Main Frequency Bands Research Articles

Surface wave mitigation by periodic wave barriers under a moving load: theoretical analysis, numerical simulation and experimental validation.

Periodic wave barriers (PWB) open a new window for vibration mitigation. However, the Doppler effect is rarely considered in most of the previous investigations on the control of ambient vibration induced by moving loads. This article reveals the significance of the speed and frequency of moving loads on surface waves, and improves the design method of PWB for ambient vibration reduction and isolation. First, the theoretical expression of the main frequency band of surface waves propagating in an elastic half-space caused by a moving load was obtained. Comparisons with the numerical results under three different types of traffic loads were also conducted and good agreement was found. Second, the theoretical expression and numerical results were verified by experimental studies. Some inherent properties of wave propagation caused by a moving load in an elastic half-space were also revealed. Third, two kinds of PWBs, i.e. periodic empty trench barrier and periodic pile barrier, were introduced to mitigate wave propagation. It has been confirmed that if the attenuation zones of PWB match the target frequency bands given by the theoretical expression, good vibration mitigation can be achieved. This article is part of the theme issue 'Current developments in elastic and acoustic metamaterials science (Part 1)'.

A Smith Predictor Modified with a Pseudo Feedforward Control for the Charge-Coupled Device-Based Optoelectronic Tracking System.

In the high-precision optoelectronic tracking system (OTS) based on a charge-coupled device (CCD), the boresight error extracted from the tracking image contains an undeniable delay, which directly limits the control bandwidth of visual tracking. High bandwidth means high response speed and tracking accuracy. Generally, a model-based delay compensation control method called the Smith predictor is utilized to separate time delay from the closed loop to promote the control bandwidth. However, due to the existence of errors between the established model and the real object, the improvement in the bandwidth is still limited to ensure system stability, resulting in insufficient tracking performance. In this paper, to solve the problem, a Smith predictor modified with pseudo feedforward control for the OTS is proposed. The experimental results demonstrate that the proposed method achieves significant improvements in tracking performance, reducing the maximum residual error at 1 Hz from 365 arcseconds (using the classic Smith predictor) to 283 arcseconds, a 22.5% improvement. Across the main frequency band (0.2 Hz to 2 Hz), the residual errors were consistently lower using the proposed method.

Mechanism of acoustic pressure spectrum shifting toward lower frequencies in applied current thermoacoustic imaging

Objective. Thermoacoustic tomography (TAT) is a promising imaging technique used for early cancer diagnosis, tumor therapy, animal study and brain imaging. Although it is widely known that the TAT frequency response depends on the pulse width of the source and the size of the object, a thorough comprehension of the quantitative frequency modulation in TAT and the mechanism governing the shift in the thermoacoustic pressure spectrum towards lower frequencies with respect to the excitation source is still lacking. This study aims to understand why the acoustic pressure spectrum and the final voltage signals shift towards lower frequencies in TAT. Approach. We employed a linear time-invariant model. In the proposed model, the applied current thermoacoustic imaging (ACTAI) process is divided into the thermoacoustic stage and the acoustoelectric stage. These two stages are characterized by the thermoacoustic transfer function(TATF) and the transducer transfer function (TDTF), respectively. We confirmed the effectiveness of our model through a rigorous examination involving both simulations and experiments. Main results. Simulation results indicate that the TATF behaves as a low-pass filter. The inherent low-pass nature induces a shift towards low frequencies in the acoustic pressure spectrum. Experiments further confirm this behavior, demonstrating that the final electrical voltage also shifts towards low frequencies. Notably, employing the proposed model, there is a remarkable consistency between the main frequency bands of the synthesized and measured final voltage spectrum. Significance. The proposed model thoroughly explains how the TATF causes shifts to low frequencies in both the acoustic pressure spectrum and the final voltage spectrum in TAT. These insights deepen our understanding of optimizing TAT systems in the frequency domain, including aspects like filter design and transducer selection. Furthermore, we underscore the potential significance of this discovery for medical applications, particularly in the context of cancer diagnosis.

