|
|
| (One intermediate revision by one other user not shown) |
| Line 1: |
Line 1: |
| {{Refimprove|date=March 2010}}
| | Cameras are connected towards the stand alone DVR with either cables or wirelessly employing a transmitter at the digital camera and a receiver to secure the DVR. As part of a Swann CCTV next to your skin various monitors available in the event you like a monitor to look at your cameras. Xdh cctv dvr software If the CCTV [http://www.meccahosting.co.uk/goodbye.php?url=http://cctvdvrreviews.com what is the best cctv dvr software] DVR method just isn't present, then this images which can be fed towards computer through the cameras can only be [http://www.sashatube.com/dtr/link.php?thumb_id=da335ef46096b9f9ec76501e45dce34f&tag_id=171&c=curly-haired&url=http%3A//cctvdvrreviews.com Cctv Dvr Alarm Input] viewed in real time.<br><br> |
| {{Other uses|RMS (disambiguation){{!}}RMS}}
| |
| In [[mathematics]], the '''root mean square''' (abbreviated '''RMS''' or '''rms'''), also known as the '''quadratic mean''', is a [[statistics|statistical]] measure of the [[magnitude (mathematics)|magnitude]] of a varying quantity. It is especially useful when [[variate]]s are positive and negative, e.g., [[Sine wave|sinusoid]]s. RMS is used in various fields, including [[electrical engineering]].
| |
|
| |
|
| It can be calculated for a series of discrete values or for a continuously varying [[function (mathematics)|function]]. Its name comes from its definition as the [[square root]] of the [[mean]] of the [[square (algebra)|squares]] of the values. It is a special case of the [[generalized mean]] with the exponent ''p'' = 2.
| | If you think that later on, you may need to expand or improve your system, obtain a DVR with samsung security system support an increase of [http://www.the-football-directory.co.uk/FrameNav.asp?U=http://cctvdvrreviews.com open Source Cctv dvr software For Windows] camera capabilites. The Digital surveillance cameras eneo dlr2 Video clip Recorder will be the ""brain"" of a CCTV program; it requires the images in the cameras and stores them on into a hard drive drive.<br><br>It is irrelevant if a game as terrible graphics, bad voice acting or possibly a [http://www6.montgomerycountymd.gov/redirect.asp?redirect=http://cctvdvrreviews.com portable cctv system with internal dvr & wireless connection] horrible soundtrack, the sport could nevertheless be fun to play. For, the essays could be written by skilled writers, there will be no chance about plagiarism together with your critique filling. Orion 16 channel d1 cctv dvr [http://nanacast.com/vp/102454/10249/15358/article-writing-service/?redirecturl=http://cctvdvrreviews.com bosch digital video recorder] If you decide to start writing and selling ebooks online, only you'll be able to decide what's right to suit your needs. It also helps should you read through your article out loud to ensure it can make sense. |
| | |
| ==Definition==
| |
| The RMS value of a set of values (or a [[continuous-time]] [[waveform]]) is the [[square root]] of the [[arithmetic mean]] ([[average]]) of the [[square (algebra)|squares]] of the original values (or the square of the function that defines the continuous waveform).
| |
| | |
| In the case of a set of ''n'' values <math>\{x_1,x_2,\dots,x_n\}</math>, the RMS value is given by this formula:
| |
| | |
| :<math>
| |
| x_{\mathrm{rms}} =
| |
| \sqrt{ \frac{1}{n} \left( x_1^2 + x_2^2 + \cdots + x_n^2 \right) }.
| |
| </math>
| |
| | |
| The corresponding formula for a continuous function (or waveform) ''f(t)'' defined over the interval <math>T_1 \le t \le T_2</math> is
| |
| | |
| :<math>
| |
| f_{\mathrm{rms}} = \sqrt {{1 \over {T_2-T_1}} {\int_{T_1}^{T_2} {[f(t)]}^2\, dt}},
| |
| </math>
| |
| | |
| and the RMS for a function over all time is
| |
| | |
| :<math>
| |
| f_\mathrm{rms} = \lim_{T\rightarrow \infty} \sqrt {{1 \over {T}} {\int_{0}^{T} {[f(t)]}^2\, dt}}.
