Subjective annoyance caused by indoor low-level and low frequency noise and control method

The influence of low_level noise has not been widely noticed. This paper discovered that low_level and low frequency noise(A_weighted equivalent level L eq <45 dB) causes higher probability of subjective annoyance. The fuzzy mathematic principle was applied to deal with the threshold level of subjective annoyance from noise in this study; there is preferable relationship between the indoor noise and noise annoyance at low frequency noise level. Study indicated at the same centered noise level, the change of annoyance probability is mainly caused by the change of the frequency spectrum characteristic of the indoor noise. Under low noise level environment, without change of the medium_low frequency noise, the slight increase of medium_high frequency noise level with the help of noise sheltering effect can significantly reduce the noise annoyance. This discovery brings a new resolution on how to improve the environmental quality of working or living places. A noise control model is given in this study according to the acoustic analysis.

Effect of Angle of Attack and Blade Tip Vortex on the Noise Level of Tandem Wind Rotors of an Intelligent Wind Power Unit

The authors have invented a superior wind power unit, which is composed of tandem wind rotors and double rotational armature type generator without the traditional stator. This unit is called ＂intelligent wind power unit＂. At upwind type unit, the large-sized front wind rotor and the small-sized rear wind rotor drive the inner and the outer rotational armatures respectively, in keeping the rotational torque counter-balance between both wind rotors/armatures. This paper discusses the acoustic noise emitted from the tandem wind rotors. As for tandem wind rotors, the tip vortex shedding from the front wind rotor may make a loud acoustic noise if the vortex attacks the rear wind rotor. Intelligent wind power unit, however, has no chance to increase the acoustic noise level by the tip vortex because the diameter of the front wind rotor is reasonably larger than the diameter of the rear wind rotor. The vorticity generated in the boundary layer on the blade can be observed obviously at wake flow and can be evaluated quantitatively at flow conditions measured by a hot-wire anemometer at a wind tunnel. The flow conditions have shown that the radial and axial components of vorticities contribute to emit the acoustic noise.

Mechanical and Acoustic Performance Test of New Designed Metal Noise Barrier Unit Plate with No Riveted Connection

The modern transportation system is increasingly developed during recent years.It is an effective solution to set the noise barriers to reduce the traffic noise pollution caused by different kinds of transportation systems.Many deficiencies on concrete noise barriers and metal noise barriers with rivet structure can be eliminated by a new kind of noise barrier with no-riveted structure.The mechanical performance examination and acoustic performance test are conducted on the new-designed noise barrier with no-riveted structure.The results indicate that the maximum stress is 1.74 MPa and the maximum deformation is 1.04 mm with load acting on the unit plate.The noise reduction coefficient of this kind of no-riveted noise barrier unit plate is 0.75 and its noise insulation is 40 dB,which were conform to or superior to the standard requirements.Therefore,this new designed noise barrier meets the field application requirements of mechanical and acoustic performance,which demonstrates the noise barriers can be widely promoted.

Effects of white noise on procedural pain-related cortical response and pain score in neonates:A randomized controlled trial

Objectives To evaluate the effects of white noise on pain-related cortical response,pain score,and behavioral and physiological parameters in neonates with procedural pain.Methods A double-blind,randomized controlled trial was conducted.Sixty-six neonates from the Neonatal Intensive Care Unit in a university-affiliated general hospital were randomly assigned to listen to white noise at 50 dB(experimental group)or 0 dB(control group)2 min before radial artery blood sampling and continued until 5 min after needle withdrawal.Pain-related cortical response was measured by regional cerebral oxygen saturation(rScO_(2))monitored with near-infrared spectroscopy,and facial expressions and physiological parameters were recorded by two video cameras.Two assessors scored the Premature Infant Pain Profile-Revised(PIPP-R)independently when viewing the videos.Primary outcomes were pain score and rScO_(2)during arterial puncture and 5 min after needle withdrawal.Secondary outcomes were pulse oximetric oxygen saturation(SpO_(2))and heart rate(HR)during arterial puncture,and duration of painful expressions.The study was registered at the Chinese Clinical Trial Registry(ChiCTR2200055571).Results Sixty neonates(experimental group,n=29;control group,n=31)were included in the final analysis.The maximum PIPP-R score in the experimental and control groups was 12.00(9.50,13.00),12.50(10.50,13.75),respectively(median difference−0.5,95%CI−2.0 to 0.5),and minimum rScO_(2)was(61.22±3.07)%,(61.32±2.79)%,respectively(mean difference−0.325,95%CI−1.382 to 0.732),without significant differences.During arterial puncture,the mean rScO_(2),HR,and SpO_(2)did not differ between groups.After needle withdrawal,the trends for rScO_(2),PIPP-R score,and facial expression returning to baseline were different between the two groups without statistical significance.Conclusion The white noise intervention did not show beneficial effects on pain-related cortical response as well as pain score,behavioral and physiological parameters in neonates with procedural pain.

