bearing 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.bearing_defect_frequencies(rpm=1800.0, n_elements=9, element_diameter=8.0, pitch_diameter=40.0, contact_angle_deg=0.0) (implementation को सीधे call करना हो तो import acoustics; acoustics.bearing_defect_frequencies(rpm=1800.0, n_elements=9, element_diameter=8.0, pitch_diameter=40.0, contact_angle_deg=0.0), registry से लेना हो तो opsacoustics.get("bearing_defect_frequencies"))
rolling-element bearing की चार characteristic rates, geometry से।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
Derived, not tabulated. Under pure rolling the cage advances at half the sum of the race surface speeds, which with r = d/D cos(alpha) gives, per shaft revolution rate f_r = rpm/60:
• FTF (cage / fundamental train) = f_r (1 - r) / 2
• BPFO (ball pass, outer race) = N f_r (1 - r) / 2 = N * FTF
• BPFI (ball pass, inner race) = N f_r (1 + r) / 2
• BSF (ball spin) = f_r (1 - r^2) D / (2 d)
Two exact identities fall out and are asserted in the tests, because they catch a transposed d and D immediately: BPFO + BPFI = N f_r exactly, and BPFO = N * FTF exactly. Measured for the defaults (1800 rpm, 9 elements, d = 8, D = 40, alpha = 0): ratio = 0.200000, f_r = 30.000000, FTF = 12.000000, BPFO = 108.000000, BPFI = 162.000000, BSF = 72.000000 Hz, with BPFO + BPFI - 9 f_r = 0.000e+00 and BPFO - 9 FTF = 0.000e+00 — exactly zero in float64, not merely small.
Returns a dict with shaft_hz, ftf_hz, bpfo_hz, bpfi_hz, bsf_hz, ratio (d/D cos alpha), and the inputs echoed back. Also bsf_hz_2x: a rolling element normally strikes *both* races per spin, so a spall on the element itself is usually seen at 2 * BSF, and reporting only BSF is the classic way to miss it.
These are the no-slip kinematic rates. Real bearings slip by roughly a percent, so an observed line within about 1 % of one of these is a match and an exact match is a coincidence; that tolerance is the caller's to apply.
Raises ValueError: non-real / string / bool scalars, rpm <= 0, n_elements not an int >= 2, non-positive diameters, an element_diameter >= pitch_diameter (geometrically impossible — the rolling elements would not fit inside the pitch circle, and the usual cause is the two arguments being swapped, which otherwise returns a negative FTF and a plausible-looking BPFI), and |contact_angle_deg| >= 90.
• 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
• poc_bearing_diagnosis — py -3.11 examples/poc_bearing_diagnosis.py
• poc_machine_condition_fusion — py -3.11 examples/poc_machine_condition_fusion.py
table को input के रूप में लेते हैं)bearing)envelope_spectrum · spectral_kurtosis · cepstrum
*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.