Experimental study of the “AE quiet period” on the eve of brittle failure in hard rock

Acoustic emission (AE) signals on the eve of brittle failure in hard rock often indicate a quiet period, i.e., a significant decrease in the number of AE signals. To address the current problem of the poor understanding of the quiet period, the failure process of hard rock was simulated by tests and acquired the AE signals. The AE signal during the quiet period were analyzed. First, compared with the AE signals in other loading periods, the AE signals during the quiet period are characterized by a greater hit amplitude, a greater rise time and ring count, a sudden increase in the cumulative absolute energy, a greater amplitude of the signals in the main frequency band and so on. Second, the inhomogeneity of rock grains, stress level and loading rate all have a nonnegligible influence. The more inhomogeneous the rock grains are, the higher the stress level is, or the larger the loading rate is, the longer the duration of the quiet period is. Third, a hard rock damage evolution equation based on AE considering the effect of the quiet period is proposed, which can reasonably reflect the objective fact of accelerating damage during this period. Finally, the quiet period is due to the brittle failure of hard rock with inhomogeneous grains under high stress conditions, so identifying the quiet period is important for AE-based monitoring and warning of hard rock failure.

Evoked oscillatory cortical activity during acute pain: Probing brain in pain by transcranial magnetic stimulation combined with electroencephalogram.

Temporal dynamics of local cortical rhythms during acute pain remain largely unknown. The current study used a novel approach based on transcranial magnetic stimulation combined with electroencephalogram (TMS-EEG) to investigate evoked-oscillatory cortical activity during acute pain. Motor (M1) and dorsolateral prefrontal cortex (DLPFC) were probed by TMS, respectively, to record oscillatory power (event-related spectral perturbation and relative spectral power) and phase synchronization (inter-trial coherence) by 63 EEG channels during experimentally induced acute heat pain in 24 healthy participants. TMS-EEG was recorded before, during, and after noxious heat (acute pain condition) and non-noxious warm (Control condition), delivered in a randomized sequence. The main frequency bands (α, β1, and β2) of TMS-evoked potentials after M1 and DLPFC stimulation were recorded close to the TMS coil and remotely. Cold and heat pain thresholds were measured before TMS-EEG. Over M1, acute pain decreased α-band oscillatory power locally and α-band phase synchronization remotely in parietal-occipital clusters compared with non-noxious warm (all p < .05). The remote (parietal-occipital) decrease in α-band phase synchronization during acute pain correlated with the cold (p = .001) and heat pain thresholds (p = .023) and to local (M1) α-band oscillatory power decrease (p = .024). Over DLPFC, acute pain only decreased β1-band power locally compared with non-noxious warm (p = .015). Thus, evoked-oscillatory cortical activity to M1 stimulation is reduced by acute pain in central and parietal-occipital regions and correlated with pain sensitivity, in contrast to DLPFC, which had only local effects. This finding expands the significance of α and β band oscillations and may have relevance for pain therapies.

Separation of signal and harmonics in non-explosive seismic prospecting with amplitude and nonlinear frequency-modulated signals

When vibroseis oscillations are excited, along with the main signal, harmonics are generated. They travel into the Earth and, like the main signal, interact with the target reflectors. Harmonics have a wider than that of the main signal frequency band, so they can be used to increase the resolution of the seismic data. To do this, the signal-related data should be separated from the harmonic-related data. This problem can be successfully solved by the previously proposed optimization recursive filtering algorithm, which, however, was developed only for linearly frequency-modulated signals. In this work, the algorithm is generalized to the case of amplitude modulation and nonlinear frequency modulation. Examples of application of the technique to increase the resolution of real vibroseis data are given.

