Most industrial activities create noise that can be harmful to the environment as well as to their workers. To minimize this effect, governments, associations, and companies have created regulations, standards, and codes to set the allowable noise both inside the sites, that can be harmful to the workers, as well as to the environment. In a lot of cases, during the planning phase, the plant owner and project management want to be sure that the noise levels are acceptable. Since the plant is not built yet, what can be done is creating a noise model to simulate the plant, so that the noise levels can be predicted. In this article, we will explore how we can do so.
The first thing we must know is how much noise does the noise sources inside of the plant will emit. The noise source is usually described in two ways which is Sound Power Level (Lw or SWL), and Sound Pressure Level (Lp or SPL) in certain distance, most commonly Lp in 1 m distance. There are multiple ways to get this information for certain noise sources. First, if the equipment type and model have been chosen, the equipment manufacturer will normally report the noise level in their datasheet. However, this is not usually the case with most of noise predictions since the noise study is normally done before the equipment suppliers are appointed. So, the second way to be able to predict the noise emission is by following empirical formulas that are developed by researchers. You can find such formulas in some textbooks, journals, and papers. For rotating parts, you will need its rated power and rotational speed to be able to estimate the noise emission.
For example, in the speed range of 3000-3600 rpm, the noise level of a pump with drive motor power above 75 kW can be predicted using the following equation:
Suppose a pump with rotational speed of 3000 rpm and 100 kW, according to the formula, it can be estimated that the noise level at 1 m from the pump would be 92 dB. And suppose the noise source can be considered as point source on the ground (hemisphere propagation), the sound power level of the pump can be calculated using the following formula:
Where r is the distance from source to receiver
And in this case, the predicted Lw would be 100 dB.
Thirds, noise measurement to a similar equipment can also be an option to be able to determine the noise level of the new equipment. Another option, in some countries, there are noise emission limit for certain equipment, you can use that limit if it is applicable for your project.
After the Lw of all noise sources is obtained, we want to calculate the noise levels (the Lp) at the receivers. There are some standards which procedure can be followed to calculate this. Few of which are ISO 9613-2, NORD 2000, CNOSSOS EU, and many others. Most of the standards consider some factors to the calculation such as distance, atmospheric absorption, ground reflection, screening effect (from barriers and obstacles) and other factors such as volume absorption from vegetation, industrial site, etc. Most consultants and projects will require a software such as SoundPLAN to do this calculation.
Depending the project, there are few types of noise limit which compliance will need to be ensured. The most common ones are environmental noise limit, noise exposure limit, area noise limit and absolute noise limit. Besides, the noise level during emergency is also modelled so that the information can be used for safety and PAGA (Public Address and General Alarm) study.
Environmental noise limit is usually calculated for the plant’s contribution to the plant’s boundary as well as to the nearest sensitive receiver such as residential and school near the plant. How this is accessed depends on the regulation applicable on the plant area. In Indonesia for example, the noise limit for residential area is Lsm 55 dBA and industrial area is Lsm 70 dBA. Lsm is a measure like Ldn, but the night noise level addition is 5 dB instead of the 10 dB addition that most other countries, especially Europeans use. To ensure compliance with this regulation, the noise level at fence should be less than Lsm 70 dBA, and suppose there is a residential area nearby, the contribution from the site should be less than 55 dBA. It is also advisable to measure the existing noise level at the sensitive receivers to make the study more relevant to the situation.
Noise exposure limit is the maximum exposure to noise that the workers get during their working period. In Indonesia, the noise exposure limit is 85 dBA for 8 working hours. To change the working hours, 3 dB exchange rate is used. For example, if the noise level in the plant is 88 dBA, then the workers can only work there for 4 hours, if it is 91 dBA, then the time limit is 2 hours, and so on. To extend the working hours on a noisy area, the options are to actually reduce the noise level by reducing the noise emission from the source or noise control at transmission (for example using barrier), or by usage of Hearing Protection Device (HPD) for the workers such as ear plugs and ear muffs. The noise exposure of workers after usage of HPD can be calculated using the following formula:
Where NRR is the noise reduction rating of the HPD in dB.
Different area might have different noise level limits, and therefore area noise limits are useful. For example, in an unmanned mechanical room, the noise level can be high, for instance 110 dBA. However, inside of the site office, the allowable noise level is much lower, for example 50 dBA. This noise level shall be calculated to ensure compliance with the noise limit. Different companies might have different limits for this to ensure their employees’ health and productivity. If the area is indoor and the noise source is outdoor, then the interior noise level can be estimated using standards such as ISO 12354-3.
The absolute noise limit is the highest noise level allowable at the plant, and shall not be exceeded at any times, including emergency. In most cases, the absolute noise limit for impulsive sound is 140 dBA. To ensure compliance with this requirement, potential high-level noise shall be calculated, for example safety valves.
