Principles of measurement of sound intensity
Introduction
In accordance with the definition of instantaneous sound intensity as the product of the instantaneous acoustic pressure and the instantaneous particle velocity, an intensity measurement system should incorporate transducers of each of these the quantities. It is imperative that the presence of the transducers diffracts the sound field to an acceptably small degree, and that the transducer(sensor) assembly does not vibrate at audio-frequencies with a velocity amplitude comparable with the particle velocity of the acoustic field.
传感器使声场发生可接受的小角度的衍射是不可避免的,同时,相比于声场的particle velocity来说,传感器组并不会由于声音频率而发生震动。
Principles of Measurement of Sound Intensity
Sound pressure and particle velocity in a sound field can both be expressed as functions of the velocity potential of the field, but the relationship between the two depends upon the type of sound field, and is not unique. Therefore it is necessary to employ at least two sensors to determine sound intensity. Two categories of probe are in use: one with a particle velocity transduction unit, the other comprises two microphones. We shall refer to the former as a 'p-u' probe, and to the later as a 'p-p' probe, which enjoys far greater use.
The p-u principle
The p-p principle
Two nominally identical pressure sensors are placed close together in a support structure which is designed to minimise diffraction of the incident sound field. Most microphone capsules take the form of short cylinders which may be associated in various configurations.

In a small amplitude sound field, the component of pressure gradient in any direction n is proportional to the component of fluid particle acceleration in that direction:

The corresponding component of particle velocity is therefore given by the time integral

This is approximated as

where d is the distance separating the acoustic centres of the transducers; this will henceforth be termed the 'separation distance'.
The pressure at the point midway between sensors is approximated as

Hence, the instantaneous intensity component is approximated by

Many sources operate steadily; their sound fields may be considered to be stationary, and for the determination of source sound power the mean intensity is of prime interest. Time stationary signals x(t) and y(t) are such that x(dx/dt) = y(dy/dt) = 0, and x(dy/dt) = -y(dx/dt). In this case, p
Frequency Distribution of Sound Intensity in Time-Stationary Sound Fields
As we have seen, the component of the instantaneous sound intensity in any particular direction is atime-dependent quantity. The expression relevant to harmonic fields.
- p-u case
‘Indirect' frequency analysis procedures are based upon Fourier (spectral) analysis of the two probe signals, which is introduced here via the correlation function which indicates the time-average relationship between two signals in the time domain. The Cross-correlation Function between the pressure and particle velocity is defined as

(Note: in the case of harmonic signals the limiting process is replaced by a time average over an integer number of cycles.)
Hence, the mean intensity component in direction r is given by

The distribution in frequency of the product of the p and u component of that frequency is given by the Fourier transform of the cross-correlation function, which is termed the Cross-spectral Density:

This function is mathematically complex. indicating the average phase relationship between p and u.
R and S form a Fourier transform pair, and thus

and

In this sense, S represents the distribution of the contributions of different frequency components of the sound field to the mean intensity.
Cross-spectra possess the following properties:

The spectral function S is defined for all positive and negative frequencies, i.e. it can be represented by pairs of counter-rotating phasors(一对旋转的矢量). For practical purposes it is convenient to redefine the spectral densities as single-sided (单面)functions of frequency, thus:

Hence, the distribution of contributions of the different frequency components to the mean intensity component is

