Combined Effects of Exposure to Noise and Vibration on Human Postural Equilibrium under Simulated Driving Conditions

There is little information about drivers’body balance responses to combined exposure of noise and vibration.To fill the gap,this study aims to investigate the combined effects of exposure to noise and whole-body vibration(WBV)on the body balance under simulated driving conditions.For this purpose,30 male participants were exposed to noise level at 85 dB(A)and two vibration levels(0.87 and 1.3 m/s^(2))in five sessions.The design of the study was repeated-measures,and it attempted to assess the effects of 40 minutes of exposure to noise and/or WBV.Moreover,the participants’fatigue was measured with the Borg scale(CR 10).The findings revealed there was a significant change in body sway after WBV and combined noise and WBV exposure(p<0.05).However,no significant difference was found in exposure to noise alone(p>0.05).The effect sizes of exposure to noise,WBV(1.3 m/s^(2)),and combined noise and WBV(1.3 m/s^(2))on body balance were 0.035,0.425,and 0.635,respectively.Also,single exposure to WBV caused more fatigue than single exposure to noise(p<0.05).Combined noise and WBV exposure descriptively caused more fatigue in comparison with the influence of WBV alone.The study concluded that the combined effects of exposure to noise and vibration are more than the sum of them.So,some synergistic effects may be observed in human body balance.It is essential to increase drivers’awareness and revise current health care interventions about new possible effects of combined exposures.

Design of multi-antenna relaying for OFDM in impulsive noise environment

A low-complexity multi-antenna relaying scheme is proposed for Orthogonal Frequency Division Multiplexing (OFDM) in the presence of Class-A Impulsive Noise (IN). One way and two way relaying are considered. The signal is transmitted and received by two terminal nodes, each with a single antenna in two time phases. In the proposed design, the processing at the relay consists of Maximal-Ratio Combining (MRC) or Power-based Selection Combining (PSC) for receive combining, Amplify and Forward (AF) for power scaling, and Space Time Block Coding (STBC) for transmit diversity. Channel State Information (CSI), Discrete Fourier Transform (DFT), and Inverse Discrete Fourier Transform (IDFT) are not needed. The Selective Mapping (SLM) technique is used at the transmitter to reduce the Peak-to-Average Power Ratio (PAPR) of the OFDM signal. Then, at the receiver, the clipping technique is used to reduce the impulses that result from the impulsive noise. The proposed system reduces the complexity of the conventional system, which uses multi-relay with a single antenna. Simulation results show that the Bit Error Rate (BER) of the proposed scheme outperforms that of the conventional scheme due to the diversity inherent in the proposed scheme.

A Comparative Study on the Excitation of Large Volume Airgun Source with Different Combinations in Hutubi,Xinjiang,China

In order to study the excitation of large-volume airgun source with different combinations in Hutubi,Xinjiang,China,we conducted a targeted experiment.The method of timefrequency analysis is used to study the signals recorded by a seismometer on the shore of the excited pool,and it is concluded that different gun combinations will lead to different frequency of bubble pulse signals.Besides,linear combination method is used to analyze the signal-to-noise ratios of signals excited by different gun combinations which was recorded by seismic stations around the airgun source.In order to improve the signal-tonoise ratios,it is more effective to increase the activation energy(the number of excited guns at the same time)than to stack the excited signals with smaller energy repeatedly.

白条猪价格预测模型构建

【目的】增强农产品价格预测准确度,为农产品价格的有效预测提供参考。【方法】以河南省白条猪每周平均批发价格为研究对象,提出一种基于序列分解、主成分分析和神经网络(CEEMDAN-PCA-CNN-LSTM)的白条猪价格预测方法。首先,使用自适应白噪声完全集合模态分解方法(CEEMDAN)对白条猪价格序列进行分解;其次,选用皮尔逊相关系数筛选影响价格波动的相关因素;再次,利用主成分分析(PCA)对影响因素及分解得到的子序列降维处理并作为原始价格序列的特征值,并行输入到作为编码器的卷积神经网络(CNN)中进行特征提取;最后,引入长短期记忆网络(LSTM)作为解码器输出得到预测结果。将该方法应用于河南省白条猪每周平均价格数据,与LSTM、门控循环单元(GRU)、CNN、基于卷积的长短期记忆网络(ConvLSTM)模型进行比较。【结果】CEEMDAN-PCA-CNN-LSTM组合模型预测方法得到的平均绝对误差分别降低了44.95%、27.30%、28.13%、43.17%。【结论】CEEMDAN-PCA-CNN-LSTM模型对于河南省白条猪市场价格的预测性能更优,有助于相关部门针对河南省白条猪价格波动做出科学决策。

