Source: https://jmrplens.github.io/phonometry/buildings/insulation/insulation-ratings/ # Insulation Ratings (ISO 717) Every sound-insulation quantity in this documentation ends its journey the same way: a band spectrum walks in, a single number walks out. Whether the spectrum is a laboratory $R$, a field $R'$ or $D_\mathrm{nT}$, a façade $D_{2\mathrm{m,nT}}$, an impact $L_\mathrm{n}$ or $L'_\mathrm{nT}$, or a flanking $D_\mathrm{n,f}$, what regulations quote is the weighted single number of ISO 717, and two reference-curve engines produce all of them: **ISO 717-1** for airborne quantities, where an unfavourable deviation is a band falling *below* the reference, and **ISO 717-2** for impact quantities, with the sign flipped because a higher impact level is worse. This guide covers the engines themselves: the shifting rule, the spectrum adaptation terms $C$, $C_\mathrm{tr}$ and $C_\mathrm{I}$, the enlarged-range and one-decimal variants, and the ISO 717 fiche. The measurements that produce the spectra live in the [field](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-field/), [laboratory](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-lab/), [intensity](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-intensity/), [survey](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-survey/) and [flanking](https://jmrplens.github.io/phonometry/buildings/insulation/flanking-lab/) guides; the prediction that consumes the ratings is [EN 12354](https://jmrplens.github.io/phonometry/buildings/design/insulation-prediction/). ## Airborne ratings (ISO 717-1) The band spectrum is collapsed to one number by the **reference-curve method** of ISO 717-1: a fixed reference curve is shifted in 1 dB steps toward the measured curve until the sum of *unfavourable* deviations (where the measurement falls below the reference) is as large as possible but not more than 32.0 dB (16 one-third-octave bands) or 10.0 dB (5 octave bands). The rating ($R_\mathrm{w}$, $R'_\mathrm{w}$, $D_\mathrm{nT,w}$ …) is the shifted reference read at 500 Hz. The **spectrum adaptation terms** $C$ (pink noise) and $C_\mathrm{tr}$ (urban traffic) add the low-frequency penalty of a real source. The two terms re-rate the same measured curve against the two source spectra of ISO 717-1 Annex A: $C$ against A-weighted pink noise, representative of living activities (speech, music, radio, television), and $C_\mathrm{tr}$ against A-weighted urban road traffic, whose energy sits at low frequency. They are defined so that the rating plus the term ($R_\mathrm{w} + C$ for a laboratory index, $R'_\mathrm{w} + C$ or $D_\mathrm{nT,w} + C$ for the quantities of the [field guide](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-field/), and likewise with $C_\mathrm{tr}$) is the A-weighted level difference achieved against that source. Reading them: * $C$ stays small for most constructions (0 to −2 dB is typical): the pink spectrum is close to the weighting already implicit in the reference curve. * $C_\mathrm{tr}$ punishes weak low-frequency insulation. A lightweight double leaf with its mass-air-mass resonance near 100 Hz can carry a $C_\mathrm{tr}$ of −5 to −10 dB, while a heavy monolithic wall with the same $R_\mathrm{w}$ loses far less: two constructions with equal ratings can differ audibly against traffic. * Design with the descriptor that matches the noise, carried by the field quantity the requirement rates: $R'_\mathrm{w} + C_\mathrm{tr}$ for a façade on a busy road, $D_\mathrm{nT,w} + C$ (or the plain rating, where the regulation says so) between dwellings, the two example requirements of ISO 717-1, 5.3. ```python from phonometry import building # Single-number rating from a measured 16-band R spectrum (ISO 717-1 Annex C) R = [20.4, 16.3, 17.7, 22.6, 22.4, 22.7, 24.8, 26.6, 28.0, 30.5, 31.8, 32.5, 33.4, 33.0, 31.0, 25.5] w = building.weighted_rating(R) print(w.rating, w.c, w.ctr) # 30 -2 -3 -> Rw(C;Ctr) = 30(-2;-3) w.plot() # measured R' vs shifted ISO 717-1 reference, deviations shaded (needs matplotlib) ```

