High-precision acoustic timegrapher and mechanical watch escapement analyzer powered by real-time DSP and Machine Learning readiness. Cross-platform (macOS/Linux/Windows) with a decoupled Python core. C/C++ optimization will be a future project, iOS and Android apps as well.
Desktop app for the Timegrapher Studio wristwatch timegrapher - rate, beat error, amplitude and BPH from escapement sound, DS3231-disciplined ESP32.
DIY watch timegrapher: Raspberry Pi Pico + INMP441 mic, rate / amplitude / beat error in the browser
Hairspring and mechanical-watch measurement resources, plus host-root crawl discovery.
3D-printable stand and fixtures for the Timegrapher Studio - watch clamp, sensor slide, pivot, and enclosure parts. Print-ready STL/3MF.
Marat Oganesyan — Hairspring and Firekeep
Timegrapher para relojes mecánicos que corre entero en el navegador: marcha, amplitud y error de batida con una sonda y una tarjeta de sonido USB de 5 €. / In-browser timegrapher for mechanical watches.
Timegrapher for mechanical watches: rate, beat error and amplitude from a microphone recording, with an AI diagnosis.
Open-source calculator for checking whether two mechanical-watch timegrapher rate readings agree, using both fits' uncertainty.
Hairspring is an iPhone timegrapher for mechanical watches—measure rate, beat error, amplitude bands, and repeatability with uncertainty stated.
Through-hole piezo preamplifier board for the Timegrapher Studio - conditions the faint escapement signal for the I2S ADC. KiCad.
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