Welcome to my Channel! I am Srinath Srinivasan. The goal of this channel is to educate everyone about various physical phenomenon that we experience in everyday life. Predominantly this channel has a strong focus on explaining various phenomenon and concepts of Sound and its applications as audio and acoustics in a clear, simple and intuitive way! I use physical visual aids for better understanding and make learning simple. Currently I'm using presentation style which make learning and grasping concepts more interesting and immersive.
Other areas that I have explored in the past include DIY (Do It Yourself) Arduino projects, creative sound effects (SFX), slow motion effects and Augmented Reality (AR).
Thank you for the lesson Sir. I am actually working on the dynamic analysis of a reinforced concrete bridge structure. But when I carried out numerical modal analysis considering 30 modes I realized the sum of my mass participation ratio for each mode is not even up to 80% of total mass, highest was at 77%. My main problem is: about the first 20 mode shapes had really small mass participation and instead of the first modes contributing a lot to the mass, I had the last modes contributing instead (to have up to 77% mass participation). From my knowledge of modal analysis, the first modes are usually the most important and the ones contributing a lot, but that's not the case with my analysis results. What could possibly be the problem Sir? (I assigned boundary conditions to both ends of the bridge)
You're welcome. As I am not from Structural engineering background but rather Mechanical, I cannot guide you accurately but will try to answer generally. If higher are modes are dominant in your structure, it could be either that higher modes are really contributing to the overall deformation or the lower modes have been suppressed by choice of boundary conditions (ex if the structure became too stiff). For example, consider a plate with too many accelerometers mounted on it. This certainly increases the system stiffness to such an extent that the lower modes are unable to make an impact. So the important thing to note here is that accelerometers need to be mounted in such a way that it does not alter the physical properties of plate (do not add mass or increase stiffness). Higher modes usually have complex shapes and are more localized. In contrast, lower modes have simple shapes and are more globalized. Also the excitation frequency range is important. Usually broad band excitation is given so as to check how the system responds overall. Certain frequencies will get excited which indicates resonance. But if the excitation frequency range is limited to high frequencies then the lower frequencies were not excited in the first place. So ensure all possible frequencies of interest are excited. These are the possible scenarios I could think of.
Have no Idea if you Will read this coments but if yes that was an amading video. Please what is the bast configuration of the piramids and which material it is more apropriate for such porpouse thanks.
There are many parameters to consider while designing an Anechoic/Semi-anechoic chamber. The most important is the cut-off frequency of the chamber which depends on the chamber dimensions and the wedge height. The lower the cut-off frequency, the larger should be the room size and the wedge height. Wedges help achieve near free field condition not only by absorbing high frequencies but also by trapping the lower frequencies due to their tapered shape. The wedge material must be a good absorber (ex. fiberglass, foam) with 0.99 absorption coefficient over a defined frequency range.
The more important - meaningful - divisions are direct field and reverberant field. The point at which they change is called the critical distance. The difference between the fields are spatial. The direct sound comes straight from the instruments, the reverberant field comes from all around you. In the reproduction the direct field is reproduced by the direct field of the speakers. The reverberant field is reproduced by the reflected sound from behind and beside the speakers. The secret of good speaker design is the radiation pattern and speaker positioning to project a good image model of these fields, including a flat power response.
The problem here is not with echoes but rather reverberation. Reverberation occurs when multiple reflections of the same sound arrives at slightly different times at the microphone creating one prolonging sound. As the room had flat walls and tiled floors, there was more opportunity for sound waves to undergo reflections. A reverberant environment does cause sound to be unintelligible and can increase the perceived amplitude of sound. However, it does not alter the frequency content of the sound since the environment (room) is not producing any sound but only reflecting already created sound.
For FEM (Finite Element Method) Simulation, one of the prerequisite is, the object of interest has to be discretized into finite particles called elements. In this video, the plate was divided into 100 elements. Larger the number of elements, better the results but also greater is the computational cost.
Good job 👍💯. I have generated wavelets with the theory of trigonometric partition equations we can create wavelets. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-p0Zc9onKQ0Q.htmlsi=dX1K0xLtJ2iWSgf5 ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-3Ebvypj577E.htmlsi=zeLyrZc54430eV5b ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-DV1iJV0oa7Y.htmlsi=798Te0vetj90Q7j1
Octave analysis is performed by passing a signal through many bandpass filters. While this is good for longer sounds, it may not be the best approach when it comes to analyzing short sounds where both time and frequency information are important. If we use FFT/Octave approach there are some things to consider. First the frequency resolution is fixed because the duration of signal is very low (ex. Door close sound). Higher frequency resolution can be obtained only when duration of signal is longer. To learn more about time-frequency relation check the link in video description. Second, this approach uses fixed frequency resolution over the entire spectrum, which also means that time resolution is fixed. The wavelet analysis overcomes this by using multi-resolution windowing so there is no further dependency on time and frequency. Hence one can achieve good time and frequency resolution at the same time.
@@SrinathSrinivasan Very thanks for your answer ! But in fact my question was not what i intended in my mind... I was thinking about iir bandpass, (Generally i use original signal minus 2th allpass.) From what i understand, wavelet use fir ? But what is the difference if we replace them with those bandpass iir filter ? would the latency be worse or the same ?
