Condition monitoring

Assets need regular condition monitoring

In all industries we work in, condition monitoring of assets is a critical task. A number of assets are infrastructure related; some not. Let us take the example of railways. Track infrastructure consists of civil, electrical, signalling and track assets. Each asset’s condition and rate of wear and tear is individual. Railways also have non-infrastructure assets such as trains with sub-components that wear out over time. Ideally we would like an intelligent chip inside each component that relays its health status to us at fixed time intervals. Unfortunately this does not exist in most cases and the only way we can assess asset health is by examining it using sensors. In some cases, the sensors may be in direct contact with the asset, in others they may be non-contact, and often multiple types of sensors may be employed. Condition monitoring refers to the process of using sensor data, filtering out the noise, analysing such data to make measurements, and then using historical records of such measurements to see the change in asset health to predict time to failure. Condition monitoring requires experts to understand the nature of assets as much as the nature of sensors. Assets must be studied in terms of which features are important to monitor (e.g. surface, sub-surface, temperature, vibration, acoustic) and properties of these assets (e.g. manufacturer specification sheets showing asset data, expected mean time between failures, rate of decay, density). Our expertise includes but is not limited to:

  •  Detailed specification and planning of condition monitoring of assets based on customer requirements, asset properties, available sensors and data management needs
  • End-to-end condition monitoring solution development and implementation to meet the custom needs of customers
  • Development of cloud based condition monitoring systems in a wide range of application areas
  • Linking condition monitoring to predictive maintenance practices
  • Surface and sub-surface asset condition monitoring
  • Remote condition monitoring systems
  • Sensor networks for monitoring assets
17 January 2023