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```python import matplotlib.pyplot as plt from phonometry import building # Single-number rating from a measured 16-band R spectrum (ISO 717-1 Annex C) R = [20.4, 16.3, 17.7, 22.6, 22.4, 22.7, 24.8, 26.6, 28.0, 30.5, 31.8, 32.5, 33.4, 33.0, 31.0, 25.5] w = building.weighted_rating(R) # One line — measured curve vs the shifted ISO 717-1 reference, deviations shaded: w.plot() plt.show() # By hand, from the band curve the result now carries: fig, ax = plt.subplots() ax.semilogx(w.band_centers, w.measured, "o-", label="Measured R'") ax.semilogx(w.band_centers, w.shifted_reference, "s--", label="Shifted reference") ax.fill_between(w.band_centers, w.measured, w.shifted_reference, where=w.measured < w.shifted_reference, interpolate=True, alpha=0.3, label="Unfavourable deviations") ax.set_xlabel("Frequency [Hz]") ax.set_ylabel("Sound reduction index [dB]") ax.set_title(f"Rw = {w.rating} dB (C={w.c:+d}; Ctr={w.ctr:+d})") ax.legend() plt.show() ```

### `weighted_rating()` parameters | Parameter | Type | Units | Range / default | Notes | | :--- | :--- | :--- | :--- | :--- | | `values_by_band` | 1D array | dB | 16 (thirds) or 5 (octaves) | Measured $R$, $R'$, $D_\mathrm{nT}$ … per band | | `bands` | str or `None` | — | `'third-octave'` / `'octave'` / `None` | `None` infers from the count | `weighted_rating()` returns a `WeightedRatingResult` (`rating`, `c`, `ctr`, `unfavourable_sum`, all integers except the sum). ## Impact ratings (ISO 717-2) The single-number rating (ISO 717-2) shifts the same style of reference curve, but an **unfavourable deviation now occurs where the measurement *exceeds* the reference** (impact noise is worse when higher), the sign opposite to ISO 717-1. The rating ($L_\mathrm{n,w}$, $L'_\mathrm{n,w}$, $L'_\mathrm{nT,w}$) is the shifted reference read at 500 Hz; for octave bands it is then reduced by 5 dB. The spectrum adaptation term $C_\mathrm{I} = L_\mathrm{n,sum} - 15 - L_\mathrm{n,w}$ uses the energetic sum over 100–2500 Hz (the first 15 thirds, excluding 3150 Hz) or 125–2000 Hz (octaves). For measurements extended down to 50 Hz, `weighted_impact_rating_extended` additionally returns the enlarged-range term $C_{\mathrm{I},50\text{–}2500}$ (A.2.1 NOTE), and with `one_decimal=True` the 0.1 dB-step rating used in uncertainty statements (it reproduces the printed $L_\mathrm{n,r,0,w} = 77.6$ dB and $C_\mathrm{I,r,0} = -10.3$ dB of A.2.2). ```python import numpy as np from phonometry import building # 16 one-third-octave impact levels (100 Hz - 3150 Hz), dB, from the # ISO 717-2 Annex C worked example; measured with T = T0, so these are # already the standardized L'nT values. l_nt = np.array([62.1, 63.2, 63.5, 66.2, 68.5, 70.0, 71.7, 73.1, 73.8, 73.5, 73.8, 73.3, 73.1, 73.0, 72.4, 71.2]) # Weighted impact rating + spectrum adaptation term CI (ISO 717-2) res_imp = building.weighted_impact_rating(l_nt) print(res_imp.rating, res_imp.ci, res_imp.unfavourable_sum) # 79 -11 28.0 -> L'nT,w(CI)=79(-11) # Octave-band data carry the extra -5 dB reduction (Clause 4.3.2) octave = np.array([65.3, 64.5, 58.0, 55.8, 43.0]) print(building.weighted_impact_rating(octave).rating) # 54 res_imp.plot() # measured L'nT vs shifted ISO 717-2 reference, measured-above shaded (needs matplotlib) ```

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```python import matplotlib.pyplot as plt import numpy as np from phonometry