| |
| </math>
| |
| | |
| The RMS over all time of a [[periodic function]] is equal to the RMS of one period of the function. The RMS value of a continuous function or signal can be approximated by taking the RMS of a series of equally spaced samples. Additionally, the RMS value of various waveforms can also be determined without calculus, as shown by Cartwright.<ref>{{Cite journal
| |
| |last=Cartwright
| |
| |first=Kenneth V
| |
| |title=Determining the Effective or RMS Voltage of Various Waveforms without Calculus
| |
| |journal=Technology Interface
| |
| |volume=8
| |
| |issue=1
| |
| |pages=20 pages
| |
| |date=Fall 2007
| |
| |url=http://technologyinterface.nmsu.edu/Fall07/
| |
| |postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}
| |
| }}</ref>
| |
| | |
| In the case of the RMS statistic of a [[random process]], the [[expected value]] is used instead of the mean.
| |
| | |
| ==RMS of common waveforms== | |
| [[File:Waveforms.svg|thumb|left|400px|[[sine wave|Sine]], [[square wave|square]], [[triangle wave|triangle]], and [[Sawtooth wave|sawtooth]] waveforms]]
| |
| [[File:Dutycycle.svg|thumb|left|400px|A rectangular pulse wave of duty cycle D, the ratio between the pulse duration (<math>\tau</math>) and the period (T); illustrated here with ''a'' = 1]]
| |
| [[File:Sine wave voltages.svg|thumb|left|400px|Graph of a sine wave's voltage vs. time (in degrees), showing RMS, peak, and peak-to-peak voltages]]
| |
| | |
| {| class="wikitable" border="1"
| |
| |-
| |
| ! Waveform!!Equation!!RMS
| |
| |-
| |
| | [[Direct current|DC]], constant||<math>y=a\,</math>||<math>a\,</math>
| |
| |-
| |
| | [[Sine wave]]||<math>y=a\sin(2\pi ft)\,</math>||<math>\frac{a}{\sqrt{2}}</math>
| |
| |-
| |
| | [[Square wave]]||<math>y=\begin{cases}a & \{ft\} < 0.5 \\ -a & \{ft\} > 0.5 \end{cases}</math>||<math>a\,</math>
| |
| |-
| |
| | [[DC Shifted Square wave]]||<math>y=\begin{cases}a+DC & \{ft\} < 0.5 \\-a+DC & \{ft\} > 0.5 \end{cases}</math>||<math>{\sqrt{a^2+DC^2}}\,</math>
| |
| |-
| |
| | [[Inverter (electrical)|Modified square wave]]||<math>y=\begin{cases}0 & \{ft\} < 0.25 \\ a & 0.25 < \{ft\} < 0.5 \\ 0 & 0.5 < \{ft\} < 0.75 \\ -a & \{ft\} > 0.75 \end{cases}</math>||<math>\frac{a}{\sqrt{2}}</math>
| |
| |-
| |
| | [[Triangle wave]]
| |
| | <math>y=|2a\{ft\}-a\,|</math>
| |
| | <math>a \over \sqrt 3</math>
| |
| |-
| |
| | [[Sawtooth wave]]
| |
| | <math>y=2a\{ft\}-a\,</math>
| |
| | <math>a \over \sqrt 3</math>
| |
| |-
| |
| | [[Pulse train]] ||<math>y=\begin{cases}a & \{ft\} < D \\ 0 & \{ft\} > D \end{cases}</math>||<math>a \sqrt{D}</math>
| |
| |-
| |
| | colspan=3 | Notes:<br>''t'' is time<br>''f'' is frequency<br>''a'' is amplitude (peak value)<br>''D'' is the [[duty cycle]] or the percent(%) spent high of the period (1/''f'')<br>{r} is the [[fractional part]] of r
| |
| |}
| |
| <!--fixme: add more waveforms-->
| |
| | |
| Waveforms made by summing known simple waveforms have an RMS that is the root of the sum of squares of the component RMS values, if the component waveforms are [[orthogonal]] (that is, if the average of the product of one simple waveform with another is zero for all pairs other than a waveform times itself).
