science

Noise curve

Noise curve is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Noise curve rather than just read about it. In short: Noise curves are a common way to characterise background noise in unoccupied buildings and spaces. Their purpose is to produce a single-value representation of a complete sound spectrum.

Key takeaways

Noise curve belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Noise curve to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Noise curve from memory before moving on to harder problems.

Reference excerpt

Noise curves are a common way to characterise background noise in unoccupied buildings and spaces. Their purpose is to produce a single-value representation of a complete sound spectrum. International standards organizations (ISO, ANSI and ASA) recognize the need to objectify judgements on the amount of ambient noise in enclosed spaces, and provide us with definitions for various noise curves. The ANSI/ASA S12.2-2008 standard, for example, recommends an NC value of 25-35 for schools and 15-18 for concert halls. Background noise may have several undesirable effects. Noise can be an annoyance that creates fatigue and negatively affects productivity, safety and the ability to communicate. Therefore, standard methodologies for quantifying noise have been developed. Noise curves reflect different standardized means of creating a single number rating for the background noise spectrum in a space. Different rooms, locations, regulations, and applications may allow different acceptable noise ratings. In most cases, the goal is that background noise should not interfere with the purpose of the room, e.g. the noise of an office air-conditioning system and consistent noise of traffic outside the building should not interfere with telephone calls or conversations. In other cases, special noise may also be tolerated or even introduced at higher levels, for example to create acoustic "privacy", or to help mask other more irritating noise sources. The process of determining the single value for a particular room is first to measure the sound frequency spectrum created by the background noise in the room while the room is unoccupied. This spectrum is then superimposed onto a template graph containing the noise curves. The result is determined by the lowest curve which is not touched by the measured spectrum at any position in the audio frequency range. Noise curves serve as uniform measuring standards and are referred to by many noise regulations covering a variety of locations from concert halls, rock concerts, lecture rooms and offices to clay target shooting ranges. There are five major methods and standards for noise curves:

Noise Criterion Curves (NC) Noise Rating Curves (NR) Preferred Noise Criterion Curves (PNC) Room Criteria Curves (RC) Room Noise Criteria (RNC)

References

Illustrations

Worked examples

Example 1 — a first encounter with Noise curve

Start with the simplest possible case. Write down what Noise curve claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Noise curve before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Noise curve ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Noise curve

In research: Noise curve appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Noise curve in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Noise curve is common in secondary-school and first-year university syllabi. It links to neighbouring topics Acoustics, Noise, Sound, so understanding it makes those chapters shorter.
In everyday life: Look for Noise curve outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Noise curve in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Noise curve means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Noise curve out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Noise curve in simple terms?

Noise curves are a common way to characterise background noise in unoccupied buildings and spaces. Their purpose is to produce a single-value representation of a complete sound spectrum.

Why does Noise curve matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Noise curve?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Noise curve.