synthesize_speed_ramp — ACOUSTICS synthesis op

Data kinds: nonetable (an op determined by its arguments alone — it takes no image or data input)

Call: import acoustics; acoustics.synthesize_speed_ramp(rate=5000.0, duration=4.0, rpm_start=600.0, rpm_end=1800.0, orders=(1.0, 3.5), amplitudes=None, resonance_hz=None, noise_sigma=0.0, seed=None) (or opsacoustics.get("synthesize_speed_ramp"))

Usage

A run-up: components locked to shaft *order*, optionally one fixed in Hz.

Order tracking has no meaning at constant speed, so its ground truth needs a

signal whose shaft rate moves. Here the shaft rate ramps linearly from

`rpm_start to rpm_end` and each component's instantaneous phase is

`2 pi * order * revolutions(t)` — so it is locked to the shaft *exactly*,

by construction, and its order is known to machine precision.

`resonance_hz` adds one component at a fixed frequency instead. That is

the discriminating case: after angular resampling an order stays put and a

resonance smears, which is the whole diagnostic value of the transform.

Returns a dict, because a speed record without its speed profile is not

analysable: `signal (the waveform), rpm` (per-sample shaft rate),

`revolutions (cumulative, per-sample), rate, duration`,

`orders, total_revolutions, resonance_hz`, and

`max_component_hz`.

Raises `ValueError`: non-real / string / bool scalars, non-positive

`rate / duration / rpm_start / rpm_end`, an empty or non-finite

`orders, an amplitudes` of the wrong length, a length over

:data:MAX_SAMPLES, and **any component reaching Nyquist at the fastest

point of the ramp** — checked at `max(rpm)`, not at the mean, because a

ramp that is legal on average can alias at its top end and produce a

perfectly plausible spectrum.

Detailed usage guide

acoustic_condition_monitoring family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

acoustic_condition_monitoringpy -3.11 examples/acoustic_condition_monitoring.py

Ops the type connects to (they accept table as input)

istft

Same category (synthesis)

synthesize_bearing_signal


*Provenance: acoustics.py — ACOUSTICS operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.