| |
| :<math>RMS_{Total} =
| |
| \sqrt {{{RMS_1}^2 + {RMS_2}^2 + \cdots + {RMS_n}^2} }
| |
| </math>
| |
| A special case of this, particularly helpful in electrical engineering, is
| |
| :<math>RMS_{Total} =
| |
| \sqrt {{{RMS_{DC}}^2 + {RMS_{AC}}^2} }
| |
| </math>
| |
| where <math>RMS_{DC}</math> refers to the [[Direct current|DC]] component of the signal and <math>RMS_{AC}</math> is the [[Alternating current|AC]] component of the signal.
| |
| | |
| ==Uses==
| |
| The RMS value of a function is often used in [[physics]] and [[electrical engineering]].
| |
| | |
| ===Average electrical power===
| |
| {{main|AC power}}
| |
| | |
| Electrical engineers often need to know the [[power (physics)|power]], ''P'', dissipated by an [[electrical resistance and conductance|electrical resistance]], ''R''. It is easy to do the calculation when there is a constant [[electric current|current]], ''I'', through the resistance. For a load of ''R'' ohms, power is defined simply as:
| |
| | |
| :<math>P = I^2 R.</math>
| |
| | |
| However, if the current is a time-varying function, ''I(t)'', this formula must be extended to reflect the fact that the current (and thus the instantaneous power) is varying over time. If the function is periodic (such as household AC power), it is still meaningful to talk about the ''average'' power dissipated over time, which we calculate by taking the average power dissipation:
| |
| :{| border=0 cellpadding=0 cellspacing=0
| |
| |-
| |
| |<math>P_\mathrm{avg}\,\!</math>
| |
| |<math>= \langle I(t)^2R \rangle \,\!</math> (where <math>\langle \ldots \rangle</math> denotes the [[Mean#Mean of a function|mean]] of a function)
| |
| |-
| |
| |
| |
| |<math>= R\langle I(t)^2 \rangle\,\!</math> (as ''R'' does not vary over time, it can be factored out)
| |
| |-
| |
| |
| |
| |<math>= (I_\mathrm{RMS})^2R\,\!</math> (by definition of RMS)
| |
| |}
| |
| So, the RMS value, ''I''<sub>RMS</sub>, of the function ''I(t)'' is the constant current that yields the same power dissipation as the time-averaged power dissipation of the current ''I(t)''.
| |
| | |
| We can also show by the same method that for a time-varying [[voltage]], ''V(t)'', with RMS value ''V''<sub>RMS</sub>,
| |
| | |
| :<math>P_\mathrm{avg} = {(V_\mathrm{RMS})^2\over R}.</math>
| |
| | |
| This equation can be used for any periodic [[waveform]], such as a [[sine wave|sinusoidal]] or [[sawtooth wave]]form, allowing us to calculate the mean power delivered into a specified load.
| |
| | |
| By taking the square root of both these equations and multiplying them together, we get the equation
| |
| | |
| :<math>P_\mathrm{avg} = V_\mathrm{RMS}I_\mathrm{RMS}.</math> | |
| | |
| Both derivations depend on ''voltage and current being proportional'' (i.e., the load, ''R'', is purely resistive). [[electrical reactance|Reactive]] loads (i.e., loads capable of not just dissipating energy but also storing it) are discussed under the topic of [[AC power]].
| |
| | |
| In the common case of [[alternating current]] when ''I(t)'' is a [[sine wave|sinusoidal]] current, as is approximately true for mains power, the RMS value is easy to calculate from the continuous case equation above. If we define ''I''<sub>p</sub> to be the peak current, then:
| |
| | |
| :<math>I_{\mathrm{RMS}} = \sqrt {{1 \over {T_2-T_1}} {\int_{T_1}^{T_2} {(I_\mathrm{p}\sin(\omega t)}\, })^2 dt}.\,\!</math>
| |
| | |
| where ''t'' is time and ''ω'' is the [[angular frequency]] (''ω'' = 2π/''T'', where ''T'' is the period of the wave).
