Frequency Distribution Characteristics Research Articles

Newly Discovered Temperature‐Related Long‐Period Signals in Lunar Seismic Data by Deep Learning

AbstractLunar seismic data are essential for understanding the Moon's internal structure and geological history. After five decades, the Apollo data set remains the only available one and continues to offer significant value for current and future lunar seismic data analyses. Recent advances in artificial intelligence for seismology have identified seismic signals that were previously unrecognized. In our study, we utilized deep learning for unsupervised clustering of lunar seismograms, leading to the discovery of a new type of long‐period lunar seismic signal that existed every lunar night from 1969 to 1976. We then conducted a thorough analysis covering the timing, frequency, polarization, and temporal distribution characteristics of this signal to study its properties, occurrence, and probable origins. This signal has a physical cause instead of artificial, such as voltage changes, according to its amplitudes during peaked and flat modes, as well as the digital converter status. Based on its relation to the lunar temperature and documents on Apollo instruments, we conclude that this signal is likely induced by the cyclic heater, with several unresolved questions that might challenge our hypothesis. Excluding interference from this newly identified signal is crucial when analyzing lunar seismic data, particularly in detecting lunar free oscillations. Our research introduced a new method for discovering new types of planetary seismic signals and helped advance our understanding of Apollo seismic data. Furthermore, the discovery of this signal holds valuable implications for the design of future planetary seismometers to avoid encountering similar issues.

Neural processing in the primary auditory cortex following cholinergic lesions of the basal forebrain in ferrets

Cortical acetylcholine (ACh) release has been linked to various cognitive functions, including perceptual learning. We have previously shown that cortical cholinergic innervation is necessary for accurate sound localization in ferrets, as well as for their ability to adapt with training to altered spatial cues. To explore whether these behavioral deficits are associated with changes in the response properties of cortical neurons, we recorded neural activity in the primary auditory cortex (A1) of anesthetized ferrets in which cholinergic inputs had been reduced by making bilateral injections of the immunotoxin ME20.4-SAP in the nucleus basalis (NB) prior to training the animals. The pattern of spontaneous activity of A1 units recorded in the ferrets with cholinergic lesions (NB ACh–) was similar to that in controls, although the proportion of burst-type units was significantly lower. Depletion of ACh also resulted in more synchronous activity in A1. No changes in thresholds, frequency tuning or in the distribution of characteristic frequencies were found in these animals. When tested with normal acoustic inputs, the spatial sensitivity of A1 neurons in the NB ACh– ferrets and the distribution of their preferred interaural level differences also closely resembled those found in control animals, indicating that these properties had not been altered by sound localization training with one ear occluded. Simulating the animals’ previous experience with a virtual earplug in one ear reduced the contralateral preference of A1 units in both groups, but caused azimuth sensitivity to change in slightly different ways, which may reflect the modest adaptation observed in the NB ACh– group. These results show that while ACh is required for behavioral adaptation to altered spatial cues, it is not required for maintenance of the spectral and spatial response properties of A1 neurons.

Experimental analysis of rotating bridge structural responses to existing railway train loads via time-frequency and Hilbert-Huang transform energy spectral analysis.

With the rapid development of national infrastructure projects, there has been a significant increase in intersecting lines in transportation construction. As a result, rotating bridges are increasingly used in engineering projects that span existing railway lines. In order to study the spatial response characteristics and vibration wave transmission mechanisms of the rotating bridge structure under the loading of existing railway trains, field experiments and numerical analyses were conducted. The response characteristics of these bridges were investigated under different types and speeds of adjacent existing lines. A comprehensive methodology has been proposed, integrating the time domain spectrum and the Hilbert-Huang Transform (HHT) energy spectrum for signal processing and vibration analysis. The analysis was carried out using MATLAB 2018a software. This methodology was applied to analyze the test data. The results show that significant resonance phenomenon occurs in the girders of the rotating bridge under the loading of trains on the existing line. The low-frequency component f1 (2-5Hz) is the primary factor contributing to the amplification of the acceleration response in the rotating bridge, while f3 (10-13Hz) plays a secondary role. The frequency distribution characteristics of vibration waves caused by train loads on the existing line have a significant influence on the acceleration response of the rotating bridge's girders. The predominant frequency of vibration waves at each measuring point along the transmission path shows a trend of decreasing → increasing → decreasing. The impact on the rotating bridge structure of vibration waves generated by low-speed freight trains on existing railways is greater. The research findings are of great importance for studying the dynamic response of rotating bridges adjacent to existing railway lines.