三维多回波聚合梯度回波序列在腰骶丛成像中的初步应用

目的 探讨3D多回波聚合梯度回波序列(3D GEMEC)在腰骶丛神经成像中的应用价值。方法 回顾性分析2022年8~9月六安市人民医院以腰腿疼为主诉的32例住院患者的影像学资料,男15例,女17例,年龄28~78(60.1±15.8)岁。在不同1.5T平台上分别完成腰骶丛3D GEMEC序列和三维T2加权快速梯度回波(3D T2 FFE)序列,比较两种序列腰骶丛神经的信噪比、对比噪声比和主观显示效果。结果 3D GEMEC序列腰骶丛神经的信噪比、对比噪声比以及主观显示效果与3D T2 FFE序列的差异均无统计学意义(P=0.250、0.146、0.083)。结论 3D GEMEC序列可以清晰地显示腰骶丛神经的解剖结构并抑制背景信号,在腰骶丛神经病变的诊断方面具有一定的临床应用前景。

CNN-LSTM车辆运动状态识别的AUKF组合导航方法

针对固定的噪声协方差难以适应车辆不同运动行为下噪声统计特性差异大的问题,提出了一种基于卷积神经网络与长短期记忆网络(CNN-LSTM)的车辆运动状态识别自适应无迹卡尔曼滤波(AUKF)组合导航方法。首先,应用CNN-LSTM网络模型进行车辆运动状态识别,解决车辆自我运动不确定性的问题;其次,将特定运动状态约束下的噪声协方差应用于UKF的时间更新与量测更新;最后,将所提方法在采集的数据集上进行验证。实验结果表明,与经典的UKF算法相比,所提方法的位置均方根误差与速度均方根误差分别下降了22.67%与2.63%,验证了所提方法的有效性。

基于小波变换的有源噪声控制算法研究

在传统的有源噪声控制系统中,原始噪声信号是获得参考噪声信号的必要条件,当原始噪声信号的信息不可获知时,有源噪声控制系统失效。为解决该问题,设计基于小波变换的有源噪声控制系统,利用小波阈值法对含噪语音信号进行处理,得到与原始噪声信号相关的参考噪声信号。在此基础上,对传统的有源噪声控制算法LMS进行改进,提出基于Sigmoid函数的γSLMS算法和C-γSLMS凸组合算法,解决LMS算法无法同时兼顾收敛速度和稳态误差的问题,为解决有源噪声控制问题提供新的解决方案。

边坡安全监测GPS-RTK信号的降噪算法研究

全球定位系统实时动态差分技术(global positioning system-real time kinematic, GPS-RTK)是解决路基边坡安全监测问题的重要手段,但GPS-RTK信号易受到多路径误差和共模误差的影响。基于小波变换(wavelet transform, WT)和主成分分析(principal component analysis, PCA)分别可以有效去除多路径误差和共模误差,提出WT-PCA算法去除信号误差。首先设置仿真信号,通过参数调优进一步提高单一算法的降噪效果。其次提出组合算法WT-PCA改进单一算法的缺陷,并与其他组合算法进行对比分析。最后,对十天高速路基边坡的GPS-RTK监测数据进行实例分析。结果表明,WT-PCA算法的信噪比和均方根误差较于WT-VMD优于66%和50%左右,算法可以有效地消除GPS-RTK信号的多路径误差和共模误差影响。提高边坡位移监测信号处理精度,进一步评估边坡结构形变及安全状态。

次级源和误差传感器布放对带弹性障板的充液直管声振复合有源控制的影响

针对充液管路系统噪声有源控制问题,研究了次级源和误差传感器布放对带弹性障板的充液直管管路系统有源消声与有源消振复合控制效果的影响。基于声固耦合方法建立了带弹性障板的充液直管管路系统的有限元模型,在声激励下对比了次级声源布放对系统有源消声性能的影响,并在组合激励下分析了次级力源、次级声源和误差传感器布放对系统复合有源控制的影响。结果表明,非对称分布的次级声源容易激起管壁振动,进而带动障板振动,导致有源消声效果不佳;采用对称分布的次级声源可使低频段的降噪量提高10 dB以上。复合有源控制可进一步提升全频段的控制效果。通过增加振动误差传感器数量,可使绝大多数频点的降噪量提高1∼20 dB不等。此外,在管壁上布放的两圈次级力源的间距小于管壁振动波长的1/4,且都不位于管壁振动节点附近时控制效果更好。