Noise Impact and Improvement on Indoors Acoustic Comfort for the Building Adjacent to Heavy Traffic Road

A good acoustic environment is absolutely essential to maintaining a high level satisfaction and moral health among residents. Noise and other boresome sounds come from both in- door and outdoor sources. For the residential buildings adjacent to heavy traffic roads, outdoors traffic noise is the main source that affects indoor acoustic quality and health. Ventilation and outdoor noise prevention become a pair of contradictions for the residents in China nowadays for those buildings adjacent to heavy traffic roads. It is investigated that traffic noise emission is mainly con- stituted by the motors of trucks, buses and motorcycles as well as brake. In this paper, two methods of traffic noise reduction on the indoor sound environment and comfort are carried out to study and compare the residential buildings adjacent to heavy traffic roadway in a city. One is to install noise barriers on the two sides of the roadway, which consist of sound-proof glass and plas- tic materials. The effect of sound-insulation of this method is heavily dependent on the relative distance between the noise bar- rier and indoors. A reduction of sound with an average pressure level of 2–15dB is achieved on the places behind and under the noise barrier. However, for the equivalent of noise barrier height, the noise reduction effect is little. As for the places of higher than the noise barrier, the traffic noise will be even strengthened by 3–7dB. Noise increment can be seen at the points of distance farther than 15m and height more than noise barrier; the noise reduction effect is not satisfactory or even worsened. In addition, not every location is appropriate to install the noise barrier along the heavy traffic roads. The other method of noise reduction for the buildings adjacent to heavy traffic is to install the airproof and soundproof windows, which is the conversion from natural venti- lation to mechanical ventilation. A reduction of sound with an average pressure level of 5dB to 17dB can be achieved compared with common glass windows, if adopting sound proof glass win- dows. These two methods are helpful to isolate high frequency noise but not for low frequency noise. For those frequency noises, installing thick and cotton curtain and porous carpet can only decrease 2.4–4.5dB, which hardly contributes to indoor sound comfort, so further study is demanded to cut down traffic noise, especially to cut down the low frequency noise.

Hybrid ToA and IMU indoor localization system by various algorithms

In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.

Ensembling Neural Networks for User’s Indoor Localization Using Magnetic Field Data from Smartphones

Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors:Smartphone heterogeneity and smaller data lengths.The use of multifarioussmartphones cripples the performance of such approaches owing to the variability of the magnetic field data.In the same vein,smaller lengths of magnetic field data decrease the localization accuracy substantially.The current study proposes the use of multiple neural networks like deep neural network(DNN),long short term memory network(LSTM),and gated recurrent unit network(GRN)to perform indoor localization based on the embedded magnetic sensor of the smartphone.A voting scheme is introduced that takes predictions from neural networks into consideration to estimate the current location of the user.Contrary to conventional magnetic field-based localization approaches that rely on the magnetic field data intensity,this study utilizes the normalized magnetic field data for this purpose.Training of neural networks is carried out using Galaxy S8 data while the testing is performed with three devices,i.e.,LG G7,Galaxy S8,and LG Q6.Experiments are performed during different times of the day to analyze the impact of time variability.Results indicate that the proposed approach minimizes the impact of smartphone variability and elevates the localization accuracy.Performance comparison with three approaches reveals that the proposed approach outperforms them in mean,50%,and 75%error even using a lesser amount of magnetic field data than those of other approaches.