Yes, a wavelet can be considered as an FIR filter as it has a finite impulse response in the time domain without recursive components. Now merely comparing FIR and IIR with respect to latency, IIR has less latency as you probably know that IIR filter being recursive in nature uses past outputs as input resulting in fewer calculations compared to FIR which is non-recursive. The less latency of an IIR comes at an expense of phase issues. These can be rectified by using All pass filters but if higher order All pass are required then again it means more computation which can increase latency.
@@SrinathSrinivasan Thanks !! I'm just testing my first FIR wavelet at 110 hz with 4096 tap. For the phase this is exact but note that at the exact frequency of interest, the phase could be exact, yet it degrade around that frequency. (depending of the type of bandpass, as a combination of lp and hp will maybe not do this ) I just test to see the difference, with only one bandpass (that is original signal minus a 2th allpass) the phase doesn't degrade so much around the frequency, but we have another problem, the envelope of the signal is extremely smoothed as 5X longer than the original, where the Fir have approximately a 1.7X longer envelope. Now i could use more bandpass filter in series with lower coefficient to get a less degraded envelope, But now, the phase is degraded even more around the frequency.. To get almost the same envelope elongation with IIR, i need to use 8 bandpass in series. But now the latency is even greater than with the FIR !... Well, this is a little approximate because i have some tool to visually see if the filter have the same response but it's not ultra precise, also, the IIR have a less sharp attenuation... But it give me an idea, using a IIR filter that degrade the envelope but have less latency and try to stop the detection with a FIR or more filter in series. But maybe i did'nt use the right windows for the wavelet, here a Hamming windows ?
Jeez this just made my day. It was so easy to easy to understand this way. You just want a periodic signal. That is the whole goal, with windowing that FTT and bam you have your awnser :0
Hello, I really like your video very much and the explanation helped a lot. However, when you showed the window at around 6:42, the window function seemed to be misplaced on the axis. I wonder if I am seeing it right :)
Awesome video, unless I missed it, is there any specific reason why many manufacturers exclude well number 0? Esthetically they'll look symmetrical but wondering if there's a benefit in terms of sound. Maybe well number zero is not that influent? Thanks in advance!
The well number 0 is present in QRD of any order. When installing QRD assuming N7, it is recommended to use arrays of N7 as using only one will not give meaningful results. So either one can leave the well '0' on one side or split the well '0' evenly along the ends. The latter option ensures that one does not need to worry about symmetry during final assembly. I do not know which manufacturer excludes well '0' altogether but there is a well known QRD manufacturer - RPG Acoustical systems. Their QRD model QRD-734 as mentioned in their website offers well '0' split along both ends. Out of curiosity I used QRDude software to check if there is any difference in keeping well '0' as it is or splitting it along ends and there was no observable difference. You can check the findings in the link in the video description now. Finally my thoughts, even if a manufacturer were to neglect well'0' altogether, they still have to use end-fins on both sides to cover the diffuser sides. In that process, they have just added an approximate well '0' on both sides since the end-fin will have some finite thickness.
Oh thank you very much for your detailed explanation! Now it makes sense... It was my mistake, never noticed that most likely those looking "simmetric" in fact have larger sides to compensate... I prefer the simmetric design, unless is equally good!
Hello Srinath, awesome video, indeed!! Thanks. Just had a quick question. At 11.58min of your video, when you are describing the effect of increasing the sampling rate, 1) you are increasing the sampling rate from 2500Hz to 25000Hz. BUT 2) you are using the SAME signal (right?), that you previously sampled at a rate of 2500Hz. IF SO, then how come the bandwidth of the signal got changed (!). Let's say, I have a sinusoidal signal of frequency 5Hz. Does the bandwidth of the SIGNAL change When I sample it at 10 Hz and at 100Hz, respectively? Would be great if you could clarify this confusion!! Thanks in advance.
Sampling rate (in the time domain) is how many samples are being acquired in a given time. In this video, I considered two cases wherein the signal was being acquired with different sampling rates (2500Hz and 25000Hz). Now sampling rate has a consequence in the frequency domain which is bandwidth. One has to sample the signal at least 2.5 times than the highest frequency of interest. Hence in acoustic recordings, as our frequencies of interest lies within the human hearing range (20Hz - 20KHz), we usually sample at 48KHz. In other words a signal sampled at 48KHz would result in a bandwidth of up to 20KHz in the frequency domain. If the signal was only sampled at 24KHz then the bandwidth is now reduced to around 12KHz because the current sampling frequency is too slow to accurately sample the fast oscillating high frequency waves. To answer the other question: If your sine wave of 5Hz is sampled at 10Hz and 100Hz, the bandwidth in frequency domain is different in each case although you will only see 5Hz result in the spectrum. If you had an additional sine wave of say 20Hz then you cannot sample it with 10Hz as it is less than 20Hz, it will fail to capture it.
Hi, Are you going to produce videos in more advance wavelet analysis? I can not link the idea of the wavelet analysis with the filtering in discrete wavelet analysis. Thank you.
Hey Srinath. Thanks for the video. I'm a doctoral student at CalArts doing research on using megaphones as musical instruments. I would love to look at your charts and diagrams in higher definition. Would you be willing to share them? Thanks for considering!