During emergency, different noise sources than normal situation will be activated, such as flare, blowdown valves, fire pumps, and other equipment. In such cases, the sound from the alarm and Public Address system must be able to be heard by the workers inside of the plant. Normally the target for the SPL from the PAGA system should be higher than 10 dB above the noise level. Therefore, the noise level during emergency in each area should be well-known.
Geonoise just made basic noise calculations even easier.
You can make free calculations online to add, subtract decibel levels, calculate NR values and make your own reverberation calculations online!
Rail transport or train transport is one of the main transportation modes these days, both for transferring passengers and goods. Every day people commute to work and back home using trains in a form of subway systems, light rail transits and other types of rail transport. These types of system can create noise both to the passengers inside of the train as well as to the environment. In this article, we will discuss about noise source components that we hear daily both inside and outside of the train.
If we pay attention to the noise when we are on board of a train, there are more than one noise source that we can hear. The main sources for interior noise in a train are turbulent boundary layer, air conditioning noise, engine/auxiliary equipment, rolling noise and aerodynamic noise from bogie, as illustrated in the following figure.
By the way, we wrote and recorded the sound of Jakarta MRT. You can see the link below to help you imagine the train situation better.
Rolling noise is caused by wheel and rail vibrations induced at the wheel/rain contact and is one of the most important components in railway noise. This type of noise depends on both wheel and rail’s roughness. The rougher the surface of both components will create higher noise level both inside and outside of the train. To be able to estimate the airborne component from the rolling noise, we must consider wheel and track characteristics and roughness.
Another noise component that contributes a lot to railway noise is aerodynamic noise which can be caused by more than one sources. These types of sources may contribute differently to internal noise and external noise. For example, aerodynamic noise contributes quite significantly at lower speeds to internal noise while for external noise, it doesn’t contribute as much if the train speed is relatively low. For example, on the report written by Federal Railroad Administration (US Department of Transportation), it is stated that aerodynamic sources start to generate significant noise at speeds of approximately 180 mph (around 290 km/h). Below that speed, only rolling noise and propulsion/machinery noise is taken into consideration for external noise calculation. In addition to external noise, machinery noise also contributes to the interior noise levels. This category includes engines, electric motors, air-conditioning equipment, and so on.
To perform the measurements of railway noise, there are several procedures that are commonly followed. For measurement of train pass-by noise, ISO 3095 Acoustics – Railway applications – measurement of noise emitted by rail bound vehicles, is commonly used. This standard has 3 editions with the first published in 1975, and then modified and approved in 2005 and again in 2013. The commonly used measures for train pass-by are Maximum Level (LAmax), Sound Exposure Level (SEL) and Transit Exposure Level (TEL).
For interior noise, the commonly used test procedure is specified in ISO 3381 Railway applications – Acoustics – Measurement of noise inside rail bound vehicles. This procedure specifies measurements in few different conditions such as measurement on trains with constant speed, accelerating trains from standstill, decelerating vehicles, and stationary vehicles.
Acoustical Design Engineer
D. J. Thompson. Railway noise and vibration: mechanisms, modelling and means of control. Elsevier, Amsterdam, 2008
Federal Railroad Administration – U.S. Department of Transportation, High-Speed Ground Transportation Noise and Vibration Impact Assessment. DOT/FRA/ORD-12/15. 2012
Sound is a collection of random signals that have certain physical characteristics that depend on the sound source. One of the physical characteristics of sound can be seen from the spectrum formed. There is a lot of noise that can be distinguished based on the spectrum character, such as White Noise, Pink Noise, Brownian Noise, Blue Noise, Violet Noise, Gray Noise, and others. In general, what is often used is White Noise, Pink Noise, and Brownian Noise both in measurement and audio testing.
Many people are very familiar with White Noise, usually, the static sound from the Air Conditioner that delivers us to sleep by disguising background noise is always considered White Noise even though technically what we hear from the Air Conditioner fan rotation is not White Noise. Many of the sounds we associate with White Noise are actually Pink Noise, Brownian Noise, Green Noise, or Blue Noise. In the world of audio engineering, there are various types of noise colors with their own unique spectrum, this is produced to give a rich impression on music arrangements, relaxation, and so forth. So, this article will explain that static noise is not always White Noise.
