🚀 Release Notes: Cable Sheath Circulation Deep Processing & AI Diagnosis Platform
We are thrilled to announce the official release of the Cable Sheath Circulation Deep Processing & AI Diagnosis Platform!
This platform is a comprehensive intelligent software specifically designed for condition monitoring and health assessment of cable currents. By integrating cutting-edge Digital Signal Processing (DSP) technology and a heuristic AI expert diagnosis matrix, the platform helps power operation and maintenance (O&M) personnel, engineers, and researchers accurately extract core electrical features from complex on-site interference, and automatically outputs highly valuable fault diagnosis conclusions.
✨ Core Feature Highlights
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🎛️ Multi-dimensional Signal Deep Cleaning & Automatic Optimization: The system features multiple built-in professional-grade digital filters and supports flexible Auto or Custom configuration modes. The platform can execute DC bias elimination, improved Butterworth low-pass filtering, IIR comb filtering, and the EMA (Exponential Moving Average) algorithm to effectively filter out high-frequency clutter and specific frequency interference on-site.
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📊 High-dimensional Electrical Feature Extraction & "Golden Cycle" Synthesis: The platform utilizes adaptive waveform zero-crossing detection and cycle alignment algorithms to automatically intercept steady-state data and synthesize a "Golden Cycle". Based on this, the system can perform high-precision Fast Fourier Transform (FFT) to accurately analyze the amplitude, phase, Total Harmonic Distortion (THD), and Individual Harmonic Distortion (IHD) of the fundamental and each harmonic, while quantifying the interference deviation rate and minute DC bias.
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🧠 Heuristic AI Expert Diagnosis System: Featuring a built-in multi-dimensional expert diagnosis matrix, the platform maps and compares weights of extracted feature fingerprints such as pure RMS, DC bias, and harmonic distortion rates. This allows it to automatically diagnose up to 18 types of underlying software and hardware faults, just like a power expert. Typically identifiable hidden dangers include: cross-bonding box wiring anomalies/poor contact, sheath open circuits/damage, grounding box water ingress and dampness, and sheath multi-point grounding.
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⚙️ Dynamic Threshold & Multi-level Early Warning Engine: It supports O&M personnel to dynamically "hot modify" various security thresholds (such as warning and alarm thresholds) on the front-end interface. The platform responds in real-time according to business standards, scores the health of each metric, and triggers alarms via eye-catching visual tags (badges), enabling early discovery and intervention of hidden dangers.
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🛠️ Composite Fault Waveform Simulator: A powerful built-in waveform generator facilitates scientific research training and algorithm verification. Even without real data, users can freely set the fundamental RMS, frequency, DC bias, various proportions of higher-order harmonics, and random Gaussian noise to generate and download high-fidelity composite fault waveform CSV files with a single click.
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🌐 Bilingual Support: The platform interface supports one-click switching between Chinese and English to meet the language needs of different users.
🛠️ Technical Architecture & Out-of-the-Box Deployment
This platform is an interactive Web application built on the Python and Dash frameworks. To significantly lower the deployment barrier, we provide the following convenient ways to run it:
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Standalone Executable: No need to install Python or configure any dependency environments. Simply upload it to a VPS server and grant execution permissions to run it. It is recommended to run it in the background as a daemon process, mapped to port 8051 by default.
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Docker Containerized Deployment: Supports one-click image building and container execution via Docker, further simplifying the cross-platform deployment process.
💡 Target Audience & Precautions
-Target Audience: Power O&M personnel, system engineers, and researchers in related fields.
-Data Requirements: The platform currently accepts raw waveform data in a standard single-column CSV format with no header.
-Precautions: The AI diagnostic conclusions output by the platform are for reference only. The final fault determination and handling still require a comprehensive assessment combined with actual on-site conditions and the experience of professional personnel.