An indoor positioning system for mobile target tracking based on VLC and IMU fusion

An indoor positioning system( IPS) is designed to realize positioning and tracking of mobile targets,by taking advantages of both the visible light communication( VLC) and inertial measurement unit( IMU). The platform of the IPS is designed,which consists of the light-emitting diode( LED)based transmitter,the receiver and the positioning server. To reduce the impact caused by measurement errors,both inertial sensing data and the received signal strength( RSS) from the VLC are calibrated. Then,a practical propagation model is established to obtain the distance between the transmitter and the receiver from the RSS measurements. Furthermore,a hybrid positioning algorithm is proposed by using the adaptive Kalman filter( AKF) and the weighted least squares( WLS)trilateration to estimate the positions of the mobile targets.Experimental results show that the developed IPS using the proposed hybrid positioning algorithm can extend the localization area of VLC,mitigate the IMU drifts and improve the positioning accuracy of mobile targets.

An Assessment of Indoor Environmental Quality in School Buildings in the State of Kuwait

In this study, indoor quality and environmental comfort were investigated in secondaiy school buildings located in the State of Kuwait. Comfort variables such as temperature and relative humidity (thermal comfort), noise (acoustic comfort), illumination (visual comfort), as well as allocated classroom floor area per student (spatial comfort) were measured. Data was collected over a 7-month period on a spot basis during school hours in student-occupied classrooms at 46 selected schools. The measured data was then compared to international guidelines and standards related to indoor environment quality. The data for noise and allocated space were shown to be in the comfort ranges in all the schools. However, 11% of the schools are not adequately illuminated, 33% had temperatures not within the recommended limits, and 22% of the schools had humidity levels either higher or lower than the recommended levels. Also, 9% of the schools had low illummation readings. In addition, during the data monitoring, a survey was conducted by which the student occupants completed a questionnaire so that subjective and objective evaluations could be compared. The findings of the questionnaire displayed significant correlations between the measured data and some ailments and other corr^laints experienced by the students. Ultimately, the results found in this research will provide a baseHne for comparison with future indoor environment quality assessments in buildings. Furthermore, recommendations are suggested in order to improve the environmental quality problems encountered in some of the schools, which may be beneficial for policymakers, facilities managers, and design engineers.

基于声学FEM-BEM的户内变电站噪声场计算

准确计算户内变电站大型、复杂的噪声场分布,进而评价可采用降噪措施的减噪效果,是解决户内变电站噪声污染的关键问题。为此,综合声学有限元法(finite element method,FEM)求解复杂声场收敛性好及精度高的优点,及声学边界元法(boundary element method,BEM)降维求解大型声场的优势,提出了一种基于声学FEM-BEM的户内变电站噪声场求解算法。首先,建立变电站内部声源声固耦合模型,采用声学FEM求解混响噪声作用下的声固耦合响应;然后,基于声学FEM-BEM耦合理论,求解内、外耦合边界处结构单元受声固耦合激励产生的位移及应力载荷;最后,根据声压及应力载荷激发的外场声波扩散模型,基于常规Gauss数值积分法,建立外部空间声域2维BEM声学积分方程,求解外部声场。该算法在湖南某110 kV户内变电站噪声场的求解分析中得到了成功应用,与实测值的相对误差为3.61%~4.87%。

基于卡尔曼滤波的室内二次辐射噪声测量修正方法

地铁运营诱发的沿线建筑物二次辐射噪声已成为城市噪声投诉重要来源,大量的轨道减振措施因而得以应用。但是由于测试条件的原因,对减振轨道区间沿线的建筑物二次辐射噪声进行测试所获取的噪声信号往往与背景噪声信号差异较小,致使室内二次辐射噪声评估结果不稳定。为评估观测信号与背景噪声信号接近时的室内二次辐射噪声,提出一种基于卡尔曼滤波方法的楼板振动与室内噪声测试数据联合评估方法。首先,根据卡尔曼滤波器工作原理,提出室内观测噪声误差矩阵和经验公式预测方法误差矩阵的构造方法。而后采用向典型信号中掺入高斯白噪声的方法结合现场实测数据验证了该方法的可行性。最后基于该方法对比分析几种经验预测公式的效果。

