synthesis op• Data kinds: कोई नहीं → table (केवल arguments से तय होने वाला op — यह कोई image या data input नहीं लेता)
• Call: import fullseye as fs; fs.ledger.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) (implementation को सीधे call करना हो तो 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), registry से लेना हो तो opsacoustics.get("synthesize_speed_ramp"))
एक run-up: shaft *order* से बँधे components, वैकल्पिक रूप से एक Hz में स्थिर।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
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 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.
• acoustic_condition_monitoring family guide
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
table को input के रूप में लेते हैं)synthesis)*Provenance: acoustics.py — ACOUSTICS operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.