propose a nonlinear regression model that can be used to evaluate the seismic vulnerability of regional hospitals and school buildings. The failure features and disaster mechanisms of hospital and school buildings affected by the Jishishan (JSS) earthquake on December 18, 2023, and the Wenchuan (WC) earthquake on May 12, 2008, were reported. The samples of 252 damaged buildings (37 hospitals and 215 schools) in Dujiangyan city affected by the Wenchuan earthquake for which the author participated in the survey were collected and counted. Hospitals and school buildings were classified according to the types of reinforced concrete (RC) and masonry structures, and earthquake vulnerability probability matrices for hospital and school building clusters were established considering the actual failure probabilities. A total of 2103,213 acceleration records (from the Wenchuan earthquake) monitored by 12 real stations were selected. Using dynamic time history and response spectrum analysis methods, time history and spectrum curves were generated, considering the influence of different seismic directions. Using the developed Gaussian regression model, vulnerability comparison curves and parameter matrices considering multiple regression algorithms were generated. This paper considers the effects of the construction year and number of floors on the seismic vulnerability of hospital and school buildings. Seismic vulnerability curves and failure probability matrices were generated and established on the basis of actual structural failure probabilities. According to regression and vulnerability surface analysis, the evaluation results of the proposed model are highly consistent with actual field observations.

A novel amplitude enhancement method of EMAT for High-frequency Rayleigh-like waves in Circumferential propagation

Currently, in terms of resolution and excitation efficiency for pipeline inspection, the high-frequency Rayleigh-like wave excited by an EMAT with a traditional Rayleigh wave EMAT structure is not optimal when using the same magnet volume. This paper introduces an EMAT performance evaluation method focused on 'bandwidth' in the high-frequency-thickness region of circumferential guided waves. A wavenumber spectrum analysis method utilizing combined equivalent surface stresses is proposed to quantify this optimize design. Comparative studies, including theoretical analysis and experimental validation, demonstrate that incorporating bandwidth significantly improves the design of Rayleigh-like waves at high frequencies. The proposed EMAT achieves a performance improvement of 2.4 times for inside pipe excitation and 2.6 times for outside pipe excitation over the conventional structure. The occurrence of multiple wave packets outside the optimal excitation frequency range is acknowledged. Therefore, this method offers a new approach for optimizing EMATs for Rayleigh-like waves.

Variation of temperature increase rate in the Northern Hemisphere according to latitude, longitude and altitude: the Turkey example

Global climate change notably influences meteorological variables such as temperature, affecting regions and countries worldwide. In this study, monthly average temperature data spanning 73 years (1950–2022) were analyzed for 28 stations in the city centers across seven regions of Turkey. The station warming rates (SWR) were calculated for selected stations and the overall country using Singular Spectrum Analysis (SSA) and Least Square Polynomial Fit (LSPF) methods. The temperature trend in Turkey exhibited a decline until the late 1970s, followed by a continuous rise due to global warming. Between 1980 and 2022, the average SWR in Turkey was found to be 0.52 °C/decade. The SWR was determined to be the lowest in Antakya (0.28 °C/decade) and the highest in Erzincan (0.69 °C/decade). The relationship between SWR and latitude, longitude, altitude, and distance to Null Island (D2NI) was explored through linear regression analysis. Altitude and D2NI were found to be the most significant variables, influencing the SWR. For altitude, the correlation coefficient (R) was 0.39 with a statistically significant value (p) of 0.039. For D2NI, R, and p values were 0.39 and 0.038, respectively. Furthermore, in the multiple regression analysis involving altitude and D2NI, R and p values were determined to be 0.50 and 0.029, respectively. Furthermore, the collinearity analysis indicates no collinearity between altitude and D2NI, suggesting that their effects are separated in the multiple regression.

가상악기를 활용한 거문고와 첼로의 음색비교 연구

This study aimed to compare and analyze the timbre of the geomungo and cello, focusing on harmonic analysis to examine the tonal characteristics of both instruments. Using pizzicato, a common playing technique for both instruments, A2, A3, and A4 notes were recorded, and the sound sources were generated using virtual instruments. By comparing the timbre of the two instruments through spectrum, spectrogram, envelope, and sound pressure analysis methods, it was found that the geomungo showed a stronger influence of harmonics than the fundamental frequency, characterized by a very fast attack and rapid release, which are key factors in forming the geomungo’s clear and bright tone. In the case of the cello, the fundamental frequency had a stronger influence than the harmonics, and it was found that the presence of subharmonics and non-harmonic partials, along with a fast attack and slow release, contribute to its deep and rich tone. This study provides an understanding of the tonal characteristics of the geomungo and cello, and it is hoped that this will contribute to the harmonious fusion of traditional Korean and Western music, as well as foster new musical diversity and creativity.