import building # 16 standardized one-third-octave impact levels L'nT, dB (ISO 717-2 # Annex C worked example, measured with T = T0). l_nt = np.array([62.1, 63.2, 63.5, 66.2, 68.5, 70.0, 71.7, 73.1, 73.8, 73.5, 73.8, 73.3, 73.1, 73.0, 72.4, 71.2]) # Weighted impact rating + spectrum adaptation term CI (ISO 717-2) res_imp = building.weighted_impact_rating(l_nt) # One line — measured L'nT vs the shifted ISO 717-2 reference (measured-above shaded): res_imp.plot() plt.show() # By hand, from the band curve the result now carries (note the opposite sign: # an unfavourable deviation is where the MEASURED level exceeds the reference). # Here the input was l_n_t, so the rated quantity is the field level L'nT,w: fig, ax = plt.subplots() ax.semilogx(res_imp.band_centers, res_imp.measured, "o-", label="Measured L'nT") ax.semilogx(res_imp.band_centers, res_imp.shifted_reference, "s--", label="Shifted reference") ax.fill_between(res_imp.band_centers, res_imp.shifted_reference, res_imp.measured, where=res_imp.measured > res_imp.shifted_reference, interpolate=True, alpha=0.3, label="Unfavourable deviations") ax.set_xlabel("Frequency [Hz]") ax.set_ylabel("Impact sound pressure level [dB]") ax.set_title(f"L'nT,w = {res_imp.rating} dB (CI={res_imp.ci:+d})") ax.legend() plt.show() ```

Feeding the standardized spectrum into `weighted_impact_rating` reproduces the ISO 717-2 Annex C values (thirds $L'_\mathrm{nT,w} = 79$, $C_\mathrm{I} = -11$; octave 54, $C_\mathrm{I} = 0$). ### `weighted_impact_rating()` parameters | Parameter | Type | Units | Range / default | Notes | | :--- | :--- | :--- | :--- | :--- | | `values_by_band` | 1D array | dB | 16 (thirds) or 5 (octaves) | Measured $L_\mathrm{n}$, $L'_\mathrm{n}$ or $L'_\mathrm{nT}$ per band | | `bands` | str or `None` | — | `'third-octave'` / `'octave'` / `None` | `None` infers from the count | `weighted_impact_rating()` returns an `ImpactRatingResult` (`rating`, `ci` integers, `unfavourable_sum` in dB). ## Enlarged frequency ranges and one-decimal ratings When the measurement covers more than the core 100–3150 Hz bands, ISO 717-1 Annex B defines additional adaptation terms with the range as a subscript ($C_{50\text{–}3150}$, $C_{50\text{–}5000}$, $C_{100\text{–}5000}$ and the $C_\mathrm{tr}$ counterparts), computed with the Table B.1 spectra over the enlarged range. `weighted_rating_extended` takes the band values *with their centre frequencies* and returns the core rating plus every extended term the input covers (the impact counterpart `weighted_impact_rating_extended` adds $C_{\mathrm{I},50\text{–}2500}$). With `one_decimal=True` the reference curve shifts in 0.1 dB steps and all reductions keep one decimal: the variant ISO 717 prescribes "for the expression of uncertainty" and ISO 12999-1 Annex B requires when stating the uncertainty of a single-number value. ```python from phonometry import building # Single-number rating from a measured 16-band R spectrum (ISO 717-1 Annex C) R = [20.4, 16.3, 17.7, 22.6, 22.4, 22.7, 24.8, 26.6, 28.0, 30.5, 31.8, 32.5, 33.4, 33.0, 31.0, 25.5] freqs = [50, 63, 80, 100, 125, 160, 200, 250, 315, 400, 500, 630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000, 5000] r_ext = [18.7, 19.2, 20.0, *R, 26.8, 29.2] # ISO 717-1 Annex C, Table C.2 ext = building.weighted_rating_extended(r_ext, freqs) print(ext.rating, ext.c, ext.ctr, ext.c_50_5000, ext.ctr_50_5000) # 30 -2 -3 -2 -4 -> Rw(C;Ctr;C50-5000;Ctr,50-5000) = 30(-2;-3;-2;-4) one_dp = building.weighted_rating_extended(r_ext, freqs, one_decimal=True) print(one_dp.rating) # 30.0, the 0.1 dB-step rating for uncertainty statements ext.plot() # enlarged-range curve vs the shifted core reference, Annex B terms in the title (needs matplotlib) ``` *The rating itself is still evaluated on the 16 core bands (100–3150 Hz); the enlarged bands only enter the Annex B adaptation terms, so the shifted reference curve stops at the core-range edges while the measured curve continues into the shaded enlarged range.*