When a p-u probe is used, the equation above may be implemented directly with a two-channel FFT analyser to give I(w) in the direction of the probe axis. The total vector in a stationary field may be obtained by vector addition of the results of sequential measurements in three orthogonal directions.
The imaginary part of G(w) is proportional to the magnitude of the reactive intensity: however, unlike the real part, it does not represent the distribution of contributions of frequency components to a time-average quantity because the mean reactive intensity is zero at all frequencies. - p-p case
Principles of measurement of sound intensity的更多相关文章
- UVA10048 Audiophobia[Floyd变形]
UVA - 10048 Audiophobia Consider yourself lucky! Consider yourself lucky to be still breathing and h ...
- UVa 10048: Audiophobia
这道题要求我们求出图中的给定的两个节点(一个起点一个终点,但这是无向图)之间所有“路径中最大权值”的最小值,这无疑是动态规划. 我开始时想到根据起点和终点用动态规划直接求结果,但最终由于题中S过大,会 ...
- Uva10048 Audiophobia (Floyd)
题意:有一个无向带权图,求出两点之间路径的最大边权值最小能为多少. 思路:使用floyd算法跑一边以备查询,每一次跑的过程中dp[i][j]=min(dp[i][j],max(dp[i][k],dp[ ...
- Audiophobia(Floyd算法)
个人心得:这在一定途径上完成查询方面还是很吃力,得多锻炼空间能力,不能再每次都看到就后退,要全力应对, 那怕被虐的不要不要的. 这题主要是求俩个端点中所有路径中最大构成的集合中最小的数值,其实开始思想 ...
- UVa10048_Audiophobia(最短路/floyd)(小白书图论专题)
解题报告 题意: 求全部路中最大分贝最小的路. 思路: 类似floyd算法的思想.u->v能够有另外一点k.通过u->k->v来走,拿u->k和k->v的最大值和u-&g ...
- Indexing Sensor Data
In particular embodiments, a method includes, from an indexer in a sensor network, accessing a set o ...
- [快速幂]Codeforces Round #576 (Div. 2)-C. MP3
C. MP3 time limit per test 1 second memory limit per test 256 megabytes input standard input output ...
- Spatial Sound Research
Spatial Sound Research What are our goals? The basic goal of our research is to develop cost-effecti ...
- java sound初探
网上关于java sound的正规资源讲解的非常好,本文不再给出示例,主要提供一些好的资源,并说说我的一些理解,用于形成对java sound的整体认识. 一.几个词汇 TTS:text-to-spe ...
随机推荐
- [知识笔记]Java 基本数据类型的大小、取值范围、默认值
数据类型 大小(字节) 范围 默认值 boolean 1/8(1bit) true/false false byte 1 -128~127 (-2^7~2^7-1) 0 short 2 -32768~ ...
- 牛顿方法(Newton's Method)
在讲义<线性回归.梯度下降>和<逻辑回归>中我们提到可以用梯度下降或梯度上升的方式求解θ.在本文中将讲解另一种求解θ的方法:牛顿方法(Newton's method). 牛顿方 ...
- [WPF]WPF Data Virtualization和UI Virtualization
这篇博客将介绍WPF中的虚拟化技术. 1. Data Virtualization 通常情况下我们说数据虚拟化是指数据源没有完全加载,仅加载当前需要显示的数据呈现给用户.这种场景会让我们想到数据分页显 ...
- 【转载】关于treeview的多层显示的科学用法!
http://blogs.msdn.com/b/mikehillberg/archive/2009/10/30/treeview-and-hierarchicaldatatemplate-step-b ...
- .NET 需要处理的高性能WEB架构 - .NET架构
1.如果不想被微软包围(其实微软的一套并不贵,是被谣言传高了),数据层依然可以选择SQL Server数据库和存储过程. 2.缓存不再依赖.net自身提供的缓存机制,迁移到部署在Linux平台上的分布 ...
- HDU 5945 / BestCoder Round #89 1002 Fxx and game 单调队列优化DP
Fxx and game 问题描述 青年理论计算机科学家Fxx给的学生设计了一款数字游戏. 一开始你将会得到一个数\:XX,每次游戏将给定两个参数\:k,tk,t, 任意时刻你可以对你的数执行下面 ...
- (UWP开发)更为合理的一种ListView下拉刷新(PullToRefresh)实现方法
最近在做的一个项目需要用到下拉刷新,但是参考了现在网络上比较普遍的方法,觉得都不太好,因为要在外部套上一个SrollViewer,容易出现滚动错误.于是刚开始的时候就把思路定到了ListView内部的 ...
- 字符串和datatime.time类型转为秒
前言 折腾了好久,还是得养成看帮助文档和help的习惯 知识 datetime模块中定义的类 datetime.date 表示日期的类,常用属性:year, month, day datetime.t ...
- jq冒泡之——点击其他地方隐藏
e.stopPropagetion(); <!DOCTYPE html> <html lang="en"> <head> <meta ch ...
- [spring源码学习]九、IOC源码-applicationEventMulticaster事件广播
一.代码实例 回到第IOC的第七章context部分,我们看源码分析部分,可以看到在spring的bean加载之后的第二个重要的bean为applicationEventMulticaster,从字面 ...