IJCM_125A: Prevalence of hypertension and obesity among adolescents: a school based, cross sectional study in Aligarh

Background: Hypertension is a serious medical condition and cause of premature death worldwide, with upwards of 1 in 4 men and 1 in 5 women having the condition. Overweight and obesity are major risk factor for noncommunicable diseases such as: cardiovascular diseases, diabetes, musculoskeletal disorders and some cancers (including endometrial, breast, ovarian, prostate, liver, gallbladder, kidney, and colon). Recent literature suggests hypertension and obesity to be a rising health problem not only in adults but also in adolescents. The early identification and effective management of hypertension and obesity in children and adolescents is key primordial and primary prevention of cardiovascular diseases. Objectives: To determine the prevalence of hypertension and obesity and their associated factors among school going adolescents in Aligarh. Methodology: A school based cross-sectional study was carried out among 569 school students of Class-V to XII studying at schools of Aligarh Muslim University, Aligarh, Uttar Pradesh. Data was collected using a predesigned, structured questionnaire. Blood pressure was measured using digital blood pressure apparatus wit age appropriate cuffs and hypertension was defined using the American Academy of Paediatrics 2017 criteria. BMI was calculated using the standard formula, weight (kg)/height2 (m2), and values were compared with the WHO growth charts. Data was analysed using IBM SPSS 20.0 software. To study frequency distribution and sociodemographic characteristics, descriptive statistics were carried out. Chi square and other appropriate tests were applied. Results: In this study 569 adolescents were participated, of which 324 (56.9%) were males. The prevalence of elevated blood pressure was 10.7% and hypertension was 18.5%. The prevalence of obesity was 2.6%. Male gender, family history of hypertension, overweight/obesity are significantly associated with hypertension. Conclusion: Approximately one fifth of the participants in this study had hypertension, highlighting the need for intervention including lifestyle modification and active case finding.

Influence of initiation modes on vibration frequency induced by single-hole blasting

To further reveal the blasting vibration frequency distribution characteristics induced by different initiation modes of the single borehole cylindrical charge, the PPV and Fourier dominant frequency formula under different initiation modes such as top initiation, bottom initiation, mid-point initiation, and two-point initiation are derived based on the Heelan equivalent unit short-column charge model. The results show that the dominant frequency distribution characteristics near the explosion source are as follows: two-point initiation > mid-point initiation > bottom initiation > top initiation; in the middle and far zones from the explosion source, the difference of dominant frequency induced by various initiation modes is insignificant; the attenuation curves of the dominant frequency of radial and vertical vibration abruptly change at the distance away from the blasting center of 20–50 m and 20–30 m, respectively. However, the curves of centroid frequency under different initiation modes attenuate smoothly with increasing distance, and the distribution rule is two-point initiation > mid-point initiation > bottom initiation > top initiation. In general, the influence of initiation mode on the particle vibration dominant frequency and centroid frequency is gradually weakened with increasing distance. Finally, the theoretical calculation is verified by the experimental data.