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```python import matplotlib.pyplot as plt from phonometry import building # Single-number rating from a measured 16-band R spectrum (ISO 717-1 Annex C) R = [20.4, 16.3, 17.7, 22.6, 22.4, 22.7, 24.8, 26.6, 28.0, 30.5, 31.8, 32.5, 33.4, 33.0, 31.0, 25.5] freqs = [50, 63, 80, 100, 125, 160, 200, 250, 315, 400, 500, 630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000, 5000] r_ext = [18.7, 19.2, 20.0, *R, 26.8, 29.2] # ISO 717-1 Annex C, Table C.2 ext = building.weighted_rating_extended(r_ext, freqs) # One line — the enlarged-range curve vs the shifted core reference: ext.plot() plt.show() # By hand, from the band curves the result carries (the full enlarged-range # curve on ext, the core-band reference on ext.core): fig, ax = plt.subplots() ax.semilogx(ext.band_centers, ext.measured, "o-", label="Measured R") ax.semilogx(ext.core.band_centers, ext.core.shifted_reference, "s--", label="Shifted reference (core bands)") ax.fill_between(ext.core.band_centers, ext.core.measured, ext.core.shifted_reference, where=ext.core.measured < ext.core.shifted_reference, interpolate=True, alpha=0.3, label="Unfavourable deviations") ax.set_xlabel("Frequency [Hz]") ax.set_ylabel("Sound reduction index [dB]") ax.set_title(f"Rw = {ext.rating} dB (C50-5000={ext.c_50_5000:+g}; " f"Ctr,50-5000={ext.ctr_50_5000:+g})") ax.legend() plt.show() ```

## ISO 717 report (`.report()`) Both rating results render a one-page PDF fiche laid out like an accredited-laboratory test report through a `report(path)` method: a standard-basis line (measurement standard plus the ISO 717 rating part), an optional metadata header block, the one-third-octave table beside the measured-versus-shifted-reference plot (the result's own `.plot()`), the boxed single-number result, an optional verdict row and a footer with the fixed disclaimer. `WeightedRatingResult.report()` labels the airborne ISO 717-1 fiche ($R_\mathrm{w}\ (C\ ;\ C_\mathrm{tr})$, deviations where the reference is above the measurement); `ImpactRatingResult.report()` labels the impact ISO 717-2 fiche ($L_\mathrm{n,w}(C_\mathrm{I})$, deviations the opposite way). `SoundReductionResult.report()` is a convenience that rates the predicted $R(f)$ and writes its fiche in one call. The report metadata is supplied as a `ReportMetadata` frozen dataclass (every field optional; only the supplied fields are rendered, and the numeric fields must satisfy their field-specific physical ranges, detailed in the table below). Passing `metadata=None` produces a lightweight prediction fiche (body, result and disclaimer only). When `metadata.requirement` is set, a verdict row is added: an airborne rating passes when it is at or above the requirement, an impact rating when it is at or below it (a lower impact level is better). Setting `verbose=True` swaps the two-column `f | value` table for the ISO 717 Annex C columns (frequency, measured value, shifted reference, unfavourable deviation). Rendering needs reportlab, kept out of the runtime dependencies as the optional `phonometry[report]` extra (`pip install phonometry[report]`); a missing reportlab raises a clear `ImportError` with the install command, and the plot still needs matplotlib (`phonometry[plot]`). Only `engine="reportlab"` is supported; any other engine raises `ValueError`. The fiche renders in English by default; pass `language="es"` for a Spanish fiche (translated fixed strings and a comma decimal