The influence of observation environment on background noise level of gPhone gravimeter

Based on the observations of 36 gPhone gravimeters in 2015, the background noise levels in the seismic frequency band（200-600 s） and sub-seismic band（1-6 h） are calculated. The differences in the PSD（power spectrum density） of each band of gPhone gravimetric gauges in different surrounding environments were analyzed and compared with Peterson＇s NLNM（new low-noise model） which is derived from the envelope at the power spectrum density of 75 seismograph stations around the world. The results showed that： the influence of station type on the noise magnitude of gPhone gravimeter is very small; The seismic band noise magnitude（hereinafter referred to as SNM） and the sub-seismic band noise magnitude（hereinafter referred to as SSNM） in the coastal gPhone gravimeter are higher than those of inland stations. Although the local hydrological change has a great influence on the gravity observation, the rainfall is not directly relative to the noise magnitude of the instrument. Except 3 coastal stations, the eight stations which had the highest amplitudes in the SNM were located near the seismic belt. This indicates that the SNM of the gPhone Gravimeter may reflect some seismic information.Compared with the NLNM model, the PSD of the gPhone gravimeter is lower than the NLNM model in the long period band（〈3×10^（-5）Hz）, indicating that the gPhone gravimeter is more suitable for detecting long-period signals（〉10 h） than the seismometer.

The background noise level of vertical pendulum tiltmeter in China

By using the observation data of the vertical pendulum tiltmeter in China,the influence of different sampling rates on the results of power spectral density is studied,and the background noise level of the seismic frequency band(200-600 s)of different stations and different types of instruments is emphatically analyzed.The conclusions are as follows:1.The results of both single station and national statistics show that the noise levels of the two types of pendulum tiltmeter equal in the seismic frequency band;2.There is no obvious regularity in the regional distribution,due to the influence of ocean and active tectonic movement,the noise levels of some stations in coastal areas are relatively high;3,The curves of high noise level instrument are generally not smooth and burr-prone.Except for some stations affected by the ocean,they are mostly caused by the observation environment or the instrument itself.

Nonparametric VSS-APA based on precise background noise power estimate

The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.

Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition:The Possibilities of Next Generation 5G Data Networks

This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction.Modern vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART vehicles.Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground noise.This article presents the new concept of a hybrid system which is implemented as a virtual instrument.The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction.The study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual vehicles.On average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.

State Estimation for Sound and Vibration Emitted from a Machine Based on Sound Measurement Under Existenceof Background Noise

Many studies on the diagnosis for machines have become important recently because of increased use of various complex industrial systems.The correlation information between sound and vibration is very important for machine diagnosis.Usually,vibration pickups are attached directly to the machine in order to measure vibration data.However,in some cases,the sensors can not be attached directly on highly precise devices.In this study,a method to estimate the fluctuation of sound and vibration is proposed based on the measurement data of sound emitted from the machine under existence of background noise.The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.

An Underwater Image Bubble Noise Removal Method Based on Optical Flow

It is very important for underwater robots to accurately detect and locate target objects. However,under many circumstances,it is difficult to clearly observe the target object due to the existence of bubble noise. In this paper,we proposed a method to solve this problem. First,we used the LK optical flow algorithm to calculate the motion vector of the image background and compensate for the background motion.Then,the optical flow field of the bubbles was calculated by the HS optical flow algorithm,and the area where the bubble existed was obtained by binarizing the image. Finally,we used the adjacent frame image to repair the bubble area. We carried out a bubble noise removal experiment. The results show that this method can effectively remove the bubble noise in the image.

Comparative Study of the Propagation of Jet Noise in Static and Flow Environments

In order to analyze the effect of the background flow on the sound prediction of fine-scale turbulence noise,the sound spectra from static and flow environments are compared.It turns out that,the two methods can obtain similar predictions not only at 90 deg to the jet axis but also at mid-and high frequencies in other directions.The discrepancies of predictions from the two environments show that the effect of the jet flow on the sound propagation is related to low frequencies in the downstream and upstream directions.It is noted that there is an obvious advantage of computational efficiency for calculating in static environment,compared with that in flow environment.A good agreement is also observed to some extent between the predictions in static environment and measurements of subsonic to supersonic.It is believed that the predictions in static environment could be an effective method to study the propagation of the sound in jet flow and to predict the fine scale turbulence noise accurately in a way as well.