THE CORRLATION BETWEEN THE ROLE OF NURSES AS EDUCATORS AND MEDICATION ADHERENCE IN DIABETES MELLITUS PATIENTS AT RAWALUMBU BEKASI HOSPITAL IN 2023

Diabetes Mellitus (DM) known in Indonesia as "Diabetes" is a disease whose prevalence is now increasing. The role of the educator itself is to help patients to improve their health by providing health education and medical actions received so that clients or families can know knowledge that is important to patients or families. This study aims to analyze the relationship between the role of nurses as educators with adherence to Treatment P there is Pasien DM at Rawalumbu Bekasi Hospital in 2023. The research method used is quantitative analytical observational with Cross Sectional Study approach and total sampling technique, which is to select samples based on the frequency distribution of patient respondent characteristics. The samples used in this study were 60 diabetes mellitus patients who were treated in the inpatient room at Rawalumbu Bekasi Hospital. The results of the study identified the role of nurses as good educators with medication adherence in non-adherent diabetes mellitus patients totaling 25 respondents (41.7%). There are Chi-Square test results with a significant level of 95% or a value of α 5% (0.05) obtained p value (0.000) < a value of α (0.05) so that it can be concluded from the results Ho rejected means that there is a relationship between the role of nurses as educators with treatment compliance in diabetes mellitus patients at Rawalumbu Bekasi Hospital in 2023.

The impact of urban spatial environment on COVID-19: a case study in Beijing.

Epidemics are dangerous and difficult to prevent and control, especially in urban areas. Clarifying the correlation between the COVID-19 Outbreak Frequency and the urban spatial environment may help improve cities' ability to respond to such public health emergencies. In this study, we firstly analyzed the spatial distribution characteristics of COVID-19 Outbreak Frequency by correlating the geographic locations of COVID-19 epidemic-affected neighborhoods in the city of Beijing with the time point of onset. Secondly, we created a geographically weighted regression model combining the COVID-19 Outbreak Frequency with the external spatial environmental elements of the city. Thirdly, different grades of epidemic-affected neighborhoods in the study area were classified according to the clustering analysis results. Finally, the correlation between the COVID-19 Outbreak Frequency and the internal spatial environmental elements of different grades of neighborhoods was investigated using a binomial logistic regression model. The study yielded the following results. (i) Epidemic outbreak frequency was evidently correlated with the urban external spatial environment, among building density, volume ratio, density of commercial facilities, density of service facilities, and density of transportation facilities were positively correlated with COVID-19 Outbreak Frequency, while water and greenery coverage was negatively correlated with it. (ii) The correlation between COVID-19 Outbreak Frequency and the internal spatial environmental elements of neighborhoods of different grades differed. House price and the number of households were positively correlated with the COVID-19 Outbreak Frequency in low-end neighborhoods, while the number of households was positively correlated with the COVID-19 Outbreak Frequency in mid-end neighborhoods. In order to achieve spatial justice, society should strive to address the inequality phenomena of income gaps and residential differentiation, and promote fair distribution of spatial environments.

Response characteristics of acoustic emission signal and judgment criteria for different fracture modes

Coal mining is going deeper into the ground, resulting in more intense and frequent mine dynamic disasters. To ensure the early warning of dynamic disasters, it is significant to accurately reveal the differences of acoustic emission (AE) signals generated by rock fractures. This paper focuses on studying how AEs average frequency (AF) and rise angle (RA) change in sandstone during loading, and examines the characteristics of waveform amplitude, energy, and frequency distribution of AE signals from different types of fractures. The findings reveal that the percentage of shear fracture gradually increases with increasing load, and the energy activity of the AE signal is significantly enhanced in the high stress stage. The occurrence of the main fracture was preceded by a large number of low-frequency tensile fracture AE signals, accompanied by a small decrease in RA and a small increase in AF. The spectra of different fracture signals were characterized as “low anomalous F” for shear fractures, “vertical F” for low-frequency tensile fractures, and “high anomalous F” for high-frequency tensile fractures. Their energy distribution in the frequency domain was respectively described as “peak-centered distribution”, “pillar-shaped distribution” and “peak-skewed distribution”. The outcomes of the decomposition and reconstruction from the P- and S-waves reveal that the P wave energy (Ep) dominates in the high-frequency tensile fracture AE signal, while the S wave energy (Es) is greater in the low-frequency tensile fracture and the shear fracture AE signals. The ES/EP threshold value for laboratory discrimination of tensile and shear fracture is 3, as the fracture extends and penetrates, the ES/EP value rises rapidly at the appearance of macroscopic fracture. The findings offer theoretical guidance for monitoring and early warning of coal and rock dynamic hazards as well as revealing the morphology of fracture source.

