Pneumatic circuits and their compressors are an essential component of rolling stock. They have multiple functions:
Passenger comfort and safety are highly dependent on the compressor and its pneumatic circuit operating properly. Nonetheless, the air production equipment on board rail vehicles is subject to harsh operating conditions and very high utilisation rates, making it essential to monitor its health.
Even though air compressors are subject to a regular and preventive maintenance schedule, unfortunately, it is not uncommon for breakdowns to take place between the two interventions.
In addition to compressor breakdowns, air leaks anywhere on the pneumatic circuit can also cause problems for rail operators. These leaks can be both temporary and permanent, and can originate in one or multiple components supplied by the compressor.
No sensors enable the real-time uploading of information on compressor health and use during operation. As a result, clients lack a dynamic view and leaks are only discovered at the maintenance centre and not during train operation. Some compressor leaks may even go unnoticed during inspection due to their intermittent nature.
Below is a non-exhaustive list of the negative consequences reported by our clients:
To correct these failures, better understand compressor behaviour under real conditions, and improve the quality of service, the continuous, real-time monitoring of compressors is therefore essential. Stimio’s Oxygen IoT solution allows our clients to rapidly resolve these problems while simultaneously offering future possibilities (see “Prediction” below).
A private wireless network can be set up in a few hours. Our Railnode certified rail IoT sensors are installed on compressors to measure on/off activation time. As a result, they allow the compressor to communicate. Moreover, our Railnet IoT gateway is the centrepiece of the private wireless network. It collects sensor data and sends it to the Oxygen cloud platform. We deliver enriched business data that can be directly exploited and integrated into our clients’ IT systems. Data analysis on the Oxygen platform allows to highlight abnormal behaviour, load rates, loading-unloading cycles, etc.
It optimises the planning and anticipation of equipment maintenance.
Our Oxygen solution makes it possible to analyse the behaviour of the different compressors installed on trains. It is then possible to define and classify this behaviour.
Doing so is of critical utility, as it allows to predict compressor behaviour, detect the early warning signs of breakdowns, and anticipate maintenance actions as accurately as possible.
This requires mathematical modelling and prediction based on data from the compressor fleet combined with the use conditions and features of each compressor (model, age, utilisation rate…).
Combining all of this data allows to define nominal behaviour. Each compressor is then regularly compared to this standard behaviour both in terms of its category and the global population. If there is an abnormal deviation in a parameter, it will be possible to predict when an inspection or repair intervention will be necessary.
This article was originally published by Stimio.
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