Tennet: Autonomous inspection robot for predictive maintanance
Avular and Sorama joined forces to develop an autonomous inspection robot for predictive maintenance in technical grids to secure reliable supply of electricity. This robot works autonomously exploring technical installations, while accurately detecting sound disturbances with an acoustic camera. These sound disturbances are indicative of imminent technical component or system failures, due to for example leakages, heat accumulation, or partial discharge. Any potential disruptions will be reported to maintenance staff for follow up.
Up to today most technical installations are still being inspected manually by an operator, possibly supported by various measuring tools and sensors on the installation. In specting these type of sites manually come with certain limitations. Observations are prone to bias and depend highly on skill and expertise of the operator. Given that skilled operators are scarce in the tight labor market, the risk of overlooking a minor clue due to inexperience or time pressure is ever looming. Moreover, many installations are difficult to access or approach or inherently unsafe to approach during operation, meaning that they need to be shut down during inspection. The resulting downtime, either for inspection or due to technical failure and subsequent repair, is a major source of costs. Her is where an autonomous inspection can help as is not prone to these challenges and is a great supplement in the overall inspection routine toolbox.
Solution & Innovation
Avular and Sorama have developed an autonomous inspection robot by combining and integrating Avular’s Ranger ground platform and Sorama’s SV600 Acoustic Imager. This makes it possible for inspection the robot to support the operator by carrying out the routine inspection rounds and marking potential disruptions as Points of Interest in a digital map of the facility (comparable to a digital twinning). The advanced autonomy features of the Ranger will enable it to freely roam the industrial site by detecting and avoiding obstacles. The solution has been tested on a substation of main grid operator and launching customer Tennet (NL).
The outcomes of the project are perceived as breakthrough technologies in the market, as they address many critical factors relating to inspection and maintenance, ranging from cost and downtime reduction, supporting scarce staff, whilst improving safety.
This project is made possible with the support of MIT South, the Ministry of Economic Affairs and Climate and the Province of North Brabant.