| |
| | |
| Since ''I''<sub>p</sub> is a positive constant:
| |
| | |
| :<math>I_{\mathrm{RMS}} = I_\mathrm{p}\sqrt {{1 \over {T_2-T_1}} {\int_{T_1}^{T_2} {\sin^2(\omega t)}\, dt}}.</math>
| |
| | |
| Using a [[list of trigonometric identities|trigonometric identity]] to eliminate squaring of trig function:
| |
| | |
| :<math>I_{\mathrm{RMS}} = I_\mathrm{p}\sqrt {{1 \over {T_2-T_1}} {\int_{T_1}^{T_2} {{1 - \cos(2\omega t) \over 2}}\, dt}}</math>
| |
| | |
| :<math>I_{\mathrm{RMS}} = I_\mathrm{p}\sqrt {{1 \over {T_2-T_1}} \left [ {{t \over 2} -{ \sin(2\omega t) \over 4\omega}} \right ]_{T_1}^{T_2} }</math>
| |
| | |
| but since the interval is a whole number of complete cycles (per definition of RMS), the ''sin'' terms will cancel out, leaving:
| |
| | |
| :<math>I_{\mathrm{RMS}} = I_\mathrm{p}\sqrt {{1 \over {T_2-T_1}} \left [ {{t \over 2}} \right ]_{T_1}^{T_2} } = I_\mathrm{p}\sqrt {{1 \over {T_2-T_1}} {{{T_2-T_1} \over 2}} } = {I_\mathrm{p} \over {\sqrt 2}}.</math>
| |
| | |
| A similar analysis leads to the analogous equation for sinusoidal voltage:
| |
| | |
| :<math>V_{\mathrm{RMS}} = {V_\mathrm{p} \over {\sqrt 2}}.</math> | |
| | |
| Where ''I''<sub>P</sub> represents the peak current and ''V''<sub>P</sub> represents the peak voltage. It bears repeating that these two solutions are for a sinusoidal wave only.
| |
| | |
| Because of their usefulness in carrying out power calculations, listed [[voltage]]s for power outlets, e.g. 120 V (USA) or 230 V (Europe), are almost always quoted in RMS values, and not peak values. Peak values can be calculated from RMS values from the above formula, which implies ''V''<sub>''p''</sub> = ''V''<sub>RMS</sub> × √2, assuming the source is a pure sine wave. Thus the peak value of the mains voltage in the USA is about 120 × √2, or about 170 volts. The peak-to-peak voltage, being twice this, is about 340 volts. A similar calculation indicates that the peak-to-peak mains voltage in Europe is about 650 volts.
| |
| | |
| The term "RMS power" is sometimes used in the audio industry as a synonym for "mean power" or "average power" (it is proportional to the square of the RMS voltage or RMS current in a resistive load). For a discussion of audio power measurements and their shortcomings, see [[Audio power]].
| |
| | |
| ===Root-mean-square speed===
| |
| {{main|Root-mean-square speed}}
| |
| | |
| In the [[physics]] of [[gas]] molecules, the '''root-mean-square speed''' is defined as the square root of the average squared-speed. The RMS speed of an ideal gas is [[Maxwell-Boltzmann distribution#Distribution of speeds|calculated]] using the following equation:
| |
| | |
| :<math>{v_\mathrm{RMS}} = {\sqrt{3RT \over {M}}}</math>
| |
| | |
| where ''R'' represents the [[ideal gas constant]], 8.314 J/(mol·K), ''T'' is the temperature of the gas in [[kelvin]]s, and ''M'' is the [[molar mass]] of the gas in kilograms. The generally accepted terminology for speed as compared to velocity is that the former is the scalar magnitude of the latter. Therefore, although the average speed is between zero and the RMS speed, the average velocity for a stationary gas is zero.
| |
| | |
| ===Root-mean-square error===
| |
| {{Main|Root-mean-square error}}
| |
| When two data sets—one set from theoretical prediction and the other from actual measurement of some physical variable, for instance—are compared, the RMS of the pairwise differences of the two data sets can serve as a measure how far on average the error is from 0.