Assessment of adjacent building vibrations induced by metro with a multigrid fully coupled method

The vibrations generated by metro operations can cause structural damage and discomfort to occupants adjacent to the metro lines. In this study, a multigrid fully coupled method of metro vehicle-track-station-soil-building systems is proposed to predict and assess building vibrations before construction. This approach facilitates the efficient calculation of the fully coupled system, while ensuring precise simulations through the utilization of multigrid techniques for wheel-rail contact, track, station, soil, and building components. Using the newly built opera theatre along Beijing metro line 4 as a case, the study demonstrates that the multigrid fully coupled model can predict the dynamics characteristics of metro-induced vibrations and distribution with high accuracy compared with the field tests. Specifically, it was found that metro operations could result in vibrations exceeding specified limits in the opera theatre, particularly at 10∼40 Hz (the building’s natural frequency) and 60∼80 Hz (the main frequency band of vibration caused by the metro). Finally, the mechanism of excessive vibration and the effectiveness of targeted vibration mitigation measures were analyzed with the proposed method. These findings have promising implications for wider applications in environmental assessments and control strategies for new metro lines or vibration-sensitive buildings.

Study on the precursor characteristics of coal energy spontaneous combustion process using infrasound wave monitoring and warning

The spontaneous combustion of coal energy has seriously threatened energy security, and there is an urgent need for monitoring and warning of coal energy. Therefore, this article innovatively proposes a method of using infrasound waves to monitor coal energy spontaneous combustion, establishes a coal spontaneous combustion(CSC) infrasound wave experimental testing system, and studies the precursor characteristics of coal energy spontaneous combustion process. The results indicate that there is a good positive correlation between the amplitude of the dominant frequency of the infrasound wave generated by CSC and temperature, with a correlation coefficient of R2 > 0.85. The energy proportion of the infrasound signal from 0 to 0.12Hz exceeds 80 %. And as the CSC stage progresses, the energy of infrasound waves in the 0.04–0.08Hz frequency band increases significantly, and the changes in infrasound signals in this frequency band have a good correlation with temperature, with a correlation coefficient above 0.8. This frequency band is the main frequency band of infrasound waves during the CSC process. The research in this article provides a theoretical basis for the application of infrasound wave monitoring and warning of coal energy spontaneous combustion, and it is of great significance to ensure the safe mining of coal energy.

Microseismic activity characteristics and range evaluation of hydraulic fracturing in coal seam

Accurately evaluating hydraulic fracturing (HF) activity characteristics and impact range is critical to optimizing the HF scheme design. This study proposes an adaptive threshold peak detection method and a wavelet transform-support vector machine (WT-SVM) polarity analysis method based on microseismic (MS) monitoring data from a coal mine in Guizhou, China. The results show that the adaptive threshold peak detection method effectively improves the accuracy and stability of the P-wave initial arrival pickup for low signal-to-noise ratio (SNR) signals. The main frequency band of the MS signal of HF is focused on 150–300 Hz. The improved particle swarm optimization algorithm was used by introducing a random-weight strategy to determine the high-density impact areas of the HF within approximately 20 m on both sides of the fracturing borehole. Density cloud map analysis revealed a small area of the blank zone at the junction of the fracturing section, which provided a basis for fracturing parameter design and scheme optimization. The directional characteristics of the MS waveform were quantitatively described by polarity analysis, where the dip angle distribution ranged from 39° to 49°, the strike angle ranged from 61° to 74°, the slip angle was concentrated near 44°, and the stretch angle ranged from 61° to 74°. The WT-SVM proposed in this study overcame the effects of low SNR signals and the limitations of a small-area station network; 62% of the shear ruptures and 38% of the tensile ruptures of the HF were obtained. Shear cracks were the primary expression of the HF rupture type.

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 Step-down Resonance Suppression and Filtering Device

In recent years, offshore wind farms have developed rapidly, and their installed capacity is getting bigger and bigger, and the offshore distance is getting farther and farther. In order to meet the needs of large-capacity and long-distance offshore wind power transmission, the AC submarine cable has the characteristics of long distance, high voltage and large cross-section. Along with the significantly improved transmission capacity, its equivalent capacitance is also increasing, which further reduces the resonance frequency of the offshore wind power AC transmission system. If the parallel resonance frequency of the offshore wind power transmission system is close to the main harmonic current frequency band of wind turbines, it will cause harmful system resonance and harmonic amplification, significantly increasing the harmonic current of grid-connected lines and the voltage distortion rate of nodes in nearby power grids, and seriously affect the safety of equipment and the safe and stable operation of offshore wind power transmission system. A step-down resonance suppression filtering device applied to the offshore wind power transmission system is proposed. The AC cable is connected to the low-voltage 35 kV side of the compensation winding of the centralized control center to eliminate the resonance risk of the 220 kV system and filter out the harmonic current. Compared with the existing technical scheme, the device has the advantages of simple control, reliable operation, stable resonance suppression effect, low operation loss and the like, and has great engineering popularization value.