Exploring Family Needs in Pediatric Intensive Care Units: A Comparative Analysis between COVID-19 Isolation and Non-Isolation Settings

This article aims to analyze the differences in family needs that arise when children are treated in the COVID-19 Isolation PICU and the COVID-19 Non-Isolation PICU. This research was conducted in the period March 2020 to December 2021. This research is a quantitative study with a retrospective cohort approach. The sampling method used was Non-Probability Sampling. The number of samples for the two groups, namely the COVID-19 Isolation PICU and the COVID-19 Non-Isolation PICU at RSUP DR M Djamil Padang, was 62 people. By detailing aspects such as closeness to the patient, service guarantees, mental support, information, and comfort, this research explores the impact of the pandemic situation on families' experiences during their child's intensive care. The research used quantitative methods with a retrospective cohort study at RSUP DR M Djamil Padang, involving patient families from both groups. The data collection instrument used the Critical Care Family Need Inventory (CCFNI) questionnaire, which was translated into Indonesian. Data analysis was carried out by comparing the frequency distribution of family characteristics, length of stay, and family needs through relevant statistical tests.

Characteristic stress variation and microcrack evolution of granite subjected to uniaxial compression using acoustic emission methods

The size of mineral grain has a significant impact on the initiation and propagation of microcracks within rocks. In this study, fine-, medium-, and coarse-grained granites were used to investigate microcrack evolution and characteristic stress under uniaxial compression using the acoustic emission (AE), digital image correlation (DIC), and nuclear magnetic resonance (NMR) measurements. The experimental results show that the characteristic stress of each granite decreased considerably with increasing grain sizes. The inflection points of the b-value occurred earlier with an increase in grain sizes, indicating that the larger grains promote the generation and propagation of microcracks. The distribution characteristics of the average frequency (AF) and the ratio of rise time to amplitude (RA) indicate that the proportion of shear microcracks increases with increasing grain size. The NMR results indicate that the porosity and the proportion of large pores increased with increasing grain size, which may intensify the microcrack evolution. Moreover, analysis of the DIC and AE event rates suggests that the high-displacement regions could serve as a criterion for the degree of microcrack propagation. The study found that granites with larger grains had a higher proportion of high-displacement regions, which can lead to larger-scale cracking or even spalling. These findings are not only beneficial to understand the pattern of microcrack evolution with different grain sizes, but also provide guidance for rock monitoring and instability assessment.

Research on Centre of Inertia Based Frequency Sampling and System Frequency Distribution Characteristics

Research on Centre of Inertia Based Frequency Sampling and System Frequency Distribution Characteristics

Simulation and parameter extraction of flying‐bird motion echo based on laser micro‐Doppler effect

AbstractTo solve the problem of target recognition for flying‐birds and biomimetic flapping‐wing unmanned aerial vehicles (UAVs), a rectangular‐trapezoidal composite scattering model for lidar detection of bird wings has been proposed and established. According to the model, the influence of different line‐of‐sight angles on the time–frequency distribution characteristics of laser micro‐Doppler under the same flapping wing motion was simulated and studied. Then, the flapping‐wing frequency and maximum frequency shift are extracted based on the two‐dimensional Fourier transform and the least squares method. When signal noise ratio = 5 dB, the accuracy rate of flapping‐wing frequency extraction can reach at 100%, the maximum relative error of frequency shift for inner contour extraction is less than 3.0%, and the maximum relative error of frequency shift for outer contour extraction is less than 7.2%.