基于改进声学有限元法的主变压器室噪声场计算

传统声学有限元法(finite element method,FEM)难以准确表征温升效应引起的主变室大空间空气介质参数变化,导致温度场-声场耦合作用下变电站主变压器室噪声场计算误差过大。在声学FEM算法基础上,引入计算流体力学(computational fluid dynamics,CFD),提取大空间主变室的复杂空间介质参量,并对波动积分方程进行改进,提出一种基于改进声学FEM的主变室内噪声场求解算法。首先,建立温度场影响下的主变室流变模型,采用CFD表征主变室大空间温度场离散空间介质参量;然后,基于流-声网格映射理论,将温度场离散空间介质参量与声音网格进行映射,建立修正大空间空气介质参数后的声学FEM积分方程;最后,基于常规Gauss数值积分法和引入Kirchhoff-Helmholtz方程,对修正声学FEM积分方程进行联合求解。该算法在西安110 kV昌明变电站1号主变室噪声场的求解分析中得到了成功应用,与实测值误差为2.168%。

基于CEEMDAN-SBiGRU-OMHA的短期电力负荷预测

为了提高短期电力负荷预测的精准度,充分挖掘电力负荷数据的复杂相关性,提出了一种优化多头注意力机制的CEEMDAN-SBiGRU组合预测模型,改进了特征提取和特征融合两个模块.首先,采用自适应噪声完全集成经验模态分解(complete ensemble empirical mode decomposition with adaptive noise,CEEMDAN)将电力负荷数据分解成多个内在模态函数(IMF)和一个残差信号(RES);同时引入降噪自编码器DAE挖掘数据中受气象因素、工作日类型和温度变化的潜在特征.其次,将提取到的复杂特征输入至堆叠双向门控循环单元(stacked bidirectional gated recurrent unit,SBiGRU)模块中继续学习,以获取隐藏状态.最后,将获取的隐藏状态输入至加入残差机制和层归一化优化的多头注意力(optimized multi-head attention,OMHA)机制模块,可以准确地给重要特征分配更高的权重,解决噪声干扰问题.实验结果表明,CEEMDAN-SBiGRU-OMHA组合模型具有更高的精确性.

基于小波包分解与CEEMDAN能量熵的水电机组振动信号特征提取

针对水电机组振动信号非平稳、非线性及噪声问题,提出一种基于自适应噪声完备经验模态分解(CEEMDAN)与能量熵结合的特征提取方法,首先对采集的振动信号进行小波包降噪处理,然后对降噪后信号进行CEEMDAN分解,运用相关系数法筛选有效固有模态函数(IMF)并计算其能量熵,由此构建特征向量集,最后将其输入到海洋捕食者优化支持向量机算法(MPA-SVM)进行模式识别。基于模拟信号、实测信号验证所提特征提取方法的有效性,并与其他方法作对比。结果表明,基于小波包分解与CEEMDAN能量熵的特征提取方法能准确提取特征,有效区分机组不同状态,为工程领域提供了应用价值。

水力机械空化实时检测技术研究

本文从空化现象的发生机理出发,开发出通过分析水力机械发生空化时辐射出的空化噪声时频特征的变化,判定水力机械空化发生及表征空化发生程度的实时检测技术。该技术已应用在包括贯流式、轴流式、混流式和水泵水轮机等水力机械型式的多个电站,具有安装便捷、安全可靠的特点,可以应用在水力机械优化运行和智慧机组建设等领域。

