I was studying about differences in 2,4 GHz and 5 GHz , i could understand the whole concept about speed, the range, the frequency etc...
But I still can understand what is a channel. I got some definitions but doesn't make sense " a wireless channel is a way to fine tune and alter the frequency " Could someone explain please.
The channels are just an agreed way to refer to different regions within the portion of bandwidth for a particular wifi range.
For example, each channel in the 2.4GHz spectrum is 5 MHz from the next one - or more accurately the 'centre' of the channels are that distance apart. See below for a diagram from Wikipedia (https://en.wikipedia.org/wiki/List_of_WLAN_channels):
Its important to note that WiFI needs a certain range each side of the centre frequency of the channels (which again are simply a shorthand for specific frequencies within the range), This is shown above and its easy to see from this how channels can 'overlap' which is a common term used in WiFi also.
I am involved in a side project that has a loop of LEDs around 1.5m in diameter with a rotor on the bottom which spins the loop. A raspberry pi controls the LEDs so that they create what appears to be a 3D globe of light. I am interested in a project that takes a microphone input and turns it into a column of pixels which is rendered on the loop in real time. The goal of this is to see if we can have it react to music in real-time. So far I've come up with this idea:
Using a FFT to quickly turn the input sound into a function that maps to certain pixels to certain colors based on the amplitude of the resultant function at frequencies, so the equator of the globe would respond to the strength of the lower-frequency sound, progressing upwards towards the poles which would respond to high frequency sound.
I can think of a few potential problems, including:
Performance on a raspberry pi. If the response lags too far behind the music it wouldn't seem to the observer to be responding to the specific song he/she is also hearing.
Without detecting the beat or some overall characteristic of the music that people understand it might be difficult for the observers to understand the output is correlated to the music.
The rotor has different speeds, so the image is only stationary if the rate of spin is matched perfectly to the refresh rate of the LEDs. This is a problem, but also possibly helpful because I might be able to turn down both the refresh rate and the rotor speed to reduce the computational load on the raspberry pi.
With that backstory, I should probably now ask a question. In general, how would you go about doing this? I have some experience with parallel computing and numerical methods but I am totally ignorant of music and tone and what-not. Part of my problem is I know the raspberry pi is the newest model, but I am not sure what its parallel capabilities are. I need to find a few linux friendly tools or libraries that can do an FFT on an ARM processor, and be able to do the post-processing in real time. I think a delay of ~0.25s or about would be acceptable. I feel like I'm in over my head so I thought id ask you guys for input.
Thanks!
I am using a PIC16F877a to drive a solid state realy connected to a 300W starter motor (R=50. millohms, L=50mH);
I tried varying The frequency and duty cycle to reduce the inrush current. it worked my current reduced to almost half.
I know that the average voltage for a pwm is V*duty cycle. But i am not driving the motor directly but through a relay. can anyone tell me a formula on how to calculate the current to the motor for validation.
Regs,
cj
I think you would need a datasheet of the motor with its electrical and mechanical characteristcs to determine the current. But that would still be a theoretical value. In the real world you will have the wires, contacts and so on, that add additional resistance and will "help" to limit the start current. But don't choose the wires to small and use a fuse for safety reasons. This should help you to choose the right wires: American Wire Gauge
If it's a DC motor there is a better and quiet simple solution.
Because of mechanical wearing and the limited switching frequency you should better not use a relay. The better solution would be an application fitting field effect transistor (FET)switching at a pwm frequency of about 20kHz so it would not produce any annoying humming or whimpering sounds in the motor. Depending on the transistor you will need a driver circuit for the FET to operate fine, dropping just a small ammount of power (passive cooling might still be needed).
For a smooth start of the motor with a minimum of peak current you should apply a linear duty cycle sweep from 0 to 100%. The optimum duration of the sweep depends on the motor and the mechanical load. Discover your optimum by trying different sweep durations.
How can I calculate A-weighted and C-weighted dB sound levels from the microphone on iOS?
Here is what I have tried, but the reading I get is far below the sound level meter I have next to my iPhone:
Using the Novocain library, which I have slightly modified to set the audio session mode to Measurement.
Using the Maximilian audio library to run the incoming audio frames through an FFT and converting the amplitudes into dB.
Using the Maximilian audio libraries's Octave Analyser to place the FFT output into octave bins from 10hz to 20480hz.
For each octave bin I am apply a db gain of the relevant dB-weighing (e.g. apply -70.f db gain to the db value stored in the 10hz bin to get an A-weighted dB gain).
Added the db values of each bin together by reducing each dB bin to an amplitude, and the gain to an an amplitude, making the addition, and converting back to a dB value again.
Is this on the correct track, I have my doubts? Can someone outline an approach? Suggest a library and/or other example (I have looked).