钢板结合连续梁桥结构噪声分析

为了探究钢板结合梁桥的振动噪声,建立车-轨-桥耦合动力分析模型,获得了列车与桥梁的动力反应,后将此动力反应作为声学边界条件求解得到了钢板结合梁桥的结构噪声辐射,并对噪声辐射影响参数进行了探究.研究表明,列车过桥时,桥梁的结构位移呈现出周期性变化,各测点的竖向加速度均大于横向加速度;全桥结构噪声表现为全频段内均有衰减,高频区段衰减速率较低频段快;当车速提高时,各场点的总体声压级逐渐变大,车速从200 km/h升至260 km/h时,各场点声压级的上升幅度更大;双向行车时总体声压级显著增加,但各板件在峰值声压级时的贡献量比例无显著变化;有板肋时,顶板声压级贡献量较上翼缘板的更大,无板肋时则相反.添加板肋能够对局部结构进行优化,但对于整体的降噪效果影响不大.本桥板肋布置间距宜在5.2m左右.

强噪声条件下物探方法组合在东坪金矿找矿研究与应用

金属矿产是现代工业的重要支撑,对经济和社会发展具有不可替代的作用。然而,强噪声环境下的矿产勘探面临着诸多挑战,需要创新性的方法和技术来解决。因此,针对强噪声条件下的物探方法组合研究与应用具有重要的实践意义和社会价值。本文以东坪金矿为研究对象,针对其强噪声环境,探讨了大功率时间域谱激发极化法和可控源音频大地电磁法两种物探方法的组合应用。通过对不同方法原理的深入分析和比较,结合实地数据,探讨了其在强噪声环境下的适用性和优势。在此基础上,提出了信噪分离和信息处理的关键技术,为矿产勘探提供了新的思路和方法。实验结果表明,该方法组合在东坪金矿找矿中具有良好的应用效果,为类似环境下的矿产勘探提供了可行性和参考。

Development of a measurement system for noise and vibration of combine harvester

Combine harvesters are important in that grain and legumes directly affect the production economy.On the other hand,it forms an important branch of the agricultural machinery sector.There are many unknown constraints on machines when harvesting with a combine harvester,including the noise and vibration that occur in the combine harvester thresher.This study aims to analyze noise and vibration in conventional combine harvesters using sensors.Two accelerometers were installed on each side of the concave and two microphones were used to register the noise of the threshing process.The result showed that effects of machine speeds(3.5 km/h,4.5 km/h and 5.5 km/h)and rotor speeds(950 r/min,850 r/min and 950 r/min)were significantly important for the mean range values of the left and right accelerometer in the X,Y and Z direction.The machine’s speed and rotor speed were not significantly important for the mean range values of the left and right microphones.

基于ACBO-GM联合方法的高维变量结构模型修正

工程结构模型修正常面临变量维度高、非线性程度强等现实问题,其模型修正的精度和效率受到严重影响,为改善这一不足,提出基于改进物体碰撞算法(Advanced Colliding Bodies Optimization,ACBO)和高斯白噪声扰动(Gaussian-white-noise Mutation,GM)的联合修正方法。在联合方法中,ACBO实现从传统的“一对一”到“优对多”的碰撞模式的转变,GM则用于保证碰撞过程中种群的多样性,可有效提升结构模型修正效率。基于一系列测试函数,对比分析标准物体碰撞算法(Colliding Bodies Optimization,CBO)和联合优化方法的优化性能;给出基于ACBO-GM联合方法的修正流程,并将其应用于钢框架修正算例和悬臂梁修正实例,对比研究基于联合修正方法与基于遗传算法(Genetic Algorithm,GA)的修正精度和效率。研究表明,ACBO-GM联合优化方法在精度和效率方面都明显优于传统的CBO方法,该优化方法的可行性得到验证;基于ACBO-GM联合方法在钢框架和悬臂梁两个工程结构修正案例中的应用,其修正精度均与基于GA方法的精度一致,但修正效率显著优于基于GA的修正方法。

Stochastic Accelerated Alternating Direction Method of Multipliers for Hedging Communication Noise in Combined Heat and Power Dispatch

Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.

