Monitoring and predicting the technical state of locomotives — the Smart Locomotive System
Target

To predict failures in locomotives using indications from equipment units, trace anomalies, and display information about the technical condition of equipment in automatic mode.

Solutions

The implementation of Clover PMM — a system of intelligent diagnostics and predictions regarding the technical condition of equipment. For this purpose, modules are consistently integrated for predictive analytics and searching for anomalies.

For the anomaly search module, we used telemetry data recorded by the regular microprocessor management systems of the locomotives. Depending on the series of the locomotives, the list of parameters ranged from 250 to 500 names.

The documentation for locomotives and the experience of the client’s experts were used to adapt the algorithms.

Intermediate result
An anomaly search module is in operation for 6400 sections of locomotives.
The system detects more than 50 types of violations in the operation of equipment and modes of operation in locomotives.
The system detects more than 50 types of violations in the operation of equipment and modes of operation in locomotives.
The system automatically detects operational disruptions resulting from user error by the locomotives’ crew.
  • Traction generator
  • Electric traction motor
  • Fuel and oil pumps
  • Water heat sink
  • Turbocharger
  • Brake resistor
  • Brake and recuperative compressors
  • Relays and contactors
  • Oil and fuel filter
  • Accumulator battery
  • LSG
  • Pantograph
  • Motor cooling fans
  • Injectors
  • Water-oil heat exchanger
  • Causative agent
  • Controlled excitation rectifier
  • Rectifier installation
  • Pole regulation system
  • Electric field weakening circuits
  • Charge-air cooler
  • Rectifier-inverter converter
  • Inverters
23 types
of equipment
analyzed
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