| |
| | |
| The [[mean]] of the pairwise differences does not measure the variability of the difference, and the variability as indicated by the [[standard deviation]] is around the mean instead of 0. Therefore, the RMS of the differences is a meaningful measure of the error.
| |
| | |
| ==RMS in frequency domain==
| |
| The RMS can be computed in the frequency domain, using [[Parseval's theorem]]. For a sampled signal,
| |
| | |
| :<math>\sum\limits_{n}{{{x}^{2}}(t)}=\frac{\sum\limits_{n}{{{\left| X(f) \right|}^{2}}}}{n}</math>,
| |
| | |
| where <math>X(f)=\mathrm{FFT}\{x(t)\}</math> and ''n'' is number of ''x(t)'' samples.
| |
| | |
| In this case, the RMS computed in the time domain is the same as in the frequency domain:
| |
| | |
| :<math>\mathrm{RMS}
| |
| =\sqrt{\frac{1}{n}\sum\limits_{n}{{{x}^{2}}(t)}}
| |
| = \sqrt{\frac{1}{n^2}\sum\limits_{n}{{{\left| X(f) \right|}^{2}}}}
| |
| = \sqrt{\sum\limits_{n}{{{ \left|\frac{X(f)}{n}\right| ^ 2 }}}}.
| |
| </math>
| |
| | |
| ==Relationship to the arithmetic mean and the standard deviation==
| |
| If <math>\bar{x}</math> is the [[arithmetic mean]] and <math>\sigma_{x}</math> is the [[standard deviation]] of a [[Statistical Population|population]] or a [[waveform]] then:<ref>
| |
| {{cite book
| |
| | title = Digital signal transmission
| |
| | edition = 2nd
| |
| | author = Chris C. Bissell and David A. Chapman
| |
| | publisher = Cambridge University Press
| |
| | year = 1992
| |
| | isbn = 978-0-521-42557-5
| |
| | page = 64
| |
| | url = http://books.google.com/books?id=ItJoq36hCoYC&pg=PA64
| |
| }}</ref>
| |
| | |
| :<math>x_{\mathrm{rms}}^2 = \bar{x}^2 + \sigma_{x}^2.</math>
| |
| | |
| From this it is clear that the RMS value is always greater than or equal to the average, in that the RMS includes the "error" / square deviation as well.
| |
| | |
| Physical scientists often use the term "root mean square" as a synonym for [[standard deviation]] when referring to the square root of the mean squared deviation of a signal from a given baseline or fit.<ref>
| |
| {{cite website
| |
| | title = Root-Mean-Square
| |
| | url=http://mathworld.wolfram.com/Root-Mean-Square.html
| |
| }}</ref>
| |
| <ref>{{cite website
| |
| | title = ROOT, TH1:GetRMS
| |
| | url=http://root.cern.ch/root/html/TH1.html#TH1:GetRMS
| |
| }}</ref>
| |
| This is useful for electrical engineers in calculating the "AC only" RMS of a signal. Standard deviation being the root mean square of a signal's variation about the mean, rather than about 0, the DC component is removed (i.e. RMS(signal) = Stdev(signal) if the mean signal is 0).
| |
| | |
| ==See also==
| |
| * [[Central moment]]
| |
| * [[Geometric mean]]
| |
| * [[L2 norm]]
| |
| * [[Least squares]]
| |
| * [[Mean squared displacement]]
| |
| * [[Mean squared error]]
| |
| * [[Root mean square deviation]]
| |
| * [[Table of mathematical symbols]]
| |
| * [[True RMS converter]]
| |
| | |
| ==References==
| |
| {{Reflist}}
| |
| | |
| ==External links==
| |
| * [http://www.hifi-writer.com/he/misc/rmspower.htm A case for why RMS is a misnomer when applied to audio power]
| |
| * [http://www.opamp-electronics.com/tutorials/measurements_of_ac_magnitude_2_01_03.htm RMS, Peak and Average for some waveforms]
| |
| * [http://phy.hk/wiki/englishhtm/Rms.htm A Java applet on learning RMS]
| |
| | |
| {{DEFAULTSORT:Root Mean Square}}
| |
| [[Category:Statistical deviation and dispersion]]
| |
| [[Category:Means]]
| |