MSENSE® DGA

Online-DGA-Monitoring of Power Transformers

Winding problems cause 45% of all transformer failures. The online oil analyzers of the MSENSE® DGA series ensure a measurably longer service life for your transformer. They continuously check for fault gases and moisture in the insulation medium, as well as a wide range of additional gases – depending on the device type. The MSENSE® DGA devices send you a timely warning in the event of electrical and thermal problems. The DGA 2/3 is the perfect early warning system for many transformers, the DGA 5/9 offers intensive monitoring for strategically important transformers with detailed fault classification. 
 

Your Advantages at a Glance

  1. Precise monitoring of the primary leading indicators hydrogen, carbon monoxide and humidity

  2. Optional fault classification of thermal and electrical faults by detection of CxHy

  3. Maintenance-free and without additional operating materials

  4. Robust design for use in any climate zone and for any application

  5. Practical installation even during operation

  6. User-friendly software

  7. Functional expansion through easy integration into ETOS®

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Product Information

Overview of the Devices of the MSENSE® DGA Series
Device name MSENSE® DGA 2 MSENSE® DGA 3 MSENSE® DGA 5 MSENSE® DGA 9
Property Early warning system
Alerts
Early warning system
Alerts
Intensive monitoring
Fault analysis
Intensive monitoring
Fault analysis
Measuring component:
Moisture in the oil X X X X
Hydrogen H2 X X X X
Carbon monoxide CO - X X X
Carbon dioxide CO2 - - - X
Methane CH4 - - - X
Acetylene C2H2 - - X X
Ethylene C2H4 - - X X
Ethane C2H6 - - - X
Oxygen O2 - - - X
Application Important transformers Important transformers Critical and strategically important transformers Critical and strategically very important transformers
Retrofit X X X X
Interpretation and fault detection:
Measurement of absolute values X X X X
Trend analysis X X X X
Fault classification - - X X
Rogers-Diagram - - - X
Duval triangle - - - X

 

According to international standards and experts in the field, hydrogen, carbon monoxide and moisture in the insulating oil of power transformers are the primary early indicators of potential thermal or electrical damage to the transformer (IEC 60475, IEC 60567, ASTM D 4057). In its “Guide for Transformer Maintenance” from 2011, for example, CIGRE pointed out that five of six frequently occurring problems can be detected quickly and affordably using dissolved gas analysis (DGA) during transformer operation. The MSENSE® DGA devices, optionally and in combination with ETOS®, provide fault classification on the basis of the following standards:

  • Duval
  • Doernenburg
  • Rogers
  • IEC 60599
  • IEEE C57.104

Classification is made possible by determining the concentration of carbon dioxide, acetylene, ethylene, methane, ethane and oxygen.

If desired, you can use the user-friendly MSET and MSET DGA parameterization software to change settings from the factory pre-sets. For example, you can adjust individual limit values and the number of measurements taken per day. Furthermore, based on the MSENSE® DGA 5 and MSENSE® DGA 9 device variants, MSET DGA offers the option of intensive monitoring and fault classification. Both solutions are included in the scope of delivery. MSET and MSET DGA present the measured data in a clear and understandable way and prepare trends graphically or exportable.

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IN-DEPTH ONLINE MONITORING FOR IMPORTANT AND CRITICAL TRANSFORMERS

Scan the gas matrix for fault classification
DETECT ERRORS, MINIMIZE RISKS

45%

of all transformer failures are the result of winding problems. The oil analysis provides information on the conditions inside the transformer.
MSENSE® DGA is the intensive monitoring system for key and critical transformers.
No additional operating costs. Practice-oriented retrofit – even during operation.

 

Dga 2/3: monitoring of the primary indicators and detection of trends

Dga 2/3: monitoring of the primary indicators and detection of trends

  • The analysis of dissolved and free gases (DGA) is the only online diagnostic option for detecting and analyzing errors in electrical equipment filled with insulating oil. 
  • Fault gases such as hydrogen and carbon monoxide indicate errors in the windings.
  • Moisture indicates oil quality.
  • The MSENSE® DGA 2/3 early warning system can reliably detect gas and moisture trends in oil.

Dga 5/9: why should i perform an in-depth analysis of the gas matrix for important and critical transformers?

Dga 5/9: why should i perform an in-depth analysis of the gas matrix for important and critical transformers?

  • 45% of all transformer failures are the result of winding problems.
  • The oil analysis provides you with information on the conditions inside of the transformer.
  • MSENSE® DGA 5/9 is the intelligent system for trend monitoring, in-depth monitoring and differentiated oil analysis.

dga 2/3: the early warning and notification system in detail

dga 2/3: the early warning and notification system in detail

  • For paper-insulated transformers
  • Detects individual gas concentrations
    • Moisture in the oil
    • Hydrogen (H2)
    • Carbon monoxide (CO)
  • Continuously monitors the primary early indicators for possible damage with thermal and electrical causes
  • Shows negative trends that could develop during the service life of a transformer
  • Warns and notifies the user when an individually defined limit value is exceeded

before it gets critical:

msense® dga 2/3

 

msense® dga 5

msense® dga 5

DETAILED FAULT ANALYSIS

A proven step in detailed fault analysis for critical and strategically important transformers: The use of MSENSE® DGA 5 guarantees comprehensive monitoring of fault gases.

msense® dga 9

msense® dga 9

DETAILED FAULT CLASSIFICATION

The device with the globally recognized 8-gas matrix. For critical transformers or transformers with a high level of strategic importance, MSENSE® DGA 9 uses the algorithms based on the Rogers or Duval methods to provide detailed information about the classification of thermal and electrical faults.

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