separator), e.g. `building.weighted_rating(R).report("Rw_fiche_es.pdf", language="es")`. ```python from phonometry import building, ReportMetadata # Airborne rating from a measured 16-band R spectrum (ISO 717-1) R = [20.4, 16.3, 17.7, 22.6, 22.4, 22.7, 24.8, 26.6, 28.0, 30.5, 31.8, 32.5, 33.4, 33.0, 31.0, 25.5] metadata = ReportMetadata( specimen="200 mm reinforced-concrete wall", client="Acoustic Test Client Ltd.", area=10.0, mass_per_area=460.0, source_volume=53.0, receiving_volume=51.0, temperature=21.5, relative_humidity=45.0, pressure=101.3, test_room="Transmission suite T1", measurement_standard="ISO 10140-2", test_date="2026-07-18", laboratory="Phonometry Reference Laboratory", operator="José Manuel Requena Plens", report_id="PHN-2026-0042", requirement=42.0, # adds the PASS/FAIL verdict row ) building.weighted_rating(R).report( "Rw_fiche.pdf", metadata=metadata ) # Rw (C; Ctr) # Impact rating from a measured 16-band L'nT spectrum (ISO 717-2) l_nt = [45.0, 47.0, 48.0, 49.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 55.0, 52.0, 49.0, 46.0] building.weighted_impact_rating(l_nt).report("Lnw_fiche.pdf") # Ln,w (CI) ``` Rendered examples of both fiches, regenerated with `make reports`, are kept in the repository. Click either preview to open the PDF: [](https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/reports/iso717_airborne_example.pdf) *Airborne rating fiche (`WeightedRatingResult.report`), $R_\mathrm{w}\ (C\ ;\ C_\mathrm{tr})$.* [](https://raw.githubusercontent.com/jmrplens/phonometry/main/.github/reports/iso717_impact_example.pdf) *Impact rating fiche (`ImpactRatingResult.report`), $L_\mathrm{n,w}(C_\mathrm{I})$.* ### Report metadata (`ReportMetadata`) Every field is optional and only the supplied ones are rendered, so the same object drives a full accredited fiche and a lightweight prediction fiche. The numeric fields are validated on construction by physical range. | Field | Type | Rendered as | | --- | --- | --- | | `specimen`, `client`, `mounted_by`, `manufacturer` | `str` | Header identity of the tested element and who it was tested for / mounted by | | `area`, `mass_per_area` | `float > 0` | Sample area $S$ (m²) and measured mass per unit area (kg/m²) | | `source_volume`, `receiving_volume` | `float > 0` | Room volumes (m³) | | `temperature`, `relative_humidity` | `float` | Single representative climate: air temperature (°C, any sign), relative humidity (0–100 %) | | `pressure` | `float > 0` | Ambient (static) air pressure during the test (kPa) | | `source_temperature`, `source_relative_humidity`, `receiving_temperature`, `receiving_relative_humidity` | `float` | Per-room climate when source and receiving rooms are reported separately (same ranges as above) | | `test_room`, `mounting`, `measurement_standard`, `test_date` | `str` | Facility, mounting condition, the measurement standard (forms the standard-basis line) and the test date | | `laboratory`, `operator`, `report_id`, `notes` | `str` | Footer: institute, operator signature line, report number and free-form remarks | | `requirement` | `float` | Target single number; adds the verdict row (airborne passes at or above it, impact at or below it) | ## Quick answers ### What is the difference between the C and Ctr spectrum adaptation terms? Both re-rate the same measured curve against the two source spectra of ISO 717-1 Annex A: $C$ against A-weighted pink noise (living activities: speech, music, radio, television) and $C_\mathrm{tr}$ against A-weighted urban road traffic, whose energy sits at low frequency. $C$ is typically 0 to −2 dB, while a lightweight double leaf with a mass-air-mass resonance near 100 Hz can carry a $C_\mathrm{tr}$ of −5 to −10 dB. ## References - Hopkins, C. (2007). *Sound