PENGARUH KONSUMSI MADU TERHADAP KENAIKAN HEMOGLOBIN PADA IBU HAMIL

WHO determines normal Hb levels, the limit for pregnant women is 11.0 g for pregnant women. Honey is given to pregnant women because honey has the property of helping increase hemoglobin levels and helping the absorption of Fe. The aim of this research is to find out how honey affects increasing hemoglobin in pregnant women. This research is a quasi-experimental research with a pre test–post test design with control group. The population in this study were pregnant women in the Baturetno Wonogiri health center area. The sample in this study was 25 respondents from the control group and 25 respondents from the intervention group. Univariate analysis was carried out to determine the frequency distribution of maternal characteristics. In this study, the data that was obtained was then tested for normality using the Shapiro Wilk test. The results of the normality test obtained a p value > 0.05, so it was stated that the data was normally distributed. The results are said to be significant if the p value is <0.05, then H0 is rejected, which means there is a significant influence and if the p value is > 0.05, then H0 is accepted, which means there is no significant influence. Bivariate analysis of the independent t test resulted in a p value of 0.01 where the p value <0.05, it can be stated that it is significant for the variables studied. There is an effect of honey consumption on increasing hemoglobin in pregnant women, so from these results it is hoped that pregnant women will be recommended to consume blood supplement tablets and honey to increase hemoglobin levels and prevent anemia in pregnancy.

The Relationship of Various Physical Activities To Menopausal Symptoms

The purpose of this study was to identify the relationship of various physical activities to menopausal symptoms in women aged 50-60 years in the work area of the Ujunggading Health Center. Research Method: This study uses a correlation research design with a cross sectional approach model with a sample of 75 respondents with a non-probability sampling method, namely using purposive sampling, data collection using GPAQ and MRS questionnaires, data analysis using correlation tests. Results: The results of the study of 75 respondents found the frequency distribution of respondents' characteristics with the most jobs as housewives, namely 23 people (30.7%), the most junior high school education was 20 people (26.7%), and the most menopause duration of 5-7 years, which was 36 people (48.0%). Showing that most respondents had moderate category physical activity 54 (72%) and most respondents experienced moderate category menopausal symptoms 37 (49.3%) There was a relationship between physical activity and menopausal symptoms with p value = 0.000 (p < 0.05). Conclusion: There is a relationship between physical activity and menopausal symptoms where the higher the physical activity carried out, the less menopausal symptoms are felt, menopausal symptoms can be reduced by routinely doing activities and exercising for 15 to 60 minutes every day

An efficient new adaptive variational mode decomposition algorithm for extracting adventitious lung sounds

The rapid and accurate extraction of adventitious lung sounds (ALSs) from original lung sounds is greatly significant for diagnosing lung diseases and assessing lung condition. Due to interference from heart sounds and various noises, the empirical mode decomposition (EMD), variational mode decomposition (VMD) and some other classical algorithms have poor performance. Here, an efficient new adaptive variational mode decomposition (AVMD) algorithm is proposed to improve the efficiency for extracting ALSs. For minimizing the bandwidth of each extracted mode and reducing frequency aliasing between modes, the proposed algorithm constructs a frequency-constrained model based on VMD. In order to further improve its performance, the algorithm adopts a strategy of gradually extracting each mode to determine the optimal number of modes for avoiding the under-decomposition or over-decomposition, and uses Pool Adjacent Violators (PAV) to automatically initialize the center frequency of each mode to reduce algorithm iteration steps. Based on the above improved characteristics, the experiments presented in this paper, which conducted on the artificial simulation signal and 102 groups of lung sounds from 20 patients with severe pulmonary diseases, highlight the proposed AVMD's superiority over the other five algorithms when comprehensively considering both decomposition quality and computational efficiency. Furthermore, the above results of 102 groups of lung sounds are statistically analyzed to obtain the characteristic frequency distribution of ALSs, which can provide important references for clinicians and demonstrate the potential application of the proposed algorithm in the diagnosis of pulmonary diseases.