地磁匹配定位中高精度地磁测量组合降噪算法

针对地磁匹配定位中,地磁测量信号包含导航载体软硬磁材料磁场、电气设备磁场、动力传动设备磁场等多种磁扰噪声问题,从理论上分析了软硬磁材料、电气设备、动力传动设备产生磁场的特性,推理了固定参数补偿软硬磁材料磁场补偿模型,分析了小波降噪的原理及可行性,首次提出了采用固定参数-小波滤波组合降噪算法消除磁扰误差,从理论上剖析了该算法的优越性及可行性,并利用多组实验数据进行了实验。通过实验及误差分析证明,该算法具有很好的降噪效果,有效解决了地磁测量磁扰噪声的关键问题,误差均方差均小于10 nT,达到了提升地磁测量精度的目的。

An adaptive image sparse reconstruction method combined with nonlocal similarity and cosparsity for mixed Gaussian-Poisson noise removal

Compressed sensing(CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation(NCSR), in terms of both visual results and quantitative measures.

一种采用组合曲线减震降噪的电磁锁的研制

以往的电磁锁在电磁铁动作时振感明显、噪声巨大、行程开关经常发生损坏。经测试发现,衔铁在运动时升降板触动行程开关,对行程开关造成冲击,这是行程开关损坏的主要原因。为此研制了一种齿轮传动式电磁锁,齿轮传动可以降低升降板的升降速度,可以消除部分噪声及振动。并针对升降板与行程开关接触的滑道曲线进行了分析,以往的滑道曲线因存在很大的加速度而对行程开关产生很大的作用力。构建一种新型的组合曲线,该组合曲线为变形余弦加速度曲线,组合曲线加速度无突变、速度曲线连续、位移曲线连续,既不会产生刚性冲击,也不会产生柔性冲击,使与之相接触的零部件不受冲击。变形余弦加速度曲线可以推广到很多有特殊要求的机械设备结构中。

基于阈值过滤的自适应无迹卡尔曼滤波在农业无人机组合导航中的应用

目的:针对无人机在进行喷药作业过程中系统模型会受到外界扰动引起滤波器噪声和干扰信号效果的问题,提出一种基于阈值过滤的自适应无迹卡尔曼滤波的方法。方法:通过设立阈值判断是否属于离群值,降低异常值的权重,减少因噪声干扰导致的系统模型误差。应用组合的信息融合方式,同时简化噪声估计过程。结果:通过MATLAB仿真实验证明,将UKF、AUKF、简化AUKF以及本算法进行比较,基于阈值过滤的自适应无迹卡尔曼算法在东向和北向速度的预测准确度上分别提高了57.9%和54.1%。结论:该方法在方位精度上有大幅提升,使得系统的鲁棒性更强。

基于完全自适应噪声集合经验模态分解的短时交通流组合预测

为了提高短时交通流预测的准确性,鉴于短时交通流非平稳、难预测的特征,提出了基于完全自适应噪声集合经验模态分解(CEEMDAN)短时交通流组合预测方法。利用CEEMDAN将原始短时交通流信号进行分解得多个复杂度、频率不同的时间序列分量,利用排列熵算法(PE算法)计算各分量的复杂度;然后根据复杂度和随机性的不同分为高频和低频,分别使用ATT-TCN-BIGRU模型和ARIMA模型对高频分量和低频分量进行预测,最后叠加高频和低频的每个分量预测结果作为最终短时交通流预测值。仿真分析结果表明:与ARIMA模型、TCN模型、BIGRU模型、ATT-TCN-BIGRU模型相比,此模型的平均绝对误差及平均绝对百分比误差为最小,预测精度更高。

Adaptive Threshold Clipper Combining Receiver for Fast Frequency Hopping Systems during Partial-Band Noise Jamming

Diversity combining technologies are analyzed for fast frequency-hopping spread spectrum systems during partial-band noise jamming to develop a novel combining receiver called an Adaptive Threshold Clipper Combining Receiver (ATCCR). The optimal clipping level for an ATCCR is analyzed, computed, and compared with several other diversity combining technologies. Since the ATCCR can estimate the power of the jamming and the number of jammed frequency cells to adaptively adjust the clipper's threshold, the system performance using the adaptive threshold clipper combining technique can be greatly improved.