Rayleigh Wave Tomography of Ningxia and Its Adjacent Areas Based on Ambient Noise

In this article,the vertical components of the continuous waveform data of 90 seismic stations in Ningxia and its adjacent regions recorded from January 2012 to December 2013 are used to obtain the Rayleigh surface wave group velocity dispersion images in the study area( 101°- 112°E,31°-42°N) according to the method of noise imaging,with period between 6s - 50s and resolution of 0.5°. The Yinchuan basin in the 6s - 26 s period obviously shows a low velocity anomaly,which is not uniform and has a tendency to gradually weaken; the Guanzhong Basin in 6 s-22s shows a strip of low velocity anomaly and demonstrates a transverse inhomogeneity,where velocity in the southeast is slightly faster than that in the northwest. In the 30s - 50s period it shows that in the Yinchuan graben basin and its southern area,there is a large low velocity anomaly area,which moves from northeast to southwest. It shows that between the main active tectonic zones,like mountains and basins,there are obvious geomorphologic boundaries. For example,the deep fault near Liupan Mountain is the dividing line between two large tectonic units of eastern and western of China. The inversion results have good correlation with the geological structure and the stratigraphic landform. The results are consistent with the results of artificial seismic section tomography across the basin. It provides an important basis for the dynamics of active tectonic zones and the mechanism of earthquake occurrence in this area.

地震背景噪声功率谱密度及概率密度函数的计算及其Matlab实现

介绍了地震背景噪声功率谱密度及概率密度函数计算方法及涉及的一些概念,以台站实际数据为例,给出了应用Matlab计算噪声功率谱密度及其概率密度函数的程序算法,该方法直接输入文本格式数据,计算台基噪声功率谱概率密度函数;以洛阳地震台24小时的连续波形记录为例,详细叙述了原始数据去仪器响应、计算功率谱密度、倍频程计算和噪声功率谱密度的概率密度函数计算实现的全过程。该方法编程简单,适用于单台噪声水平评估,在野外台站的快速勘选中具有潜在应用价值。

南极和格陵兰岛GPS连续台站背景噪声时空特性

基于GPS观测数据获取的陆地垂向运动对研究现今两极区域的冰川质量变化具有重要的科学意义.受地表环境负荷对GPS时间序列中背景噪声空间异质性的影响,在利用GPS时间序列获取垂向速度场时,估计结果存在较大不确定度.本文针对南极和格陵兰岛区域的GPS连续观测时间序列中背景噪声的空间特性对速度场及其不确定度的影响问题,利用地表环境负荷模型(包括大气、非潮汐海洋和水文负荷)和重力卫星GRACE/GRACE-FO观测数据反演的地表弹性形变对GPS时间序列进行了改正.通过对改正前后的数据进行背景噪声特性分析,揭示出修正环境负荷形变能够有效降低极区GPS时间序列背景噪声幅度,但是大气和非潮汐海洋负荷改正造成了大多数台站背景噪声谱指数的减小,南极和格陵兰岛分别约为其GPS台站总数的46.1%和84.6%,直接导致了对GPS速度不确定度估计的改善效果不明显.对背景噪声空间异质性的研究结果表明,极区台站的背景噪声参数主要表现为随纬度变化的空间特性.

光伏型红外焦平面探测器NETD的理论计算和测试分析

噪声等效温差(NETD)是表征红外焦平面探测器灵敏度的重要参数,除了器件本身的因素以外,与实际应用条件及测试条件密切相关。从红外焦平面探测器NETD的测试方法和流程出发,对光伏型红外焦平面探测器NETD的理论计算公式进行了推导,分析了影响器件NETD的主要因素,对典型红外焦平面探测器在不同积分时间、不同电荷存储量、不同F数及半阱输出条件下的背景限NETD进行了理论计算及分析。在固定背景温度下,通过理论公式可从某一温差的NETD推算出不同温差的NETD,选择典型器件进行验证,从常规NETD测试结果推算出的一组NETD与相应温差下的实测结果符合较好,其中1 K温差的NETD推算结果已非常接近实际情况,可为热像仪系统应用提供参考。

山西垂直摆倾斜仪背景噪声分析

利用山西地区垂直摆倾斜仪正常时段的观测数据,计算功率谱密度PSD和噪声水平SNM,对观测的正常背景特征进行分析和讨论。结果表明,未受任何干扰的观测数据每日PSD变化不大,分钟采样观测数据能反映最大为8.3 mHz的PSD分布,秒采样观测数据能反映最大为0.5 Hz的PSD分布。临汾地震台同址VS型、VP型垂直摆观测数据的噪声水平具有一致性;有2套仪器的背景噪声水平偏高,有4套仪器的背景噪声水平较低;低噪声水平仪器观测曲线光滑、固体潮清晰,运行稳定;高噪声水平仪器观测曲线毛刺多、不光滑。该现象除受观测环境影响以外,主要还受仪器自身的影响。

承德地区摆式仪器观测背景功率谱密度特征分析

为获取承德地区摆式倾斜仪捕捉的地震前兆信息及仪器性能,利用功率谱密度分析方法研究3台VP型垂直摆和1台水平摆倾斜仪的噪声频谱特征。研究结果表明,正常情况下,4台仪器记录的主要背景噪声为0.2 Hz以下的低频自然环境噪声;降雨事件主要影响0.2 Hz以下的低频段;摆式仪器能较好地记录到地震波,近震为更多高频成分,远震以记录面波占主导;地震事件可导致0~0.3 Hz频段的噪声显著增加;仪器标定过程中,低频噪声会显著增加。

