I’m building a PdM application and need one-on-one guidance from a CAT II-level vibration analyst. My biggest gap is turning raw vibration data into reliable insight, so I’d like your help in two areas: first, fine-tuning data collection and interpretation practices; second, shaping the core algorithms that will power the software. We’ll be working with the classic trio of techniques—Time Domain, Frequency Domain, and Envelope Analysis—so please be comfortable explaining best-practice workflows and translating them into practical code logic. I already have sample datasets and a basic development environment (Python + NumPy/Pandas/Matplotlib), but I’m flexible if you prefer other analysis libraries such as SciPy or MATLAB. Deliverables • Live or recorded coaching sessions walking through proper sensor placement, sampling parameters, and data cleansing • Annotated pseudo-code or prototype functions that implement the three analysis techniques, ready for integration into the larger architecture • A brief checklist I can reuse to validate data quality before each algorithm run Acceptance criteria • Each algorithm returns accurate metrics when tested against my benchmark datasets • Your explanations leave me confident in independently refining and extending the code If this matches your expertise, let’s schedule our first session and start transforming those vibration signals into actionable intelligence.