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HEALTH AND USAGE

MONITORING SYSTEMS

HEALTH & USAGE MONITORING SYSTEMS (HUMS)

Health Usage Monitoring Units are electronic defence systems specifically designed for mobile, remote or high value platforms subjected to severe operational use in extreme environments. The vehicle monitoring systems have been adopted through automotive manufactured black boxes on an international basis and have been incorporated into military land vehicles and equipment, naval vessels and civilian trains. The equipment is equally applicable to telematics for civilian assets where operation with minimum downtime is essential.

Data collection, data extraction, data analysis and decision making

HEALTH & USAGE MONITORING SYSTEMS KEY ATTRIBUTES

A range of configurable monitoring and daa processing products.

The range of configurable monitoring and data processing products includes:

  • VMU hardware: Configurable for the specific asset information required.

  • VIDI software: For providing data analysis and display in a user friendly format.

Full end to end connectivity:

  • Optimised data acquired from the asset in real time.

  • Downloads accurate and tailored asset data without user intervention.

  • Transfers data direct to fleet management data centre.

  • Automatically presents asset advice to the fleet manager for informed decision making via in-service asset management systems .

End to end connectivitiy.
Example of HUMs in action

An overview of the complete asset:

  • Increased user awareness of input effects

  • Quantitative   appreciation   of   system   and component reliability

  • Predictable   maintenance   free   operational periods

  • Improved asset availability

  • Vision  of  component  or  system  degradation as definitive measurements

  • Predictive maintenance requirements

  • Condition based maintenance

  • Root cause fault diagnosis

  • Optimum spares holding

PRODUCT VARIANTS

Vehicle HUMS

Systems which record the state of a vehicle at frequent intervals (many times per second), including mechanical data available on the vehicle’s CAN bus (such as speed, engine revolution rate, temperature, oil and water pressures) and metadata available from other sensors (ambient temperature, vibration, acceleration, location via GPS etc.) This data can be used to assess the condition of the vehicle and perform predictive maintenance, or to assess the skills of the driver and assist with driver training. Driver behaviour can also be influenced by presenting the driver with a live readout of the HUMS data being collected, alongside the vehicle’s standard instrumentation. Proper use of the data can extend the vehicle’s lifetime and significantly reduce running costs and overall cost-of-ownership.

HUMS Data Collection & Transmission

Depending on the specific use case, the data from the automotive usage monitor can be relayed in a number of different ways. Where security is the highest priority and the vehicle must maintain radio silence (and all Exsel Electronics HUMS systems adhere to the highest standards of electromagnetic suppression), the only solution is to store the data and enable download by hardware (such as a network cable or a USB stick) when the vehicle is safely back at base. At the other extreme, data can be streamed in real time by a live cellular, satellite or tactical radio link. In other circumstances, radio silence can be maintained when the vehicle is out on operations but the data can be automatically and wirelessly transferred (for example by WiFi, Bluetooth or UWB) when the vehicle enters base or any other trusted secure location.

HUMS Data Analysis

Data only becomes valuable when it can be processed and converted into information or, even better, knowledge. The processing can be as simple as summarisation (for example, only storing data at times when there are significant changes, or when parameters move outside pre-defined limits) or as complex as a full machine-learning driven analysis to detect patterns associated with imminent component failure. Exsel Electronics can integrate data processing into the collection process itself, dynamically summarising the data so as to reduce storage space and transfer times, or format the data for export to external data-mining applications for in-depth offline analysis.

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