01
What is SV500?
Predicting the Future of Equipment Through Electrical Signal Analysis and AI Technology.
02
Key Features
Detect Equipment Anomalies in Advance Through Ultra-High-Resolution Waveform Analysis and Digital Twin-Based AI Diagnostics.
- Measures electrical signals at 32 kHz and applies Digital Twin algorithms
with AI-driven analytics to deliver accurate equipment condition insights.
- Access equipment directly through a web browser without additional software installation
and monitor real-time measurements, equipment status, power quality, alarms, and event history.
- Monitor a wide range of industrial electrical and mechanical assets
including motors, transformers, VFDs, pumps, fans, and chillers through a single platform.
- Supports RS-485 and Ethernet communication networks,
enabling seamless integration with external modules and higher-level systems.
- Minimizes unplanned downtime and performs maintenance
only when necessary, significantly reducing maintenance expenses.
03
Equipment Diagnosis
01. Digital-Twin Algorithm
Based on machine learning through real-time equipment monitoring, the SV500 applies various mathematical techniques and diagnostic algorithms to analyze equipment conditions in detail.
Physical Motor
- Voltage Variations
- Operating States
- Stress Events
- Maintenance & Aging
- Load Variations
Digital Twin Motor
- 24Bits - 8kHz
3 phase V1 Waveform - Mathematical diagnostic algorithm
- Power Spectral
Density Analysis - Power Quality Analysis
- Machine Learning
- Predictive AI Analysis
Dashboard
Signal Processing & Data Transformation
- 32 kHz real-time data acquisition
- Three-phase voltage and current waveform analysis
- Various data analysis techniques
Key Analysis Techniques
- Power quality analysis
- Power spectral density analysis
AI-Based Predictive Analysis
- Machine learning & predictive AI analysis
- Fault detection framework
02. Diagnostic items
① Motor Diagnostics
The SV500 is capable of monitoring three-phase induction motors.The failure impacts and diagnostic indicators for motor diagnostic items are listed below.
Input Voltage
- Failure Impact: Equipment malfunction, accelerated motor degradation
- Diagnostic Indicators: Voltage RMS, Crest Factor, Voltage Imbalance, THD
Rotor
- Primary Impact: Increased vibration and noise, accelerated bearing wear
- Diagnostic Indicators: Current spectrum frequencies, static and dynamic eccentricity frequencies
Stator
- Primary Impact: Reduced efficiency, phase imbalance, increased heat, vibration, and noise
- Diagnostic Indicators: Park Vector Analysis, current spectrum frequencies, current imbalance
Noise / Vibration
- Primary Impact: Increased electrical and mechanical stress, reduced insulation and structural integrity
- Diagnostic Indicators: Noise frequency bands in voltage/current spectra, spectral instability
Overheating
- Primary Impact: Motor degradation, reduced lifespan, and decreased efficiency
- Diagnostic Indicators: RMS current, harmonic/distortion indices, DC components
Cable Connections
- Primary Impact: Increased resistance, voltage drop, overheating, and arc generation
- Diagnostic Indicators: Phase current imbalance and resistance imbalance
Bearings
- Failure Impact: Increased vibration and noise, stator-rotor contact damage
- Diagnostic Indicators: Roller and journal bearing defect frequencies
Torque Ripple
- Primary Impact: Increased vibration and noise, accelerated bearing wear
- Diagnostic Indicators: Positive/negative sequence components, torque stability
② VFD Diagnostics
The SV500 is capable of monitoring inverters (VFDs).The failure impacts and diagnostic indicators for inverter diagnostic items are listed below.
DC Link
- Failure Impact: Voltage instability, increased harmonics, inverter trips, reduced motor performance
- Diagnostic Indicators: DC voltage/current components, transient voltage events, harmonics
Switching Stage
- Failure Impact: IGBT/MOSFET degradation, increased EMI, switching losses, overheating, and insulation stress
- Diagnostic Indicators: Switching-related harmonics and sidebands in voltage/current signals
Overheating
- Primary Impact: Motor degradation, reduced lifespan, and decreased efficiency
- Diagnostic Indicators: RMS current, harmonic/distortion indices, DC components
Load
- Failure Impact: Overheating, mechanical stress, torque instability
- Diagnostic Indicators: RMS current and imbalance, current Crest Factor, harmonic distortion, phase angle imbalance
Rectifier Stage
- Failure Impact: Increased current harmonics/TDD, upstream voltage distortion, overheating
- Diagnostic Indicators: Rectifier-related harmonic components in voltage/current signals
③ Transformer Diagnostics
The SV500 is capable of monitoring transformers.The failure impacts and diagnostic indicators for transformer diagnostic items are listed below.
Stress
- Primary Impact: Insulation degradation, reduced service life, and performance deterioration
- Diagnostic Indicators: Harmonic Load Factor (FHL/K-factor), overcurrent, voltage/current Crest Factor
Capacitors
- Primary Impact: Reduced power factor, increased losses, voltage instability, and elevated system stress
- Diagnostic Indicators: Transient voltage/current events, capacitor overcurrent
Ground Fault (Y)
- Primary Impact: Equipment damage, electric shock risk, and system instability
- Diagnostic Indicators: Residual/zero-sequence components, ground fault ratio
Bushings
- Primary Impact: Insulation breakdown, discharge, and insulation failure
- Diagnostic Indicators: Voltage interruption, sag, swell events, insulation abnormalities, surface discharge
Tap Changer
- Primary Impact: Abnormal voltage regulation, contact failures, transformer damage
- Diagnostic Indicators: Voltage interruption, transient, sag, and swell events
Windings
- Primary Impact: Complete failure, outages, equipment damage, and reduced efficiency
- Diagnostic Indicators: Park Vector Analysis, even-order harmonic voltages, voltage imbalance, negative/zero-sequence voltage, phase angle analysis
Core
- Primary Impact: Core losses, overheating, increased excitation (magnetizing) current
- Diagnostic Indicators: No-load condition, excitation current waveform distortion, excitation current harmonic components