Study on the variation characteristics of ionospheric F2 layer in Qinghai-Tibet plateau and surrounding areas

The Qinghai-Tibet Plateau (QTP) region is the largest plateau in China and the highest altitude in the world, with a unique geographical environment. Based on the observation data of the 24th solar cycle from six sites on the QTP and its surrounding areas, the multi-station joint detection method is adopted to analyze the temporal variation and spatial distribution characteristics of the critical frequency of the F2 layer(foF2) and the bottom height of the F2 layer (h'F2). The results indicate that the critical frequency of the ionospheric F layer in the QTP is controlled by solar illumination conditions, and conforms to the ionospheric variation law of middle and low latitudes. The height of the F layer has significant regional characteristics, and the F layer height variation in Kunming and Chongqing is particularly drastic, and the average height of the F layer in Chongqing is significantly higher than that in Kunming, which is at a lower latitude, and Lhasa, which is at the same latitude as Chongqing. This phenomenon may be attributed to the unique geographical environment of the QTP, which has an influential effect on the motion of the lower atmosphere, and through the coupling mechanism between the lower and upper atmosphere, has a substantial impact on the F2 layer. The research findings of this article are of great interest to the study of the coupling mechanism between the upper and lower atmosphere.

Field monitoring of vibration characteristics during advanced ductule installation in sandy cobble stratum

The sandy cobble stratum presents a high risk for underground tunnel construction due to its low cohesive properties and susceptibility to loosening and falling. The use of Advanced ductule for grouting reinforcement inevitably results in vibrations, and understanding how these vibrations propagate is crucial in selecting tunnel engineering support schemes and responding to accident risks. Based on a bored tunnel under construction in Xi’an, field vibration propagation characteristics testing were carried out for advanced ductile installation. The time-history response and frequency distribution characteristics of the vibration velocity within the tunnel face under sandy cobble stratum conditions were studied, and the law of vibration propagation attenuation within the tunnel face range was obtained. The results showed that: 1) During the conduit drilling process, the tunnel face mainly experienced vertical vibrations, with the horizontal velocity amplitude accounting for only 15%–20% of the vertical velocity amplitude. At a distance of 1.0 m from the conduit, the vertical velocity amplitude reaches 10.602 mm/s, and the vibration energy concentrates mainly in the frequency range of 150–250 Hz. At a distance of 1.5 m from the conduit, the bidirectional vibration velocity significantly attenuates; 2) The vibration characteristics within the tunnel face can be classified into three primary areas: “Loose and Falling” area, “Significant Vibration” area, and “Vibration Attenuation” area. Loose, falling and significant vibrations occurred mainly within a range of about 1.25 m around the conduit. 3) As the diameter of the conduit decreases, the amplitude of vertical vibration velocity decreases by about 20%. By reducing the design diameter of the advanced ductule in a reasonable manner, it is possible to effectively mitigate the impact of vibration caused by the sandy cobble stratum during installation. This can yield a positive impact, curtailing the occurrence of the tunnel’s collapse phenomenon and ensuring its stability.