大连养老建筑供暖季室内环境与老年人心率关联性

为了解养老建筑室内环境与老年人心率之间的关联性,对大连城市和农村地区的26名住户在供暖季展开了调研及入户实测,对其室内环境参数及心率健康情况进行了72 h的连续监测,并采取问卷调查的方式获得受试老年人对室内环境的主观评价。研究结果表明:被调查的城市住宅室内热环境均表现良好,城市住宅的室内温度高于农村且温湿度的波动均小于农村;农村和城市的实测房间室内CO_(2)浓度均较高,农村室内的PM2.5污染严重,比城市室内平均浓度高出302%;实测房间无严重噪声污染,存在部分时间段噪声值超标情况,城市住宅的老年人对声环境营造有着更高的要求;老年人动态心率与温度、PM2.5浓度、噪声呈正相关关系。

《LED室内照明建筑一体化技术规程》(T/CECS 1122—2022)技术要点解析

本文针对LED照明建筑一体化系统的特点,结合《LED室内照明建筑一体化技术规程》(T/CECS 1122—2022)的条文,对LED照明建筑一体化产品性能要求、系统设计策略、照明质量新指标的要求及技术要点进行了深入分析,为LED照明建筑一体化系统的设计提供指导。

地铁沿线建筑内噪声多维度感受影响机制

随着城市铁路系统的快速发展,铁路沿线建筑内人群对地铁运行产生噪声的抱怨逐渐增多,为控制室内地铁噪声对人群所产生的负面影响,有必要对地铁噪声产生的多维度负面情绪进行评估。采集了79名受试者对建筑内地铁噪声的多维度负面感受(压抑感,不舒适度和不满意度),基于偏最小二乘法分析了主客观影响因素对多维度负面感受的作用机制,并比较了多维度负面感受在反映地铁噪声影响上的差异。结果表明,多维度负面感受主要取决于主观响度和声学参数,活动干扰度、地铁噪声的敏感度、厌烦度和适应性的影响明显更弱;3个多维度负面感受中,相比于压抑感,不舒适度和不满意度受主观响度的影响轻微更显著,在相同的主观响度感受下,不满意度等级最高。该文可以为地铁沿线建筑物内噪声负面感受的评价和改善提供参考。

高速铁路对沿线建筑噪声影响及控制措施研究

针对某在建综合交通枢纽内高速铁路沿线高标准星级酒店噪声超标问题,分别采用几何声线法和统计能量分析法,建立铁路沿线噪声以及建筑室内噪声预测模型,研究列车高速通过及进出站时铁路沿线噪声分布特性和酒店内部噪声情况,讨论了声屏障对铁路沿线噪声、建筑外墙(窗)隔声以及酒店内部房间尺寸酒店内部噪声的影响规律。研究结果表明:(1)列车通过时,铁路沿线环境噪声水平将达到90 dB(A)以上,酒店内部噪声也将超过50 dB(A);(2)设立声屏障可有效降低铁路沿线噪声2~10 dB(A),同时提高建筑外墙隔声、增大室内房间面积可有效降低室内噪声16~18 dB(A);(3)在铁路声屏障和建筑外墙(窗)隔声都难以进一步有效降低沿线敏感建筑室内噪声时,可通过改变房间用途来使内部噪声满足标准要求。研究成果可为高速铁路沿线敏感建筑的噪声控制提供参考。

基于深度学习GRU网络的UWB室内定位优化

为减少信号传输质量和距离估计算法等因素对定位精度的影响,将深度学习应用于超宽带(ultra wide band,UWB)室内定位系统,利用门控循环单元(gated recurrent unit,GRU)网络代替传统UWB室内定位系统中的三边测量过程,以提高UWB室内定位精度。在得到定位标签到基站的距离信息后,将距离信息输入GRU网络中,输出最终位置坐标。GRU作为循环神经网络(recurrent neural network,RNN)的变种,既含有RNN处理时序数据的优势,又解决了RNN中的长程依赖问题。对GRU网络模型中不同学习率、优化器、批量大小、网络层数、隐藏神经元数量参数进行调整和训练。结果表明,基于GRU网络模型的UWB室内定位系统显著提高了定位精度,平均定位误差为6.8 cm。