Empirical Ramanujan decomposition and iterative envelope spectrum for fault diagnosis

Ramanujan Fourier mode decomposition obtains components by scanning from low frequency to high frequency, which will cause too many components, and then the fault information in mode components is incomplete. Based on this, the empirical Ramanujan decomposition (ERD) method is proposed. Firstly, ERD uses the optimized lowest minima technique to segment the spectrum and determines the segmentation boundary and the number of components. Subsequently, ERD constructs the filter bank for filtering and retains the spectral components corresponding to the main frequency band. Finally, the time domain components are recovered by the inverse Ramanujan Fourier transform. To further improve the capability of envelope spectrum (ES), an iterative ES (IES) method is proposed. IES enhances the periodic components through iterative envelope to make the fault feature more conspicuous. The analysis results of simulation and experimental signals show that the ERD and IES can extract features effectively.

Intra- and inter-brain synchrony oscillations underlying social adjustment

Humans naturally synchronize their behavior with other people. However, although it happens almost automatically, adjusting behavior and conformity to others is a complex phenomenon whose neural mechanisms are still yet to be understood entirely. The present experiment aimed to study the oscillatory synchronization mechanisms underlying automatic dyadic convergence in an EEG hyperscanning experiment. Thirty-six people performed a cooperative decision-making task where dyads had to guess the correct position of a point on a line. A reinforcement learning algorithm was used to model different aspects of the participants’ behavior and their expectations of their peers. Intra- and inter-connectivity among electrode sites were assessed using inter-site phase clustering in three main frequency bands (theta, alpha, beta) using a two-level Bayesian mixed-effects modeling approach. The results showed two oscillatory synchronization dynamics related to attention and executive functions in alpha and reinforcement learning in theta. In addition, inter-brain synchrony was mainly driven by beta oscillations. This study contributes preliminary evidence on the phase-coherence mechanism underlying inter-personal behavioral adjustment.

Complexity analysis from EEG data in congestive heart failure: A study via approximate entropy.

Congestive heart failure (CHF) is a very complex clinical syndrome that may lead to ischemic cerebral hypoxia condition. The aim of the present study is to analyze the effects of CHF on brain activity through electroencephalographic (EEG) complexity measures, like approximate entropy (ApEn). Twenty patients with CHF and 18 healthy elderly people were recruited. ApEn values were evaluated in the total spectrum (0.2-47 Hz) and main EEG frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-11 Hz), alpha 2 (11-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz) to identify differences between CHF group and control. Moreover, a correlation analysis was performed between ApEn parameters and clinical data (i.e., B-type natriuretic peptides (BNP), New York Heart Association (NYHA), and systolic blood pressure (SBP)) within the CHF group. Statistical topographic maps showed statistically significant differences between the two groups in the total spectrum and theta frequency band. Within the CHF group, significant negative correlations were found between total ApEn and BNP in O2 channel and between theta ApEn and NYHA scores in Fp1, Fp2, and Fz channels; instead, a significant positive correlation was found between theta ApEn and SBP in C3 channel and a nearly significant positive correlation was obtained between theta ApEn and SBP in F4 channel. EEG abnormalities in CHF are very similar to those observed in cognitive-impaired patients, suggesting analogies between the effects of neurodegeneration and brain chronic hypovolaemia due to heart disorder and underlying high brain sensitivity to CHF.