To note – I would like approximate dB(A) and dB(C) values, this does not need to be scientific. Not sure how to compensate for the frequency response of the microphone, could the above technique be correct if it were compensating for the response of the microphone?
I don't think you can measure physical Sound Pressure Levels from a device. In step 2 you "convert the amplitudes into dB." However the amplitude that you record from the device has arbitrary units. When recording 16-bit audio, the audio is represented as numbers in the range -32768 to +32767. If you are working with floating point data then this is normalised by 32768 so that it has a range of (approximately) -1 to +1.
The device's microphone has to cope with a wide variety of sound levels. Generally devices will have some form of Automatic Gain Control which adapts to the current average sound level. This means that if you measure a peak value of 1.0 then you have no way of knowing the actual SPL it corresponded to. You can convert a recording to a series of dBs, but this uses a different definition of dB: as a power ratio. This has no correlation with SPL measurements such as dB(A).
It may be possible to produce an approximate dB(A) measurement if you are able to turn off the AGC and calibrate your device against your sound meter
EDIT: JASA have published a paper with a detailed comparison of existing SPL measurement apps with stats for the comparison of different generations of iPhone: Evaluation of smartphone sound measurement applications
I want to calculate room noise level with the computer's microphone. I record noise as an audio file, but how can I calculate the noise dB level?
I don't know how to start!
All the previous answers are correct if you want a technically accurate or scientifically valuable answer. But if you just want a general estimation of comparative loudness, like if you want to check whether the dog is barking or whether a baby is crying and you want to specify the threshold in dB, then it's a relatively simple calculation.
Many wave-file editors have a vertical scale in decibels. There is no calibration or reference measurements, just a simple calculation:
dB = 20 * log10(amplitude)
The amplitude in this case is expressed as a number between 0 and 1, where 1 represents the maximum amplitude in the sound file. For example, if you have a 16 bit sound file, the amplitude can go as high as 32767. So you just divide the sample by 32767. (We work with absolute values, positive numbers only.) So if you have a wave that peaks at 14731, then:
amplitude = 14731 / 32767
= 0.44
dB = 20 * log10(0.44)
= -7.13
But there are very important things to consider, specifically the answers given by the others.
1) As Jörg W Mittag says, dB is a relative measurement. Since we don't have calibrations and references, this measurement is only relative to itself. And by that I mean that you will be able to see that the sound in the sound file at this point is 3 dB louder than at that point, or that this spike is 5 decibels louder than the background. But you cannot know how loud it is in real life, not without the calibrations that the others are referring to.
2) This was also mentioned by PaulR and user545125: Because you're evaluating according to a recorded sound, you are only measuring the sound at the specific location where the microphone is, biased to the direction the microphone is pointing, and filtered by the frequency response of your hardware. A few feet away, a human listening with human ears will get a totally different sound level and different frequencies.
3) Without calibrated hardware, you cannot say that the sound is 60dB or 89dB or whatever. All that this calculation can give you is how the peaks in the sound file compares to other peaks in the same sound file.
If this is all you want, then it's fine, but if you want to do something serious, like determine whether the noise level in a factory is safe for workers, then listen to Paul, user545125 and Jörg.
You do need reference hardware (i.e., a reference mic) to calculate noise level (dB SPL, or sound pressure level). One thing Radio Shack sells is a $50 dB SPL meter. If you're doing scientific calculations, I wouldn't use it. But if the goal is to get a general idea of a weighted measurement (dBA or dBC) of the sound pressure in a given environment, then it might be useful. As a sound engineer, I use mine all the time to see how much sound volume I'm generating while I mix. It's usually accurate to within 2 dB.
That's my answer. The rest is FYI stuff.
Jorg is correct that dB SPL is a relative measurement. All decibel measurements are. But you've implied a reference of 0 dB SPL, or 20 micropascals, scientifically agreed to be the most quiet sound a human ear can detect (though, understandably, what a person can actually hear is very difficult to determine). This, according to Wikipedia, is about the sound of a flying mosquito from about 10 feet away (http://en.wikipedia.org/wiki/Decibel).