机场噪声监测中的背景噪声影响及其监测方法研究

基于典型飞机噪声事件监测数据,采用声级叠加方法分析背景噪声对飞机噪声暴露声级LAE的影响。结果显示,为了保证测量数据的有效性,开展机场噪声监测时,背景噪声应低于单次飞机噪声事件最大声级15 dB以上。通过比选等效声级L_(eq)和累积百分声级L_(10)、L_(50)、L_(90)、L_(95)等常用噪声监测指标,证明采用与单次飞机噪声事件同期的5~10 min累积百分声级L_(50)作为背景噪声具有较好的代表性,并基于此提出了机场噪声监测中的背景噪声测量及处理方法。此方法科学、高效,适用于通过噪声监测设备自动获取背景噪声,对完善机场噪声监测方法具有较好的借鉴意义。

基于深度学习的多视图火焰面三维重建

针对火焰面三维重建时存在背景噪点的问题,提出了一种基于MVSNet多视图三维重构网络的IM-MVSNet网络用于重构层流火焰的火焰面。该网络通过对输入采样图像的参考帧以及邻域帧进行图像分割,去除采样时的背景噪声,得到高质量分割图像,然后将多视图图像进行三维重建,构建层流火焰面三维点云,进而得到重构的层流火焰面。通过不同重构模型火焰面重构效果对比,本文提出的三维重构网络能够有效减少重构火焰面的点云噪点,提高火焰面重构精度,为燃烧研究提供了一种新的方法。

安徽霍山区域科学台阵背景噪声分析

安徽霍山地区区域科学台阵为“十三五”期间新建台阵,为了评估该台阵各子站背景噪声水平,采用噪声功率谱密度法和功率谱概率密度函数法,进行背景噪声数据分析,结果显示:参照台基分类标准,Ⅰ类台基13个,Ⅱ类台基5个,Ⅲ类台基1个,Ⅳ类台基1个,台基噪声水平整体较低,各子站台基勘选较为合理;CLZ站UD分量背景噪声偏大,需要对观测系统运行进行检查;各子站背景噪声概率密度函数分布结果同功率谱密度结果基本一致,但包含的细节或信息更多,特别是叠加噪声功率谱密度后,包含了背景噪声在时间和频率2个维度上的信息,能够显著显示人类活动、仪器标定等干扰在频率、时间上分布。

声学实验室设计与技术要求

声学实验室是声学专业的测试实验室,它在音视频产品的声学性能检测和电子电器产品的噪声声功率级测量中得到广泛的应用。声学实验室由消音室和声学测试系统构成,要分别做好消音室的设计和声学测试系统的设计。从设计和建设声学实验室的角度出发,详尽阐述了声学测试标准、消音室的设计指标以及核心构成、关键技术指标,以及配套声学测试系统的组成。为声学实验室设计者和使用者提供科学的参考依据。

录音室背景噪声控制策略

通过深入分析录音室背景噪声的来源和对录音环境的影响,探讨如何有效地控制录音室的背景噪声,总结出优化隔声设计、消声处理、振动控制等方面的措施,为广播电视台提供有益的参考和借鉴。

基于拉曼光谱数据处理和谱峰识别的变压器油绝缘老化研究

针对变压器油的拉曼光谱分析通常受到噪声和荧光背景等的干扰以及谱峰位置难以识别的问题,提出了一种改进的数据处理和谱峰识别算法,用于变压器油老化评估时的拉曼光谱分析。提出一种自适应Savitzky-Golay滤波法,引入自适应窗口大小拉曼光谱数据进行去噪处理。采用改进的多项式拟合算法对去噪后的数据进行去除荧光背景处理,减小荧光背景对拟合结果的影响。通过数据点与期望的拉曼信号的接近程度为每个数据点赋予权重,以实现更准确的去荧光背景处理。利用谱峰识别技术判别变压器油的老化程度,采用大小两种尺度高斯窗口判别法来识别谱峰,并结合局部加权信噪比(local weighted signal-to-noise ratio,LW_SNR)来判断疑似拉曼谱峰的真实性。最后通过实验验证了所提算法在变压器油老化评估中的有效性。

全球超导重力仪地震频段背景噪声

详细研究了超导重力仪台站背景噪声水平的评估方法;基于该方法,选取了2010智利地震、2011Tohoku地震和2015智利地震前后多台超导重力观测数据,评估其在地震频段的背景噪声水平,得到了不同台站的地震噪声等级SNM;对不同超导重力仪记录背景噪声水平最低的5天进行统计分析,得出包含大震事件的多台站连续超导重力数据求取最平静期时段,大震发生前5天至大震发生后10天可不予考虑,为多台站的地震平静期时段选取提供参考。