Research on a novel γ-ray spectrum analysis method for low- and intermediate-level radioactive solid waste in nuclear power plants

Accurate nuclide identification in γ-spectrum analysis of low- and intermediate-level radioactive waste with high-purity germanium detectors necessitates initial forced fitting with a nuclide library, yet inaccuracies in library data may lead to misidentification and missing nuclides. To this end, background clipping strategies were hereby analyzed, and a novel deconvolution spectrum analysis method was proposed, which utilized continuous wavelet transform for peak searching and Gaussian first-order derivative quadratic convolution for calculating peak width. Furthermore, to effectively realize the nuclide identification and peak area calculation, a response filter function model was established through the peak shape calibration. By eliminating the need for nuclide library parameter settings prior to overlapping peak separation, the issue of inaccurate matching arising from reliance on the precision of the nuclide library was addressed. Moreover, spectrum analysis experiments were carried out on standard point sources and 200 L drums, and the results were compared and analyzed using GammaVision. Compared to the GammaVision results set by the accurate nuclide library, the area error of strong peaks decreased from 27.5 % to 4.82 %, while that of weak peaks witnessed a decline from 49.98 % to 27.5 %. Finally, the accuracy of the proposed method was verified using the Pakistan Nuclear Library.

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Abstract Piezoelectric ultrasonic transducers with the function of energy conversation, as well as their numerous advantages in high-power density, quick response, flexible design, and service reliability, are involved in wide applications of industrial processing, precision driving, smart sensing, and medical services. The electromechanical equivalent circuit and Kirchhoff’s law indicate that mechatronics parameters are essential for performance evaluation, reliability analysis, and fault diagnosis of ultrasonic transducers. Importantly, the ultrasonic transducer is a time-variant system, data of one single parameter collected from a certain test cannot match with the data of another single parameter acquired from a different test. So, a synchronous and precise online measurement of electronic parameters is encouraged for performance evaluation and optimization design of ultrasonic transducers. With the combination of virtual instrument technology, an asynchronous measurement system of electrical excitation parameters for the ultrasonic transducers of linear driving motors was established in this study. Furthermore, the systematic measurement methods and error theory were illustrated, including the calculation methods and measuring circuits of electric signals. Experimental results proved that the proposed system and methods for measuring the input electronic power of ultrasonic transducer (e.g. effective value method for voltage and current, energy moment method for frequency, and spectrum analysis method for phase difference) are highly precise, quickly responsive, robust, and reliable for ultrasonic transducers. The findings of this study provide valuable references and suggestions for efficient, accurate, and online performance evaluation of ultrasonic transducers, particularly for piezoelectric transducers utilizing ultrasonic high-voltage exciting signals.

Extraction and evaluation of cable forces of a cable-stayed bridge based on amplitude and phase estimation method

In order to identify the time-varying frequency and amplitude of structural vibration based on the bridge structural health monitoring data and obtain the cable force of cable-stayed bridges in real time, a spectrum analysis method based on amplitude and phase estimation (APES) was proposed in this study. The amplitude spectrum of the acceleration data is first calculated by the APES method, the real-time spectrogram of the cable is obtained by the sliding window method. Then the modal frequency and amplitude are automatically extracted from the real-time spectrum by using a frequency extrusion post-processing technique, which can be regarded as the average value of the instantaneous frequency and amplitude respectively. Next, the fundamental frequency of the cable is extracted by using an automatic identification method, and the performance of the proposed method is verified. Finally, real-time scoring of cable forces and structural condition assessment is achieved with consideration of the moderation index model as well as the material strength. The results show that the APES method can use shorter calculation samples than the traditional Fast Fourier Transform (FFT) to obtain higher resolution and more accurate amplitude, which provides a theoretical basis for the real-time identification of fundamental frequency based on short-term monitoring data. The frequency extrusion post-processing-algorithm can reduce the spectrum recognition delay and improve timeliness of the cable force evaluation. The time-varying cable force with an interval of 10 s can be used to reflect the health status of the cable in time. The research results can provide technical support for the real-time extraction of cable force of long-span cable-stayed bridges, and can also provide an effective basis for component condition evaluation and bridge maintenance decision-making.

Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements

The time-varying periodic variations in Global Navigation Satellite System (GNSS) stations affect the reliable time series analysis and appropriate geophysical interpretation. In this study, we apply the singular spectrum analysis (SSA) method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets. These include 23-year observations from the Crustal Movement Observation Network of China (CMONOC), displacements inferred from the Gravity Recovery and Climate Experiment (GRACE), and loadings derived from Geophysical models (GM). The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations, and the SSA method outperforms the traditional least squares fitting (LSF) method in extracting and interpreting the time-varying seasonal signals from the original time series. The decrease in the root mean square (RMS) correlates well with the annual cycle variance estimated by the SSA method, and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method. With SSA analysis, the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues. Moreover, both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations, and the geophysical effects can account for 71% of the GNSS annual amplitudes, and the average RMS reduction is 15%. The SSA method has proved to be useful for investigating the GNSS time-varying seasonal signals. It could be applicable as an auxiliary tool in the improvement of non-linear variations investigations.

Alternative data evaluation methodology for infrared thermography analogous to the Shock Response Spectrum analysis method

We propose an alternative method for processing infrared thermography (IRT) data based on a thermal 1-layer model. The method is based on the analogy of the Shock Response Spectrum (SRS) analysis for mechanical systems (ISO 18431). A thermal Q-factor, similar to the resonance sharpness (Q-factor) of a mechanical oscillator, is introduced as a parameter for selecting a specific thermal 1-layer model. Two main aspects of this method and corresponding properties have been considered: the strictly model-based treatment of this methodology and an empirical introduction of additional bandpass filters. The method is validated with two practical examples: for a homogeneous polymer sheet with blind holes and an inhomogeneous plate made of carbon fiber reinforced polymer (CFRP) with artificial defects, the capability of defect detection is compared with established methods. The comparison of the results with the commonly used data processing methods of IRT as Pulsed Phase Thermography (PPT) and Modified Differential Absolute Contrast (MDAC) shows equivalent or sometimes improved performance.

Qualitative and quantitative analysis of major components of Qiye Shen'an tablet by UPLC Q-TOF/MS and UPLC-TQS-MS/MS

The Qiye Shen'an tablet is formulated using total saponins extracted from Notoginseng stems and leaves. At present, the study on its chemical composition remains scarce and the quality control indicators are limited, which seriously hindering the effective quality control and clinical research. Hence, this study aims to comprehensively identify and characterize the Qiye Shen'an tablet while controlling its main component contents. To achieve a comprehensive understanding of this tablet, an ultra-high performance liquid coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) method was employed for its separation and characterization. Through the analysis of 99 batches of Qiye Shen'an tablet produced by 9 enterprises, the characteristic quantitative components were further obtained. A total of 113 compounds were characterized and identified, among which 17 representative compounds were selected, and the ultra-high performance liquid-triple quadrupole tandem mass spectrometry (UPLC-TQS-MS/MS) method was established for further quantitative determination. It has been successfully applied to the content determination of 99 batches of Qiye Shen'an tablet, and a new quality control method is being formed. This study provides a new method for chemical spectrum analysis and determination of labeled compounds of Qiye Shen'an tablet, and lays a solid foundation for further study of potential active ingredients and comprehensive quality evaluation.

Characteristics of inclusions in chang 7 member and shale oil accumulation stages in Zhijing-Ansai area, Ordos Basin.

In order to further clarify the shale oil accumulation period of the Chang 7 member of the Mesozoic Triassic Yanchang Formation in the Zhijing-Ansai area of the central Ordos Basin, Using fluid inclusion petrography analysis, microscopic temperature measurement, salinity analysis and fluorescence spectrum analysis methods, combined with the burial history-thermal history recovery in the area, the oil and gas accumulation period of the Chang 7 member of the Yanchang Formation in the Zhijing-Ansai area was comprehensively analyzed. Sixteen shale oil reservoir samples of the Mesozoic Triassic Yanchang Formation in seven typical wells in the study area were selected.The results show that the fluid inclusions in the Chang 7 member of Yanchang Formation can be divided into two stages. The first stage inclusions mainly develop liquid hydrocarbon inclusions and a large number of associated brine inclusions, which are mainly beaded in fracture-filled quartz and fracture-filled calcite. The fluorescence color is blue and blue-green, and the homogenization temperature of the associated brine inclusions is between 90-110°C. The second stage inclusions are mainly gas-liquid two-phase hydrocarbon inclusions, gas inclusions and asphalt inclusions. Most of them are distributed in the fracture-filled quartz, and the temperature of the associated brine inclusions is between 120-130°C. Fluid inclusions in Chang 7 member of the Yanchang Formation can be divided into two stages. The CO2 inclusions and high temperature inclusions in the Chang 7 member of the Yanchang Formation are mainly derived from deep volcanic activity in the crust.