APM5000
APM 5000 detects and alerts
various defects inside GIS by
analyzing UHF signals generated by
partial discharge that can cause
progressive deterioration of
insulating materials, ultimately
leading to electrical breakdown.
APM5000
APM 5000 detects and alerts
various defects inside GIS by
analyzing UHF signals generated by
partial discharge that can cause
progressive deterioration of
insulating materials, ultimately
leading to electrical breakdown.
APM3000
APM 3000 is an Online Partial Discharge
Monitoring System (OPDM) for power
transformers base on UHF partial
discharge technologies. APM 3000
monitors and diagnoses various defects
timely and accurately to support
improved Condition Based Management
(CBM) and to prevent serious breakdown
of power transformers.
APM2000
APM 2000 detects and alerts various
defects inside EHV/MV equipment by
analyzing UHF signals generated by
partial discharge. It monitors, records
and analyzes PD signal continuously
and alerts the condition with light-weight
and small-sized equipment.
APM1200
It is an advanced online diagnosis
system for metal clad switch gear
that predicts any problems for
advanced maintenance by
detecting partial discharge.
SENSOR
The PD sensor is used to detect
partial discharge signals in UHF
(Ultra High Frequency) band.
APM7000
APM7000 is the most effective
insulation diagnosis system
that analyzes the cable’s failure
phenomenon due top artial discharge
in real time to prevent accidental power failure.
PDMS with true UHF bandwidth
Superior accuracy and noise gating features based on the state-of-the-art UHF technology. Conventional PDMS systems may convert PD signals in UHF band to RF band because their systems do not have performance enough to analyze PD signals in UHF band directly. PDMS systems of APM Technologies include high performance data acquisition units that are enabled to analyze PD signals in UHF band without down converting.
IEC 61850 certified
Supports the latest Substation Automation System including remote PD monitoring using IEC 61850 protocol
Unparalleled multi-step noise filtering method
Step 1 ) | Programmable hardware band pass filtering |
Step 2 ) | Eliminating external noises by comparing signals from PD Sensors with Noise Sensor |
Step 3 ) | Distinguishing various types of Noise signals including Mobile Network, WIFI by using Neural Network AI engine |
AI analysis
Signals measured from each PD Sensor are analyzed in real time based on the database by AI, and reported instantly with its cause in case they are PD signals. The AI database includes carious types of defect including Protrusion Electrode, Floating Electrode, Defective Insulator Free moving particle and Noises.
Enhanced HMI
Provides PD analyzing features using AI, Trend features which shows
PD changes over time, and integrated features such as real time signal analysis
Provides independent conditions setting according to each
sensor’s installation environment
Provides user account and control management and regular auto-matic
report generating features
Expandability
In case more bays are added to an existing GIS where APM’s PDMS has been installed, the PDMS can be expanded to support the additional bays by adding Local Units and PD Sensors with the minimum cost.
Self-Diagnosis
Monitors Local Units in HMI providing alarms and automatic recovery feature
Provides PRPD, PRPS and other graphic charts for PD experts
Stores and data for long period