insulation*. Butterworth-Heinemann. ISBN 978-0-7506-6526-1. [doi:10.4324/9780080550473](https://doi.org/10.4324/9780080550473). The interpretation of the single-number ratings and what they hide about the underlying band spectra. - International Organization for Standardization. (2020). *Acoustics — Rating of sound insulation in buildings and of building elements — Part 1: Airborne sound insulation* (ISO 717-1:2020). [iso.org catalogue](https://www.iso.org/standard/77435.html). The airborne reference-curve rating and the spectrum adaptation terms interpreted above. - International Organization for Standardization. (2020). *Acoustics — Rating of sound insulation in buildings and of building elements — Part 2: Impact sound insulation* (ISO 717-2:2020). [iso.org catalogue](https://www.iso.org/standard/69867.html). The impact reference-curve rating and the CI adaptation term, with the enlarged-range CI,50-2500. ## Standards ISO 717-1:2020 and ISO 717-2:2020, which define the reference-curve single-number ratings, the spectrum adaptation terms $C$, $C_\mathrm{tr}$ and $C_\mathrm{I}$, the enlarged-range terms of Annex B / A.2.1 and the 0.1 dB-step variant used in uncertainty statements. The spectra they rate come from ISO 16283 (field), ISO 10140 (laboratory), ISO 15186 (intensity), ISO 10052 (survey) and ISO 10848 (flanking); conformance is anchored on the standards' own Annex C worked examples. **Not covered.** Nothing here measures: every function takes an already-measured or predicted band spectrum from the field, laboratory, intensity, survey or flanking guides. The façade single number of **ISO 16283-3** Annex F and the flanking $D_\mathrm{n,f,w}$ reuse these engines from their own pages rather than duplicating them. One member of the family is deliberately absent: the A-weighted maximum impact level of **ISO 717-2:2020 Annex D**, which rates the rubber ball and the bang machine. It shifts no curve at all — it is an energy sum of A-weighted band levels — so it belongs with the sources it rates, in [Heavy and soft impact sources](https://jmrplens.github.io/phonometry/buildings/insulation/heavy-impact-sources/). ## See also - [Field Insulation Measurement (ISO 16283)](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-field/): the airborne, impact and façade spectra these engines rate in the field. - [Laboratory Insulation Measurement](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-lab/): the laboratory $R$ and $L_\mathrm{n}$ behind $R_\mathrm{w}$ and $L_\mathrm{n,w}$. - [Sound Insulation by Intensity (ISO 15186)](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-intensity/): the intensity indices rated with the same airborne engine. - [Sound Insulation Survey Method (ISO 10052)](https://jmrplens.github.io/phonometry/buildings/insulation/insulation-survey/): the survey quantities and their automatic ratings. - [Laboratory Flanking Transmission (ISO 10848)](https://jmrplens.github.io/phonometry/buildings/insulation/flanking-lab/): the flanking descriptors $D_\mathrm{n,f,w}$ and $L_\mathrm{n,f,w}$. - [Floor-Covering Impact Improvement (ISO 16251-1)](https://jmrplens.github.io/phonometry/buildings/design/impact-improvement/): the weighted improvement $\Delta L_\mathrm{w}$ built on the ISO 717-2 reference floor. - [Predicting Sound Insulation (EN 12354)](https://jmrplens.github.io/phonometry/buildings/design/insulation-prediction/): the single-number model that consumes these ratings. - [Theory](https://jmrplens.github.io/phonometry/reference/theory/rooms-buildings/): the reference-curve derivation behind the weighted single-number ratings. - API reference: [`building.measurement.insulation`](https://jmrplens.github.io/phonometry/reference/api/building/insulation/).