Prediction of ground-borne vibration from random traffic flow and road roughness: Theoretical model and experimental validation

With the densification and closer distance to buildings of road traffic network in urban areas, the assessment and control of environmental vibrations becomes the focus of attention, in which the prediction of traffic flow-induced ground vibration is very critical. However, few studies have been reported on the theoretical prediction method of traffic flow-induced ground vibration from the perspective of stochastic theory. The present work contributes to the perfection and innovation of the current methodologies for the prediction of traffic flow-induced ground vibration. In this paper, a semi-analytical and semi-numerical method for predicting traffic flow induced ground vibrations is developed, in which the random effect generated from traffic flow and road roughness is considered by establishing the vehicle-road-soil coupling model. Aiming to predict the long-term vibration and transient vibration induced by road traffic flow, the average and the adverse velocity levels are used as the evaluation indicators. The effectiveness of the proposed method is validated by an on-site experiment, and the characteristics of ground vibrations are investigated in time and frequency domains, respectively. The results demonstrate that the proposed method can effectively predict the road traffic flow-induced ground vibrations, and the randomness of both traffic flow and road roughness cannot be neglected. For the experimental site, the main frequency band of ground vibrations concentrates on 7–25 Hz, and the predominant center frequency is 12.5 Hz, resulting from the resonance between the overlapping dominant frequency bands of the dynamic vehicle loads and the natural frequency of the soil.

Distributed dynamic strain sensing of very long period and long period events on telecom fiber-optic cables at Vulcano, Italy

Volcano-seismic signals can help for volcanic hazard estimation and eruption forecasting. However, the underlying mechanism for their low frequency components is still a matter of debate. Here, we show signatures of dynamic strain records from Distributed Acoustic Sensing in the low frequencies of volcanic signals at Vulcano Island, Italy. Signs of unrest have been observed since September 2021, with CO2 degassing and occurrence of long period and very long period events. We interrogated a fiber-optic telecommunication cable on-shore and off-shore linking Vulcano Island to Sicily. We explore various approaches to automatically detect seismo-volcanic events both adapting conventional algorithms and using machine learning techniques. During one month of acquisition, we found 1488 events with a great variety of waveforms composed of two main frequency bands (from 0.1 to 0.2 Hz and from 3 to 5 Hz) with various relative amplitudes. On the basis of spectral signature and family classification, we propose a model in which gas accumulates in the hydrothermal system and is released through a series of resonating fractures until the surface. Our findings demonstrate that fiber optic telecom cables in association with cutting-edge machine learning algorithms contribute to a better understanding and monitoring of volcanic hydrothermal systems.

Study on feeding behavior and biological sound of Sebastes schlegelii

The construction of marine ranches can enrich and conserve the fishery resources and improve the marine ecosystem, which helps realize the sustainable utilization of these resources. Sebastes schlegelii is a major breeding and releasing fish species in the marine ranches of North China. Its behavioral characteristics can be understood better by researching its vocalization, which will provide data support for constructing acoustic taming marine ranches with S. schlegelii as the target fish species. However, there are few studies focusing on its sounds and behaviors. Therefore, based on the passive acoustic monitoring technology, the audios of underwater noises made by S. schlegelii were extracted using an AQH hydrophone. The high-definition internet protocol camera was used to monitor the behavior change of S. schlegelii. Then, by collating and replaying the collected audios and videos, the feeding behavior and biological noises of S. schlegelii were matched to analyze their relationship. Results are as follows: (1) The noise of chewing settling granular baits (Φ5.0 mm) has a main frequency band and sound pressure level of 2000~4500 Hz and 96.53 ± 0.65 dB, respectively; in this feeding process, the main frequency band and sound pressure level of the swimming noise are 25~400 Hz and 95.63 ± 0.38 dB, respectively; the values are 500~700 Hz and 97.34 ± 4.91 dB, respectively, for the noise of flapping the water with the tail. (2) The sound signals emitted by S. schlegelii are mostly presented as single pulses during normal habitation or ingestion of baits on the surface of the water tank. However, S. schlegelii will attack and fight against each other when scrambling for baits, during which these signals are presented as continuous pulses. To sum up, the vocalization of S. schlegelii is closely related to feeding activities, and the sounds produced under different behaviors have specific biological significance.

