Why put a person in a dangerous situation when a robot can do it for them?
In recent years, drones have gone from being a rarity in infrastructure inspections to becoming more widespread. Dams, bridges and other systems must be checked regularly to ensure that there are no dangerous cracks or other damage. Traditionally, these operations require the abseiling of professionals. When you give them drones, these inspections become safer, more accurate, and more affordable, which means teams can do more.
Top tips from the editors
Subscribe to CNET Now for the day's most engaging reviews, news, and videos.
"Drones are able to see things and reach certain areas that a traditional rope inspection might not allow due to restricted access," says Cameron Schaefer, director of data collection at HDR, an engineering, architectural, environmental and construction services company specialized company that has been using drones for three years. The program has grown from five to over 20 pilots and is trained for situations such as strong winds or emergency landings.
HDR
The requirements of the process determine the planning and the hardware used. In some processes, simple consumer devices may be sufficient while others require specialized devices. Taking 8,000 images provides greater accuracy than 2,000, and some drones are fine for certain areas but very limited in others.
Take, for example, the inspection of the Diablo Dam in northern Washington state. Last summer, HDR used its drones to complement the rating of this 389-foot-tall structure that powers Seattle. The result was more than 82 million data points that create a 3D representation and document the condition of the dam and the areas in need of repair.
The team linked the images captured by the drone with ground control data and engineering drawings to create a virtual model of the dam that can later be updated with additional data - including information from other technologies, such as B. Ground penetrating radar. This allows the model to become more effective over time and allows the team to predict the structural repairs needed using machine learning and predictive analysis.
The result, says Schäfer, is not just an increase in safety: "It is an increase in quality. It is an increase in accuracy. It is an increase in historical monitoring."