By assuming you don't understand decibels, I think Jorg is just trying to out-geek you. He clearly didn't give you a practical answer. :-)
Unweighted measurements (dB, instead of dBA or dBC) are rarely used, because most sound pressure is not detected by the human ear. In a given office environment, there is usually 80-100 dB SPL (sound pressure level). To give you an idea of exactly how much is not heard, in the U.S., occupational regulations limit noise exposure to 80 dBA for a given 8-hour work shift (80 dBA is about the background noise level of your average downtown street - difficult, but not impossible to talk over). 85 dBA is oppressive, and at 90, most people are trying to get away. So the difference between 80 dB and 80 dBA is very significant -- 80 dBA is difficult to talk over, and 80 dB is quite peaceful. :-)
So what is 'A' weighting? 'A' weighting compensates for the fact that we don't perceive lower frequency sounds as well as high frequency sounds (we hear 20 Hz to 20,000 Hz). There's a lot of low-end rumble that our ears/brains pretty much ignore. In addition, we're more sensitive to a certain midrange (1000 Hz to 4000 Hz). Most agree that this frequency range contains the sounds of consonants of speech (vowels happen at a much lower frequency). Imagine talking with just vowels. You can't understand anything. Thus, the ability of a human to be able to communicate (conventionally) rests in the 1kHz-5kHz bump in hearing sensitivity. Interestingly, this is why most telephone systems only transmit 300 Hz to 3000 Hz. It was determined that this was the minimal response needed to understand the voice on the other end.
But I think that's more than you wanted to know. Hope it helps. :-)
You can't easily measure absolute dB SPL, since your microphone and analogue hardware are not calibrated. You may be able to do an approximate calibration for a particular hardware set up but you would need to repeat this for every different microphone and hardware set up that you plan to support.
If you do have some kind of SPL reference source that you can use then then it gets easier:
use your reference source to generate a tone at a known dB SPL - measure this
measure the ambient noise
calculate noise level = 20 * log10 (V_noise / V_ref) + dB_ref
Of course this assumes that the frequency response of your microphone and audio hardware is reasonably flat and that you just want a flat (unweighted) noise figure. If you want a weighted (e.g. A-weight) noise figure then you'll have to do rather more processing.
According to Merchant et al. (section 3.2 in the appendix: "Measuring acoustic habitats", Methods in Ecology and Evolution, 2015), you can actually calculate absolute, calibrated SPL values using manufacturer specifications by subtracting a correction term S to your relative (scaled to maximum) SPL values:
S = M + G + 20*log10(1/Vadc) + 20*log10(2^Nbit-1)
where M is the sensitivity of the transducer (microphone) re 1 V/Pa. G is the gain applied by the user. Vadc is the zero-to-peak voltage, given by multiplying the rms ADC voltage by a conversion factor of squareroot(2). Nbit is the bit sampling depth.
The last term is necessary if your system scales the amplitude by its maximum.
The correction will be more accurate using end-to-end calibration with sound calibrators.
Note that the formula above is dependent on frequency, but you could apply it over a wider frequency range if your microphone has a flat frequency response.
You can't. dB is a relative unit, IOW it is a unit for comparing two measurements against each other. You can only say that measurement A is x dB louder than measurement B, but in your case you only have one measurement. Therefore, it simply isn't possible to calculate the dB level.
The short answer is: you cannot do sound level measurements with your laptop, nor with your cellphone, etc., for all the reasons outlined previously, plus the fact your cellphone, laptop, etc. use compression algorithms to assure that everything recorded is within the hardware capability. So, if for example you measure a sound then run it through signal processing software such as Head Artemis or LMS Test.Lab, the indicated sound pressure level will always be in the neighborhood of 80 dB(A) regardless of the true level. I can say this from having used cellphone or laptop audio to get an idea of a noise frequency spectrum, while taking level measurements using a calibrated sound level meter. Interestingly, Radio Shack used to sell a microphone intended for speech input while videoconferencing that had very flat frequency response over a broad range, and only cost about $15.
I use a sound level calibrator.
It produces 94 dB or 114dB at 1 KHz
wich is a frecuency where weighting
filters share the same level.
With calibrator at 114dB I adjust mic gain to reach almost full scale
input simply watching a sound card based virtual osciloscope.
Now I know Vref # 114dB.
I developed a simple software based SPL meter
that can be provided if needed. You can use REW too.
You hace to know that PC hardware hardly
reaches 60 dB of dynamic range so calibrating
#114 dB it wont read less than 54dB, wich
is pretty high if you consider that sleeping
is good with less than 35 dB A.
In this case you can calibrate at 94dB
and then you may measure down to 34dB
but again you will hit pc and mic self noise
wich may you prevent to reach such low levels.
Anyway, once calibrated, measures at 114dB
and 94dB should read fine.
Note: the lab standard pistonphone calibrator operates at 250 Hz.
Well! I Used RobertT's Method But It Always Giving Me Oveflow Exception, Then I Used:- int dB = -36 - (value * -1), The Exception Gone, I Don't Know Whether It's Telling dB Values, If You Knew Using Code Given Below, Please Comment Me Whether it's A dB Value or not.
VB.NET:-
Dim dB As Integer = -36 - (9 * -1)
C#:-
int dB = -36 - (9 * -1)