Mechanical fault diagnosis of gas-insulated switchgear based on saliency feature of auditory brainstem response under noise background

The mechanical fault of gas-insulated switchgear (GIS) seriously threatens the security of the power grid. Recently, acoustic-based fault diagnosis methods, which have the advantage of non-contact measurement, have been applied to the GIS mechanical fault diagnosis, but vulnerable to the interference of the background noise. To improve the capacity of the acoustic-based GIS fault diagnosis under noise background, by simulating the sound feature extraction ability and anti-noise ability of human auditory system, a novel GIS mechanical fault diagnosis method based on saliency feature of auditory brainstem response (SFABR) is proposed. First, an auditory saliency model, which considers both the auditory periphery and the auditory nerve center was constructed by combining the deep auditory model and the saliency model. After processing GIS emitted acoustic signal, the auditory brainstem response (ABR) was obtained, and the saliency features of the ABR were extracted to obtain the SFABR. Then, the characteristic frequency distribution of the auditory saliency model was adjusted to make it more suitable for the spectral characteristics of the GIS sound signal. Finally, the SFABR was mapped to a two-dimensional CNN to train a model for GIS mechanical fault diagnosis. This method simulates the process of auditory response extraction and the selection effect of auditory attention on sound elements. The 110 kV three-phase GIS fault simulation experiment shows that for GIS mechanical faults, the diagnosis method based on SFABR can obtain 96.1% fault identification accuracy. In different noise environments, compared with the traditional acoustic-based fault diagnosis methods, this method has stronger anti-noise performance, and can more effectively realize the identification of GIS mechanical failure types. In future research, the method can be further extended to fault diagnosis of more types of power equipment.

Extraction and identification of spectrum characteristics of coal and rock hydraulic fracturing and uniaxial compression signals

Microseismic (MS) events generated during coal and rock hydraulic fracturing (HF) include wet events caused by fracturing fluid injection, in addition to dry events caused by stress perturbations. The mixture of these two events makes effective fracturing MS events pickup difficult. This study is based on physical experiments of different coal and rock HF and uniaxial compression. The differences of waveform characteristic parameters of various coal and rock ruptures were analyzed using the Hilbert–Huang transform, leading to some useful conclusions. The phase characteristics of the acoustic emission (AE) energy differed significantly and responded well to the pumping pressure curve. The AE waveforms of HF exhibit similar energy and frequency distribution characteristics after Empirical mode decomposition. The main frequency bands for coal, sandstone, and shale samples are 100–300 kHz, while the mudstone sample is in the range of 50–150 kHz. The decay ratios for coal, sandstone, shale and mudstone samples are 0.78, 0.83, 0.67 and 0.85, respectively. When compared to the uniaxial compression test, the main frequency bands of HF were reduced for coal, sandstone and mudstone samples, whereas shale remained essentially unchanged. The duration, instantaneous energy, and total energy of the HF waveform are smaller than those of uniaxial compression, while the decay ratio is greater, especially for the mudstone samples. The waveform characteristic parameters, trained using the multilayer perceptron neural network, can effectively identify HF and uniaxial compression events with an accuracy of 96%.

Research on the Response Characteristics and Identification of Infrasound Signals in the Jialongcuo Ice Avalanche, Tibet

Due to the inability of remote sensing satellites to monitor avalanches in real time, this study focuses on the glaciers in the rear edge of Jialongcuo, Tibet, and uses infrasound sensors to conduct real-time monitoring of ice avalanches. The following conclusions are drawn: (1) In terms of waveform, compared to background noise, ice avalanche events have a slight left deviation and a slightly steep shape; compared to wind, rain, and floods events, ice avalanche events have less obvious kurtosis and skewness. (2) In terms of frequency distribution, the infrasound frequency generated by ice avalanche events is mainly distributed in the range of 1.5 Hz to 9.5 Hz; compared to other events, ice avalanche events differ some in frequency characteristics. (3) The model based on information entropy and marginal spectral frequency distribution characteristics of infrasound have higher accuracy in signal classification and recognition, as they can better represent the differences between infrasound signals of different events than other features. (4) Compared with the K-nearest neighbor algorithm and classification tree algorithm, the support vector machine and BP (Back Propagation) neural network algorithm are more suitable for identifying infrasound signals in the Jialongcuo ice avalanche. The research results can provide theoretical support for the application of infrasound-based ice avalanche monitoring technology.