Here are some sound colors that are quite familiar and often discussed in the world of audio engineering:
- White Noise
The most commonly mentioned noisy color in everyday life is White Noise. White Noise is called “White” as a symbolization of a white light containing all frequencies evenly or flatly in mathematical calculations. It is said mathematically because, in reality, it is not perfectly flat. The White Noise calculation pattern is evenly distributed if it is calculated using the following equation:
So in the case of White Noise, the signal power becomes:
The resulting spectrum is in the form of a constant straight line like the following graph,
Keep in mind that the graph shown is a logarithmic function and not a linear function where the frequency range at high frequencies is wider than the frequency range at low frequency. Here is a White Noise that can be heard:
2. Pink Noise
Proportionally the pink noise spectrum is seen to decrease on a logarithmic scale but it has equal power in bands that are proportionally wide. This means that pink noise would have equal power in the frequency range from 40 to 60 Hz as in the band from 4000 to 6000 Hz. Since humans hear in such a proportional space, where a doubling of frequency (an octave) is perceived the same regardless of actual frequency (40–60 Hz is heard as the same interval and distance as 4000–6000 Hz), every octave contains the same amount of energy and thus pink noise is often used as a reference signal in audio engineering. The spectral power density, compared with white noise, decreases by 3 dB per octave (density proportional to 1/f ). For this reason, pink noise is often called “1/f noise”. Some people associate pink with red and white where pink is brighter than red and fainter than white so that it is described as a decreased spectrum with values close to a ~ 1. Mathematically, Pink Noise can be calculated using the formulation below:
The depiction of the curve produced by Pink Noise is as follows:
Pink Noise will heard like the following audio file below,
3. Brownian Noise (Red Noise)
Brownian Noise color has several names, some people call it Brown Noise, Brownian Noise, or Red Noise. Brownian was discovered by Robert Brown, the inventor of Brownian Motion (Random Walk or Drunkard’s Walk) where the Noise produced by Brownian Motion is the same as Red Noise / Brown Noise. Described as a red light that is darker than Pink and White, the spectrum formed has the characteristic of a sharp decrease that exceeds a decrease in Pink Noise (1 / f2 or a decrease of 6 dB per octave). Visually the Red Noise value is the boundary of the Pink Noise, together with the White Noise, so the spectrum curve formed is as follows:
Brownian Noise will sound like the following audio file below:
4. Blue Noise (Azure Noise)
If Red Noise and Pink Noise have a decreased character, then Blue Noise is the opposite. Blue Noise has an uphill spectrum curve characteristic that is inversely proportional to Pink Noise. Blue noise’s power density increases 3 dB per octave with increasing frequency (density proportional to f ) over a finite frequency range. In computer graphics, the term “blue noise” is sometimes used more loosely as any noise with minimal low-frequency components and no concentrated spikes in energy. This can be a good noise for dithering. Cherenkov radiation is a naturally occurring example of almost perfect blue noise, with the power density growing linearly with frequency over spectrum regions where the permeability of the index of refraction of the medium is approximately constant. The exact density spectrum is given by the Frank–Tamm formula. In this case, the finiteness of the frequency range comes from the finiteness of the range over which a material can have a refractive index greater than unity. Cherenkov radiation also appears as a bright blue color, for these reasons.
The curve produced by Blue Noise is as follows:
Blue Noise will sound like the following audio file below:
5. Violet Noise (Purple Noise)
If Blue Noise is the opposite of Pink Noise, then Violet can be categorized as the opposite of Red or Brownian Noise. This can be seen from the addition of the power density of Violet Noise which is 6 dB per octave with increasing frequency value. The proportional density of Violet Noise or often also called Purple Noise is f2 over a finite frequency range. Violet Noise is also known as differentiated white noise, due to its being the result of the differentiation of a white noise signal.
The curve produced by Violet Noise is as follows:
Violet Noise will sound like the following audio file below:
6. Grey Noise
Gray Noise is a randomized White Noise that is correlated with the same psychoacoustic noise curve or can be said to be an inverse A-weighting curve, with a specific frequency range that gives the impression or perception that this sounds equally loud at all frequencies. This is in contrast to standard white noise which has equal strength over a linear scale of frequencies but is not perceived as being equally loud due to biases in the human equal-loudness contour.
The curve produced by Grey Noise is as follows:
Grey Noise will sound like the following audio file below:
Acoustic Design Engineer
Pics: Noise Curves By Warrakkk – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=19274696
Hartmann, William M. Signals, sound, and sensation. Springer Science & Business Media, 2004.
“Federal Standard 1037C”. Institute for Telecommunication Sciences. Institute for Telecommunication Sciences, National Telecommunications and Information Administration (ITS-NTIA). Retrieved 16 January 2018.
Lau, Daniel Leo; Arce, Gonzalo R.; Gallagher, Neal C. (1998), “Green-noise digital halftoning”, Proceedings of the IEEE, 86 (12): 2424–42, doi:10.1109/5.735449
Joseph S. Wisniewski (7 October 1996). “Colors of noise pseudo FAQ, version 1.3”. Newsgroup: comp.dsp. Archived from the original on 30 April 2011. Retrieved 1 March 2011.