Polarization-Independent Dual-Band Metasurface Absorber for Wireless Power Transmission

A new design of a polarization-independent dual-band metasurface absorber based on an improved Minkowski fractal structure is proposed in this paper. It is designed for wireless power transmission. The proposed metasurface absorber is composed of many sub-wavelength elements. By adjusting the structure of the elements, it has rotational symmetry and multi-frequency resonance characteristics. The proposed metasurface absorber array can keep more than 87% harvested efficiency at 2.45GHz and 93% harvested efficiency at 5.8GHz for arbitrary polarization of incident electromagnetic waves. The working frequency of the proposed absorber can cover the main working frequency bands of the current microwave wireless energy transmission system. The proposed metasurface absorber, which has the great advantage of subwavelength, polarization-independent, and high harvested efficiency, is suitable for wireless power transmission, especially in ambient power harvesting and UAV remote power supply.

Identification method for subgrade settlement of ballastless track based on vehicle vibration signals and machine learning

High-frequency train loads and complex environmental factors over a long period will inevitably cause subgrade settlement, an issue that adversely affects line smoothness. The existing monitoring methods are inefficient, manpower consuming and small in scope. This paper takes the subgrade settlement disease of the double-block ballastless track as the research object and proposes a subgrade settlement identification method based on vehicle vibration signals. In addition, it establishes a vehicle-track-subgrade vertical coupling model that combines feature extraction with algorithms such as support vector machines (SVMs) and convolutional neural networks (CNNs) to accurately identify subgrade settlement diseases on ballastless tracks. The results show: I) the subgrade settlement is far more impactful than fastener failure and debonding of the supporting layer on the vehicle vibration, with the main frequency band concentrated in 0 to 10 Hz, and the vertical vibration acceleration of the vehicle body and bogie can be used as a sensitive feature to identify ballastless track subgrade settlement, II) both the particle swarm optimization (PSO)-SVM and CNN-SVM algorithms can effectively determine the existence of subgrade settlement and the values of the settlement wavelength and amplitude. Both algorithms run a 100 % identification of subgrade settlement, with the lowest identification rates of settlement wavelength being 97.56 % and 100 %, respectively and the lowest identification rates of amplitude being 84.78 % and 97.56 %, respectively. In general, the overall accuracy of the CNN-SVM always outperforms PSO-SVM, and III) changes to the vehicle passing speed will create a more obvious interference effect on the identification of the settlement amplitude. For the PSO-SVM algorithm, the identification rate for the amplitude has a difference of up to 8.70 %, while this is 2.44 % for the CNN-SVM algorithm, indicating the CNN-SVM algorithm is more robust than the PSO-SVM algorithm.

Experimental Study on Fan Aerodynamic Noise Variation Characteristics under Non-Proportional Variation Law

This paper presents the noise characteristics of axial fans in the process of variable frequency adjustment, so as to clarify the basis of frequency adjustment and high-risk area division for practical purposes. In the aerodynamic performance experiment, 11 kinds of operating conditions (OC) were divided into 3 groups, and the air flow rate and power consumption were measured. At the same time, an aerodynamic noise experiment was carried out, and nine measuring points were selected to test the noise of the air inlet and shell. The data showed that the aerodynamic performance parameters have the characteristics of non-proportional law. The maximum ventilation coefficient of OC2, OC7, OC11 is 3.9%, and its noise always has a negative growth rate. Furthermore, the typical OC were selected from all experiments, and broadband noise and discrete noise analyses were performed. The results indicated that the fan noise of the changes under variable frequency adjustment may come from boundary layer noise and shedding noise. In addition, the fundamental frequency sound pressure level of discrete noise is the highest in the whole frequency band. At the high-speed condition, the contribution of higher harmonics to the fan overall noise increases, but the broadband noise is still the dominant noise. Finally, the noise rating was introduced, and the high-risk noise index was divided for the noise of the air inlet and the shell. It was found that the main noise variation index of typical OC mostly exceeded the high-risk noise index, and the main target frequency band of noise control is 250–4000 Hz.