vib-spectra-dsp 1.3.0

No project description provided

vib-spectra-dsp

High-Performance Computational Framework for Advanced Vibration Signal Processing

vib-spectra-dsp is a heavily optimized, C-compiled analytical engine designed for processing complex time-series telemetry and performing high-resolution order-tracked diagnostics. Engineered for reliability ecosystems and heavy industrial data pipelines, this library provides deterministic execution for advanced spectral feature extraction and synchronous averaging across complex rotating kinematics.

Architectural Design: C-Optimized Execution

Processing high-density vibration time-waveforms—specifically involving iterative scalar generation and synchronous envelope demodulation—introduces significant computational latency in standard interpreted environments.

To achieve enterprise-grade scalability and real-time processing capabilities, vib-spectra-dsp bypasses standard Python execution overhead. The core DSP engine is written in Cython and compiled directly to C machine code, providing two foundational architectural advantages:

1. Deterministic C-Level Execution

By enforcing static C-types across all heavy mathematical arrays and intentionally bypassing the Python Global Interpreter Lock (GIL) during iterative processing, the engine executes Fast Fourier Transforms (FFTs) and complex looping algorithms at near-native C speeds. This prevents the computational bottlenecks typically associated with standard dynamic typing in Python.

2. Zero-Copy Memory Management (NumPy C-API)

Standard cross-language integrations suffer from data serialization overhead. vib-spectra-dsp circumvents this by interfacing directly with NumPy's underlying C-API. Utilizing Cython Typed MemoryViews, the engine performs zero-copy, memory-contiguous array manipulations. It reads and writes directly to the physical memory addresses of the host system, drastically reducing RAM overhead during large block-size matrix convolutions and multi-dimensional array transformations.

Core Capabilities

• Synchronous Time-Series Processing: Optimized for high-frequency resampling and time-synchronous averaging (TSA) algorithms.
• Order Domain Transformations: High-fidelity conversion of non-stationary time-domain signals into the angular order domain.
• Algorithmic Feature Extraction: Rapid generation of complex statistical scalars and spectral envelope indicators for early-stage fault detection in multi-stage transmissions.

Deployment & Installation

The engine is distributed via pre-compiled, architecture-specific binary wheels. No local C/C++ build tools are required for deployment.

It is natively compatible with standard Windows operating systems and scalable enterprise Linux environments (including Databricks, Snowflake, and standard Dockerized containers).

pip install vib-spectra-dsp